memcasecmp \
memchr \
memchr2 \
+ memmem \
mempcpy \
memrchr \
minmax \
the entire case is excluded whenever any value in that case has a
system-missing or, if @subcmd{INCLUDE} is set, user-missing value.
-The @subcmd{FORMAT} subcommand affects the output format. Currently the
-@subcmd{LABELS/NOLABELS} and @subcmd{NOINDEX/INDEX} settings are not used.
-When @subcmd{SERIAL} is
-set, both valid and missing number of cases are listed in the output;
-when @subcmd{NOSERIAL} is set, only valid cases are listed.
+The @subcmd{FORMAT} subcommand has no effect. It is accepted for
+backward compatibility.
The @subcmd{SAVE} subcommand causes @cmd{DESCRIPTIVES} to calculate Z scores for all
the specified variables. The Z scores are saved to new variables.
table basis. When set to @subcmd{INCLUDE}, user-missing values are included in
tables and statistics. When set to @subcmd{REPORT}, which is allowed only in
integer mode, user-missing values are included in tables but marked with
-an @samp{M} (for ``missing'') and excluded from statistical
-calculations.
+a footnote and excluded from statistical calculations.
Currently the @subcmd{WRITE} subcommand is ignored.
It should show the following output:
@example
@group
-Case# forename height
------ ------------ --------
- 1 Ahmed 188.00
- 2 Bertram 167.00
- 3 Catherine 134.23
- 4 David 109.10
+ Data List
++-----------+---------+------+
+|Case Number| forename|height|
++-----------+---------+------+
+|1 |Ahmed |188.00|
+|2 |Bertram |167.00|
+|3 |Catherine|134.23|
+|4 |David |109.10|
++-----------+---------+------+
@end group
@end example
@noindent
Output:
@example
-DESCRIPTIVES. Valid cases = 40; cases with missing value(s) = 0.
-+--------#--+-------+-------+-------+-------+
-|Variable# N| Mean |Std Dev|Minimum|Maximum|
-#========#==#=======#=======#=======#=======#
-|sex #40| .45| .50| .00| 1.00|
-|height #40|1677.12| 262.87| 179.00|1903.00|
-|weight #40| 72.12| 26.70| -55.60| 92.07|
-+--------#--+-------+-------+-------+-------+
+ Descriptive Statistics
++---------------------+--+-------+-------+-------+-------+
+| | N| Mean |Std Dev|Minimum|Maximum|
++---------------------+--+-------+-------+-------+-------+
+|Sex of subject |40| .45| .50|Male |Female |
+|Weight in kilograms |40| 72.12| 26.70| -55.6| 92.1|
+|Height in millimeters|40|1677.12| 262.87| 179| 1903|
+|Valid N (listwise) |40| | | | |
+|Missing N (listwise) | 0| | | | |
++---------------------+--+-------+-------+-------+-------+
@end example
@end cartouche
@caption{Using the @cmd{DESCRIPTIVES} command to display simple
Output:
@example
-#===============================#===========#=======#
-# #Case Number| Value #
-#===============================#===========#=======#
-#Height in millimetres Highest 1# 14|1903.00#
-# 2# 15|1884.00#
-# 3# 12|1801.65#
-# ----------#-----------+-------#
-# Lowest 1# 30| 179.00#
-# 2# 31|1598.00#
-# 3# 28|1601.00#
-# ----------#-----------+-------#
-#Weight in kilograms Highest 1# 13| 92.07#
-# 2# 5| 92.07#
-# 3# 17| 91.74#
-# ----------#-----------+-------#
-# Lowest 1# 38| -55.60#
-# 2# 39| 54.48#
-# 3# 33| 55.45#
-#===============================#===========#=======#
+ Extreme Values
++-------------------------------+-----------+-----+
+| |Case Number|Value|
++-------------------------------+-----------+-----+
+|Height in millimeters Highest 1| 14| 1903|
+| 2| 15| 1884|
+| 3| 12| 1802|
+| Lowest 1| 30| 179|
+| 2| 31| 1598|
+| 3| 28| 1601|
++-------------------------------+-----------+-----+
+|Weight in kilograms Highest 1| 13| 92.1|
+| 2| 5| 92.1|
+| 3| 17| 91.7|
+| Lowest 1| 38|-55.6|
+| 2| 39| 54.5|
+| 3| 33| 55.4|
++-------------------------------+-----------+-----+
@end example
@end cartouche
@caption{Using the @cmd{EXAMINE} command to see the extremities of the data
Output (dictionary information omitted for clarity):
@example
-1.1 RELIABILITY. Case Processing Summary
-#==============#==#======#
-# # N| % #
-#==============#==#======#
-#Cases Valid #17|100.00#
-# Excluded# 0| .00#
-# Total #17|100.00#
-#==============#==#======#
-
-1.2 RELIABILITY. Reliability Statistics
-#================#==========#
-#Cronbach's Alpha#N of Items#
-#================#==========#
-# .81# 3#
-#================#==========#
+Scale: ANY
+
+Case Processing Summary
++--------+--+-------+
+|Cases | N|Percent|
++--------+--+-------+
+|Valid |17| 100.0%|
+|Excluded| 0| .0%|
+|Total |17| 100.0%|
++--------+--+-------+
+
+ Reliability Statistics
++----------------+----------+
+|Cronbach's Alpha|N of Items|
++----------------+----------+
+| .81| 3|
++----------------+----------+
@end example
@end cartouche
@caption{Recoding negatively scaled variables, and testing for
Output:
@example
-1.2 EXAMINE. Descriptives
-#====================================================#=========#==========#
-# #Statistic|Std. Error#
-#====================================================#=========#==========#
-#mtbf Mean # 8.32 | 1.62 #
-# 95% Confidence Interval for Mean Lower Bound# 4.85 | #
-# Upper Bound# 11.79 | #
-# 5% Trimmed Mean # 7.69 | #
-# Median # 8.12 | #
-# Variance # 39.21 | #
-# Std. Deviation # 6.26 | #
-# Minimum # 1.63 | #
-# Maximum # 26.47 | #
-# Range # 24.84 | #
-# Interquartile Range # 5.83 | #
-# Skewness # 1.85 | .58 #
-# Kurtosis # 4.49 | 1.12 #
-#====================================================#=========#==========#
-
-2.2 EXAMINE. Descriptives
-#====================================================#=========#==========#
-# #Statistic|Std. Error#
-#====================================================#=========#==========#
-#mtbf_ln Mean # 1.88 | .19 #
-# 95% Confidence Interval for Mean Lower Bound# 1.47 | #
-# Upper Bound# 2.29 | #
-# 5% Trimmed Mean # 1.88 | #
-# Median # 2.09 | #
-# Variance # .54 | #
-# Std. Deviation # .74 | #
-# Minimum # .49 | #
-# Maximum # 3.28 | #
-# Range # 2.79 | #
-# Interquartile Range # .92 | #
-# Skewness # -.16 | .58 #
-# Kurtosis # -.09 | 1.12 #
-#====================================================#=========#==========#
+ Case Processing Summary
++-----------------------------------+-------------------------------+
+| | Cases |
+| +----------+---------+----------+
+| | Valid | Missing | Total |
+| | N|Percent|N|Percent| N|Percent|
++-----------------------------------+--+-------+-+-------+--+-------+
+|Mean time between failures (months)|15| 100.0%|0| .0%|15| 100.0%|
++-----------------------------------+--+-------+-+-------+--+-------+
+
+ Descriptives
++----------------------------------------------------------+---------+--------+
+| | | Std. |
+| |Statistic| Error |
++----------------------------------------------------------+---------+--------+
+|Mean time between Mean | 8.32| 1.62|
+|failures (months) 95% Confidence Interval Lower | 4.85| |
+| for Mean Bound | | |
+| Upper | 11.79| |
+| Bound | | |
+| 5% Trimmed Mean | 7.69| |
+| Median | 8.12| |
+| Variance | 39.21| |
+| Std. Deviation | 6.26| |
+| Minimum | 1.63| |
+| Maximum | 26.47| |
+| Range | 24.84| |
+| Interquartile Range | 5.83| |
+| Skewness | 1.85| .58|
+| Kurtosis | 4.49| 1.12|
++----------------------------------------------------------+---------+--------+
+
+ Case Processing Summary
++-------+-------------------------------+
+| | Cases |
+| +----------+---------+----------+
+| | Valid | Missing | Total |
+| | N|Percent|N|Percent| N|Percent|
++-------+--+-------+-+-------+--+-------+
+|mtbf_ln|15| 100.0%|0| .0%|15| 100.0%|
++-------+--+-------+-+-------+--+-------+
+
+ Descriptives
++----------------------------------------------------+---------+----------+
+| |Statistic|Std. Error|
++----------------------------------------------------+---------+----------+
+|mtbf_ln Mean | 1.88| .19|
+| 95% Confidence Interval for Mean Lower Bound| 1.47| |
+| Upper Bound| 2.29| |
+| 5% Trimmed Mean | 1.88| |
+| Median | 2.09| |
+| Variance | .54| |
+| Std. Deviation | .74| |
+| Minimum | .49| |
+| Maximum | 3.28| |
+| Range | 2.79| |
+| Interquartile Range | .92| |
+| Skewness | -.16| .58|
+| Kurtosis | -.09| 1.12|
++----------------------------------------------------+---------+----------+
@end example
@end cartouche
@caption{Testing for normality using the @cmd{EXAMINE} command and applying
@end example
Output:
@example
-1.1 T-TEST. Group Statistics
-#==================#==#=======#==============#========#
-# sex | N| Mean |Std. Deviation|SE. Mean#
-#==================#==#=======#==============#========#
-#height Male |22|1796.49| 49.71| 10.60#
-# Female|17|1610.77| 25.43| 6.17#
-#temperature Male |22| 36.68| 1.95| .42#
-# Female|18| 37.43| 1.61| .38#
-#==================#==#=======#==============#========#
-1.2 T-TEST. Independent Samples Test
-#===========================#=========#=============================== =#
-# # Levene's| t-test for Equality of Means #
-# #----+----+------+-----+------+---------+- -#
-# # | | | | | | #
-# # | | | |Sig. 2| | #
-# # F |Sig.| t | df |tailed|Mean Diff| #
-#===========================#====#====#======#=====#======#=========#= =#
-#height Equal variances# .97| .33| 14.02|37.00| .00| 185.72| ... #
-# Unequal variances# | | 15.15|32.71| .00| 185.72| ... #
-#temperature Equal variances# .31| .58| -1.31|38.00| .20| -.75| ... #
-# Unequal variances# | | -1.33|37.99| .19| -.75| ... #
-#===========================#====#====#======#=====#======#=========#= =#
+ Group Statistics
++-------------------------------------------+--+-------+-------------+--------+
+| | | | Std. | S.E. |
+| Group | N| Mean | Deviation | Mean |
++-------------------------------------------+--+-------+-------------+--------+
+|Height in millimeters Male |22|1796.49| 49.71| 10.60|
+| Female|17|1610.77| 25.43| 6.17|
++-------------------------------------------+--+-------+-------------+--------+
+|Internal body temperature in degrees Male |22| 36.68| 1.95| .42|
+|Celcius Female|18| 37.43| 1.61| .38|
++-------------------------------------------+--+-------+-------------+--------+
+
+ Independent Samples Test
++---------------------+-----------------------------------------------------
+| | Levene's
+| | Test for
+| | Equality
+| | of
+| | Variances T-Test for Equality of Means
+| +----+-----+-----+-----+-------+----------+----------+
+| | | | | | | | |
+| | | | | | | | |
+| | | | | | | | |
+| | | | | | | | |
+| | | | | | Sig. | | |
+| | | | | | (2- | Mean |Std. Error|
+| | F | Sig.| t | df |tailed)|Difference|Difference|
++---------------------+----+-----+-----+-----+-------+----------+----------+
+|Height in Equal | .97| .331|14.02|37.00| .000| 185.72| 13.24|
+|millimeters variances| | | | | | | |
+| assumed | | | | | | | |
+| Equal | | |15.15|32.71| .000| 185.72| 12.26|
+| variances| | | | | | | |
+| not | | | | | | | |
+| assumed | | | | | | | |
++---------------------+----+-----+-----+-----+-------+----------+----------+
+|Internal Equal | .31| .581|-1.31|38.00| .198| -.75| .57|
+|body variances| | | | | | | |
+|temperature assumed | | | | | | | |
+|in degrees Equal | | |-1.33|37.99| .190| -.75| .56|
+|Celcius variances| | | | | | | |
+| not | | | | | | | |
+| assumed | | | | | | | |
++---------------------+----+-----+-----+-----+-------+----------+----------+
+
++---------------------+-------------+
+| | |
+| | |
+| | |
+| | |
+| | |
+| +-------------+
+| | 95% |
+| | Confidence |
+| | Interval of |
+| | the |
+| | Difference |
+| +------+------+
+| | Lower| Upper|
++---------------------+------+------+
+|Height in Equal |158.88|212.55|
+|millimeters variances| | |
+| assumed | | |
+| Equal |160.76|210.67|
+| variances| | |
+| not | | |
+| assumed | | |
++---------------------+------+------+
+|Internal Equal | -1.91| .41|
+|body variances| | |
+|temperature assumed | | |
+|in degrees Equal | -1.89| .39|
+|Celcius variances| | |
+| not | | |
+| assumed | | |
++---------------------+------+------+
@end example
@end cartouche
@caption{The @cmd{T-TEST} command tests for differences of means.
@prompt{PSPP>} regression /variables = mtbf duty_cycle /dependent = mttr.
@prompt{PSPP>} regression /variables = mtbf /dependent = mttr.
@end example
-Output:
+Output (excerpts):
@example
-1.3(1) REGRESSION. Coefficients
-#=============================================#====#==========#====#=====#
-# # B |Std. Error|Beta| t #
-#========#====================================#====#==========#====#=====#
-# |(Constant) #9.81| 1.50| .00| 6.54#
-# |Mean time between failures (months) #3.10| .10| .99|32.43#
-# |Ratio of working to non-working time#1.09| 1.78| .02| .61#
-# | # | | | #
-#========#====================================#====#==========#====#=====#
-
-1.3(2) REGRESSION. Coefficients
-#=============================================#============#
-# #Significance#
-#========#====================================#============#
-# |(Constant) # .10#
-# |Mean time between failures (months) # .00#
-# |Ratio of working to non-working time# .55#
-# | # #
-#========#====================================#============#
-2.3(1) REGRESSION. Coefficients
-#============================================#=====#==========#====#=====#
-# # B |Std. Error|Beta| t #
-#========#===================================#=====#==========#====#=====#
-# |(Constant) #10.50| .96| .00|10.96#
-# |Mean time between failures (months)# 3.11| .09| .99|33.39#
-# | # | | | #
-#========#===================================#=====#==========#====#=====#
-
-2.3(2) REGRESSION. Coefficients
-#============================================#============#
-# #Significance#
-#========#===================================#============#
-# |(Constant) # .06#
-# |Mean time between failures (months)# .00#
-# | # #
-#========#===================================#============#
+ Coefficients (Mean time to repair (hours) )
++------------------------+-----------------------------------------+-----+----+
+| | Unstandardized Standardized | | |
+| | Coefficients Coefficients | | |
+| +---------+-----------+-------------------+ | |
+| | B | Std. Error| Beta | t |Sig.|
++------------------------+---------+-----------+-------------------+-----+----+
+|(Constant) | 9.81| 1.50| .00| 6.54|.000|
+|Mean time between | 3.10| .10| .99|32.43|.000|
+|failures (months) | | | | | |
+|Ratio of working to non-| 1.09| 1.78| .02| .61|.552|
+|working time | | | | | |
++------------------------+---------+-----------+-------------------+-----+----+
+
+ Coefficients (Mean time to repair (hours) )
++-----------------------+------------------------------------------+-----+----+
+| | Unstandardized Standardized | | |
+| | Coefficients Coefficients | | |
+| +---------+------------+-------------------+ | |
+| | B | Std. Error | Beta | t |Sig.|
++-----------------------+---------+------------+-------------------+-----+----+
+|(Constant) | 10.50| .96| .00|10.96|.000|
+|Mean time between | 3.11| .09| .99|33.39|.000|
+|failures (months) | | | | | |
++-----------------------+---------+------------+-------------------+-----+----+
@end example
@end cartouche
@caption{Linear regression analysis to find a predictor for
@display
OUTPUT MODIFY
/SELECT TABLES
- /TABLECELLS SELECT = [ @{SIGNIFICANCE, COUNT@} ]
+ /TABLECELLS SELECT = [ @var{class}... ]
FORMAT = @var{fmt_spec}.
@end display
@note{In the above synopsis the characters @samp{[} and @samp{]} are literals.
Each class can be:
@table @asis
+@item RESIDUAL
+Residual values. Default: @t{F40.2}.
+
+@item CORRELATION
+Correlations. Default: @t{F40.3}.
+
+@item PERCENT
+Percentages. Default: @t{PCT40.1}.
+
@item SIGNIFICANCE
-Significance of tests (p-values).
+Significance of tests (p-values). Default: @t{F40.3}.
@item COUNT
-Counts or sums of weights.
+Counts or sums of weights. For a weighted data set, the default is
+the weight variable's print format. For an unweighted data set, the
+default is F40.0.
@end table
+For most other numeric values that appear in tables, @code{SET FORMAT}
+may be used to specify the format (@pxref{SET FORMAT}).
+
The value of @var{fmt_spec} must be a valid output format (@pxref{Input and Output Formats}).
Note that not all possible formats are meaningful for all classes.
The default value is determined from the system locale.
@item FORMAT
+@anchor{SET FORMAT}
Allows the default numeric input/output format to be specified. The
default is F8.2. @xref{Input and Output Formats}.
id,1,,Scale,Input,8,Right,F2.0,F2.0,
name,2,,Nominal,Input,20,Left,A20,A20,
-File label: This is the file label
-
-Documents in the active dataset:
+Table: File Label
+Label,This is the file label
+Table: Documents
This is a document line
Table: Data List
id,name
-21,wheelbarrow
+21,wheelbarrow
RESULT
longstring,3,My Long String,Nominal,Input,9,Left,A9,A9,
Table: Value Labels
-Variable,Value,Label
-integer,0,Zero
+Variable Value,,Label
+My Integer,0,Zero
,1,Unity
,2,Duality
-string,xx ,foo
-,yy ,bar
-longstring,xxx ,xfoo
+My String,xx,foo
+,yy,bar
+My Long String,xxx,xfoo
RESULT
}
enum settings_output_devices output_routing[SETTINGS_N_OUTPUT_TYPES];
- enum settings_var_style var_output_style;
- enum settings_value_style value_output_style;
+ enum settings_value_show show_values;
+ enum settings_value_show show_variables;
};
static struct settings the_settings = {
0,
SETTINGS_DEVICE_LISTING | SETTINGS_DEVICE_TERMINAL},
- SETTINGS_VAR_STYLE_LABELS,
- SETTINGS_VAL_STYLE_LABELS
+ SETTINGS_VALUE_SHOW_LABEL,
+ SETTINGS_VALUE_SHOW_LABEL
};
/* Initializes the settings module. */
return the_settings.output_routing[type] | SETTINGS_DEVICE_UNFILTERED;
}
-enum settings_value_style
-settings_get_value_style (void)
+enum settings_value_show
+settings_get_show_values (void)
{
- return the_settings.value_output_style;
+ return the_settings.show_values;
}
void
-settings_set_value_style (enum settings_value_style s)
+settings_set_show_values (enum settings_value_show s)
{
- the_settings.value_output_style = s;
+ the_settings.show_values = s;
}
-
-enum settings_var_style
-settings_get_var_style (void)
+enum settings_value_show
+settings_get_show_variables (void)
{
- return the_settings.var_output_style;
+ return the_settings.show_variables;
}
-
void
-settings_set_var_style (enum settings_var_style s)
+settings_set_show_variables (enum settings_value_show s)
{
- the_settings.var_output_style = s;
+ the_settings.show_variables = s;
}
int settings_get_fuzzbits (void);
void settings_set_fuzzbits (int);
-enum settings_var_style
+/* Whether to show variable or value labels or the underlying value or variable
+ name. */
+enum settings_value_show
{
- SETTINGS_VAR_STYLE_NAMES,
- SETTINGS_VAR_STYLE_LABELS,
- SETTINGS_VAR_STYLE_BOTH
+ /* Use higher-level default.
+ In a pivot_value, the default is taken from the pivot_table.
+ In a pivot_table, the default is a global default.
+ As a global default, this is invalid. */
+ SETTINGS_VALUE_SHOW_DEFAULT = 0,
+
+ SETTINGS_VALUE_SHOW_VALUE = 1, /* Show value or variable name only. */
+ SETTINGS_VALUE_SHOW_LABEL = 2, /* Show label only. */
+ SETTINGS_VALUE_SHOW_BOTH = 3, /* Show both value/name and label. */
};
-enum settings_value_style
- {
- SETTINGS_VAL_STYLE_VALUES,
- SETTINGS_VAL_STYLE_LABELS,
- SETTINGS_VAL_STYLE_BOTH
- };
-
-
-enum settings_value_style settings_get_value_style (void);
-enum settings_var_style settings_get_var_style (void);
+enum settings_value_show settings_get_show_values (void);
+enum settings_value_show settings_get_show_variables (void);
-void settings_set_value_style (enum settings_value_style s);
-void settings_set_var_style (enum settings_var_style s);
+void settings_set_show_values (enum settings_value_show);
+void settings_set_show_variables (enum settings_value_show);
enum behavior_mode {
var_append_value_name (const struct variable *v, const union value *value,
struct string *str)
{
- enum settings_value_style style = settings_get_value_style ();
- const char *name = var_lookup_value_label (v, value);
+ const char *label = var_lookup_value_label (v, value);
- switch (style)
+ switch (settings_get_show_values ())
{
- case SETTINGS_VAL_STYLE_VALUES:
+ case SETTINGS_VALUE_SHOW_VALUE:
append_value (v, value, str);
break;
- case SETTINGS_VAL_STYLE_LABELS:
- if (name == NULL)
- append_value (v, value, str);
+ default:
+ case SETTINGS_VALUE_SHOW_LABEL:
+ if (label)
+ ds_put_cstr (str, label);
else
- ds_put_cstr (str, name);
+ append_value (v, value, str);
break;
- case SETTINGS_VAL_STYLE_BOTH:
- default:
+ case SETTINGS_VALUE_SHOW_BOTH:
append_value (v, value, str);
- if (name != NULL)
- {
- ds_put_cstr (str, " (");
- ds_put_cstr (str, name);
- ds_put_cstr (str, ")");
- }
+ if (label != NULL)
+ ds_put_format (str, " %s", label);
break;
- };
+ }
}
\f
/* Print and write formats. */
const char *
var_to_string (const struct variable *v)
{
- enum settings_var_style style = settings_get_var_style ();
-
- switch (style)
- {
- case SETTINGS_VAR_STYLE_NAMES:
+ switch (settings_get_show_variables ())
+ {
+ case SETTINGS_VALUE_SHOW_VALUE:
return v->name;
- break;
- case SETTINGS_VAR_STYLE_LABELS:
+
+ case SETTINGS_VALUE_SHOW_LABEL:
+ default:
return v->label != NULL ? v->label : v->name;
- break;
- case SETTINGS_VAR_STYLE_BOTH:
+
+ case SETTINGS_VALUE_SHOW_BOTH:
update_vl_string (v);
return ds_cstr (&v->name_and_label);
- break;
- default:
- NOT_REACHED ();
- break;
- };
+ }
}
/* Returns V's variable label, or a null pointer if it has none. */
#include "language/data-io/data-reader.h"
#include "libpspp/message.h"
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
/* Data parser for textual data like that read by DATA LIST. */
dump_fixed_table (const struct data_parser *parser,
const struct file_handle *fh)
{
- struct tab_table *t;
- size_t i;
-
- t = tab_create (4, parser->field_cnt + 1);
- tab_headers (t, 0, 0, 1, 0);
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Variable"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Record"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Columns"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Format"));
- tab_box (t, TAL_1, TAL_1, TAL_0, TAL_1, 0, 0, 3, parser->field_cnt);
- tab_hline (t, TAL_2, 0, 3, 1);
-
- for (i = 0; i < parser->field_cnt; i++)
+ /* XXX This should not be preformatted. */
+ char *title = xasprintf (ngettext ("Reading %d record from %s.",
+ "Reading %d records from %s.",
+ parser->records_per_case),
+ parser->records_per_case, fh_get_name (fh));
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_user_text (title, -1));
+ free (title);
+
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Attributes"),
+ N_("Record"), N_("Columns"), N_("Format"));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+ variables->root->show_label = true;
+ for (size_t i = 0; i < parser->field_cnt; i++)
{
struct field *f = &parser->fields[i];
- char fmt_string[FMT_STRING_LEN_MAX + 1];
- int row = i + 1;
-
- tab_text (t, 0, row, TAB_LEFT, f->name);
- tab_text_format (t, 1, row, 0, "%d", f->record);
- tab_text_format (t, 2, row, 0, "%3d-%3d",
- f->first_column, f->first_column + f->format.w - 1);
- tab_text (t, 3, row, TAB_LEFT | TAB_FIX,
- fmt_to_string (&f->format, fmt_string));
+
+ /* XXX It would be better to have the actual variable here. */
+ int variable_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_user_text (f->name, -1));
+
+ pivot_table_put2 (table, 0, variable_idx,
+ pivot_value_new_integer (f->record));
+
+ int first_column = f->first_column;
+ int last_column = f->first_column + f->format.w - 1;
+ char *columns = xasprintf ("%3d-%3d", first_column, last_column);
+ pivot_table_put2 (table, 1, variable_idx,
+ pivot_value_new_user_text (columns, -1));
+ free (columns);
+
+ char str[FMT_STRING_LEN_MAX + 1];
+ pivot_table_put2 (table, 2, variable_idx,
+ pivot_value_new_user_text (
+ fmt_to_string (&f->format, str), -1));
+
}
- tab_title (t, ngettext ("Reading %d record from %s.",
- "Reading %d records from %s.",
- parser->records_per_case),
- parser->records_per_case, fh_get_name (fh));
- tab_submit (t);
+ pivot_table_submit (table);
}
/* Displays a table giving information on free-format variable parsing
dump_delimited_table (const struct data_parser *parser,
const struct file_handle *fh)
{
- struct tab_table *t;
- size_t i;
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("Reading free-form data from %s."),
+ fh_get_name (fh)));
- t = tab_create (2, parser->field_cnt + 1);
- tab_headers (t, 0, 0, 1, 0);
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Variable"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Format"));
- tab_box (t, TAL_1, TAL_1, TAL_0, TAL_1, 0, 0, 1, parser->field_cnt);
- tab_hline (t, TAL_2, 0, 1, 1);
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Attributes"), N_("Format"));
- for (i = 0; i < parser->field_cnt; i++)
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+ variables->root->show_label = true;
+ for (size_t i = 0; i < parser->field_cnt; i++)
{
struct field *f = &parser->fields[i];
- char str[FMT_STRING_LEN_MAX + 1];
- int row = i + 1;
- tab_text (t, 0, row, TAB_LEFT, f->name);
- tab_text (t, 1, row, TAB_LEFT | TAB_FIX,
- fmt_to_string (&f->format, str));
- }
+ /* XXX It would be better to have the actual variable here. */
+ int variable_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_user_text (f->name, -1));
- tab_title (t, _("Reading free-form data from %s."), fh_get_name (fh));
+ char str[FMT_STRING_LEN_MAX + 1];
+ pivot_table_put2 (table, 0, variable_idx,
+ pivot_value_new_user_text (
+ fmt_to_string (&f->format, str), -1));
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
/* Displays a table giving information on how PARSER will read
#include "data/session.h"
#include "language/lexer/lexer.h"
#include "libpspp/message.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
\f
static int
cmd_dataset_display (struct lexer *lexer UNUSED, struct dataset *ds)
{
struct session *session = dataset_session (ds);
- struct dataset **datasets, **p;
- struct tab_table *t;
- size_t i, n;
-
- n = session_n_datasets (session);
- datasets = xmalloc (n * sizeof *datasets);
- p = datasets;
+ size_t n = session_n_datasets (session);
+ struct dataset **datasets = xmalloc (n * sizeof *datasets);
+ struct dataset **p = datasets;
session_for_each_dataset (session, dataset_display_cb, &p);
qsort (datasets, n, sizeof *datasets, sort_datasets);
- t = tab_create (1, n + 1);
- tab_headers (t, 0, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, -1, TAL_1, 0, 0, tab_nc (t) - 1, tab_nr (t) - 1);
- tab_hline (t, TAL_2, 0, 0, 1);
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Dataset"));
- for (i = 0; i < n; i++)
+ struct pivot_table *table = pivot_table_create (N_("Datasets"));
+
+ struct pivot_dimension *datasets_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dataset"));
+ datasets_dim->hide_all_labels = true;
+
+ for (size_t i = 0; i < n; i++)
{
struct dataset *ds = datasets[i];
const char *name;
if (name[0] == '\0')
name = _("unnamed dataset");
- if (ds == session_active_dataset (session))
- tab_text_format (t, 0, i + 1, TAB_LEFT, "%s %s",
- name, _("(active dataset)"));
- else
- tab_text (t, 0, i + 1, TAB_LEFT, name);
+ char *text = (ds == session_active_dataset (session)
+ ? xasprintf ("%s (%s)", name, _("active dataset"))
+ : xstrdup (name));
+
+ int dataset_idx = pivot_category_create_leaf (
+ datasets_dim->root, pivot_value_new_integer (i));
+
+ pivot_table_put1 (table, dataset_idx,
+ pivot_value_new_user_text_nocopy (text));
}
- tab_title (t, "Open datasets.");
- tab_submit (t);
- free (datasets);
+ pivot_table_submit (table);
return CMD_SUCCESS;
}
#include "libpspp/ll.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "output/table-item.h"
#include "gl/intprops.h"
#include "gl/xmalloca.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
enum numbering
grouper = casegrouper_create_splits (proc_open (ds), dict);
while (casegrouper_get_next_group (grouper, &group))
{
- struct ccase *ccase;
- struct table *t = NULL;
-
- ccase = casereader_peek (group, 0);
- if (ccase != NULL)
+ struct ccase *c = casereader_peek (group, 0);
+ if (c != NULL)
{
- output_split_file_values (ds, ccase);
- case_unref (ccase);
+ output_split_file_values (ds, c);
+ case_unref (c);
}
group = casereader_project (group, &sc);
- if (lcmd->numbering == format_numbered)
- group = casereader_create_arithmetic_sequence (group, 1, 1);
group = casereader_select (group, lcmd->first - 1,
(lcmd->last != LONG_MAX ? lcmd->last
: CASENUMBER_MAX), lcmd->step);
- if (lcmd->numbering == format_numbered)
- {
- struct fmt_spec fmt;
- size_t col;
- int width;
+ struct pivot_table *table = pivot_table_create (N_("Data List"));
+ table->show_values = table->show_variables = SETTINGS_VALUE_SHOW_VALUE;
- width = lcmd->last == LONG_MAX ? 5 : intlog10 (lcmd->last);
- fmt = fmt_for_output (FMT_F, width, 0);
- col = caseproto_get_n_widths (casereader_get_proto (group)) - 1;
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Variables"));
+ for (int i = 0; i < lcmd->n_variables; i++)
+ pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (lcmd->v_variables[i]));
- t = table_from_casereader (group, col, _("Case Number"), &fmt);
- }
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Case Number"));
+ if (lcmd->numbering == format_numbered)
+ cases->root->show_label = true;
else
- t = NULL;
+ cases->hide_all_labels = true;
- for (i = 0; i < lcmd->n_variables; i++)
+ casenumber case_num = 1;
+ for (; (c = casereader_read (group)) != NULL; case_unref (c))
{
- const struct variable *var = lcmd->v_variables[i];
- struct table *c;
+ int case_idx = pivot_category_create_leaf (
+ cases->root, pivot_value_new_integer (case_num++));
- c = table_from_casereader (group, i, var_get_name (var),
- var_get_print_format (var));
- t = table_hpaste (t, c);
+ for (int i = 0; i < lcmd->n_variables; i++)
+ pivot_table_put2 (table, i, case_idx,
+ pivot_value_new_var_value (
+ lcmd->v_variables[i], case_data_idx (c, i)));
}
-
casereader_destroy (group);
- if (t)
- table_item_submit (table_item_create (t, "Data List", NULL));
+ pivot_table_submit (table);
}
ok = casegrouper_destroy (grouper);
ok = proc_commit (ds) && ok;
#include "libpspp/misc.h"
#include "libpspp/pool.h"
#include "libpspp/u8-line.h"
+#include "output/pivot-table.h"
#include "output/tab.h"
#include "output/text-item.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
/* Describes what to do when an output field is encountered. */
static trns_free_func print_trns_free;
static bool parse_specs (struct lexer *, struct pool *tmp_pool, struct print_trns *,
struct dictionary *dict, enum which_formats);
-static void dump_table (struct print_trns *, const struct file_handle *);
+static void dump_table (struct print_trns *);
\f
/* Basic parsing. */
/* Output the variable table if requested. */
if (print_table)
- dump_table (trns, fh);
+ dump_table (trns);
/* Put the transformation in the queue. */
add_transformation (ds,
/* Prints the table produced by the TABLE subcommand to the listing
file. */
static void
-dump_table (struct print_trns *trns, const struct file_handle *fh)
+dump_table (struct print_trns *trns)
{
+ struct pivot_table *table = pivot_table_create (N_("Print Summary"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Attributes"),
+ N_("Record"), N_("Columns"), N_("Format"));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+
struct prt_out_spec *spec;
- struct tab_table *t;
- int spec_cnt;
- int row;
-
- spec_cnt = ll_count (&trns->specs);
- t = tab_create (4, spec_cnt + 1);
- tab_box (t, TAL_1, TAL_1, TAL_0, TAL_1, 0, 0, 3, spec_cnt);
- tab_hline (t, TAL_2, 0, 3, 1);
- tab_headers (t, 0, 0, 1, 0);
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Variable"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Record"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Columns"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Format"));
- row = 1;
ll_for_each (spec, struct prt_out_spec, ll, &trns->specs)
{
+ if (spec->type != PRT_VAR)
+ continue;
+
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (spec->var));
+
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_integer (spec->record));
+ int last_column = spec->first_column + spec->format.w - 1;
+ pivot_table_put2 (table, 1, row, pivot_value_new_user_text_nocopy (
+ xasprintf ("%3d-%3d",
+ spec->first_column, last_column)));
+
char fmt_string[FMT_STRING_LEN_MAX + 1];
- int width;
- switch (spec->type)
- {
- case PRT_LITERAL:
- tab_text_format (t, 0, row, TAB_LEFT | TAB_FIX, "`%.*s'",
- (int) ds_length (&spec->string),
- ds_data (&spec->string));
- width = ds_length (&spec->string);
- break;
- case PRT_VAR:
- tab_text (t, 0, row, TAB_LEFT, var_get_name (spec->var));
- tab_text (t, 3, row, TAB_LEFT | TAB_FIX,
- fmt_to_string (&spec->format, fmt_string));
- width = spec->format.w;
- break;
- default:
- NOT_REACHED ();
- }
- tab_text_format (t, 1, row, 0, "%d", spec->record);
- tab_text_format (t, 2, row, 0, "%3d-%3d",
- spec->first_column, spec->first_column + width - 1);
- row++;
+ pivot_table_put2 (table, 2, row, pivot_value_new_user_text (
+ fmt_to_string (&spec->format, fmt_string), -1));
}
- if (fh != NULL)
- tab_title (t, ngettext ("Writing %zu record to %s.",
- "Writing %zu records to %s.", trns->record_cnt),
- trns->record_cnt, fh_get_name (fh));
- else
- tab_title (t, ngettext ("Writing %zu record.",
- "Writing %zu records.", trns->record_cnt),
- trns->record_cnt);
- tab_submit (t);
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_text (N_("N of Records")));
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_integer (trns->record_cnt));
+
+ pivot_table_submit (table);
}
\f
/* Transformation, for all-text output. */
#include "libpspp/str.h"
#include "libpspp/stringi-map.h"
#include "libpspp/stringi-set.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static bool parse_group (struct lexer *, struct dictionary *, enum mrset_type);
static bool
parse_display (struct lexer *lexer, struct dictionary *dict)
{
- struct string details, var_names;
struct stringi_set mrset_names_set;
- char **mrset_names;
- struct tab_table *table;
- size_t i, n;
-
if (!parse_mrset_names (lexer, dict, &mrset_names_set))
return false;
- n = stringi_set_count (&mrset_names_set);
+ size_t n = stringi_set_count (&mrset_names_set);
if (n == 0)
{
if (dict_get_n_mrsets (dict) == 0)
return true;
}
- table = tab_create (3, n + 1);
- tab_headers (table, 0, 0, 1, 0);
- tab_box (table, TAL_1, TAL_1, TAL_1, TAL_1, 0, 0, 2, n);
- tab_hline (table, TAL_2, 0, 2, 1);
- tab_title (table, "%s", _("Multiple Response Sets"));
- tab_text (table, 0, 0, TAB_EMPH | TAB_LEFT, _("Name"));
- tab_text (table, 1, 0, TAB_EMPH | TAB_LEFT, _("Variables"));
- tab_text (table, 2, 0, TAB_EMPH | TAB_LEFT, _("Details"));
-
- ds_init_empty (&details);
- ds_init_empty (&var_names);
- mrset_names = stringi_set_get_sorted_array (&mrset_names_set);
- for (i = 0; i < n; i++)
+ struct pivot_table *table = pivot_table_create (
+ N_("Multiple Response Sets"));
+
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Attributes"),
+ N_("Label"), N_("Encoding"), N_("Counted Value"), N_("Member Variables"));
+
+ struct pivot_dimension *mrsets = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Name"));
+ mrsets->root->show_label = true;
+
+ char **mrset_names = stringi_set_get_sorted_array (&mrset_names_set);
+ for (size_t i = 0; i < n; i++)
{
const struct mrset *mrset = dict_lookup_mrset (dict, mrset_names[i]);
- const int row = i + 1;
- size_t j;
-
- /* Details. */
- ds_clear (&details);
- ds_put_format (&details, "%s\n", (mrset->type == MRSET_MD
- ? _("Multiple dichotomy set")
- : _("Multiple category set")));
+
+ int row = pivot_category_create_leaf (
+ mrsets->root, pivot_value_new_user_text (mrset->name, -1));
+
if (mrset->label != NULL)
- ds_put_format (&details, "%s: %s\n", _("Label"), mrset->label);
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_user_text (mrset->label, -1));
+
+ pivot_table_put2 (table, 1, row,
+ pivot_value_new_text (mrset->type == MRSET_MD
+ ? _("Dichotomies")
+ : _("Categories")));
+
if (mrset->type == MRSET_MD)
- {
- if (mrset->label != NULL || mrset->label_from_var_label)
- ds_put_format (&details, "%s: %s\n", _("Label source"),
- (mrset->label_from_var_label
- ? _("First variable label among variables")
- : _("Provided by user")));
- ds_put_format (&details, "%s: ", _("Counted value"));
- if (mrset->width == 0)
- ds_put_format (&details, "%.0f\n", mrset->counted.f);
- else
- {
- const uint8_t *raw = value_str (&mrset->counted, mrset->width);
- char *utf8 = recode_string ("UTF-8", dict_get_encoding (dict),
- CHAR_CAST (const char *, raw),
- mrset->width);
- ds_put_format (&details, "`%s'\n", utf8);
- free (utf8);
- }
- ds_put_format (&details, "%s: %s\n", _("Category label source"),
- (mrset->cat_source == MRSET_VARLABELS
- ? _("Variable labels")
- : _("Value labels of counted value")));
- }
+ pivot_table_put2 (table, 2, row,
+ pivot_value_new_value (
+ &mrset->counted, mrset->width,
+ &F_8_0, dict_get_encoding (dict)));
/* Variable names. */
- ds_clear (&var_names);
- for (j = 0; j < mrset->n_vars; j++)
+ struct string var_names = DS_EMPTY_INITIALIZER;
+ for (size_t j = 0; j < mrset->n_vars; j++)
ds_put_format (&var_names, "%s\n", var_get_name (mrset->vars[j]));
-
- tab_text (table, 0, row, TAB_LEFT, mrset_names[i]);
- tab_text (table, 1, row, TAB_LEFT, ds_cstr (&var_names));
- tab_text (table, 2, row, TAB_LEFT, ds_cstr (&details));
+ ds_chomp_byte (&var_names, '\n');
+ pivot_table_put2 (table, 3, row,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&var_names)));
}
free (mrset_names);
- ds_destroy (&var_names);
- ds_destroy (&details);
stringi_set_destroy (&mrset_names_set);
- tab_submit (table);
+ pivot_table_submit (table);
return true;
}
#include "language/lexer/variable-parser.h"
#include "libpspp/message.h"
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
int
output_split_file_values (const struct dataset *ds, const struct ccase *c)
{
const struct dictionary *dict = dataset_dict (ds);
- const struct variable *const *split;
- struct tab_table *t;
- size_t split_cnt;
- int i;
-
- split_cnt = dict_get_split_cnt (dict);
- if (split_cnt == 0)
+ size_t n_vars = dict_get_split_cnt (dict);
+ if (n_vars == 0)
return;
- t = tab_create (3, split_cnt + 1);
- tab_text (t, 0, 0, TAB_NONE, _("Variable"));
- tab_text (t, 1, 0, TAB_LEFT, _("Value"));
- tab_text (t, 2, 0, TAB_LEFT, _("Label"));
- split = dict_get_split_vars (dict);
- for (i = 0; i < split_cnt; i++)
- {
- const struct variable *v = split[i];
- char *s;
- const char *val_lab;
- const struct fmt_spec *print = var_get_print_format (v);
-
- tab_text_format (t, 0, i + 1, TAB_LEFT, "%s", var_get_name (v));
-
- s = data_out (case_data (c, v), dict_get_encoding (dict), print);
+ struct pivot_table *table = pivot_table_create (N_("Split Values"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Value"),
+ N_("Value"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+ variables->root->show_label = true;
- tab_text_format (t, 1, i + 1, 0, "%.*s", print->w, s);
-
- free (s);
+ for (size_t i = 0; i < n_vars; i++)
+ {
+ const struct variable *v = dict_get_split_vars (dict)[i];
+ int row = pivot_category_create_leaf (variables->root,
+ pivot_value_new_variable (v));
- val_lab = var_lookup_value_label (v, case_data (c, v));
- if (val_lab)
- tab_text (t, 2, i + 1, TAB_LEFT, val_lab);
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_var_value (v, case_data (c, v)));
}
- tab_submit (t);
+
+ pivot_table_submit (table);
}
#include "libpspp/misc.h"
#include "libpspp/pool.h"
#include "libpspp/string-array.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "output/text-item.h"
#include "output/table-item.h"
char **titles, bool *ids,
char **strings, size_t n_strings);
+static void
+add_row (struct pivot_table *table, const char *attribute,
+ struct pivot_value *value)
+{
+ int row = pivot_category_create_leaf (table->dimensions[0]->root,
+ pivot_value_new_text (attribute));
+ if (value)
+ pivot_table_put1 (table, row, value);
+}
+
/* SYSFILE INFO utility. */
int
cmd_sysfile_info (struct lexer *lexer, struct dataset *ds UNUSED)
struct any_reader *any_reader;
struct file_handle *h;
struct dictionary *d;
- struct tab_table *t;
struct casereader *reader;
struct any_read_info info;
char *encoding;
- int r;
h = NULL;
encoding = NULL;
goto error;
casereader_destroy (reader);
- t = tab_create (2, 11 + (info.product_ext != NULL));
- r = 0;
-
- tab_text (t, 0, r, TAB_LEFT, _("File:"));
- tab_text (t, 1, r++, TAB_LEFT, fh_get_file_name (h));
-
- tab_text (t, 0, r, TAB_LEFT, _("Label:"));
- {
- const char *label = dict_get_label (d);
- if (label == NULL)
- label = _("No label.");
- tab_text (t, 1, r++, TAB_LEFT, label);
- }
-
- tab_text (t, 0, r, TAB_LEFT, _("Created:"));
- tab_text_format (t, 1, r++, TAB_LEFT, "%s %s by %s",
- info.creation_date, info.creation_time, info.product);
-
- if (info.product_ext)
- {
- tab_text (t, 0, r, TAB_LEFT, _("Product:"));
- tab_text (t, 1, r++, TAB_LEFT, info.product_ext);
- }
-
- tab_text (t, 0, r, TAB_LEFT, _("Integer Format:"));
- tab_text (t, 1, r++, TAB_LEFT,
- info.integer_format == INTEGER_MSB_FIRST ? _("Big Endian")
- : info.integer_format == INTEGER_LSB_FIRST ? _("Little Endian")
- : _("Unknown"));
-
- tab_text (t, 0, r, TAB_LEFT, _("Real Format:"));
- tab_text (t, 1, r++, TAB_LEFT,
- info.float_format == FLOAT_IEEE_DOUBLE_LE ? _("IEEE 754 LE.")
- : info.float_format == FLOAT_IEEE_DOUBLE_BE ? _("IEEE 754 BE.")
- : info.float_format == FLOAT_VAX_D ? _("VAX D.")
- : info.float_format == FLOAT_VAX_G ? _("VAX G.")
- : info.float_format == FLOAT_Z_LONG ? _("IBM 390 Hex Long.")
- : _("Unknown"));
-
- tab_text (t, 0, r, TAB_LEFT, _("Variables:"));
- tab_text_format (t, 1, r++, TAB_LEFT, "%zu", dict_get_var_cnt (d));
-
- tab_text (t, 0, r, TAB_LEFT, _("Cases:"));
- if (info.case_cnt == -1)
- tab_text (t, 1, r, TAB_LEFT, _("Unknown"));
- else
- tab_text_format (t, 1, r, TAB_LEFT, "%ld", (long int) info.case_cnt);
- r++;
-
- tab_text (t, 0, r, TAB_LEFT, _("Type:"));
- tab_text (t, 1, r++, TAB_LEFT, gettext (info.klass->name));
+ struct pivot_table *table = pivot_table_create (N_("File Information"));
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Attribute"));
- tab_text (t, 0, r, TAB_LEFT, _("Weight:"));
- {
- struct variable *weight_var = dict_get_weight (d);
- tab_text (t, 1, r++, TAB_LEFT,
- (weight_var != NULL
- ? var_get_name (weight_var) : _("Not weighted.")));
- }
+ add_row (table, N_("File"),
+ pivot_value_new_user_text (fh_get_file_name (h), -1));
- tab_text (t, 0, r, TAB_LEFT, _("Compression:"));
- tab_text_format (t, 1, r++, TAB_LEFT,
- info.compression == ANY_COMP_NONE ? _("None")
- : info.compression == ANY_COMP_SIMPLE ? "SAV"
- : "ZSAV");
+ const char *label = dict_get_label (d);
+ add_row (table, N_("Label"),
+ label ? pivot_value_new_user_text (label, -1) : NULL);
- tab_text (t, 0, r, TAB_LEFT, _("Encoding:"));
- tab_text (t, 1, r++, TAB_LEFT, dict_get_encoding (d));
+ add_row (table, N_("Created"),
+ pivot_value_new_user_text_nocopy (
+ xasprintf ("%s %s by %s", info.creation_date,
+ info.creation_time, info.product)));
- tab_submit (t);
+ if (info.product_ext)
+ add_row (table, N_("Product"),
+ pivot_value_new_user_text (info.product_ext, -1));
+
+ add_row (table, N_("Integer Format"),
+ pivot_value_new_text (
+ info.integer_format == INTEGER_MSB_FIRST ? N_("Big Endian")
+ : info.integer_format == INTEGER_LSB_FIRST ? N_("Little Endian")
+ : N_("Unknown")));
+
+ add_row (table, N_("Real Format"),
+ pivot_value_new_text (
+ info.float_format == FLOAT_IEEE_DOUBLE_LE ? N_("IEEE 754 LE.")
+ : info.float_format == FLOAT_IEEE_DOUBLE_BE ? N_("IEEE 754 BE.")
+ : info.float_format == FLOAT_VAX_D ? N_("VAX D.")
+ : info.float_format == FLOAT_VAX_G ? N_("VAX G.")
+ : info.float_format == FLOAT_Z_LONG ? N_("IBM 390 Hex Long.")
+ : N_("Unknown")));
+
+ add_row (table, N_("Variables"),
+ pivot_value_new_integer (dict_get_var_cnt (d)));
+
+ add_row (table, N_("Cases"),
+ (info.case_cnt == -1
+ ? pivot_value_new_text (N_("Unknown"))
+ : pivot_value_new_integer (info.case_cnt)));
+
+ add_row (table, N_("Type"),
+ pivot_value_new_text (info.klass->name));
+
+ struct variable *weight_var = dict_get_weight (d);
+ add_row (table, N_("Weight"),
+ (weight_var
+ ? pivot_value_new_variable (weight_var)
+ : pivot_value_new_text (N_("Not weighted"))));
+
+ add_row (table, N_("Compression"),
+ (info.compression == ANY_COMP_NONE
+ ? pivot_value_new_text (N_("None"))
+ : pivot_value_new_user_text (
+ info.compression == ANY_COMP_SIMPLE ? "SAV" : "ZSAV", -1)));
+
+ add_row (table, N_("Encoding"),
+ pivot_value_new_user_text (dict_get_encoding (d), -1));
+
+ pivot_table_submit (table);
size_t n_vars = dict_get_var_cnt (d);
const struct variable **vars = xnmalloc (n_vars, sizeof *vars);
{
if (!lex_force_match_id (lexer, "LABEL"))
return CMD_FAILURE;
- if (dict_get_label (dataset_dict (ds)) == NULL)
- tab_output_text (TAB_LEFT,
- _("The active dataset does not have a file label."));
- else
- tab_output_text_format (TAB_LEFT, _("File label: %s"),
- dict_get_label (dataset_dict (ds)));
+
+ const char *label = dict_get_label (dataset_dict (ds));
+
+ struct pivot_table *table = pivot_table_create (N_("File Label"));
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Label"),
+ N_("Label"));
+ pivot_table_put1 (table, 0,
+ (label ? pivot_value_new_user_text (label, -1)
+ : pivot_value_new_text (N_("(none)"))));
+ pivot_table_submit (table);
}
else
{
static void
display_macros (void)
{
- tab_output_text (TAB_LEFT, _("Macros not supported."));
+ msg (SW, _("Macros not supported."));
}
static void
display_documents (const struct dictionary *dict)
{
- const struct string_array *documents = dict_get_documents (dict);
+ struct pivot_table *table = pivot_table_create (N_("Documents"));
+ struct pivot_dimension *d = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Documents"), N_("Document"));
+ d->hide_all_labels = true;
- if (string_array_is_empty (documents))
- tab_output_text (TAB_LEFT, _("The active dataset dictionary does not "
- "contain any documents."));
+ const struct string_array *documents = dict_get_documents (dict);
+ if (!documents->n)
+ pivot_table_put1 (table, 0, pivot_value_new_text (N_("(none)")));
else
{
- size_t i;
-
- tab_output_text (TAB_LEFT | TAT_TITLE,
- _("Documents in the active dataset:"));
- for (i = 0; i < dict_get_document_line_cnt (dict); i++)
- tab_output_text (TAB_LEFT | TAB_FIX, dict_get_document_line (dict, i));
+ struct string s = DS_EMPTY_INITIALIZER;
+ for (size_t i = 0; i < documents->n; i++)
+ {
+ if (i)
+ ds_put_byte (&s, '\n');
+ ds_put_cstr (&s, documents->strings[i]);
+ }
+ pivot_table_put1 (table, 0,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&s)));
}
+
+ pivot_table_submit (table);
}
static void
display_variables (const struct variable **vl, size_t n, int flags)
{
- int nc = count_one_bits (flags);
- struct tab_table *t = tab_create (nc, n + 1);
- tab_title (t, "%s", _("Variables"));
- tab_headers (t, 0, 0, 1, 0);
- tab_hline (t, TAL_2, 0, nc - 1, 1);
+ struct pivot_table *table = pivot_table_create (N_("Variables"));
+
+ struct pivot_dimension *attributes = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Attributes"));
struct heading
{
const char *title;
};
static const struct heading headings[] = {
- { DF_NAME, N_("Name") },
{ DF_POSITION, N_("Position") },
{ DF_LABEL, N_("Label") },
{ DF_MEASUREMENT_LEVEL, N_("Measurement Level") },
{ DF_WRITE_FORMAT, N_("Write Format") },
{ DF_MISSING_VALUES, N_("Missing Values") },
};
- for (size_t i = 0, x = 0; i < sizeof headings / sizeof *headings; i++)
+ for (size_t i = 0; i < sizeof headings / sizeof *headings; i++)
if (flags & headings[i].flag)
- tab_text (t, x++, 0, TAB_LEFT | TAT_TITLE, gettext (headings[i].title));
+ pivot_category_create_leaf (attributes->root,
+ pivot_value_new_text (headings[i].title));
+
+ struct pivot_dimension *names = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Name"));
+ names->root->show_label = true;
for (size_t i = 0; i < n; i++)
{
const struct variable *v = vl[i];
- size_t y = i + 1;
- size_t x = 0;
- if (flags & DF_NAME)
- tab_text (t, x++, y, TAB_LEFT, var_get_name (v));
+
+ struct pivot_value *name = pivot_value_new_variable (v);
+ name->variable.show = SETTINGS_VALUE_SHOW_VALUE;
+ int row = pivot_category_create_leaf (names->root, name);
+
+ int x = 0;
if (flags & DF_POSITION)
- {
- char s[INT_BUFSIZE_BOUND (size_t)];
+ pivot_table_put2 (table, x++, row, pivot_value_new_integer (
+ var_get_dict_index (v) + 1));
- sprintf (s, "%zu", var_get_dict_index (v) + 1);
- tab_text (t, x++, y, TAB_LEFT, s);
- }
if (flags & DF_LABEL)
{
const char *label = var_get_label (v);
if (label)
- tab_text (t, x, y, TAB_LEFT, label);
+ pivot_table_put2 (table, x, row,
+ pivot_value_new_user_text (label, -1));
x++;
}
+
if (flags & DF_MEASUREMENT_LEVEL)
- tab_text (t, x++, y, TAB_LEFT,
- gettext (measure_to_string (var_get_measure (v))));
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_text (measure_to_string (var_get_measure (v))));
+
if (flags & DF_ROLE)
- tab_text (t, x++, y, TAB_LEFT,
- gettext (var_role_to_string (var_get_role (v))));
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_text (var_role_to_string (var_get_role (v))));
+
if (flags & DF_WIDTH)
- {
- char s[INT_BUFSIZE_BOUND (int)];
- sprintf (s, "%d", var_get_display_width (v));
- tab_text (t, x++, y, TAB_RIGHT, s);
- }
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_integer (var_get_display_width (v)));
+
if (flags & DF_ALIGNMENT)
- tab_text (t, x++, y, TAB_LEFT,
- gettext (alignment_to_string (var_get_alignment (v))));
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_text (alignment_to_string (
+ var_get_alignment (v))));
+
if (flags & DF_PRINT_FORMAT)
{
const struct fmt_spec *print = var_get_print_format (v);
char s[FMT_STRING_LEN_MAX + 1];
- tab_text (t, x++, y, TAB_LEFT, fmt_to_string (print, s));
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_user_text (fmt_to_string (print, s), -1));
}
+
if (flags & DF_WRITE_FORMAT)
{
const struct fmt_spec *write = var_get_write_format (v);
char s[FMT_STRING_LEN_MAX + 1];
- tab_text (t, x++, y, TAB_LEFT, fmt_to_string (write, s));
+ pivot_table_put2 (
+ table, x++, row,
+ pivot_value_new_user_text (fmt_to_string (write, s), -1));
}
+
if (flags & DF_MISSING_VALUES)
{
- const struct missing_values *mv = var_get_missing_values (v);
-
- char *s = mv_to_string (mv, var_get_encoding (v));
+ char *s = mv_to_string (var_get_missing_values (v),
+ var_get_encoding (v));
if (s)
- {
- tab_text (t, x, y, TAB_LEFT, s);
- free (s);
- }
- x++;
+ pivot_table_put2 (
+ table, x, row,
+ pivot_value_new_user_text_nocopy (s));
- assert (x == nc);
+ x++;
}
}
- tab_submit (t);
+ pivot_table_submit (table);
+}
+
+static bool
+any_value_labels (const struct variable **vars, size_t n_vars)
+{
+ for (size_t i = 0; i < n_vars; i++)
+ if (val_labs_count (var_get_value_labels (vars[i])))
+ return true;
+ return false;
}
static void
display_value_labels (const struct variable **vars, size_t n_vars)
{
- size_t n_value_labels = 0;
- for (size_t i = 0; i < n_vars; i++)
- n_value_labels += val_labs_count (var_get_value_labels (vars[i]));
- if (!n_value_labels)
+ if (!any_value_labels (vars, n_vars))
return;
- struct tab_table *t = tab_create (3, n_value_labels + 1);
- tab_title (t, "%s", _("Value Labels"));
- tab_headers (t, 0, 0, 1, 0);
- tab_hline (t, TAL_2, 0, 2, 1);
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Variable"));
- tab_text (t, 1, 0, TAB_LEFT | TAT_TITLE, _("Value"));
- tab_text (t, 2, 0, TAB_LEFT | TAT_TITLE, _("Label"));
+ struct pivot_table *table = pivot_table_create (N_("Value Labels"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN,
+ N_("Label"), N_("Label"));
+
+ struct pivot_dimension *values = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable Value"));
+ values->root->show_label = true;
+
+ struct pivot_footnote *missing_footnote = pivot_table_create_footnote (
+ table, pivot_value_new_text (N_("User-missing value")));
- int y = 1;
for (size_t i = 0; i < n_vars; i++)
{
const struct val_labs *val_labs = var_get_value_labels (vars[i]);
if (!n_labels)
continue;
- tab_joint_text (t, 0, y, 0, y + (n_labels - 1), TAB_LEFT,
- var_get_name (vars[i]));
+ struct pivot_category *group = pivot_category_create_group__ (
+ values->root, pivot_value_new_variable (vars[i]));
const struct val_lab **labels = val_labs_sorted (val_labs);
for (size_t j = 0; j < n_labels; j++)
{
const struct val_lab *vl = labels[j];
- tab_value (t, 1, y, TAB_NONE, &vl->value, vars[i], NULL);
- tab_text (t, 2, y, TAB_LEFT, val_lab_get_escaped_label (vl));
- y++;
+ struct pivot_value *value = pivot_value_new_var_value (
+ vars[i], &vl->value);
+ if (value->type == PIVOT_VALUE_NUMERIC)
+ value->numeric.show = SETTINGS_VALUE_SHOW_VALUE;
+ else
+ value->string.show = SETTINGS_VALUE_SHOW_VALUE;
+ if (var_is_value_missing (vars[i], &vl->value, MV_USER))
+ pivot_value_add_footnote (value, missing_footnote);
+ int row = pivot_category_create_leaf (group, value);
+
+ struct pivot_value *label = pivot_value_new_var_value (
+ vars[i], &vl->value);
+ char *escaped_label = xstrdup (val_lab_get_escaped_label (vl));
+ if (label->type == PIVOT_VALUE_NUMERIC)
+ {
+ free (label->numeric.value_label);
+ label->numeric.value_label = escaped_label;
+ label->numeric.show = SETTINGS_VALUE_SHOW_LABEL;
+ }
+ else
+ {
+ free (label->string.value_label);
+ label->string.value_label = escaped_label;
+ label->string.show = SETTINGS_VALUE_SHOW_LABEL;
+ }
+ pivot_table_put2 (table, 0, row, label);
}
free (labels);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
\f
static bool
return n_attrs;
}
-static int
-display_attrset (const char *name, const struct attrset *set, int flags,
- struct tab_table *t, int y)
+static void
+display_attrset (struct pivot_table *table, struct pivot_value *set_name,
+ const struct attrset *set, int flags)
{
size_t n_total = count_attributes (set, flags);
if (!n_total)
- return y;
+ {
+ pivot_value_destroy (set_name);
+ return;
+ }
- tab_joint_text (t, 0, y, 0, y + (n_total - 1), TAB_LEFT, name);
+ struct pivot_category *group = pivot_category_create_group__ (
+ table->dimensions[1]->root, set_name);
size_t n_attrs = attrset_count (set);
struct attribute **attrs = attrset_sorted (set);
size_t n_values = attribute_get_n_values (attr);
for (size_t j = 0; j < n_values; j++)
{
- if (n_values > 1)
- tab_text_format (t, 1, y, TAB_LEFT, "%s[%zu]", name, j + 1);
- else
- tab_text (t, 1, y, TAB_LEFT, name);
- tab_text (t, 2, y, TAB_LEFT, attribute_get_value (attr, j));
- y++;
+ int row = pivot_category_create_leaf (
+ group,
+ (n_values > 1
+ ? pivot_value_new_user_text_nocopy (xasprintf (
+ "%s[%zu]", name, j + 1))
+ : pivot_value_new_user_text (name, -1)));
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_user_text (
+ attribute_get_value (attr, j), -1));
}
}
free (attrs);
-
- return y;
}
static void
display_attributes (const struct attrset *dict_attrset,
const struct variable **vars, size_t n_vars, int flags)
{
- size_t n_attributes = count_attributes (dict_attrset, flags);
- for (size_t i = 0; i < n_vars; i++)
- n_attributes += count_attributes (var_get_attributes (vars[i]), flags);
- if (!n_attributes)
- return;
+ struct pivot_table *table = pivot_table_create (
+ N_("Variable and Dataset Attributes"));
- struct tab_table *t = tab_create (3, n_attributes + 1);
- tab_title (t, "%s", _("Variable and Dataset Attributes"));
- tab_headers (t, 0, 0, 1, 0);
- tab_hline (t, TAL_2, 0, 2, 1);
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Variable"));
- tab_text (t, 1, 0, TAB_LEFT | TAT_TITLE, _("Name"));
- tab_text (t, 2, 0, TAB_LEFT | TAT_TITLE, _("Value"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN,
+ N_("Value"), N_("Value"));
- int y = display_attrset (_("(dataset)"), dict_attrset, flags, t, 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable and Name"));
+ variables->root->show_label = true;
+
+ display_attrset (table, pivot_value_new_text (N_("(dataset)")),
+ dict_attrset, flags);
for (size_t i = 0; i < n_vars; i++)
- y = display_attrset (var_get_name (vars[i]), var_get_attributes (vars[i]),
- flags, t, y);
+ display_attrset (table, pivot_value_new_variable (vars[i]),
+ var_get_attributes (vars[i]), flags);
- tab_submit (t);
+ if (pivot_table_is_empty (table))
+ pivot_table_destroy (table);
+ else
+ pivot_table_submit (table);
}
/* Display a list of vectors. If SORTED is nonzero then they are
static void
display_vectors (const struct dictionary *dict, int sorted)
{
- const struct vector **vl;
- int i;
- struct tab_table *t;
- size_t nvec;
- size_t nrow;
- size_t row;
-
- nvec = dict_get_vector_cnt (dict);
- if (nvec == 0)
+ size_t n_vectors = dict_get_vector_cnt (dict);
+ if (n_vectors == 0)
{
msg (SW, _("No vectors defined."));
return;
}
- vl = xnmalloc (nvec, sizeof *vl);
- nrow = 0;
- for (i = 0; i < nvec; i++)
- {
- vl[i] = dict_get_vector (dict, i);
- nrow += vector_get_var_cnt (vl[i]);
- }
+ const struct vector **vectors = xnmalloc (n_vectors, sizeof *vectors);
+ for (size_t i = 0; i < n_vectors; i++)
+ vectors[i] = dict_get_vector (dict, i);
if (sorted)
- qsort (vl, nvec, sizeof *vl, compare_vector_ptrs_by_name);
-
- t = tab_create (4, nrow + 1);
- tab_headers (t, 0, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, -1, -1, 0, 0, 3, nrow);
- tab_box (t, -1, -1, -1, TAL_1, 0, 0, 3, nrow);
- tab_hline (t, TAL_2, 0, 3, 1);
- tab_text (t, 0, 0, TAT_TITLE | TAB_LEFT, _("Vector"));
- tab_text (t, 1, 0, TAT_TITLE | TAB_LEFT, _("Position"));
- tab_text (t, 2, 0, TAT_TITLE | TAB_LEFT, _("Variable"));
- tab_text (t, 3, 0, TAT_TITLE | TAB_LEFT, _("Print Format"));
-
- row = 1;
- for (i = 0; i < nvec; i++)
+ qsort (vectors, n_vectors, sizeof *vectors, compare_vector_ptrs_by_name);
+
+ struct pivot_table *table = pivot_table_create (N_("Vectors"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Attributes"),
+ N_("Variable"), N_("Print Format"));
+ struct pivot_dimension *vector_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Vector and Position"));
+ vector_dim->root->show_label = true;
+
+ for (size_t i = 0; i < n_vectors; i++)
{
- const struct vector *vec = vl[i];
- size_t j;
+ const struct vector *vec = vectors[i];
- tab_joint_text (t, 0, row, 0, row + vector_get_var_cnt (vec) - 1,
- TAB_LEFT, vector_get_name (vl[i]));
+ struct pivot_category *group = pivot_category_create_group__ (
+ vector_dim->root, pivot_value_new_user_text (
+ vector_get_name (vectors[i]), -1));
- for (j = 0; j < vector_get_var_cnt (vec); j++)
+ for (size_t j = 0; j < vector_get_var_cnt (vec); j++)
{
struct variable *var = vector_get_var (vec, j);
+
+ int row = pivot_category_create_leaf (
+ group, pivot_value_new_integer (j + 1));
+
+ pivot_table_put2 (table, 0, row, pivot_value_new_variable (var));
char fmt_string[FMT_STRING_LEN_MAX + 1];
fmt_to_string (var_get_print_format (var), fmt_string);
-
- tab_text_format (t, 1, row, TAB_RIGHT, "%zu", j + 1);
- tab_text (t, 2, row, TAB_LEFT, var_get_name (var));
- tab_text (t, 3, row, TAB_LEFT, fmt_string);
- row++;
+ pivot_table_put2 (table, 1, row,
+ pivot_value_new_user_text (fmt_string, -1));
}
- tab_hline (t, TAL_1, 0, 3, row);
}
- tab_submit (t);
+ pivot_table_submit (table);
- free (vl);
+ free (vectors);
}
\f
/* Encoding analysis. */
{
struct encoding encodings[N_ENCODING_NAMES];
size_t n_encodings, n_unique_strings;
- size_t i, j;
- struct tab_table *t;
- size_t row;
n_encodings = 0;
- for (i = 0; i < N_ENCODING_NAMES; i++)
+ for (size_t i = 0; i < N_ENCODING_NAMES; i++)
{
char **utf8_strings;
struct encoding *e;
/* Hash utf8_strings. */
hash = 0;
- for (j = 0; j < n_strings; j++)
+ for (size_t j = 0; j < n_strings; j++)
hash = hash_string (utf8_strings[j], hash);
/* If there's a duplicate encoding, just mark it. */
return;
}
- t = tab_create (2, n_encodings + 1);
- tab_title (t, _("Usable encodings for %s."), fh_get_name (h));
- tab_caption (t, _("Encodings that can successfully read %s (by specifying "
- "the encoding name on the GET command's ENCODING "
- "subcommand). Encodings that yield identical text are "
- "listed together."), fh_get_name (h));
- tab_headers (t, 1, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, -1, -1, 0, 0, 1, n_encodings);
- tab_hline (t, TAL_1, 0, 1, 1);
- tab_text (t, 0, 0, TAB_RIGHT, "#");
- tab_text (t, 1, 0, TAB_LEFT, _("Encodings"));
- for (i = 0; i < n_encodings; i++)
+ /* Table of valid encodings. */
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("Usable encodings for %s."),
+ fh_get_name (h)));
+ table->caption = pivot_value_new_text_format (
+ N_("Encodings that can successfully read %s (by specifying the encoding "
+ "name on the GET command's ENCODING subcommand). Encodings that "
+ "yield identical text are listed together."),
+ fh_get_name (h));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Encodings"),
+ N_("Encodings"));
+ struct pivot_dimension *number = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_user_text ("#", -1));
+ number->root->show_label = true;
+
+ for (size_t i = 0; i < n_encodings; i++)
{
- struct string s;
-
- ds_init_empty (&s);
- for (j = 0; j < 64; j++)
+ struct string s = DS_EMPTY_INITIALIZER;
+ for (size_t j = 0; j < 64; j++)
if (encodings[i].encodings & (UINT64_C (1) << j))
ds_put_format (&s, "%s, ", encoding_names[j]);
ds_chomp (&s, ss_cstr (", "));
- tab_text_format (t, 0, i + 1, TAB_RIGHT, "%zu", i + 1);
- tab_text (t, 1, i + 1, TAB_LEFT, ds_cstr (&s));
- ds_destroy (&s);
+ int row = pivot_category_create_leaf (number->root,
+ pivot_value_new_integer (i + 1));
+ pivot_table_put2 (
+ table, 0, row, pivot_value_new_user_text_nocopy (ds_steal_cstr (&s)));
}
- tab_submit (t);
+ pivot_table_submit (table);
n_unique_strings = 0;
- for (i = 0; i < n_strings; i++)
+ for (size_t i = 0; i < n_strings; i++)
if (!all_equal (encodings, n_encodings, i))
n_unique_strings++;
if (!n_unique_strings)
return;
- t = tab_create (3, (n_encodings * n_unique_strings) + 1);
- tab_title (t, _("%s encoded text strings."), fh_get_name (h));
- tab_caption (t, _("Text strings in the file dictionary that the previously "
- "listed encodings interpret differently, along with the "
- "interpretations."));
- tab_headers (t, 1, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, -1, -1, 0, 0, 2, n_encodings * n_unique_strings);
- tab_hline (t, TAL_1, 0, 2, 1);
-
- tab_text (t, 0, 0, TAB_LEFT, _("Purpose"));
- tab_text (t, 1, 0, TAB_RIGHT, "#");
- tab_text (t, 2, 0, TAB_LEFT, _("Text"));
-
- row = 1;
- for (i = 0; i < n_strings; i++)
+ /* Table of alternative interpretations. */
+ table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("%s Encoded Text Strings"),
+ fh_get_name (h)));
+ table->caption = pivot_value_new_text (
+ N_("Text strings in the file dictionary that the previously listed "
+ "encodings interpret differently, along with the interpretations."));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Text"), N_("Text"));
+
+ number = pivot_dimension_create__ (table, PIVOT_AXIS_ROW,
+ pivot_value_new_user_text ("#", -1));
+ number->root->show_label = true;
+ for (size_t i = 0; i < n_encodings; i++)
+ pivot_category_create_leaf (number->root,
+ pivot_value_new_integer (i + 1));
+
+ struct pivot_dimension *purpose = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Purpose"));
+ purpose->root->show_label = true;
+
+ for (size_t i = 0; i < n_strings; i++)
if (!all_equal (encodings, n_encodings, i))
{
int prefix = equal_prefix (encodings, n_encodings, i);
int suffix = equal_suffix (encodings, n_encodings, i);
- tab_joint_text (t, 0, row, 0, row + n_encodings - 1,
- TAB_LEFT, titles[i]);
- tab_hline (t, TAL_1, 0, 2, row);
- for (j = 0; j < n_encodings; j++)
+ int purpose_idx = pivot_category_create_leaf (
+ purpose->root, pivot_value_new_user_text (titles[i], -1));
+
+ for (size_t j = 0; j < n_encodings; j++)
{
const char *s = encodings[j].utf8_strings[i] + prefix;
- tab_text_format (t, 1, row, TAB_RIGHT, "%zu", j + 1);
if (prefix || suffix)
{
size_t len = strlen (s) - suffix;
ds_put_substring (&entry, ss_buffer (s, len));
if (suffix)
ds_put_cstr (&entry, "...");
- tab_text (t, 2, row, TAB_LEFT, ds_cstr (&entry));
+
+ pivot_table_put3 (table, 0, j, purpose_idx,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&entry)));
}
else
- tab_text (t, 2, row, TAB_LEFT, s);
- row++;
+ pivot_table_put3 (table, 0, j, purpose_idx,
+ pivot_value_new_user_text (s, -1));
}
}
- tab_submit (t);
+
+ pivot_table_submit (table);
}
#include "libpspp/compiler.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gl/minmax.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static double calculate_binomial_internal (double n1, double n2,
bool exact UNUSED,
double timer UNUSED)
{
- int v;
const struct dictionary *dict = dataset_dict (ds);
const struct one_sample_test *ost = UP_CAST (test, const struct one_sample_test, parent);
const struct binomial_test *bst = UP_CAST (ost, const struct binomial_test, parent);
value = bst->category2;
cat[i] = xnmalloc (ost->n_vars, sizeof *cat[i]);
- for (v = 0; v < ost->n_vars; v++)
+ for (size_t v = 0; v < ost->n_vars; v++)
{
cat[i][v].values[0].f = value;
cat[i][v].count = 0;
if (do_binomial (dataset_dict (ds), input, ost, cat[0], cat[1], exclude))
{
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- struct tab_table *table = tab_create (7, ost->n_vars * 3 + 1);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_title (table, _("Binomial Test"));
-
- tab_headers (table, 2, 0, 1, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr(table) - 1 );
-
- for (v = 0 ; v < ost->n_vars; ++v)
+ struct pivot_table *table = pivot_table_create (N_("Binomial Test"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Category"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Observed Prop."), PIVOT_RC_OTHER,
+ N_("Test Prop."), PIVOT_RC_OTHER,
+ (bst->p == 0.5
+ ? N_("Exact Sig. (2-tailed)")
+ : N_("Exact Sig. (1-tailed)")), PIVOT_RC_SIGNIFICANCE);
+
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Groups"),
+ N_("Group 1"), N_("Group 2"), N_("Total"));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t v = 0; v < ost->n_vars; ++v)
{
- double n_total, sig;
- struct string catstr[2];
const struct variable *var = ost->vars[v];
- ds_init_empty (&catstr[0]);
- ds_init_empty (&catstr[1]);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (var));
- if ( bst->cutpoint != SYSMIS)
- {
- ds_put_format (&catstr[0], "<= %.*g",
- DBL_DIG + 1, bst->cutpoint);
- }
+ /* Category. */
+ if (bst->cutpoint != SYSMIS)
+ pivot_table_put3 (
+ table, 0, 0, var_idx,
+ pivot_value_new_user_text_nocopy (
+ xasprintf ("<= %.*g", DBL_DIG + 1, bst->cutpoint)));
else
+ for (int i = 0; i < 2; i++)
+ pivot_table_put3 (
+ table, 0, i, var_idx,
+ pivot_value_new_var_value (var, cat[i][v].values));
+
+ double n_total = cat[0][v].count + cat[1][v].count;
+ double sig = calculate_binomial (cat[0][v].count, cat[1][v].count,
+ bst->p);
+ struct entry
{
- var_append_value_name (var, cat[0][v].values, &catstr[0]);
- var_append_value_name (var, cat[1][v].values, &catstr[1]);
+ int stat_idx;
+ int group_idx;
+ double x;
+ }
+ entries[] = {
+ /* N. */
+ { 1, 0, cat[0][v].count },
+ { 1, 1, cat[1][v].count },
+ { 1, 2, n_total },
+ /* Observed Prop. */
+ { 2, 0, cat[0][v].count / n_total },
+ { 2, 1, cat[1][v].count / n_total },
+ { 2, 2, 1.0 },
+ /* Test Prop. */
+ { 3, 0, bst->p },
+ /* Significance. */
+ { 4, 0, sig }
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put3 (table, e->stat_idx, e->group_idx,
+ var_idx, pivot_value_new_number (e->x));
}
-
- tab_hline (table, TAL_1, 0, tab_nc (table) -1, 1 + v * 3);
-
- /* Titles */
- tab_text (table, 0, 1 + v * 3, TAB_LEFT, var_to_string (var));
- tab_text (table, 1, 1 + v * 3, TAB_LEFT, _("Group1"));
- tab_text (table, 1, 2 + v * 3, TAB_LEFT, _("Group2"));
- tab_text (table, 1, 3 + v * 3, TAB_LEFT, _("Total"));
-
- /* Test Prop */
- tab_double (table, 5, 1 + v * 3, TAB_NONE, bst->p, NULL, RC_OTHER);
-
- /* Category labels */
- tab_text (table, 2, 1 + v * 3, TAB_NONE, ds_cstr (&catstr[0]));
- tab_text (table, 2, 2 + v * 3, TAB_NONE, ds_cstr (&catstr[1]));
-
- /* Observed N */
- tab_double (table, 3, 1 + v * 3, TAB_NONE, cat[0][v].count, NULL, RC_WEIGHT);
- tab_double (table, 3, 2 + v * 3, TAB_NONE, cat[1][v].count, NULL, RC_WEIGHT);
-
- n_total = cat[0][v].count + cat[1][v].count;
- tab_double (table, 3, 3 + v * 3, TAB_NONE, n_total, NULL, RC_WEIGHT);
-
- /* Observed Proportions */
- tab_double (table, 4, 1 + v * 3, TAB_NONE,
- cat[0][v].count / n_total, NULL, RC_OTHER);
- tab_double (table, 4, 2 + v * 3, TAB_NONE,
- cat[1][v].count / n_total, NULL, RC_OTHER);
-
- tab_double (table, 4, 3 + v * 3, TAB_NONE,
- (cat[0][v].count + cat[1][v].count) / n_total, NULL, RC_OTHER);
-
- /* Significance */
- sig = calculate_binomial (cat[0][v].count, cat[1][v].count, bst->p);
- tab_double (table, 6, 1 + v * 3, TAB_NONE, sig, NULL, RC_PVALUE);
-
- ds_destroy (&catstr[0]);
- ds_destroy (&catstr[1]);
}
- tab_text (table, 2, 0, TAB_CENTER, _("Category"));
- tab_text (table, 3, 0, TAB_CENTER, _("N"));
- tab_text (table, 4, 0, TAB_CENTER, _("Observed Prop."));
- tab_text (table, 5, 0, TAB_CENTER, _("Test Prop."));
-
- tab_text_format (table, 6, 0, TAB_CENTER,
- _("Exact Sig. (%d-tailed)"),
- bst->p == 0.5 ? 2 : 1);
-
- tab_vline (table, TAL_2, 2, 0, tab_nr (table) -1);
- tab_submit (table);
+ pivot_table_submit (table);
}
for (i = 0; i < 2; i++)
#include "libpspp/hash-functions.h"
#include "libpspp/message.h"
#include "libpspp/taint.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
/* Adds frequency counts of each value of VAR in INPUT between LO and HI to
return casereader_destroy (input);
}
-static struct tab_table *
-create_variable_frequency_table (const struct dictionary *dict,
- struct casereader *input,
- const struct chisquare_test *test,
- int v, struct hmap *freq_hash)
-
-{
- int i;
- const struct one_sample_test *ost = (const struct one_sample_test*)test;
- int n_cells;
- struct tab_table *table ;
- const struct variable *var = ost->vars[v];
-
- const struct variable *wvar = dict_get_weight (dict);
- const struct fmt_spec *wfmt = wvar ? var_get_print_format (wvar) : & F_8_0;
-
- hmap_init (freq_hash);
- if (!create_freq_hash (dict, input, var, freq_hash))
- {
- freq_hmap_destroy (freq_hash, var_get_width (var));
- return NULL;
- }
-
- n_cells = hmap_count (freq_hash);
-
- if ( test->n_expected > 0 && n_cells != test->n_expected )
- {
- msg(ME, _("CHISQUARE test specified %d expected values, but"
- " %d distinct values were encountered in variable %s."),
- test->n_expected, n_cells,
- var_get_name (var)
- );
- freq_hmap_destroy (freq_hash, var_get_width (var));
- return NULL;
- }
-
- table = tab_create(4, n_cells + 2);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_title (table, "%s", var_to_string(var));
- tab_text (table, 1, 0, TAB_LEFT, _("Observed N"));
- tab_text (table, 2, 0, TAB_LEFT, _("Expected N"));
- tab_text (table, 3, 0, TAB_LEFT, _("Residual"));
-
- tab_headers (table, 1, 0, 1, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr(table) - 1 );
-
- tab_hline (table, TAL_1, 0, tab_nc(table) - 1, 1);
-
- tab_vline (table, TAL_2, 1, 0, tab_nr(table) - 1);
- for ( i = 2 ; i < 4 ; ++i )
- tab_vline (table, TAL_1, i, 0, tab_nr(table) - 1);
-
-
- tab_text (table, 0, tab_nr (table) - 1, TAB_LEFT, _("Total"));
-
- return table;
-}
-
-
-static struct tab_table *
-create_combo_frequency_table (const struct dictionary *dict, const struct chisquare_test *test)
-{
- int i;
- const struct one_sample_test *ost = (const struct one_sample_test*)test;
-
- struct tab_table *table ;
-
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- int n_cells = test->hi - test->lo + 1;
-
- table = tab_create(1 + ost->n_vars * 4, n_cells + 3);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_title (table, _("Frequencies"));
- for ( i = 0 ; i < ost->n_vars ; ++i )
- {
- const struct variable *var = ost->vars[i];
- tab_text (table, i * 4 + 1, 1, TAB_LEFT, _("Category"));
- tab_text (table, i * 4 + 2, 1, TAB_LEFT, _("Observed N"));
- tab_text (table, i * 4 + 3, 1, TAB_LEFT, _("Expected N"));
- tab_text (table, i * 4 + 4, 1, TAB_LEFT, _("Residual"));
-
- tab_vline (table, TAL_2, i * 4 + 1,
- 0, tab_nr (table) - 1);
-
- tab_vline (table, TAL_1, i * 4 + 2,
- 0, tab_nr (table) - 1);
-
- tab_vline (table, TAL_1, i * 4 + 3,
- 1, tab_nr (table) - 1);
-
- tab_vline (table, TAL_1, i * 4 + 4,
- 1, tab_nr (table) - 1);
-
-
- tab_joint_text (table,
- i * 4 + 1, 0,
- i * 4 + 4, 0,
- TAB_CENTER,
- var_to_string (var));
- }
-
- for ( i = test->lo ; i <= test->hi ; ++i )
- tab_double (table, 0, 2 + i - test->lo, TAB_LEFT, 1 + i - test->lo, NULL, RC_INTEGER);
-
- tab_headers (table, 1, 0, 2, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr(table) - 1 );
-
- tab_hline (table, TAL_1, 1, tab_nc(table) - 1, 1);
- tab_hline (table, TAL_1, 0, tab_nc(table) - 1, 2);
-
- tab_text (table, 0, tab_nr (table) - 1, TAB_LEFT, _("Total"));
-
- return table;
-}
-
-
-static struct tab_table *
-create_stats_table (const struct chisquare_test *test)
-{
- const struct one_sample_test *ost = (const struct one_sample_test*) test;
-
- struct tab_table *table;
- table = tab_create (1 + ost->n_vars, 4);
- tab_title (table, _("Test Statistics"));
- tab_headers (table, 1, 0, 1, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, -1,
- 0, 0, tab_nc(table) - 1, tab_nr(table) - 1 );
-
- tab_box (table, -1, -1, -1, TAL_1,
- 1, 0, tab_nc(table) - 1, tab_nr(table) - 1 );
-
-
- tab_vline (table, TAL_2, 1, 0, tab_nr (table) - 1);
- tab_hline (table, TAL_1, 0, tab_nc (table) - 1, 1);
-
-
- tab_text (table, 0, 1, TAB_LEFT, _("Chi-Square"));
- tab_text (table, 0, 2, TAB_LEFT, _("df"));
- tab_text (table, 0, 3, TAB_LEFT, _("Asymp. Sig."));
-
- return table;
-}
-
-
void
chisquare_execute (const struct dataset *ds,
struct casereader *input,
struct chisquare_test *cst = UP_CAST (test, struct chisquare_test,
parent.parent);
struct one_sample_test *ost = &cst->parent;
- int n_cells = 0;
double total_expected = 0.0;
double *df = xzalloc (sizeof (*df) * ost->n_vars);
for ( v = 0 ; v < ost->n_vars ; ++v )
{
const struct variable *var = ost->vars[v];
- double total_obs = 0.0;
- struct hmap freq_hash;
+
+ struct hmap freq_hash = HMAP_INITIALIZER (freq_hash);
struct casereader *reader =
casereader_create_filter_missing (casereader_clone (input),
&var, 1, exclude,
NULL, NULL);
- struct tab_table *freq_table =
- create_variable_frequency_table (dict, reader, cst, v, &freq_hash);
+ if (!create_freq_hash (dict, reader, var, &freq_hash))
+ {
+ freq_hmap_destroy (&freq_hash, var_get_width (var));
+ return;
+ }
- struct freq **ff;
+ size_t n_cells = hmap_count (&freq_hash);
+ if (cst->n_expected > 0 && n_cells != cst->n_expected)
+ {
+ msg (ME, _("CHISQUARE test specified %d expected values, but "
+ "variable %s has %d distinct values."),
+ cst->n_expected, var_get_name (var), n_cells);
+ freq_hmap_destroy (&freq_hash, var_get_width (var));
+ continue;
+ }
+
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_variable (var));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- if ( NULL == freq_table )
- continue;
- ff = freq_hmap_sort (&freq_hash, var_get_width (var));
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Observed N"), PIVOT_RC_COUNT,
+ N_("Expected N"), PIVOT_RC_OTHER,
+ N_("Residual"), PIVOT_RC_RESIDUAL);
- n_cells = hmap_count (&freq_hash);
+ struct freq **ff = freq_hmap_sort (&freq_hash, var_get_width (var));
- for ( i = 0 ; i < n_cells ; ++i )
+ double total_obs = 0.0;
+ for (size_t i = 0; i < n_cells; i++)
total_obs += ff[i]->count;
+ struct pivot_dimension *values = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Value"));
+ values->root->show_label = true;
+
xsq[v] = 0.0;
- for ( i = 0 ; i < n_cells ; ++i )
+ for (size_t i = 0; i < n_cells; i++)
{
- struct string str;
- double exp;
- const union value *observed_value = &ff[i]->values[0];
-
- ds_init_empty (&str);
- var_append_value_name (var, observed_value, &str);
-
- /* The key */
- tab_text (freq_table, 0, i + 1, TAB_LEFT, ds_cstr (&str));
- ds_destroy (&str);
-
-
- /* The observed N */
- tab_double (freq_table, 1, i + 1, TAB_NONE,
- ff[i]->count, NULL, RC_WEIGHT);
-
- if ( cst->n_expected > 0 )
- exp = cst->expected[i] * total_obs / total_expected ;
- else
- exp = total_obs / (double) n_cells;
-
- tab_double (freq_table, 2, i + 1, TAB_NONE,
- exp, NULL, RC_OTHER);
-
- /* The residual */
- tab_double (freq_table, 3, i + 1, TAB_NONE,
- ff[i]->count - exp, NULL, RC_OTHER);
+ int row = pivot_category_create_leaf (
+ values->root, pivot_value_new_var_value (
+ var, &ff[i]->values[0]));
+
+ double exp = (cst->n_expected > 0
+ ? cst->expected[i] * total_obs / total_expected
+ : total_obs / (double) n_cells);
+ double entries[] = {
+ ff[i]->count,
+ exp,
+ ff[i]->count - exp,
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (
+ table, j, row, pivot_value_new_number (entries[j]));
xsq[v] += (ff[i]->count - exp) * (ff[i]->count - exp) / exp;
}
df[v] = n_cells - 1.0;
- tab_double (freq_table, 1, i + 1, TAB_NONE,
- total_obs, NULL, RC_WEIGHT);
+ int row = pivot_category_create_leaf (
+ values->root, pivot_value_new_text (N_("Total")));
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_number (total_obs));
- tab_submit (freq_table);
+ pivot_table_submit (table);
freq_hmap_destroy (&freq_hash, var_get_width (var));
free (ff);
}
else /* ranged == true */
{
- struct tab_table *freq_table = create_combo_frequency_table (dict, cst);
-
- n_cells = cst->hi - cst->lo + 1;
-
- for ( v = 0 ; v < ost->n_vars ; ++v )
+ struct pivot_table *table = pivot_table_create (N_("Frequencies"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Category"),
+ N_("Observed N"), PIVOT_RC_COUNT,
+ N_("Expected N"), PIVOT_RC_OTHER,
+ N_("Residual"), PIVOT_RC_RESIDUAL);
+
+ struct pivot_dimension *var_dim
+ = pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Variable"));
+ for ( size_t i = 0 ; i < ost->n_vars ; ++i )
+ pivot_category_create_leaf (var_dim->root,
+ pivot_value_new_variable (ost->vars[i]));
+
+ struct pivot_dimension *category_dim
+ = pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Category"));
+ size_t n_cells = cst->hi - cst->lo + 1;
+ for (size_t i = 0 ; i < n_cells; ++i )
+ pivot_category_create_leaf (category_dim->root,
+ pivot_value_new_integer (i + 1));
+ pivot_category_create_leaves (category_dim->root, N_("Total"));
+
+ for ( size_t v = 0 ; v < ost->n_vars ; ++v )
{
const struct variable *var = ost->vars[v];
- double total_obs = 0.0;
struct casereader *reader =
casereader_create_filter_missing (casereader_clone (input),
&var, 1, exclude,
NULL, NULL);
- struct hmap freq_hash;
- struct freq **ff;
-
- hmap_init (&freq_hash);
+ struct hmap freq_hash = HMAP_INITIALIZER (freq_hash);
if (!create_freq_hash_with_range (dict, reader, var,
cst->lo, cst->hi, &freq_hash))
{
continue;
}
- ff = freq_hmap_sort (&freq_hash, var_get_width (var));
+ struct freq **ff = freq_hmap_sort (&freq_hash, var_get_width (var));
- for ( i = 0 ; i < hmap_count (&freq_hash) ; ++i )
+ double total_obs = 0.0;
+ for ( size_t i = 0 ; i < hmap_count (&freq_hash) ; ++i )
total_obs += ff[i]->count;
xsq[v] = 0.0;
- for ( i = 0 ; i < hmap_count (&freq_hash) ; ++i )
+ for ( size_t i = 0 ; i < hmap_count (&freq_hash) ; ++i )
{
- struct string str;
- double exp;
-
- const union value *observed_value = &ff[i]->values[0];
+ /* Category. */
+ pivot_table_put3 (table, 0, v, i,
+ pivot_value_new_var_value (
+ var, &ff[i]->values[0]));
+
+ double exp = (cst->n_expected > 0
+ ? cst->expected[i] * total_obs / total_expected
+ : total_obs / (double) hmap_count (&freq_hash));
+ double entries[] = {
+ ff[i]->count,
+ exp,
+ ff[i]->count - exp,
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put3 (table, j + 1, v, i,
+ pivot_value_new_number (entries[j]));
- ds_init_empty (&str);
- var_append_value_name (ost->vars[v], observed_value, &str);
- /* The key */
- tab_text (freq_table, v * 4 + 1, i + 2 , TAB_LEFT,
- ds_cstr (&str));
- ds_destroy (&str);
-
- /* The observed N */
- tab_double (freq_table, v * 4 + 2, i + 2 , TAB_NONE,
- ff[i]->count, NULL, RC_WEIGHT);
-
- if ( cst->n_expected > 0 )
- exp = cst->expected[i] * total_obs / total_expected ;
- else
- exp = total_obs / (double) hmap_count (&freq_hash);
-
- /* The expected N */
- tab_double (freq_table, v * 4 + 3, i + 2 , TAB_NONE,
- exp, NULL, RC_OTHER);
-
- /* The residual */
- tab_double (freq_table, v * 4 + 4, i + 2 , TAB_NONE,
- ff[i]->count - exp, NULL, RC_OTHER);
xsq[v] += (ff[i]->count - exp) * (ff[i]->count - exp) / exp;
}
-
- tab_double (freq_table, v * 4 + 2, tab_nr (freq_table) - 1, TAB_NONE,
- total_obs, NULL, RC_WEIGHT);
-
df[v] = n_cells - 1.0;
freq_hmap_destroy (&freq_hash, var_get_width (var));
free (ff);
+
+ pivot_table_put3 (table, 1, v, n_cells,
+ pivot_value_new_number (total_obs));
}
- tab_submit (freq_table);
+ pivot_table_submit (table);
}
ok = !taint_has_tainted_successor (casereader_get_taint (input));
casereader_destroy (input);
if (ok)
{
- struct tab_table *stats_table = create_stats_table (cst);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
- /* Populate the summary statistics table */
- for ( v = 0 ; v < ost->n_vars ; ++v )
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Chi-square"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Asymp. Sig."), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+
+ for ( size_t v = 0 ; v < ost->n_vars ; ++v )
{
const struct variable *var = ost->vars[v];
- tab_text (stats_table, 1 + v, 0, TAB_CENTER, var_get_name (var));
-
- tab_double (stats_table, 1 + v, 1, TAB_NONE, xsq[v], NULL, RC_OTHER);
- tab_double (stats_table, 1 + v, 2, TAB_NONE, df[v], NULL, RC_INTEGER);
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (var));
- tab_double (stats_table, 1 + v, 3, TAB_NONE,
- gsl_cdf_chisq_Q (xsq[v], df[v]), NULL, RC_PVALUE);
+ double sig = gsl_cdf_chisq_Q (xsq[v], df[v]);
+ double entries[] = { xsq[v], df[v], sig };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, row,
+ pivot_value_new_number (entries[i]));
}
- tab_submit (stats_table);
+ pivot_table_submit (table);
}
free (xsq);
#include "libpspp/cast.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
struct cochran
static void
show_freqs_box (const struct one_sample_test *ost, const struct cochran *ct)
{
- int i;
- const struct fmt_spec *wfmt = dict_get_weight_format (ct->dict);
-
- const int row_headers = 1;
- const int column_headers = 2;
- struct tab_table *table =
- tab_create (row_headers + 2, column_headers + ost->n_vars);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Frequencies"));
-
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_joint_text (table, 1, 0, 2, 0,
- TAT_TITLE | TAB_CENTER, _("Value"));
-
- tab_text_format (table, 1, 1, 0, _("Success (%.*g)"),
- DBL_DIG + 1, ct->success);
- tab_text_format (table, 2, 1, 0, _("Failure (%.*g)"),
- DBL_DIG + 1, ct->failure);
-
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- for (i = 0 ; i < ost->n_vars ; ++i)
+ struct pivot_table *table = pivot_table_create (N_("Frequencies"));
+ pivot_table_set_weight_var (table, dict_get_weight (ct->dict));
+
+ char *success = xasprintf (_("Success (%.*g)"), DBL_DIG + 1, ct->success);
+ char *failure = xasprintf (_("Failure (%.*g)"), DBL_DIG + 1, ct->failure);
+ struct pivot_dimension *values = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Value"),
+ success, PIVOT_RC_COUNT,
+ failure, PIVOT_RC_COUNT);
+ values->root->show_label = true;
+ free (failure);
+ free (success);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+
+ for (size_t i = 0 ; i < ost->n_vars ; ++i)
{
- tab_text (table, 0, column_headers + i,
- TAB_LEFT, var_to_string (ost->vars[i]));
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (ost->vars[i]));
- tab_double (table, 1, column_headers + i, 0,
- ct->hits[i], NULL, RC_WEIGHT);
-
- tab_double (table, 2, column_headers + i, 0,
- ct->misses[i], NULL, RC_WEIGHT);
+ pivot_table_put2 (table, 0, row, pivot_value_new_number (ct->hits[i]));
+ pivot_table_put2 (table, 1, row, pivot_value_new_number (ct->misses[i]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
-
-
static void
show_sig_box (const struct cochran *ch)
{
- const struct fmt_spec *wfmt = dict_get_weight_format (ch->dict);
-
- const int row_headers = 1;
- const int column_headers = 0;
- struct tab_table *table =
- tab_create (row_headers + 1, column_headers + 4);
-
-
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Test Statistics"));
-
- tab_text (table, 0, column_headers,
- TAT_TITLE | TAB_LEFT , _("N"));
-
- tab_text (table, 0, 1 + column_headers,
- TAT_TITLE | TAB_LEFT , _("Cochran's Q"));
-
- tab_text (table, 0, 2 + column_headers,
- TAT_TITLE | TAB_LEFT, _("df"));
-
- tab_text (table, 0, 3 + column_headers,
- TAT_TITLE | TAB_LEFT, _("Asymp. Sig."));
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- tab_double (table, 1, column_headers,
- 0, ch->cc, NULL, RC_WEIGHT);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
- tab_double (table, 1, column_headers + 1,
- 0, ch->q, NULL, RC_OTHER);
+ pivot_table_set_weight_format (table, dict_get_weight_format (ch->dict));
- tab_double (table, 1, column_headers + 2,
- 0, ch->df, NULL, RC_INTEGER);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Value"), N_("Value"));
- tab_double (table, 1, column_headers + 3,
- 0, gsl_cdf_chisq_Q (ch->q, ch->df),
- NULL, RC_PVALUE);
+ pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Cochran's Q"), PIVOT_RC_SIGNIFICANCE,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Asymp. Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_submit (table);
+ double sig = gsl_cdf_chisq_Q (ch->q, ch->df);
+ double entries[] = { ch->cc, ch->q, ch->df, sig };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, 0, i, pivot_value_new_number (entries[i]));
+ pivot_table_submit (table);
}
#include "math/correlation.h"
#include "math/covariance.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gl/minmax.h"
static void
-output_descriptives (const struct corr *corr, const gsl_matrix *means,
+output_descriptives (const struct corr *corr, const struct corr_opts *opts,
+ const gsl_matrix *means,
const gsl_matrix *vars, const gsl_matrix *ns)
{
- const int nr = corr->n_vars_total + 1;
- const int nc = 4;
- int c, r;
+ struct pivot_table *table = pivot_table_create (
+ N_("Descriptive Statistics"));
+ pivot_table_set_weight_var (table, opts->wv);
- const int heading_columns = 1;
- const int heading_rows = 1;
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("N"), PIVOT_RC_COUNT);
- struct tab_table *t = tab_create (nc, nr);
- tab_title (t, _("Descriptive Statistics"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
-
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("N"));
-
- for (r = 0 ; r < corr->n_vars_total ; ++r)
+ for (size_t r = 0 ; r < corr->n_vars_total ; ++r)
{
const struct variable *v = corr->vars[r];
- tab_text (t, 0, r + heading_rows, TAB_LEFT | TAT_TITLE, var_to_string (v));
-
- for (c = 1 ; c < nc ; ++c)
- {
- double x ;
- double n;
- switch (c)
- {
- case 1:
- x = gsl_matrix_get (means, r, 0);
- break;
- case 2:
- x = gsl_matrix_get (vars, r, 0);
- /* Here we want to display the non-biased estimator */
- n = gsl_matrix_get (ns, r, 0);
- x *= n / (n -1);
-
- x = sqrt (x);
- break;
- case 3:
- x = gsl_matrix_get (ns, r, 0);
- break;
- default:
- NOT_REACHED ();
- };
+ int row = pivot_category_create_leaf (variables->root,
+ pivot_value_new_variable (v));
- tab_double (t, c, r + heading_rows, 0, x, NULL, RC_OTHER);
- }
+ double mean = gsl_matrix_get (means, r, 0);
+ /* Here we want to display the non-biased estimator */
+ double n = gsl_matrix_get (ns, r, 0);
+ double stddev = sqrt (gsl_matrix_get (vars, r, 0) * n / (n - 1));
+ double entries[] = { mean, stddev, n };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, row, pivot_value_new_number (entries[i]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
const gsl_matrix *cm, const gsl_matrix *samples,
const gsl_matrix *cv)
{
- int r, c;
- struct tab_table *t;
- int matrix_cols;
- int nr = corr->n_vars1;
- int nc = matrix_cols = corr->n_vars_total > corr->n_vars1 ?
- corr->n_vars_total - corr->n_vars1 : corr->n_vars1;
-
- const struct fmt_spec *wfmt = opts->wv ? var_get_print_format (opts->wv) : & F_8_0;
-
- const int heading_columns = 2;
- const int heading_rows = 1;
-
- int rows_per_variable = opts->missing_type == CORR_LISTWISE ? 2 : 3;
-
- if (opts->statistics & STATS_XPROD)
- rows_per_variable += 2;
-
- /* Two header columns */
- nc += heading_columns;
-
- /* Three data per variable */
- nr *= rows_per_variable;
-
- /* One header row */
- nr += heading_rows;
-
- t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_title (t, _("Correlations"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
+ struct pivot_table *table = pivot_table_create (N_("Correlations"));
+ pivot_table_set_weight_var (table, opts->wv);
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
+ /* Column variable dimension. */
+ struct pivot_dimension *columns = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Variables"));
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_vline (t, TAL_1, 1, heading_rows, nr - 1);
-
- /* Row Headers */
- for (r = 0 ; r < corr->n_vars1 ; ++r)
- {
- tab_text (t, 0, 1 + r * rows_per_variable, TAB_LEFT | TAT_TITLE,
- var_to_string (corr->vars[r]));
-
- tab_text (t, 1, 1 + r * rows_per_variable, TAB_LEFT | TAT_TITLE, _("Pearson Correlation"));
- tab_text (t, 1, 2 + r * rows_per_variable, TAB_LEFT | TAT_TITLE,
- (opts->tails == 2) ? _("Sig. (2-tailed)") : _("Sig. (1-tailed)"));
-
- if (opts->statistics & STATS_XPROD)
- {
- tab_text (t, 1, 3 + r * rows_per_variable, TAB_LEFT | TAT_TITLE, _("Cross-products"));
- tab_text (t, 1, 4 + r * rows_per_variable, TAB_LEFT | TAT_TITLE, _("Covariance"));
- }
-
- if ( opts->missing_type != CORR_LISTWISE )
- tab_text (t, 1, rows_per_variable + r * rows_per_variable, TAB_LEFT | TAT_TITLE, _("N"));
-
- tab_hline (t, TAL_1, 0, nc - 1, r * rows_per_variable + 1);
- }
-
- /* Column Headers */
- for (c = 0 ; c < matrix_cols ; ++c)
+ int matrix_cols = (corr->n_vars_total > corr->n_vars1
+ ? corr->n_vars_total - corr->n_vars1
+ : corr->n_vars1);
+ for (int c = 0; c < matrix_cols; c++)
{
const struct variable *v = corr->n_vars_total > corr->n_vars1 ?
corr->vars[corr->n_vars1 + c] : corr->vars[c];
- tab_text (t, heading_columns + c, 0, TAB_LEFT | TAT_TITLE, var_to_string (v));
+ pivot_category_create_leaf (columns->root, pivot_value_new_variable (v));
}
- for (r = 0 ; r < corr->n_vars1 ; ++r)
- {
- const int row = r * rows_per_variable + heading_rows;
- for (c = 0 ; c < matrix_cols ; ++c)
- {
- unsigned char flags = 0;
- const int col_index = corr->n_vars_total > corr->n_vars1 ?
- corr->n_vars1 + c :
- c;
- double pearson = gsl_matrix_get (cm, r, col_index);
- double w = gsl_matrix_get (samples, r, col_index);
- double sig = opts->tails * significance_of_correlation (pearson, w);
-
- if ( opts->missing_type != CORR_LISTWISE )
- tab_double (t, c + heading_columns, row + rows_per_variable - 1, 0, w, NULL, RC_WEIGHT);
+ /* Statistics dimension. */
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Pearson Correlation"), PIVOT_RC_CORRELATION,
+ opts->tails == 2 ? N_("Sig. (2-tailed)") : N_("Sig. (1-tailed)"),
+ PIVOT_RC_SIGNIFICANCE);
- if ( col_index != r)
- tab_double (t, c + heading_columns, row + 1, 0, sig, NULL, RC_PVALUE);
+ if (opts->statistics & STATS_XPROD)
+ pivot_category_create_leaves (statistics->root, N_("Cross-products"),
+ N_("Covariance"));
- if ( opts->sig && col_index != r && sig < 0.05)
- flags = TAB_EMPH;
+ if (opts->missing_type != CORR_LISTWISE)
+ pivot_category_create_leaves (statistics->root, N_("N"), PIVOT_RC_COUNT);
- tab_double (t, c + heading_columns, row, flags, pearson, NULL, RC_OTHER);
+ /* Row variable dimension. */
+ struct pivot_dimension *rows = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+ for (size_t r = 0; r < corr->n_vars1; r++)
+ pivot_category_create_leaf (rows->root,
+ pivot_value_new_variable (corr->vars[r]));
- if (opts->statistics & STATS_XPROD)
- {
- double cov = gsl_matrix_get (cv, r, col_index);
- const double xprod_dev = cov * w;
- cov *= w / (w - 1.0);
+ struct pivot_footnote *sig_footnote = pivot_table_create_footnote (
+ table, pivot_value_new_text (N_("Significant at .05 level")));
- tab_double (t, c + heading_columns, row + 2, 0, xprod_dev, NULL, RC_OTHER);
- tab_double (t, c + heading_columns, row + 3, 0, cov, NULL, RC_OTHER);
- }
- }
- }
+ for (int r = 0; r < corr->n_vars1; r++)
+ for (int c = 0; c < matrix_cols; c++)
+ {
+ const int col_index = (corr->n_vars_total > corr->n_vars1
+ ? corr->n_vars1 + c
+ : c);
+ double pearson = gsl_matrix_get (cm, r, col_index);
+ double w = gsl_matrix_get (samples, r, col_index);
+ double sig = opts->tails * significance_of_correlation (pearson, w);
+
+ double entries[5];
+ int n = 0;
+ entries[n++] = pearson;
+ entries[n++] = col_index != r ? sig : SYSMIS;
+ if (opts->statistics & STATS_XPROD)
+ {
+ double cov = gsl_matrix_get (cv, r, col_index);
+ const double xprod_dev = cov * w;
+ cov *= w / (w - 1.0);
+
+ entries[n++] = xprod_dev;
+ entries[n++] = cov;
+ }
+ if (opts->missing_type != CORR_LISTWISE)
+ entries[n++] = w;
+
+ for (int i = 0; i < n; i++)
+ if (entries[i] != SYSMIS)
+ {
+ struct pivot_value *v = pivot_value_new_number (entries[i]);
+ if (!i && opts->sig && col_index != r && sig < 0.05)
+ pivot_value_add_footnote (v, sig_footnote);
+ pivot_table_put3 (table, c, i, r, v);
+ }
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
corr_matrix = correlation_from_covariance (cov_matrix, var_matrix);
if ( opts->statistics & STATS_DESCRIPTIVES)
- output_descriptives (corr, mean_matrix, var_matrix, samples_matrix);
+ output_descriptives (corr, opts, mean_matrix, var_matrix, samples_matrix);
output_correlation (corr, opts, corr_matrix,
samples_matrix, cov_matrix);
#include "libpspp/misc.h"
#include "libpspp/pool.h"
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "output/chart-item.h"
#include "output/charts/barchart.h"
/* Constants (0 or more). */
int n_consts;
struct xtab_var *const_vars;
+ size_t *const_indexes;
/* Data. */
struct hmap data;
static void tabulate_integer_case (struct crosstabulation *, const struct ccase *,
double weight);
static void postcalc (struct crosstabs_proc *);
-static void submit (struct crosstabulation *, struct tab_table *);
static double
round_weight (const struct crosstabs_proc *proc, double weight)
return proc->round_down ? floor (weight) : floor (weight + 0.5);
}
+#define FOR_EACH_POPULATED_COLUMN(C, XT) \
+ for (int C = next_populated_column (0, XT); \
+ C < (XT)->vars[COL_VAR].n_values; \
+ C = next_populated_column (C + 1, XT))
+static int
+next_populated_column (int c, const struct crosstabulation *xt)
+{
+ int n_columns = xt->vars[COL_VAR].n_values;
+ for (; c < n_columns; c++)
+ if (xt->col_tot[c])
+ break;
+ return c;
+}
+
+#define FOR_EACH_POPULATED_ROW(R, XT) \
+ for (int R = next_populated_row (0, XT); R < (XT)->vars[ROW_VAR].n_values; \
+ R = next_populated_row (R + 1, XT))
+static int
+next_populated_row (int r, const struct crosstabulation *xt)
+{
+ int n_rows = xt->vars[ROW_VAR].n_values;
+ for (; r < n_rows; r++)
+ if (xt->row_tot[r])
+ break;
+ return r;
+}
+
/* Parses and executes the CROSSTABS procedure. */
int
cmd_crosstabs (struct lexer *lexer, struct dataset *ds)
if (xt->n_vars > 2)
{
assert (xt->n_consts == 0);
- subset->missing = xt->missing;
subset->n_vars = 2;
subset->vars = xt->vars;
subset->n_consts = xt->n_vars - 2;
subset->const_vars = xt->vars + 2;
+ subset->const_indexes = xcalloc (subset->n_consts,
+ sizeof *subset->const_indexes);
for (size_t i = 0; i < subset->n_consts; i++)
{
- subset->const_vars[i].n_values = 1;
- subset->const_vars[i].values = &xt->entries[row0]->values[2 + i];
+ const union value *value = &xt->entries[row0]->values[2 + i];
+
+ for (size_t j = 0; j < xt->vars[2 + i].n_values; j++)
+ if (value_equal (&xt->vars[2 + i].values[j], value,
+ var_get_width (xt->vars[2 + i].var)))
+ {
+ subset->const_indexes[i] = j;
+ goto found;
+ }
+ NOT_REACHED ();
+ found: ;
}
}
subset->entries = &xt->entries[row0];
return -compare_table_entry_3way (ap_, bp_, xt_);
}
-static int
-find_first_difference (const struct crosstabulation *xt, size_t row)
-{
- if (row == 0)
- return xt->n_vars - 1;
- else
- {
- const struct freq *a = xt->entries[row];
- const struct freq *b = xt->entries[row - 1];
- int col;
-
- for (col = xt->n_vars - 1; col >= 0; col--)
- if (compare_table_entry_var_3way (a, b, xt, col))
- return col;
- NOT_REACHED ();
- }
-}
-
/* Output a table summarizing the cases processed. */
static void
make_summary_table (struct crosstabs_proc *proc)
{
- struct tab_table *summary;
- struct crosstabulation *xt;
- struct string name;
- int i;
+ struct pivot_table *table = pivot_table_create (N_("Summary"));
+ pivot_table_set_weight_var (table, dict_get_weight (proc->dict));
- summary = tab_create (7, 3 + proc->n_pivots);
- tab_set_format (summary, RC_WEIGHT, &proc->weight_format);
- tab_title (summary, _("Summary."));
- tab_headers (summary, 1, 0, 3, 0);
- tab_joint_text (summary, 1, 0, 6, 0, TAB_CENTER, _("Cases"));
- tab_joint_text (summary, 1, 1, 2, 1, TAB_CENTER, _("Valid"));
- tab_joint_text (summary, 3, 1, 4, 1, TAB_CENTER, _("Missing"));
- tab_joint_text (summary, 5, 1, 6, 1, TAB_CENTER, _("Total"));
- tab_hline (summary, TAL_1, 1, 6, 1);
- tab_hline (summary, TAL_1, 1, 6, 2);
- tab_vline (summary, TAL_1, 3, 1, 1);
- tab_vline (summary, TAL_1, 5, 1, 1);
- for (i = 0; i < 3; i++)
- {
- tab_text (summary, 1 + i * 2, 2, TAB_RIGHT, _("N"));
- tab_text (summary, 2 + i * 2, 2, TAB_RIGHT, _("Percent"));
- }
- tab_offset (summary, 0, 3);
-
- ds_init_empty (&name);
- for (xt = &proc->pivots[0]; xt < &proc->pivots[proc->n_pivots]; xt++)
- {
- double valid;
- double n[3];
- size_t i;
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
- tab_hline (summary, TAL_1, 0, 6, 0);
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Cases"),
+ N_("Valid"), N_("Missing"), N_("Total"));
+ cases->root->show_label = true;
- ds_clear (&name);
- for (i = 0; i < xt->n_vars; i++)
+ struct pivot_dimension *tables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Crosstabulation"));
+ for (struct crosstabulation *xt = &proc->pivots[0];
+ xt < &proc->pivots[proc->n_pivots]; xt++)
+ {
+ struct string name = DS_EMPTY_INITIALIZER;
+ for (size_t i = 0; i < xt->n_vars; i++)
{
if (i > 0)
- ds_put_cstr (&name, " * ");
+ ds_put_cstr (&name, " × ");
ds_put_cstr (&name, var_to_string (xt->vars[i].var));
}
- tab_text (summary, 0, 0, TAB_LEFT, ds_cstr (&name));
- valid = 0.;
- for (i = 0; i < xt->n_entries; i++)
+ int row = pivot_category_create_leaf (
+ tables->root,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&name)));
+
+ double valid = 0.;
+ for (size_t i = 0; i < xt->n_entries; i++)
valid += xt->entries[i]->count;
+ double n[3];
n[0] = valid;
n[1] = xt->missing;
n[2] = n[0] + n[1];
- for (i = 0; i < 3; i++)
+ for (int i = 0; i < 3; i++)
{
- tab_double (summary, i * 2 + 1, 0, TAB_RIGHT, n[i], NULL, RC_WEIGHT);
- tab_text_format (summary, i * 2 + 2, 0, TAB_RIGHT, "%.1f%%",
- n[i] / n[2] * 100.);
+ pivot_table_put3 (table, 0, i, row, pivot_value_new_number (n[i]));
+ pivot_table_put3 (table, 1, i, row,
+ pivot_value_new_number (n[i] / n[2] * 100.0));
}
-
- tab_next_row (summary);
}
- ds_destroy (&name);
- submit (NULL, summary);
+ pivot_table_submit (table);
}
\f
/* Output. */
-static struct tab_table *create_crosstab_table (struct crosstabs_proc *,
- struct crosstabulation *);
-static struct tab_table *create_chisq_table (struct crosstabs_proc *proc, struct crosstabulation *);
-static struct tab_table *create_sym_table (struct crosstabs_proc *proc, struct crosstabulation *);
-static struct tab_table *create_risk_table (struct crosstabs_proc *proc, struct crosstabulation *);
-static struct tab_table *create_direct_table (struct crosstabs_proc *proc, struct crosstabulation *);
-static void display_dimensions (struct crosstabs_proc *, struct crosstabulation *,
- struct tab_table *, int first_difference);
+static struct pivot_table *create_crosstab_table (
+ struct crosstabs_proc *, struct crosstabulation *,
+ size_t crs_leaves[CRS_CL_count]);
+static struct pivot_table *create_chisq_table (struct crosstabulation *);
+static struct pivot_table *create_sym_table (struct crosstabulation *);
+static struct pivot_table *create_risk_table (
+ struct crosstabulation *, struct pivot_dimension **risk_statistics);
+static struct pivot_table *create_direct_table (struct crosstabulation *);
static void display_crosstabulation (struct crosstabs_proc *,
struct crosstabulation *,
- struct tab_table *);
-static void display_chisq (struct crosstabulation *, struct tab_table *,
- bool *showed_fisher);
-static void display_symmetric (struct crosstabs_proc *, struct crosstabulation *,
- struct tab_table *);
-static void display_risk (struct crosstabulation *, struct tab_table *);
-static void display_directional (struct crosstabs_proc *, struct crosstabulation *,
- struct tab_table *);
-static void table_value_missing (struct crosstabs_proc *proc,
- struct tab_table *table, int c, int r,
- unsigned char opt, const union value *v,
- const struct variable *var);
+ struct pivot_table *,
+ size_t crs_leaves[CRS_CL_count]);
+static void display_chisq (struct crosstabulation *, struct pivot_table *);
+static void display_symmetric (struct crosstabs_proc *,
+ struct crosstabulation *, struct pivot_table *);
+static void display_risk (struct crosstabulation *, struct pivot_table *,
+ struct pivot_dimension *risk_statistics);
+static void display_directional (struct crosstabs_proc *,
+ struct crosstabulation *,
+ struct pivot_table *);
static void delete_missing (struct crosstabulation *);
static void build_matrix (struct crosstabulation *);
static void
output_crosstabulation (struct crosstabs_proc *proc, struct crosstabulation *xt)
{
- struct tab_table *table = NULL; /* Crosstabulation table. */
- struct tab_table *chisq = NULL; /* Chi-square table. */
- bool showed_fisher = false;
- struct tab_table *sym = NULL; /* Symmetric measures table. */
- struct tab_table *risk = NULL; /* Risk estimate table. */
- struct tab_table *direct = NULL; /* Directional measures table. */
- size_t row0, row1;
-
- enum_var_values (xt, COL_VAR, proc->descending);
+ for (size_t i = 0; i < xt->n_vars; i++)
+ enum_var_values (xt, i, proc->descending);
if (xt->vars[COL_VAR].n_values == 0)
{
ds_init_cstr (&vars, var_to_string (xt->vars[0].var));
for (i = 1; i < xt->n_vars; i++)
- ds_put_format (&vars, " * %s", var_to_string (xt->vars[i].var));
+ ds_put_format (&vars, " × %s", var_to_string (xt->vars[i].var));
/* TRANSLATORS: The %s here describes a crosstabulation. It takes the
form "var1 * var2 * var3 * ...". */
return;
}
- if (proc->cells)
- table = create_crosstab_table (proc, xt);
- if (proc->statistics & (1u << CRS_ST_CHISQ))
- chisq = create_chisq_table (proc, xt);
- if (proc->statistics & ((1u << CRS_ST_PHI) | (1u << CRS_ST_CC)
- | (1u << CRS_ST_BTAU) | (1u << CRS_ST_CTAU)
- | (1u << CRS_ST_GAMMA) | (1u << CRS_ST_CORR)
- | (1u << CRS_ST_KAPPA)))
- sym = create_sym_table (proc, xt);
- if (proc->statistics & (1u << CRS_ST_RISK))
- risk = create_risk_table (proc, xt);
- if (proc->statistics & ((1u << CRS_ST_LAMBDA) | (1u << CRS_ST_UC)
- | (1u << CRS_ST_D) | (1u << CRS_ST_ETA)))
- direct = create_direct_table (proc, xt);
-
- row0 = row1 = 0;
+ size_t crs_leaves[CRS_CL_count];
+ struct pivot_table *table = (proc->cells
+ ? create_crosstab_table (proc, xt, crs_leaves)
+ : NULL);
+ struct pivot_table *chisq = (proc->statistics & (1u << CRS_ST_CHISQ)
+ ? create_chisq_table (xt)
+ : NULL);
+ struct pivot_table *sym
+ = (proc->statistics & ((1u << CRS_ST_PHI) | (1u << CRS_ST_CC)
+ | (1u << CRS_ST_BTAU) | (1u << CRS_ST_CTAU)
+ | (1u << CRS_ST_GAMMA) | (1u << CRS_ST_CORR)
+ | (1u << CRS_ST_KAPPA))
+ ? create_sym_table (xt)
+ : NULL);
+ struct pivot_dimension *risk_statistics = NULL;
+ struct pivot_table *risk = (proc->statistics & (1u << CRS_ST_RISK)
+ ? create_risk_table (xt, &risk_statistics)
+ : NULL);
+ struct pivot_table *direct
+ = (proc->statistics & ((1u << CRS_ST_LAMBDA) | (1u << CRS_ST_UC)
+ | (1u << CRS_ST_D) | (1u << CRS_ST_ETA))
+ ? create_direct_table (xt)
+ : NULL);
+
+ size_t row0 = 0;
+ size_t row1 = 0;
while (find_crosstab (xt, &row0, &row1))
{
struct crosstabulation x;
- int first_difference;
make_crosstabulation_subset (xt, row0, row1, &x);
- /* Find all the row variable values. */
- enum_var_values (&x, ROW_VAR, proc->descending);
-
size_t n_rows = x.vars[ROW_VAR].n_values;
size_t n_cols = x.vars[COL_VAR].n_values;
if (size_overflow_p (xtimes (xtimes (n_rows, n_cols), sizeof (double))))
x.col_tot = xmalloc (n_cols * sizeof *x.col_tot);
x.mat = xmalloc (n_rows * n_cols * sizeof *x.mat);
- /* Allocate table space for the matrix. */
- if (table
- && tab_row (table) + (n_rows + 1) * proc->n_cells > tab_nr (table))
- tab_realloc (table, -1,
- MAX (tab_nr (table) + (n_rows + 1) * proc->n_cells,
- tab_nr (table) * xt->n_entries / x.n_entries));
-
build_matrix (&x);
/* Find the first variable that differs from the last subtable. */
- first_difference = find_first_difference (xt, row0);
if (table)
- {
- display_dimensions (proc, &x, table, first_difference);
- display_crosstabulation (proc, &x, table);
- }
+ display_crosstabulation (proc, &x, table, crs_leaves);
if (proc->exclude == MV_NEVER)
delete_missing (&x);
if (chisq)
- {
- display_dimensions (proc, &x, chisq, first_difference);
- display_chisq (&x, chisq, &showed_fisher);
- }
+ display_chisq (&x, chisq);
+
if (sym)
- {
- display_dimensions (proc, &x, sym, first_difference);
- display_symmetric (proc, &x, sym);
- }
+ display_symmetric (proc, &x, sym);
if (risk)
- {
- display_dimensions (proc, &x, risk, first_difference);
- display_risk (&x, risk);
- }
+ display_risk (&x, risk, risk_statistics);
if (direct)
- {
- display_dimensions (proc, &x, direct, first_difference);
- display_directional (proc, &x, direct);
- }
-
- /* Free the parts of x that are not owned by xt. In
- particular we must not free x.cols, which is the same as
- xt->cols, which is freed at the end of this function. */
- free_var_values (&x, ROW_VAR);
+ display_directional (proc, &x, direct);
free (x.mat);
free (x.row_tot);
free (x.col_tot);
}
- submit (NULL, table);
+ if (table)
+ pivot_table_submit (table);
if (chisq)
+ pivot_table_submit (chisq);
+
+ if (sym)
+ pivot_table_submit (sym);
+
+ if (risk)
{
- if (!showed_fisher)
- tab_resize (chisq, 4 + (xt->n_vars - 2), -1);
- submit (xt, chisq);
+ if (!pivot_table_is_empty (risk))
+ pivot_table_submit (risk);
+ else
+ pivot_table_destroy (risk);
}
- submit (xt, sym);
- submit (xt, risk);
- submit (xt, direct);
+ if (direct)
+ pivot_table_submit (direct);
- free_var_values (xt, COL_VAR);
+ for (size_t i = 0; i < xt->n_vars; i++)
+ free_var_values (xt, i);
}
static void
x->total += x->col_tot[col];
}
-static struct tab_table *
-create_crosstab_table (struct crosstabs_proc *proc, struct crosstabulation *xt)
+static void
+add_var_dimension (struct pivot_table *table, const struct xtab_var *var,
+ enum pivot_axis_type axis_type, bool total)
{
- struct tuple
- {
- int value;
- const char *name;
- };
- static const struct tuple names[] =
- {
- {CRS_CL_COUNT, N_("count")},
- {CRS_CL_ROW, N_("row %")},
- {CRS_CL_COLUMN, N_("column %")},
- {CRS_CL_TOTAL, N_("total %")},
- {CRS_CL_EXPECTED, N_("expected")},
- {CRS_CL_RESIDUAL, N_("residual")},
- {CRS_CL_SRESIDUAL, N_("std. resid.")},
- {CRS_CL_ASRESIDUAL, N_("adj. resid.")},
- };
- const int n_names = sizeof names / sizeof *names;
- const struct tuple *t;
+ struct pivot_dimension *d = pivot_dimension_create__ (
+ table, axis_type, pivot_value_new_variable (var->var));
- struct tab_table *table;
- struct string title;
- struct crosstabulation x;
+ struct pivot_footnote *missing_footnote = pivot_table_create_footnote (
+ table, pivot_value_new_text (N_("Missing value")));
- int i;
+ struct pivot_category *group = pivot_category_create_group__ (
+ d->root, pivot_value_new_variable (var->var));
+ for (size_t j = 0; j < var->n_values; j++)
+ {
+ struct pivot_value *value = pivot_value_new_var_value (
+ var->var, &var->values[j]);
+ if (var_is_value_missing (var->var, &var->values[j], MV_ANY))
+ pivot_value_add_footnote (value, missing_footnote);
+ pivot_category_create_leaf (group, value);
+ }
- make_crosstabulation_subset (xt, 0, 0, &x);
-
- size_t n_cols = x.vars[COL_VAR].n_values;
- table = tab_create (x.n_consts + 1 + n_cols + 1,
- (x.n_entries / n_cols) * 3 / 2 * proc->n_cells + 10);
- tab_headers (table, x.n_consts + 1, 0, 2, 0);
- tab_set_format (table, RC_WEIGHT, &proc->weight_format);
-
- /* First header line. */
- tab_joint_text (table, x.n_consts + 1, 0,
- (x.n_consts + 1) + (n_cols - 1), 0,
- TAB_CENTER | TAT_TITLE, var_to_string (x.vars[COL_VAR].var));
-
- tab_hline (table, TAL_1, x.n_consts + 1,
- x.n_consts + 2 + n_cols - 2, 1);
-
- /* Second header line. */
- for (i = 2; i < x.n_consts + 2; i++)
- tab_joint_text (table, x.n_consts + 2 - i - 1, 0,
- x.n_consts + 2 - i - 1, 1,
- TAB_RIGHT | TAT_TITLE, var_to_string (x.vars[i].var));
- tab_text (table, x.n_consts + 2 - 2, 1, TAB_RIGHT | TAT_TITLE,
- var_to_string (x.vars[ROW_VAR].var));
- for (i = 0; i < n_cols; i++)
- table_value_missing (proc, table, x.n_consts + 2 + i - 1, 1, TAB_RIGHT,
- &x.vars[COL_VAR].values[i], x.vars[COL_VAR].var);
- tab_text (table, x.n_consts + 2 + n_cols - 1, 1, TAB_CENTER, _("Total"));
-
- tab_hline (table, TAL_1, 0, x.n_consts + 2 + n_cols - 1, 2);
- tab_vline (table, TAL_1, x.n_consts + 2 + n_cols - 1, 0, 1);
+ if (total)
+ pivot_category_create_leaf (d->root, pivot_value_new_text (N_("Total")));
+}
+static struct pivot_table *
+create_crosstab_table (struct crosstabs_proc *proc, struct crosstabulation *xt,
+ size_t crs_leaves[CRS_CL_count])
+{
/* Title. */
- ds_init_empty (&title);
- for (i = 0; i < x.n_consts + 2; i++)
+ struct string title = DS_EMPTY_INITIALIZER;
+ for (size_t i = 0; i < xt->n_vars; i++)
{
if (i)
- ds_put_cstr (&title, " * ");
- ds_put_cstr (&title, var_to_string (x.vars[i].var));
+ ds_put_cstr (&title, " × ");
+ ds_put_cstr (&title, var_to_string (xt->vars[i].var));
}
- for (i = 0; i < xt->n_consts; i++)
+ for (size_t i = 0; i < xt->n_consts; i++)
{
const struct variable *var = xt->const_vars[i].var;
+ const union value *value = &xt->entries[0]->values[2 + i];
char *s;
ds_put_format (&title, ", %s=", var_to_string (var));
/* Insert the formatted value of VAR without any leading spaces. */
- s = data_out (&xt->const_vars[i].values[0], var_get_encoding (var),
- var_get_print_format (var));
+ s = data_out (value, var_get_encoding (var), var_get_print_format (var));
ds_put_cstr (&title, s + strspn (s, " "));
free (s);
}
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&title)));
+ pivot_table_set_weight_format (table, &proc->weight_format);
+ table->omit_empty = true;
- ds_put_cstr (&title, " [");
- i = 0;
- for (t = names; t < &names[n_names]; t++)
- if (proc->cells & (1u << t->value))
- {
- if (i++)
- ds_put_cstr (&title, ", ");
- ds_put_cstr (&title, gettext (t->name));
- }
- ds_put_cstr (&title, "].");
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"));
+
+ struct statistic
+ {
+ const char *label;
+ const char *rc;
+ };
+ static const struct statistic stats[CRS_CL_count] =
+ {
+ [CRS_CL_COUNT] = { N_("Count"), PIVOT_RC_COUNT },
+ [CRS_CL_ROW] = { N_("Row %"), PIVOT_RC_PERCENT },
+ [CRS_CL_COLUMN] = { N_("Column %"), PIVOT_RC_PERCENT },
+ [CRS_CL_TOTAL] = { N_("Total %"), PIVOT_RC_PERCENT },
+ [CRS_CL_EXPECTED] = { N_("Expected"), PIVOT_RC_OTHER },
+ [CRS_CL_RESIDUAL] = { N_("Residual"), PIVOT_RC_RESIDUAL },
+ [CRS_CL_SRESIDUAL] = { N_("Std. Residual"), PIVOT_RC_RESIDUAL },
+ [CRS_CL_ASRESIDUAL] = { N_("Adjusted Residual"), PIVOT_RC_RESIDUAL },
+ };
+ for (size_t i = 0; i < CRS_CL_count; i++)
+ if (proc->cells & (1u << i) && stats[i].label)
+ crs_leaves[i] = pivot_category_create_leaf_rc (
+ statistics->root, pivot_value_new_text (stats[i].label),
+ stats[i].rc);
- tab_title (table, "%s", ds_cstr (&title));
- ds_destroy (&title);
+ for (size_t i = 0; i < xt->n_vars; i++)
+ add_var_dimension (table, &xt->vars[i],
+ i == COL_VAR ? PIVOT_AXIS_COLUMN : PIVOT_AXIS_ROW,
+ true);
- tab_offset (table, 0, 2);
return table;
}
-static struct tab_table *
-create_chisq_table (struct crosstabs_proc *proc, struct crosstabulation *xt)
+static struct pivot_table *
+create_chisq_table (struct crosstabulation *xt)
{
- struct tab_table *chisq;
-
- size_t n_cols = xt->vars[COL_VAR].n_values;
- chisq = tab_create (6 + (xt->n_vars - 2),
- xt->n_entries / n_cols * 3 / 2 * N_CHISQ + 10);
- tab_headers (chisq, 1 + (xt->n_vars - 2), 0, 1, 0);
- tab_set_format (chisq, RC_WEIGHT, &proc->weight_format);
-
- tab_title (chisq, _("Chi-square tests."));
-
- tab_offset (chisq, xt->n_vars - 2, 0);
- tab_text (chisq, 0, 0, TAB_LEFT | TAT_TITLE, _("Statistic"));
- tab_text (chisq, 1, 0, TAB_RIGHT | TAT_TITLE, _("Value"));
- tab_text (chisq, 2, 0, TAB_RIGHT | TAT_TITLE, _("df"));
- tab_text (chisq, 3, 0, TAB_RIGHT | TAT_TITLE,
- _("Asymp. Sig. (2-tailed)"));
- tab_text_format (chisq, 4, 0, TAB_RIGHT | TAT_TITLE,
- _("Exact Sig. (%d-tailed)"), 2);
- tab_text_format (chisq, 5, 0, TAB_RIGHT | TAT_TITLE,
- _("Exact Sig. (%d-tailed)"), 1);
- tab_offset (chisq, 0, 1);
+ struct pivot_table *chisq = pivot_table_create (N_("Chi-Square Tests"));
+ pivot_table_set_weight_format (chisq, &xt->weight_format);
+ chisq->omit_empty = true;
+
+ pivot_dimension_create (
+ chisq, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Pearson Chi-Square"),
+ N_("Likelihood Ratio"),
+ N_("Fisher's Exact Test"),
+ N_("Continuity Correction"),
+ N_("Linear-by-Linear Association"),
+ N_("N of Valid Cases"), PIVOT_RC_COUNT);
+
+ pivot_dimension_create (
+ chisq, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Asymptotic Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Exact Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Exact Sig. (1-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ for (size_t i = 2; i < xt->n_vars; i++)
+ add_var_dimension (chisq, &xt->vars[i], PIVOT_AXIS_ROW, false);
return chisq;
}
/* Symmetric measures. */
-static struct tab_table *
-create_sym_table (struct crosstabs_proc *proc, struct crosstabulation *xt)
+static struct pivot_table *
+create_sym_table (struct crosstabulation *xt)
{
- struct tab_table *sym;
-
- size_t n_cols = xt->vars[COL_VAR].n_values;
- sym = tab_create (6 + (xt->n_vars - 2),
- xt->n_entries / n_cols * 7 + 10);
-
- tab_set_format (sym, RC_WEIGHT, &proc->weight_format);
-
- tab_headers (sym, 2 + (xt->n_vars - 2), 0, 1, 0);
- tab_title (sym, _("Symmetric measures."));
-
- tab_offset (sym, xt->n_vars - 2, 0);
- tab_text (sym, 0, 0, TAB_LEFT | TAT_TITLE, _("Category"));
- tab_text (sym, 1, 0, TAB_LEFT | TAT_TITLE, _("Statistic"));
- tab_text (sym, 2, 0, TAB_RIGHT | TAT_TITLE, _("Value"));
- tab_text (sym, 3, 0, TAB_RIGHT | TAT_TITLE, _("Asymp. Std. Error"));
- tab_text (sym, 4, 0, TAB_RIGHT | TAT_TITLE, _("Approx. T"));
- tab_text (sym, 5, 0, TAB_RIGHT | TAT_TITLE, _("Approx. Sig."));
- tab_offset (sym, 0, 1);
+ struct pivot_table *sym = pivot_table_create (N_("Symmetric Measures"));
+ pivot_table_set_weight_format (sym, &xt->weight_format);
+ sym->omit_empty = true;
+
+ pivot_dimension_create (
+ sym, PIVOT_AXIS_COLUMN, N_("Values"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("Asymp. Std. Error"), PIVOT_RC_OTHER,
+ N_("Approx. T"), PIVOT_RC_OTHER,
+ N_("Approx. Sig."), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ sym, PIVOT_AXIS_ROW, N_("Statistics"));
+ pivot_category_create_group (
+ statistics->root, N_("Nominal by Nominal"),
+ N_("Phi"), N_("Cramer's V"), N_("Contingency Coefficient"));
+ pivot_category_create_group (
+ statistics->root, N_("Ordinal by Ordinal"),
+ N_("Kendall's tau-b"), N_("Kendall's tau-c"),
+ N_("Gamma"), N_("Spearman Correlation"));
+ pivot_category_create_group (
+ statistics->root, N_("Interval by Interval"),
+ N_("Pearson's R"));
+ pivot_category_create_group (
+ statistics->root, N_("Measure of Agreement"),
+ N_("Kappa"));
+ pivot_category_create_leaves (statistics->root, N_("N of Valid Cases"),
+ PIVOT_RC_COUNT);
+
+ for (size_t i = 2; i < xt->n_vars; i++)
+ add_var_dimension (sym, &xt->vars[i], PIVOT_AXIS_ROW, false);
return sym;
}
/* Risk estimate. */
-static struct tab_table *
-create_risk_table (struct crosstabs_proc *proc, struct crosstabulation *xt)
+static struct pivot_table *
+create_risk_table (struct crosstabulation *xt,
+ struct pivot_dimension **risk_statistics)
{
- struct tab_table *risk;
+ struct pivot_table *risk = pivot_table_create (N_("Risk Estimate"));
+ pivot_table_set_weight_format (risk, &xt->weight_format);
+ risk->omit_empty = true;
- size_t n_cols = xt->vars[COL_VAR].n_values;
- risk = tab_create (4 + (xt->n_vars - 2), xt->n_entries / n_cols * 4 + 10);
- tab_headers (risk, 1 + xt->n_vars - 2, 0, 2, 0);
- tab_title (risk, _("Risk estimate."));
- tab_set_format (risk, RC_WEIGHT, &proc->weight_format);
-
- tab_offset (risk, xt->n_vars - 2, 0);
- tab_joint_text_format (risk, 2, 0, 3, 0, TAB_CENTER | TAT_TITLE,
- _("95%% Confidence Interval"));
- tab_text (risk, 0, 1, TAB_LEFT | TAT_TITLE, _("Statistic"));
- tab_text (risk, 1, 1, TAB_RIGHT | TAT_TITLE, _("Value"));
- tab_text (risk, 2, 1, TAB_RIGHT | TAT_TITLE, _("Lower"));
- tab_text (risk, 3, 1, TAB_RIGHT | TAT_TITLE, _("Upper"));
- tab_hline (risk, TAL_1, 2, 3, 1);
- tab_vline (risk, TAL_1, 2, 0, 1);
- tab_offset (risk, 0, 2);
+ struct pivot_dimension *values = pivot_dimension_create (
+ risk, PIVOT_AXIS_COLUMN, N_("Values"),
+ N_("Value"), PIVOT_RC_OTHER);
+ pivot_category_create_group (
+ values->root, N_("95% Confidence Interval"),
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+
+ *risk_statistics = pivot_dimension_create (
+ risk, PIVOT_AXIS_ROW, N_("Statistics"));
+
+ for (size_t i = 2; i < xt->n_vars; i++)
+ add_var_dimension (risk, &xt->vars[i], PIVOT_AXIS_ROW, false);
return risk;
}
-/* Directional measures. */
-static struct tab_table *
-create_direct_table (struct crosstabs_proc *proc, struct crosstabulation *xt)
+static void
+create_direct_stat (struct pivot_category *parent,
+ const struct crosstabulation *xt,
+ const char *name, bool symmetric)
{
- struct tab_table *direct;
+ struct pivot_category *group = pivot_category_create_group (
+ parent, name);
+ if (symmetric)
+ pivot_category_create_leaf (group, pivot_value_new_text (N_("Symmetric")));
+
+ char *row_label = xasprintf (_("%s Dependent"),
+ var_to_string (xt->vars[ROW_VAR].var));
+ pivot_category_create_leaf (group, pivot_value_new_user_text_nocopy (
+ row_label));
+
+ char *col_label = xasprintf (_("%s Dependent"),
+ var_to_string (xt->vars[COL_VAR].var));
+ pivot_category_create_leaf (group, pivot_value_new_user_text_nocopy (
+ col_label));
+}
- size_t n_cols = xt->vars[COL_VAR].n_values;
- direct = tab_create (7 + (xt->n_vars - 2),
- xt->n_entries / n_cols * 7 + 10);
- tab_headers (direct, 3 + (xt->n_vars - 2), 0, 1, 0);
- tab_title (direct, _("Directional measures."));
- tab_set_format (direct, RC_WEIGHT, &proc->weight_format);
-
- tab_offset (direct, xt->n_vars - 2, 0);
- tab_text (direct, 0, 0, TAB_LEFT | TAT_TITLE, _("Category"));
- tab_text (direct, 1, 0, TAB_LEFT | TAT_TITLE, _("Statistic"));
- tab_text (direct, 2, 0, TAB_LEFT | TAT_TITLE, _("Type"));
- tab_text (direct, 3, 0, TAB_RIGHT | TAT_TITLE, _("Value"));
- tab_text (direct, 4, 0, TAB_RIGHT | TAT_TITLE, _("Asymp. Std. Error"));
- tab_text (direct, 5, 0, TAB_RIGHT | TAT_TITLE, _("Approx. T"));
- tab_text (direct, 6, 0, TAB_RIGHT | TAT_TITLE, _("Approx. Sig."));
- tab_offset (direct, 0, 1);
+/* Directional measures. */
+static struct pivot_table *
+create_direct_table (struct crosstabulation *xt)
+{
+ struct pivot_table *direct = pivot_table_create (N_("Directional Measures"));
+ pivot_table_set_weight_format (direct, &xt->weight_format);
+ direct->omit_empty = true;
+
+ pivot_dimension_create (
+ direct, PIVOT_AXIS_COLUMN, N_("Values"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("Asymp. Std. Error"), PIVOT_RC_OTHER,
+ N_("Approx. T"), PIVOT_RC_OTHER,
+ N_("Approx Sig."), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ direct, PIVOT_AXIS_ROW, N_("Statistics"));
+ struct pivot_category *nn = pivot_category_create_group (
+ statistics->root, N_("Nominal by Nominal"));
+ create_direct_stat (nn, xt, N_("Lambda"), true);
+ create_direct_stat (nn, xt, N_("Goodman and Kruskal tau"), false);
+ create_direct_stat (nn, xt, N_("Uncertainty Coefficient"), true);
+ struct pivot_category *oo = pivot_category_create_group (
+ statistics->root, N_("Ordinal by Ordinal"));
+ create_direct_stat (oo, xt, N_("Somers' d"), true);
+ struct pivot_category *ni = pivot_category_create_group (
+ statistics->root, N_("Nominal by Interval"));
+ create_direct_stat (ni, xt, N_("Eta"), false);
+
+ for (size_t i = 2; i < xt->n_vars; i++)
+ add_var_dimension (direct, &xt->vars[i], PIVOT_AXIS_ROW, false);
return direct;
}
-
/* Delete missing rows and columns for statistical analysis when
/MISSING=REPORT. */
static void
}
}
-/* Prepare table T for submission, and submit it. */
-static void
-submit (struct crosstabulation *xt, struct tab_table *t)
-{
- int i;
-
- if (t == NULL)
- return;
-
- tab_resize (t, -1, 0);
- if (tab_nr (t) == tab_t (t))
- {
- table_unref (&t->table);
- return;
- }
- tab_offset (t, 0, 0);
- if (xt != NULL)
- for (i = 2; i < xt->n_vars; i++)
- tab_text (t, xt->n_vars - i - 1, 0, TAB_RIGHT | TAT_TITLE,
- var_to_string (xt->vars[i].var));
- tab_box (t, TAL_2, TAL_2, -1, -1, 0, 0, tab_nc (t) - 1, tab_nr (t) - 1);
- tab_box (t, -1, -1, -1, TAL_1, tab_l (t), tab_t (t) - 1, tab_nc (t) - 1,
- tab_nr (t) - 1);
- tab_vline (t, TAL_2, tab_l (t), 0, tab_nr (t) - 1);
-
- tab_submit (t);
-}
-
static bool
find_crosstab (struct crosstabulation *xt, size_t *row0p, size_t *row1p)
{
free_var_values (const struct crosstabulation *xt, int var_idx)
{
struct xtab_var *xv = &xt->vars[var_idx];
- free (xv->values);
+ //free (xv->values);
xv->values = NULL;
xv->n_values = 0;
}
-/* Sets cell (C,R) in TABLE, with options OPT, to have a value taken
- from V, displayed with print format spec from variable VAR. When
- in REPORT missing-value mode, missing values have an M appended. */
-static void
-table_value_missing (struct crosstabs_proc *proc,
- struct tab_table *table, int c, int r, unsigned char opt,
- const union value *v, const struct variable *var)
-{
- const char *label = var_lookup_value_label (var, v);
- if (label != NULL)
- tab_text (table, c, r, TAB_LEFT, label);
- else
- {
- const struct fmt_spec *print = var_get_print_format (var);
- if (proc->exclude == MV_NEVER && var_is_value_missing (var, v, MV_USER))
- {
- char *s = data_out (v, dict_get_encoding (proc->dict), print);
- tab_text_format (table, c, r, opt, "%sM", s + strspn (s, " "));
- free (s);
- }
- else
- tab_value (table, c, r, opt, v, var, print);
- }
-}
-
-/* Draws a line across TABLE at the current row to indicate the most
- major dimension variable with index FIRST_DIFFERENCE out of N_VARS
- that changed, and puts the values that changed into the table. TB
- and XT must be the corresponding table_entry and crosstab,
- respectively. */
-static void
-display_dimensions (struct crosstabs_proc *proc, struct crosstabulation *xt,
- struct tab_table *table, int first_difference)
-{
- tab_hline (table, TAL_1, xt->n_consts + xt->n_vars - first_difference - 1, tab_nc (table) - 1, 0);
-
- for (; first_difference >= 2; first_difference--)
- table_value_missing (proc, table, xt->n_consts + xt->n_vars - first_difference - 1, 0,
- TAB_RIGHT, &xt->entries[0]->values[first_difference],
- xt->vars[first_difference].var);
-}
-
-/* Put VALUE into cell (C,R) of TABLE, suffixed with character
- SUFFIX if nonzero. If MARK_MISSING is true the entry is
- additionally suffixed with a letter `M'. */
-static void
-format_cell_entry (struct tab_table *table, int c, int r, double value,
- char suffix, bool mark_missing, const struct dictionary *dict)
-{
- union value v;
- char suffixes[3];
- int suffix_len;
- char *s;
-
- v.f = value;
- s = data_out (&v, dict_get_encoding (dict), settings_get_format ());
-
- suffix_len = 0;
- if (suffix != 0)
- suffixes[suffix_len++] = suffix;
- if (mark_missing)
- suffixes[suffix_len++] = 'M';
- suffixes[suffix_len] = '\0';
-
- tab_text_format (table, c, r, TAB_RIGHT, "%s%s",
- s + strspn (s, " "), suffixes);
-
- free (s);
-}
-
/* Displays the crosstabulation table. */
static void
display_crosstabulation (struct crosstabs_proc *proc,
- struct crosstabulation *xt, struct tab_table *table)
+ struct crosstabulation *xt, struct pivot_table *table,
+ size_t crs_leaves[CRS_CL_count])
{
size_t n_rows = xt->vars[ROW_VAR].n_values;
size_t n_cols = xt->vars[COL_VAR].n_values;
- int last_row;
- int r, c, i;
- double *mp;
- for (r = 0; r < n_rows; r++)
- table_value_missing (proc, table, xt->n_consts + xt->n_vars - 2,
- r * proc->n_cells, TAB_RIGHT,
- &xt->vars[ROW_VAR].values[r],
- xt->vars[ROW_VAR].var);
-
- tab_text (table, xt->n_vars - 2, n_rows * proc->n_cells,
- TAB_LEFT, _("Total"));
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
+ assert (xt->n_vars == 2);
+ for (size_t i = 0; i < xt->n_consts; i++)
+ indexes[i + 3] = xt->const_indexes[i];
/* Put in the actual cells. */
- mp = xt->mat;
- tab_offset (table, xt->n_consts + xt->n_vars - 1, -1);
- for (r = 0; r < n_rows; r++)
+ double *mp = xt->mat;
+ for (size_t r = 0; r < n_rows; r++)
{
- if (proc->n_cells > 1)
- tab_hline (table, TAL_1, -1, n_cols, 0);
- for (c = 0; c < n_cols; c++)
+ if (!xt->row_tot[r] && proc->mode != INTEGER)
+ continue;
+
+ indexes[ROW_VAR + 1] = r;
+ for (size_t c = 0; c < n_cols; c++)
{
- bool mark_missing = false;
+ if (!xt->col_tot[c] && proc->mode != INTEGER)
+ continue;
+
+ indexes[COL_VAR + 1] = c;
+
double expected_value = xt->row_tot[r] * xt->col_tot[c] / xt->total;
- if (proc->exclude == MV_NEVER
- && (var_is_num_missing (xt->vars[COL_VAR].var,
- xt->vars[COL_VAR].values[c].f, MV_USER)
- || var_is_num_missing (xt->vars[ROW_VAR].var,
- xt->vars[ROW_VAR].values[r].f,
- MV_USER)))
- mark_missing = true;
- for (i = 0; i < proc->n_cells; i++)
- {
- double v;
- int suffix = 0;
-
- switch (proc->a_cells[i])
- {
- case CRS_CL_COUNT:
- v = *mp;
- break;
- case CRS_CL_ROW:
- v = *mp / xt->row_tot[r] * 100.;
- suffix = '%';
- break;
- case CRS_CL_COLUMN:
- v = *mp / xt->col_tot[c] * 100.;
- suffix = '%';
- break;
- case CRS_CL_TOTAL:
- v = *mp / xt->total * 100.;
- suffix = '%';
- break;
- case CRS_CL_EXPECTED:
- v = expected_value;
- break;
- case CRS_CL_RESIDUAL:
- v = *mp - expected_value;
- break;
- case CRS_CL_SRESIDUAL:
- v = (*mp - expected_value) / sqrt (expected_value);
- break;
- case CRS_CL_ASRESIDUAL:
- v = ((*mp - expected_value)
- / sqrt (expected_value
+ double residual = *mp - expected_value;
+ double sresidual = residual / sqrt (expected_value);
+ double asresidual = (sresidual
* (1. - xt->row_tot[r] / xt->total)
- * (1. - xt->col_tot[c] / xt->total)));
- break;
- default:
- NOT_REACHED ();
- }
- format_cell_entry (table, c, i, v, suffix, mark_missing, proc->dict);
+ * (1. - xt->col_tot[c] / xt->total));
+ double entries[] = {
+ [CRS_CL_COUNT] = *mp,
+ [CRS_CL_ROW] = *mp / xt->row_tot[r] * 100.,
+ [CRS_CL_COLUMN] = *mp / xt->col_tot[c] * 100.,
+ [CRS_CL_TOTAL] = *mp / xt->total * 100.,
+ [CRS_CL_EXPECTED] = expected_value,
+ [CRS_CL_RESIDUAL] = residual,
+ [CRS_CL_SRESIDUAL] = sresidual,
+ [CRS_CL_ASRESIDUAL] = asresidual,
+ };
+ for (size_t i = 0; i < proc->n_cells; i++)
+ {
+ int cell = proc->a_cells[i];
+ indexes[0] = crs_leaves[cell];
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (entries[cell]));
}
mp++;
}
-
- tab_offset (table, -1, tab_row (table) + proc->n_cells);
}
/* Row totals. */
- tab_offset (table, -1, tab_row (table) - proc->n_cells * n_rows);
- for (r = 0; r < n_rows; r++)
- {
- bool mark_missing = false;
-
- if (proc->exclude == MV_NEVER
- && var_is_num_missing (xt->vars[ROW_VAR].var,
- xt->vars[ROW_VAR].values[r].f, MV_USER))
- mark_missing = true;
-
- for (i = 0; i < proc->n_cells; i++)
+ for (size_t r = 0; r < n_rows; r++)
+ {
+ if (!xt->row_tot[r] && proc->mode != INTEGER)
+ continue;
+
+ double expected_value = xt->row_tot[r] / xt->total;
+ double entries[] = {
+ [CRS_CL_COUNT] = xt->row_tot[r],
+ [CRS_CL_ROW] = 100.0,
+ [CRS_CL_COLUMN] = expected_value * 100.,
+ [CRS_CL_TOTAL] = expected_value * 100.,
+ [CRS_CL_EXPECTED] = expected_value,
+ [CRS_CL_RESIDUAL] = SYSMIS,
+ [CRS_CL_SRESIDUAL] = SYSMIS,
+ [CRS_CL_ASRESIDUAL] = SYSMIS,
+ };
+ for (size_t i = 0; i < proc->n_cells; i++)
{
- char suffix = 0;
- double v;
-
- switch (proc->a_cells[i])
+ int cell = proc->a_cells[i];
+ double entry = entries[cell];
+ if (entry != SYSMIS)
{
- case CRS_CL_COUNT:
- v = xt->row_tot[r];
- break;
- case CRS_CL_ROW:
- v = 100.0;
- suffix = '%';
- break;
- case CRS_CL_COLUMN:
- v = xt->row_tot[r] / xt->total * 100.;
- suffix = '%';
- break;
- case CRS_CL_TOTAL:
- v = xt->row_tot[r] / xt->total * 100.;
- suffix = '%';
- break;
- case CRS_CL_EXPECTED:
- case CRS_CL_RESIDUAL:
- case CRS_CL_SRESIDUAL:
- case CRS_CL_ASRESIDUAL:
- v = 0.;
- break;
- default:
- NOT_REACHED ();
+ indexes[ROW_VAR + 1] = r;
+ indexes[COL_VAR + 1] = n_cols;
+ indexes[0] = crs_leaves[cell];
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (entry));
}
-
- format_cell_entry (table, n_cols, 0, v, suffix, mark_missing, proc->dict);
- tab_next_row (table);
}
}
- /* Column totals, grand total. */
- last_row = 0;
- if (proc->n_cells > 1)
- tab_hline (table, TAL_1, -1, n_cols, 0);
- for (c = 0; c <= n_cols; c++)
+ for (size_t c = 0; c <= n_cols; c++)
{
- double ct = c < n_cols ? xt->col_tot[c] : xt->total;
- bool mark_missing = false;
- int i;
+ if (c < n_cols && !xt->col_tot[c] && proc->mode != INTEGER)
+ continue;
- if (proc->exclude == MV_NEVER && c < n_cols
- && var_is_num_missing (xt->vars[COL_VAR].var,
- xt->vars[COL_VAR].values[c].f, MV_USER))
- mark_missing = true;
-
- for (i = 0; i < proc->n_cells; i++)
+ double ct = c < n_cols ? xt->col_tot[c] : xt->total;
+ double expected_value = ct / xt->total;
+ double entries[] = {
+ [CRS_CL_COUNT] = ct,
+ [CRS_CL_ROW] = expected_value * 100.0,
+ [CRS_CL_COLUMN] = 100.0,
+ [CRS_CL_TOTAL] = expected_value * 100.,
+ [CRS_CL_EXPECTED] = expected_value,
+ [CRS_CL_RESIDUAL] = SYSMIS,
+ [CRS_CL_SRESIDUAL] = SYSMIS,
+ [CRS_CL_ASRESIDUAL] = SYSMIS,
+ };
+ for (size_t i = 0; i < proc->n_cells; i++)
{
- char suffix = 0;
- double v;
-
- switch (proc->a_cells[i])
+ int cell = proc->a_cells[i];
+ double entry = entries[cell];
+ if (entry != SYSMIS)
{
- case CRS_CL_COUNT:
- v = ct;
- break;
- case CRS_CL_ROW:
- v = ct / xt->total * 100.;
- suffix = '%';
- break;
- case CRS_CL_COLUMN:
- v = 100.;
- suffix = '%';
- break;
- case CRS_CL_TOTAL:
- v = ct / xt->total * 100.;
- suffix = '%';
- break;
- case CRS_CL_EXPECTED:
- case CRS_CL_RESIDUAL:
- case CRS_CL_SRESIDUAL:
- case CRS_CL_ASRESIDUAL:
- continue;
- default:
- NOT_REACHED ();
+ indexes[ROW_VAR + 1] = n_rows;
+ indexes[COL_VAR + 1] = c;
+ indexes[0] = crs_leaves[cell];
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (entry));
}
-
- format_cell_entry (table, c, i, v, suffix, mark_missing, proc->dict);
}
- last_row = i;
}
-
- tab_offset (table, -1, tab_row (table) + last_row);
- tab_offset (table, 0, -1);
}
static void calc_r (struct crosstabulation *,
/* Display chi-square statistics. */
static void
-display_chisq (struct crosstabulation *xt, struct tab_table *chisq,
- bool *showed_fisher)
+display_chisq (struct crosstabulation *xt, struct pivot_table *chisq)
{
- static const char *chisq_stats[N_CHISQ] =
- {
- N_("Pearson Chi-Square"),
- N_("Likelihood Ratio"),
- N_("Fisher's Exact Test"),
- N_("Continuity Correction"),
- N_("Linear-by-Linear Association"),
- };
double chisq_v[N_CHISQ];
double fisher1, fisher2;
int df[N_CHISQ];
-
- int i;
-
calc_chisq (xt, chisq_v, df, &fisher1, &fisher2);
- tab_offset (chisq, xt->n_consts + xt->n_vars - 2, -1);
-
- for (i = 0; i < N_CHISQ; i++)
+ size_t *indexes = xnmalloc (chisq->n_dimensions, sizeof *indexes);
+ assert (xt->n_vars == 2);
+ for (size_t i = 0; i < xt->n_consts; i++)
+ indexes[i + 2] = xt->const_indexes[i];
+ for (int i = 0; i < N_CHISQ; i++)
{
- if ((i != 2 && chisq_v[i] == SYSMIS)
- || (i == 2 && fisher1 == SYSMIS))
- continue;
+ indexes[0] = i;
- tab_text (chisq, 0, 0, TAB_LEFT, gettext (chisq_stats[i]));
- if (i != 2)
- {
- tab_double (chisq, 1, 0, TAB_RIGHT, chisq_v[i], NULL, RC_OTHER);
- tab_double (chisq, 2, 0, TAB_RIGHT, df[i], NULL, RC_WEIGHT);
- tab_double (chisq, 3, 0, TAB_RIGHT,
- gsl_cdf_chisq_Q (chisq_v[i], df[i]), NULL, RC_PVALUE);
- }
- else
- {
- *showed_fisher = true;
- tab_double (chisq, 4, 0, TAB_RIGHT, fisher2, NULL, RC_PVALUE);
- tab_double (chisq, 5, 0, TAB_RIGHT, fisher1, NULL, RC_PVALUE);
- }
- tab_next_row (chisq);
+ double entries[5] = { SYSMIS, SYSMIS, SYSMIS, SYSMIS, SYSMIS };
+ if (i == 2)
+ {
+ entries[3] = fisher2;
+ entries[4] = fisher1;
+ }
+ else if (chisq_v[i] != SYSMIS)
+ {
+ entries[0] = chisq_v[i];
+ entries[1] = df[i];
+ entries[2] = gsl_cdf_chisq_Q (chisq_v[i], df[i]);
+ }
+
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ if (entries[j] != SYSMIS)
+ {
+ indexes[1] = j;
+ pivot_table_put (chisq, indexes, chisq->n_dimensions,
+ pivot_value_new_number (entries[j]));
+ }
}
- tab_text (chisq, 0, 0, TAB_LEFT, _("N of Valid Cases"));
- tab_double (chisq, 1, 0, TAB_RIGHT, xt->total, NULL, RC_WEIGHT);
- tab_next_row (chisq);
+ indexes[0] = 5;
+ indexes[1] = 0;
+ pivot_table_put (chisq, indexes, chisq->n_dimensions,
+ pivot_value_new_number (xt->total));
- tab_offset (chisq, 0, -1);
+ free (indexes);
}
static int calc_symmetric (struct crosstabs_proc *, struct crosstabulation *,
/* Display symmetric measures. */
static void
display_symmetric (struct crosstabs_proc *proc, struct crosstabulation *xt,
- struct tab_table *sym)
+ struct pivot_table *sym)
{
- static const char *categories[] =
- {
- N_("Nominal by Nominal"),
- N_("Ordinal by Ordinal"),
- N_("Interval by Interval"),
- N_("Measure of Agreement"),
- };
-
- static const char *stats[N_SYMMETRIC] =
- {
- N_("Phi"),
- N_("Cramer's V"),
- N_("Contingency Coefficient"),
- N_("Kendall's tau-b"),
- N_("Kendall's tau-c"),
- N_("Gamma"),
- N_("Spearman Correlation"),
- N_("Pearson's R"),
- N_("Kappa"),
- };
-
- static const int stats_categories[N_SYMMETRIC] =
- {
- 0, 0, 0, 1, 1, 1, 1, 2, 3,
- };
-
- int last_cat = -1;
double sym_v[N_SYMMETRIC], sym_ase[N_SYMMETRIC], sym_t[N_SYMMETRIC];
double somers_d_v[3], somers_d_ase[3], somers_d_t[3];
- int i;
if (!calc_symmetric (proc, xt, sym_v, sym_ase, sym_t,
somers_d_v, somers_d_ase, somers_d_t))
return;
- tab_offset (sym, xt->n_consts + xt->n_vars - 2, -1);
+ size_t *indexes = xnmalloc (sym->n_dimensions, sizeof *indexes);
+ assert (xt->n_vars == 2);
+ for (size_t i = 0; i < xt->n_consts; i++)
+ indexes[i + 2] = xt->const_indexes[i];
- for (i = 0; i < N_SYMMETRIC; i++)
+ for (int i = 0; i < N_SYMMETRIC; i++)
{
if (sym_v[i] == SYSMIS)
continue;
- if (stats_categories[i] != last_cat)
- {
- last_cat = stats_categories[i];
- tab_text (sym, 0, 0, TAB_LEFT, gettext (categories[last_cat]));
- }
+ indexes[1] = i;
- tab_text (sym, 1, 0, TAB_LEFT, gettext (stats[i]));
- tab_double (sym, 2, 0, TAB_RIGHT, sym_v[i], NULL, RC_OTHER);
- if (sym_ase[i] != SYSMIS)
- tab_double (sym, 3, 0, TAB_RIGHT, sym_ase[i], NULL, RC_OTHER);
- if (sym_t[i] != SYSMIS)
- tab_double (sym, 4, 0, TAB_RIGHT, sym_t[i], NULL, RC_OTHER);
- /*tab_double (sym, 5, 0, TAB_RIGHT, normal_sig (sym_v[i]), NULL, RC_PVALUE);*/
- tab_next_row (sym);
+ double entries[] = { sym_v[i], sym_ase[i], sym_t[i] };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ if (entries[j] != SYSMIS)
+ {
+ indexes[0] = j;
+ pivot_table_put (sym, indexes, sym->n_dimensions,
+ pivot_value_new_number (entries[j]));
+ }
}
- tab_text (sym, 0, 0, TAB_LEFT, _("N of Valid Cases"));
- tab_double (sym, 2, 0, TAB_RIGHT, xt->total, NULL, RC_WEIGHT);
- tab_next_row (sym);
-
- tab_offset (sym, 0, -1);
+ indexes[1] = N_SYMMETRIC;
+ indexes[0] = 0;
+ struct pivot_value *total = pivot_value_new_number (xt->total);
+ pivot_value_set_rc (sym, total, PIVOT_RC_COUNT);
+ pivot_table_put (sym, indexes, sym->n_dimensions, total);
}
-static int calc_risk (struct crosstabulation *,
- double[], double[], double[], union value *);
+static bool calc_risk (struct crosstabulation *,
+ double[], double[], double[], union value *,
+ double *);
/* Display risk estimate. */
static void
-display_risk (struct crosstabulation *xt, struct tab_table *risk)
+display_risk (struct crosstabulation *xt, struct pivot_table *risk,
+ struct pivot_dimension *risk_statistics)
{
- char buf[256];
- double risk_v[3], lower[3], upper[3];
+ double risk_v[3], lower[3], upper[3], n_valid;
union value c[2];
- int i;
-
- if (!calc_risk (xt, risk_v, upper, lower, c))
+ if (!calc_risk (xt, risk_v, upper, lower, c, &n_valid))
return;
- tab_offset (risk, xt->n_consts + xt->n_vars - 2, -1);
+ size_t *indexes = xnmalloc (risk->n_dimensions, sizeof *indexes);
+ assert (xt->n_vars == 2);
+ for (size_t i = 0; i < xt->n_consts; i++)
+ indexes[i + 2] = xt->const_indexes[i];
- for (i = 0; i < 3; i++)
+ for (int i = 0; i < 3; i++)
{
const struct variable *cv = xt->vars[COL_VAR].var;
const struct variable *rv = xt->vars[ROW_VAR].var;
- int cvw = var_get_width (cv);
- int rvw = var_get_width (rv);
if (risk_v[i] == SYSMIS)
continue;
+ struct string label = DS_EMPTY_INITIALIZER;
switch (i)
{
case 0:
- if (var_is_numeric (cv))
- sprintf (buf, _("Odds Ratio for %s (%g / %g)"),
- var_to_string (cv), c[0].f, c[1].f);
- else
- sprintf (buf, _("Odds Ratio for %s (%.*s / %.*s)"),
- var_to_string (cv),
- cvw, value_str (&c[0], cvw),
- cvw, value_str (&c[1], cvw));
+ ds_put_format (&label, _("Odds Ratio for %s"), var_to_string (rv));
+ ds_put_cstr (&label, " (");
+ var_append_value_name (rv, &c[0], &label);
+ ds_put_cstr (&label, " / ");
+ var_append_value_name (rv, &c[1], &label);
+ ds_put_cstr (&label, ")");
break;
case 1:
case 2:
- if (var_is_numeric (rv))
- sprintf (buf, _("For cohort %s = %.*g"),
- var_to_string (rv), DBL_DIG + 1,
- xt->vars[ROW_VAR].values[i - 1].f);
- else
- sprintf (buf, _("For cohort %s = %.*s"),
- var_to_string (rv),
- rvw, value_str (&xt->vars[ROW_VAR].values[i - 1], rvw));
+ ds_put_format (&label, _("For cohort %s = "), var_to_string (cv));
+ var_append_value_name (cv, &xt->vars[ROW_VAR].values[i - 1], &label);
break;
}
- tab_text (risk, 0, 0, TAB_LEFT, buf);
- tab_double (risk, 1, 0, TAB_RIGHT, risk_v[i], NULL, RC_OTHER);
- tab_double (risk, 2, 0, TAB_RIGHT, lower[i], NULL, RC_OTHER);
- tab_double (risk, 3, 0, TAB_RIGHT, upper[i], NULL, RC_OTHER);
- tab_next_row (risk);
- }
-
- tab_text (risk, 0, 0, TAB_LEFT, _("N of Valid Cases"));
- tab_double (risk, 1, 0, TAB_RIGHT, xt->total, NULL, RC_WEIGHT);
- tab_next_row (risk);
+ indexes[1] = pivot_category_create_leaf (
+ risk_statistics->root,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&label)));
- tab_offset (risk, 0, -1);
+ double entries[] = { risk_v[i], lower[i], upper[i] };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ indexes[0] = j;
+ pivot_table_put (risk, indexes, risk->n_dimensions,
+ pivot_value_new_number (entries[i]));
+ }
+ }
+ indexes[1] = pivot_category_create_leaf (
+ risk_statistics->root,
+ pivot_value_new_text (N_("N of Valid Cases")));
+ indexes[0] = 0;
+ pivot_table_put (risk, indexes, risk->n_dimensions,
+ pivot_value_new_number (n_valid));
+ free (indexes);
}
static int calc_directional (struct crosstabs_proc *, struct crosstabulation *,
/* Display directional measures. */
static void
-display_directional (struct crosstabs_proc *proc, struct crosstabulation *xt,
- struct tab_table *direct)
+display_directional (struct crosstabs_proc *proc,
+ struct crosstabulation *xt, struct pivot_table *direct)
{
- static const char *categories[] =
- {
- N_("Nominal by Nominal"),
- N_("Ordinal by Ordinal"),
- N_("Nominal by Interval"),
- };
-
- static const char *stats[] =
- {
- N_("Lambda"),
- N_("Goodman and Kruskal tau"),
- N_("Uncertainty Coefficient"),
- N_("Somers' d"),
- N_("Eta"),
- };
-
- static const char *types[] =
- {
- N_("Symmetric"),
- N_("%s Dependent"),
- N_("%s Dependent"),
- };
-
- static const int stats_categories[N_DIRECTIONAL] =
- {
- 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 2,
- };
-
- static const int stats_stats[N_DIRECTIONAL] =
- {
- 0, 0, 0, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4,
- };
-
- static const int stats_types[N_DIRECTIONAL] =
- {
- 0, 1, 2, 1, 2, 0, 1, 2, 0, 1, 2, 1, 2,
- };
-
- static const int *stats_lookup[] =
- {
- stats_categories,
- stats_stats,
- stats_types,
- };
-
- static const char **stats_names[] =
- {
- categories,
- stats,
- types,
- };
-
- int last[3] =
- {
- -1, -1, -1,
- };
-
double direct_v[N_DIRECTIONAL];
double direct_ase[N_DIRECTIONAL];
double direct_t[N_DIRECTIONAL];
double sig[N_DIRECTIONAL];
-
- int i;
-
if (!calc_directional (proc, xt, direct_v, direct_ase, direct_t, sig))
return;
- tab_offset (direct, xt->n_consts + xt->n_vars - 2, -1);
+ size_t *indexes = xnmalloc (direct->n_dimensions, sizeof *indexes);
+ assert (xt->n_vars == 2);
+ for (size_t i = 0; i < xt->n_consts; i++)
+ indexes[i + 2] = xt->const_indexes[i];
- for (i = 0; i < N_DIRECTIONAL; i++)
+ for (int i = 0; i < N_DIRECTIONAL; i++)
{
if (direct_v[i] == SYSMIS)
continue;
- {
- int j;
-
- for (j = 0; j < 3; j++)
- if (last[j] != stats_lookup[j][i])
- {
- if (j < 2)
- tab_hline (direct, TAL_1, j, 6, 0);
-
- for (; j < 3; j++)
- {
- const char *string;
- int k = last[j] = stats_lookup[j][i];
-
- if (k == 0)
- string = NULL;
- else if (k == 1)
- string = var_to_string (xt->vars[0].var);
- else
- string = var_to_string (xt->vars[1].var);
-
- tab_text_format (direct, j, 0, TAB_LEFT,
- gettext (stats_names[j][k]), string);
- }
- }
- }
+ indexes[1] = i;
- tab_double (direct, 3, 0, TAB_RIGHT, direct_v[i], NULL, RC_OTHER);
- if (direct_ase[i] != SYSMIS)
- tab_double (direct, 4, 0, TAB_RIGHT, direct_ase[i], NULL, RC_OTHER);
- if (direct_t[i] != SYSMIS)
- tab_double (direct, 5, 0, TAB_RIGHT, direct_t[i], NULL, RC_OTHER);
- tab_double (direct, 6, 0, TAB_RIGHT, sig[i], NULL, RC_PVALUE);
- tab_next_row (direct);
+ double entries[] = {
+ direct_v[i], direct_ase[i], direct_t[i], sig[i],
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ if (entries[j] != SYSMIS)
+ {
+ indexes[0] = j;
+ pivot_table_put (direct, indexes, direct->n_dimensions,
+ pivot_value_new_number (entries[j]));
+ }
}
-
- tab_offset (direct, 0, -1);
}
\f
/* Statistical calculations. */
double chisq[N_CHISQ], int df[N_CHISQ],
double *fisher1, double *fisher2)
{
- int r, c;
-
chisq[0] = chisq[1] = 0.;
chisq[2] = chisq[3] = chisq[4] = SYSMIS;
*fisher1 = *fisher2 = SYSMIS;
return;
}
- size_t n_rows = xt->vars[ROW_VAR].n_values;
size_t n_cols = xt->vars[COL_VAR].n_values;
- for (r = 0; r < n_rows; r++)
- for (c = 0; c < n_cols; c++)
+ FOR_EACH_POPULATED_ROW (r, xt)
+ FOR_EACH_POPULATED_COLUMN (c, xt)
{
- const double expected = xt->row_tot[r] * xt->col_tot[c] / xt->total;
- const double freq = xt->mat[n_cols * r + c];
- const double residual = freq - expected;
+ const double expected = xt->row_tot[r] * xt->col_tot[c] / xt->total;
+ const double freq = xt->mat[n_cols * r + c];
+ const double residual = freq - expected;
chisq[0] += residual * residual / expected;
- if (freq)
- chisq[1] += freq * log (expected / freq);
+ if (freq)
+ chisq[1] += freq * log (expected / freq);
}
if (chisq[0] == 0.)
{
int nz_cols[2];
- int i, j;
-
- for (i = j = 0; i < n_cols; i++)
- if (xt->col_tot[i] != 0.)
- {
- nz_cols[j++] = i;
- if (j == 2)
- break;
- }
+ int j = 0;
+ FOR_EACH_POPULATED_COLUMN (c, xt)
+ {
+ nz_cols[j++] = c;
+ if (j == 2)
+ break;
+ }
assert (j == 2);
f11 = xt->mat[nz_cols[0]];
if (proc->statistics & ((1u << CRS_ST_PHI) | (1u << CRS_ST_CC)))
{
double Xp = 0.; /* Pearson chi-square. */
- int r, c;
- for (r = 0; r < n_rows; r++)
- for (c = 0; c < n_cols; c++)
+ FOR_EACH_POPULATED_ROW (r, xt)
+ FOR_EACH_POPULATED_COLUMN (c, xt)
{
- const double expected = xt->row_tot[r] * xt->col_tot[c] / xt->total;
- const double freq = xt->mat[n_cols * r + c];
- const double residual = freq - expected;
+ double expected = xt->row_tot[r] * xt->col_tot[c] / xt->total;
+ double freq = xt->mat[n_cols * r + c];
+ double residual = freq - expected;
Xp += residual * residual / expected;
}
}
/* Calculate risk estimate. */
-static int
+static bool
calc_risk (struct crosstabulation *xt,
- double *value, double *upper, double *lower, union value *c)
+ double *value, double *upper, double *lower, union value *c,
+ double *n_valid)
{
size_t n_cols = xt->vars[COL_VAR].n_values;
double f11, f12, f21, f22;
double v;
- {
- int i;
-
- for (i = 0; i < 3; i++)
- value[i] = upper[i] = lower[i] = SYSMIS;
- }
+ for (int i = 0; i < 3; i++)
+ value[i] = upper[i] = lower[i] = SYSMIS;
if (xt->ns_rows != 2 || xt->ns_cols != 2)
- return 0;
+ return false;
{
+ /* Find populated columns. */
int nz_cols[2];
- int i, j;
-
- for (i = j = 0; i < n_cols; i++)
- if (xt->col_tot[i] != 0.)
- {
- nz_cols[j++] = i;
- if (j == 2)
- break;
- }
-
- assert (j == 2);
-
- f11 = xt->mat[nz_cols[0]];
- f12 = xt->mat[nz_cols[1]];
- f21 = xt->mat[nz_cols[0] + n_cols];
- f22 = xt->mat[nz_cols[1] + n_cols];
+ int n = 0;
+ FOR_EACH_POPULATED_COLUMN (c, xt)
+ nz_cols[n++] = c;
+ assert (n == 2);
+
+ /* Find populated rows. */
+ int nz_rows[2];
+ n = 0;
+ FOR_EACH_POPULATED_ROW (r, xt)
+ nz_rows[n++] = r;
+ assert (n == 2);
+
+ f11 = xt->mat[nz_cols[0] + n_cols * nz_rows[0]];
+ f12 = xt->mat[nz_cols[1] + n_cols * nz_rows[0]];
+ f21 = xt->mat[nz_cols[0] + n_cols * nz_rows[1]];
+ f22 = xt->mat[nz_cols[1] + n_cols * nz_rows[1]];
+ *n_valid = f11 + f12 + f21 + f22;
c[0] = xt->vars[COL_VAR].values[nz_cols[0]];
c[1] = xt->vars[COL_VAR].values[nz_cols[1]];
lower[2] = value[2] * exp (-1.960 * v);
upper[2] = value[2] * exp (1.960 * v);
- return 1;
+ return true;
}
/* Calculate directional measures. */
{
size_t n_rows = xt->vars[ROW_VAR].n_values;
size_t n_cols = xt->vars[COL_VAR].n_values;
- {
- int i;
-
- for (i = 0; i < N_DIRECTIONAL; i++)
- v[i] = ase[i] = t[i] = sig[i] = SYSMIS;
- }
+ for (int i = 0; i < N_DIRECTIONAL; i++)
+ v[i] = ase[i] = t[i] = sig[i] = SYSMIS;
/* Lambda. */
if (proc->statistics & (1u << CRS_ST_LAMBDA))
{
+ /* Find maximum for each row and their sum. */
double *fim = xnmalloc (n_rows, sizeof *fim);
int *fim_index = xnmalloc (n_rows, sizeof *fim_index);
- double *fmj = xnmalloc (n_cols, sizeof *fmj);
- int *fmj_index = xnmalloc (n_cols, sizeof *fmj_index);
- double sum_fim, sum_fmj;
- double rm, cm;
- int rm_index, cm_index;
- int i, j;
-
- /* Find maximum for each row and their sum. */
- for (sum_fim = 0., i = 0; i < n_rows; i++)
+ double sum_fim = 0.0;
+ for (int i = 0; i < n_rows; i++)
{
double max = xt->mat[i * n_cols];
int index = 0;
- for (j = 1; j < n_cols; j++)
+ for (int j = 1; j < n_cols; j++)
if (xt->mat[j + i * n_cols] > max)
{
max = xt->mat[j + i * n_cols];
index = j;
}
- sum_fim += fim[i] = max;
+ fim[i] = max;
+ sum_fim += max;
fim_index[i] = index;
}
/* Find maximum for each column. */
- for (sum_fmj = 0., j = 0; j < n_cols; j++)
+ double *fmj = xnmalloc (n_cols, sizeof *fmj);
+ int *fmj_index = xnmalloc (n_cols, sizeof *fmj_index);
+ double sum_fmj = 0.0;
+ for (int j = 0; j < n_cols; j++)
{
double max = xt->mat[j];
int index = 0;
- for (i = 1; i < n_rows; i++)
+ for (int i = 1; i < n_rows; i++)
if (xt->mat[j + i * n_cols] > max)
{
max = xt->mat[j + i * n_cols];
index = i;
}
- sum_fmj += fmj[j] = max;
+ fmj[j] = max;
+ sum_fmj += max;
fmj_index[j] = index;
}
/* Find maximum row total. */
- rm = xt->row_tot[0];
- rm_index = 0;
- for (i = 1; i < n_rows; i++)
+ double rm = xt->row_tot[0];
+ int rm_index = 0;
+ for (int i = 1; i < n_rows; i++)
if (xt->row_tot[i] > rm)
{
rm = xt->row_tot[i];
}
/* Find maximum column total. */
- cm = xt->col_tot[0];
- cm_index = 0;
- for (j = 1; j < n_cols; j++)
+ double cm = xt->col_tot[0];
+ int cm_index = 0;
+ for (int j = 1; j < n_cols; j++)
if (xt->col_tot[j] > cm)
{
cm = xt->col_tot[j];
/* ASE1 for Y given XT. */
{
- double accum;
-
- accum = 0.;
- for (i = 0; i < n_rows; i++)
+ double accum = 0.0;
+ for (int i = 0; i < n_rows; i++)
if (cm_index == fim_index[i])
accum += fim[i];
ase[2] = sqrt ((xt->total - sum_fim) * (sum_fim + cm - 2. * accum)
/* ASE0 for Y given XT. */
{
- double accum;
-
- for (accum = 0., i = 0; i < n_rows; i++)
+ double accum = 0.0;
+ for (int i = 0; i < n_rows; i++)
if (cm_index != fim_index[i])
accum += (xt->mat[i * n_cols + fim_index[i]]
+ xt->mat[i * n_cols + cm_index]);
/* ASE1 for XT given Y. */
{
- double accum;
-
- accum = 0.;
- for (j = 0; j < n_cols; j++)
+ double accum = 0.0;
+ for (int j = 0; j < n_cols; j++)
if (rm_index == fmj_index[j])
accum += fmj[j];
ase[1] = sqrt ((xt->total - sum_fmj) * (sum_fmj + rm - 2. * accum)
/* ASE0 for XT given Y. */
{
- double accum;
-
- for (accum = 0., j = 0; j < n_cols; j++)
+ double accum = 0.0;
+ for (int j = 0; j < n_cols; j++)
if (rm_index != fmj_index[j])
accum += (xt->mat[j + n_cols * fmj_index[j]]
+ xt->mat[j + n_cols * rm_index]);
/* Symmetric ASE0 and ASE1. */
{
- double accum0;
- double accum1;
-
- for (accum0 = accum1 = 0., i = 0; i < n_rows; i++)
- for (j = 0; j < n_cols; j++)
+ double accum0 = 0.0;
+ double accum1 = 0.0;
+ for (int i = 0; i < n_rows; i++)
+ for (int j = 0; j < n_cols; j++)
{
int temp0 = (fmj_index[j] == i) + (fim_index[i] == j);
int temp1 = (i == rm_index) + (j == cm_index);
/ (2. * xt->total - rm - cm));
}
- for (i = 0; i < 3; i++)
+ for (int i = 0; i < 3; i++)
sig[i] = 2 * gsl_cdf_ugaussian_Q (t[i]);
free (fim);
/* Tau. */
{
- double sum_fij2_ri, sum_fij2_ci;
- double sum_ri2, sum_cj2;
-
- for (sum_fij2_ri = sum_fij2_ci = 0., i = 0; i < n_rows; i++)
- for (j = 0; j < n_cols; j++)
+ double sum_fij2_ri = 0.0;
+ double sum_fij2_ci = 0.0;
+ FOR_EACH_POPULATED_ROW (i, xt)
+ FOR_EACH_POPULATED_COLUMN (j, xt)
{
double temp = pow2 (xt->mat[j + i * n_cols]);
sum_fij2_ri += temp / xt->row_tot[i];
sum_fij2_ci += temp / xt->col_tot[j];
}
- for (sum_ri2 = 0., i = 0; i < n_rows; i++)
+ double sum_ri2 = 0.0;
+ for (int i = 0; i < n_rows; i++)
sum_ri2 += pow2 (xt->row_tot[i]);
- for (sum_cj2 = 0., j = 0; j < n_cols; j++)
+ double sum_cj2 = 0.0;
+ for (int j = 0; j < n_cols; j++)
sum_cj2 += pow2 (xt->col_tot[j]);
v[3] = (xt->total * sum_fij2_ci - sum_ri2) / (pow2 (xt->total) - sum_ri2);
if (proc->statistics & (1u << CRS_ST_UC))
{
- double UX, UY, UXY, P;
- double ase1_yx, ase1_xy, ase1_sym;
- int i, j;
+ double UX = 0.0;
+ FOR_EACH_POPULATED_ROW (i, xt)
+ UX -= xt->row_tot[i] / xt->total * log (xt->row_tot[i] / xt->total);
- for (UX = 0., i = 0; i < n_rows; i++)
- if (xt->row_tot[i] > 0.)
- UX -= xt->row_tot[i] / xt->total * log (xt->row_tot[i] / xt->total);
+ double UY = 0.0;
+ FOR_EACH_POPULATED_COLUMN (j, xt)
+ UY -= xt->col_tot[j] / xt->total * log (xt->col_tot[j] / xt->total);
- for (UY = 0., j = 0; j < n_cols; j++)
- if (xt->col_tot[j] > 0.)
- UY -= xt->col_tot[j] / xt->total * log (xt->col_tot[j] / xt->total);
-
- for (UXY = P = 0., i = 0; i < n_rows; i++)
- for (j = 0; j < n_cols; j++)
+ double UXY = 0.0;
+ double P = 0.0;
+ for (int i = 0; i < n_rows; i++)
+ for (int j = 0; j < n_cols; j++)
{
double entry = xt->mat[j + i * n_cols];
UXY -= entry / xt->total * log (entry / xt->total);
}
- for (ase1_yx = ase1_xy = ase1_sym = 0., i = 0; i < n_rows; i++)
- for (j = 0; j < n_cols; j++)
+ double ase1_yx = 0.0;
+ double ase1_xy = 0.0;
+ double ase1_sym = 0.0;
+ for (int i = 0; i < n_rows; i++)
+ for (int j = 0; j < n_cols; j++)
{
double entry = xt->mat[j + i * n_cols];
if (calc_symmetric (proc, xt, v_dummy, ase_dummy, t_dummy,
somers_d_v, somers_d_ase, somers_d_t))
{
- int i;
- for (i = 0; i < 3; i++)
+ for (int i = 0; i < 3; i++)
{
v[8 + i] = somers_d_v[i];
ase[8 + i] = somers_d_ase[i];
/* Eta. */
if (proc->statistics & (1u << CRS_ST_ETA))
{
- {
- double sum_Xr, sum_X2r;
- double SX, SXW;
- int i, j;
-
- for (sum_Xr = sum_X2r = 0., i = 0; i < n_rows; i++)
- {
- sum_Xr += xt->vars[ROW_VAR].values[i].f * xt->row_tot[i];
- sum_X2r += pow2 (xt->vars[ROW_VAR].values[i].f) * xt->row_tot[i];
- }
- SX = sum_X2r - pow2 (sum_Xr) / xt->total;
-
- for (SXW = 0., j = 0; j < n_cols; j++)
- {
- double cum;
-
- for (cum = 0., i = 0; i < n_rows; i++)
- {
- SXW += (pow2 (xt->vars[ROW_VAR].values[i].f)
- * xt->mat[j + i * n_cols]);
- cum += (xt->vars[ROW_VAR].values[i].f
- * xt->mat[j + i * n_cols]);
- }
+ /* X dependent. */
+ double sum_Xr = 0.0;
+ double sum_X2r = 0.0;
+ for (int i = 0; i < n_rows; i++)
+ {
+ sum_Xr += xt->vars[ROW_VAR].values[i].f * xt->row_tot[i];
+ sum_X2r += pow2 (xt->vars[ROW_VAR].values[i].f) * xt->row_tot[i];
+ }
+ double SX = sum_X2r - pow2 (sum_Xr) / xt->total;
- SXW -= cum * cum / xt->col_tot[j];
- }
- v[11] = sqrt (1. - SXW / SX);
- }
+ double SXW = 0.0;
+ FOR_EACH_POPULATED_COLUMN (j, xt)
+ {
+ double cum = 0.0;
- {
- double sum_Yc, sum_Y2c;
- double SY, SYW;
- int i, j;
+ for (int i = 0; i < n_rows; i++)
+ {
+ SXW += (pow2 (xt->vars[ROW_VAR].values[i].f)
+ * xt->mat[j + i * n_cols]);
+ cum += (xt->vars[ROW_VAR].values[i].f
+ * xt->mat[j + i * n_cols]);
+ }
- for (sum_Yc = sum_Y2c = 0., i = 0; i < n_cols; i++)
- {
- sum_Yc += xt->vars[COL_VAR].values[i].f * xt->col_tot[i];
- sum_Y2c += pow2 (xt->vars[COL_VAR].values[i].f) * xt->col_tot[i];
- }
- SY = sum_Y2c - sum_Yc * sum_Yc / xt->total;
+ SXW -= cum * cum / xt->col_tot[j];
+ }
+ v[11] = sqrt (1. - SXW / SX);
- for (SYW = 0., i = 0; i < n_rows; i++)
- {
- double cum;
+ /* Y dependent. */
+ double sum_Yc = 0.0;
+ double sum_Y2c = 0.0;
+ for (int i = 0; i < n_cols; i++)
+ {
+ sum_Yc += xt->vars[COL_VAR].values[i].f * xt->col_tot[i];
+ sum_Y2c += pow2 (xt->vars[COL_VAR].values[i].f) * xt->col_tot[i];
+ }
+ double SY = sum_Y2c - pow2 (sum_Yc) / xt->total;
- for (cum = 0., j = 0; j < n_cols; j++)
- {
- SYW += (pow2 (xt->vars[COL_VAR].values[j].f)
- * xt->mat[j + i * n_cols]);
- cum += (xt->vars[COL_VAR].values[j].f
- * xt->mat[j + i * n_cols]);
- }
+ double SYW = 0.0;
+ FOR_EACH_POPULATED_ROW (i, xt)
+ {
+ double cum = 0.0;
+ for (int j = 0; j < n_cols; j++)
+ {
+ SYW += (pow2 (xt->vars[COL_VAR].values[j].f)
+ * xt->mat[j + i * n_cols]);
+ cum += (xt->vars[COL_VAR].values[j].f
+ * xt->mat[j + i * n_cols]);
+ }
- SYW -= cum * cum / xt->row_tot[i];
- }
- v[12] = sqrt (1. - SYW / SY);
- }
+ SYW -= cum * cum / xt->row_tot[i];
+ }
+ v[12] = sqrt (1. - SYW / SY);
}
return 1;
#include "libpspp/i18n.h"
#include "libpspp/message.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
double stats[DSC_N_STATS]; /* All the stats' values. */
};
-/* Output format. */
-enum dsc_format
- {
- DSC_LINE, /* Abbreviated format. */
- DSC_SERIAL /* Long format. */
- };
-
/* A DESCRIPTIVES procedure. */
struct dsc_proc
{
/* Per-variable info. */
+ struct dictionary *dict; /* Dictionary. */
struct dsc_var *vars; /* Variables. */
size_t var_cnt; /* Number of variables. */
/* User options. */
enum dsc_missing_type missing_type; /* Treatment of missing values. */
enum mv_class exclude; /* Classes of missing values to exclude. */
- int show_var_labels; /* Nonzero to show variable labels. */
- int show_index; /* Nonzero to show variable index. */
- enum dsc_format format; /* Output format. */
/* Accumulated results. */
double missing_listwise; /* Sum of weights of cases missing listwise. */
/* Create and initialize dsc. */
dsc = xmalloc (sizeof *dsc);
+ dsc->dict = dict;
dsc->vars = NULL;
dsc->var_cnt = 0;
dsc->missing_type = DSC_VARIABLE;
dsc->exclude = MV_ANY;
- dsc->show_var_labels = 1;
- dsc->show_index = 0;
- dsc->format = DSC_LINE;
dsc->missing_listwise = 0.;
dsc->valid = 0.;
dsc->bad_warn = 1;
lex_match (lexer, T_EQUALS);
while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
- if (lex_match_id (lexer, "LABELS"))
- dsc->show_var_labels = 1;
- else if (lex_match_id (lexer, "NOLABELS"))
- dsc->show_var_labels = 0;
- else if (lex_match_id (lexer, "INDEX"))
- dsc->show_index = 1;
- else if (lex_match_id (lexer, "NOINDEX"))
- dsc->show_index = 0;
- else if (lex_match_id (lexer, "LINE"))
- dsc->format = DSC_LINE;
- else if (lex_match_id (lexer, "SERIAL"))
- dsc->format = DSC_SERIAL;
+ if (lex_match_id (lexer, "LABELS")
+ || lex_match_id (lexer, "NOLABELS")
+ || lex_match_id (lexer, "INDEX")
+ || lex_match_id (lexer, "NOINDEX")
+ || lex_match_id (lexer, "LINE")
+ || lex_match_id (lexer, "SERIAL"))
+ {
+ /* Ignore. */
+ }
else
{
lex_error (lexer, NULL);
static void
dump_z_table (struct dsc_proc *dsc)
{
- size_t cnt = 0;
- struct tab_table *t;
+ struct pivot_table *table = pivot_table_create (
+ N_("Mapping of Variables to Z-scores"));
- {
- size_t i;
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Names"),
+ N_("Source"), N_("Target"));
- for (i = 0; i < dsc->var_cnt; i++)
- if (dsc->vars[i].z_name != NULL)
- cnt++;
- }
-
- t = tab_create (2, cnt + 1);
- tab_title (t, _("Mapping of variables to corresponding Z-scores."));
- tab_headers (t, 0, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, TAL_0, TAL_1, 0, 0, 1, cnt);
- tab_hline (t, TAL_2, 0, 1, 1);
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Source"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Target"));
+ struct pivot_dimension *names = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+ names->hide_all_labels = true;
- {
- size_t i, y;
+ for (size_t i = 0; i < dsc->var_cnt; i++)
+ if (dsc->vars[i].z_name != NULL)
+ {
+ int row = pivot_category_create_leaf (names->root,
+ pivot_value_new_number (i));
- for (i = 0, y = 1; i < dsc->var_cnt; i++)
- if (dsc->vars[i].z_name != NULL)
- {
- tab_text (t, 0, y, TAB_LEFT, var_to_string (dsc->vars[i].v));
- tab_text (t, 1, y++, TAB_LEFT, dsc->vars[i].z_name);
- }
- }
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_variable (dsc->vars[i].v));
+ pivot_table_put2 (table, 1, row,
+ pivot_value_new_user_text (dsc->vars[i].z_name, -1));
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
static void
display (struct dsc_proc *dsc)
{
- size_t i;
- int nc;
- struct tab_table *t;
-
- nc = 1 + (dsc->format == DSC_SERIAL ? 2 : 1);
- for (i = 0; i < DSC_N_STATS; i++)
+ struct pivot_table *table = pivot_table_create (
+ N_("Descriptive Statistics"));
+ pivot_table_set_weight_var (table, dict_get_weight (dsc->dict));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_leaf_rc (
+ statistics->root, pivot_value_new_text (N_("N")), PIVOT_RC_COUNT);
+ for (int i = 0; i < DSC_N_STATS; i++)
if (dsc->show_stats & (1ul << i))
- nc++;
+ pivot_category_create_leaf (statistics->root,
+ pivot_value_new_text (dsc_info[i].name));
if (dsc->sort_by_stat != DSC_NONE)
sort (dsc->vars, dsc->var_cnt, sizeof *dsc->vars,
descriptives_compare_dsc_vars, dsc);
- t = tab_create (nc, dsc->var_cnt + 1);
- tab_headers (t, 1, 0, 1, 0);
- tab_box (t, TAL_1, TAL_1, -1, -1, 0, 0, nc - 1, dsc->var_cnt);
- tab_box (t, -1, -1, -1, TAL_1, 1, 0, nc - 1, dsc->var_cnt);
- tab_hline (t, TAL_2, 0, nc - 1, 1);
- tab_vline (t, TAL_2, 1, 0, dsc->var_cnt);
-
- nc = 0;
- tab_text (t, nc++, 0, TAB_LEFT | TAT_TITLE, _("Variable"));
- if (dsc->format == DSC_SERIAL)
- {
- tab_text (t, nc++, 0, TAB_CENTER | TAT_TITLE, _("Valid N"));
- tab_text (t, nc++, 0, TAB_CENTER | TAT_TITLE, _("Missing N"));
- }
- else
- tab_text (t, nc++, 0, TAB_CENTER | TAT_TITLE, "N");
-
- for (i = 0; i < DSC_N_STATS; i++)
- if (dsc->show_stats & (1ul << i))
- {
- const char *title = gettext (dsc_info[i].name);
- tab_text (t, nc++, 0, TAB_CENTER | TAT_TITLE, title);
- }
-
- for (i = 0; i < dsc->var_cnt; i++)
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+ for (size_t i = 0; i < dsc->var_cnt; i++)
{
struct dsc_var *dv = &dsc->vars[i];
- size_t j;
- nc = 0;
- tab_text (t, nc++, i + 1, TAB_LEFT, var_to_string (dv->v));
- tab_text_format (t, nc++, i + 1, 0, "%.*g", DBL_DIG + 1, dv->valid);
- if (dsc->format == DSC_SERIAL)
- tab_text_format (t, nc++, i + 1, 0, "%.*g", DBL_DIG + 1, dv->missing);
+ int row = pivot_category_create_leaf (variables->root,
+ pivot_value_new_variable (dv->v));
- for (j = 0; j < DSC_N_STATS; j++)
+ int column = 0;
+ pivot_table_put2 (table, column++, row,
+ pivot_value_new_number (dv->valid));
+
+ for (int j = 0; j < DSC_N_STATS; j++)
if (dsc->show_stats & (1ul << j))
- tab_double (t, nc++, i + 1, TAB_NONE, dv->stats[j], NULL, RC_OTHER);
+ {
+ union value v = { .f = dv->stats[j] };
+ struct pivot_value *pv = (j == DSC_MIN || j == DSC_MAX
+ ? pivot_value_new_var_value (dv->v, &v)
+ : pivot_value_new_number (dv->stats[j]));
+ pivot_table_put2 (table, column++, row, pv);
+ }
}
- tab_title (t, _("Valid cases = %.*g; cases with missing value(s) = %.*g."),
- DBL_DIG + 1, dsc->valid,
- DBL_DIG + 1, dsc->missing_listwise);
-
- tab_submit (t);
+ int row = pivot_category_create_leaves (
+ variables->root, N_("Valid N (listwise)"), N_("Missing N (listwise)"));
+ pivot_table_put2 (table, 0, row, pivot_value_new_number (dsc->valid));
+ pivot_table_put2 (table, 0, row + 1,
+ pivot_value_new_number (dsc->missing_listwise));
+ pivot_table_submit (table);
}
/* Compares `struct dsc_var's A and B according to the ordering
#include "language/lexer/value-parser.h"
#include "language/lexer/variable-parser.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
double cmin;
};
-
-/* Returns an array of (iact->n_vars) pointers to union value initialised to NULL.
- The caller must free this array when no longer required. */
-static const union value **
-previous_value_alloc (const struct interaction *iact)
-{
- int ivar_idx;
-
- const union value **prev_val = xcalloc (iact->n_vars, sizeof (*prev_val));
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
- prev_val[ivar_idx] = NULL;
-
- return prev_val;
-}
-
-/* Set the contents of PREV_VAL to the values of C indexed by the variables of IACT */
-static int
-previous_value_record (const struct interaction *iact, const struct ccase *c, const union value **prev_val)
-{
- int ivar_idx;
- int diff_idx = -1;
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
- {
- const struct variable *ivar = iact->vars[ivar_idx];
- const int width = var_get_width (ivar);
- const union value *val = case_data (c, ivar);
-
- if (prev_val[ivar_idx])
- if (! value_equal (prev_val[ivar_idx], val, width))
- {
- diff_idx = ivar_idx;
- break;
- }
- }
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
- {
- const struct variable *ivar = iact->vars[ivar_idx];
- const union value *val = case_data (c, ivar);
-
- prev_val[ivar_idx] = val;
- }
- return diff_idx;
-}
-
-
static void
show_boxplot_grouped (const struct examine *cmd, int iact_idx)
{
}
}
-static void
-percentiles_report (const struct examine *cmd, int iact_idx)
+static struct pivot_value *
+new_value_with_missing_footnote (const struct variable *var,
+ const union value *value,
+ struct pivot_footnote *missing_footnote)
{
- const struct interaction *iact = cmd->iacts[iact_idx];
- int i, v;
- const int heading_columns = 1 + iact->n_vars + 1;
- const int heading_rows = 2;
- struct tab_table *t;
-
- const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
-
- const int rows_per_cat = 2;
- const int rows_per_var = n_cats * rows_per_cat;
-
- const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
- const int nc = heading_columns + cmd->n_percentiles;
-
- t = tab_create (nc, nr);
-
- tab_title (t, _("Percentiles"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Internal Vertical lines */
- tab_box (t, -1, -1, -1, TAL_1,
- heading_columns, 0, nc - 1, nr - 1);
-
- /* External Frame */
- tab_box (t, TAL_2, TAL_2, -1, -1,
- 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_joint_text (t, heading_columns, 0,
- nc - 1, 0,
- TAT_TITLE | TAB_CENTER,
- _("Percentiles")
- );
-
- tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
-
-
- for (i = 0; i < cmd->n_percentiles; ++i)
- {
- tab_text_format (t, heading_columns + i, 1,
- TAT_TITLE | TAB_CENTER,
- _("%g"), cmd->ptiles[i]);
- }
+ struct pivot_value *pv = pivot_value_new_var_value (var, value);
+ if (var_is_value_missing (var, value, MV_USER))
+ pivot_value_add_footnote (pv, missing_footnote);
+ return pv;
+}
- for (i = 0; i < iact->n_vars; ++i)
+static void
+create_interaction_dimensions (struct pivot_table *table,
+ const struct categoricals *cats,
+ const struct interaction *iact,
+ struct pivot_footnote *missing_footnote)
+{
+ for (size_t i = iact->n_vars; i-- > 0; )
{
- tab_text (t,
- 1 + i, 1,
- TAT_TITLE,
- var_to_string (iact->vars[i])
- );
+ const struct variable *var = iact->vars[i];
+ struct pivot_dimension *d = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (var));
+ d->root->show_label = true;
+
+ size_t n;
+ union value *values = categoricals_get_var_values (cats, var, &n);
+ for (size_t j = 0; j < n; j++)
+ pivot_category_create_leaf (
+ d->root, new_value_with_missing_footnote (var, &values[j],
+ missing_footnote));
}
+}
+static struct pivot_footnote *
+create_missing_footnote (struct pivot_table *table)
+{
+ return pivot_table_create_footnote (
+ table, pivot_value_new_text (N_("User-missing value.")));
+}
+static void
+percentiles_report (const struct examine *cmd, int iact_idx)
+{
+ struct pivot_table *table = pivot_table_create (N_("Percentiles"));
+ table->omit_empty = true;
- if (n_cats > 0)
- {
- tab_vline (t, TAL_1, heading_columns - 1, heading_rows, nr - 1);
-
- for (v = 0; v < cmd->n_dep_vars; ++v)
- {
- const union value **prev_vals = previous_value_alloc (iact);
-
- int ivar_idx;
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
-
- tab_text (t,
- 0, heading_rows + v * rows_per_var,
- TAT_TITLE | TAB_LEFT,
- var_to_string (cmd->dep_vars[v])
- );
-
- for (i = 0; i < n_cats; ++i)
- {
- const struct ccase *c =
- categoricals_get_case_by_category_real (cmd->cats,
- iact_idx, i);
-
- const struct exploratory_stats *ess =
- categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
-
- const struct exploratory_stats *es = ess + v;
-
- int diff_idx = previous_value_record (iact, c, prev_vals);
-
- double hinges[3];
- int p;
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
- {
- const struct variable *ivar = iact->vars[ivar_idx];
- const union value *val = case_data (c, ivar);
+ struct pivot_dimension *percentiles = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Percentiles"));
+ percentiles->root->show_label = true;
+ for (int i = 0; i < cmd->n_percentiles; ++i)
+ pivot_category_create_leaf (
+ percentiles->root,
+ pivot_value_new_user_text_nocopy (xasprintf ("%g", cmd->ptiles[i])));
- if (( diff_idx != -1 && diff_idx <= ivar_idx)
- || i == 0)
- {
- struct string str;
- ds_init_empty (&str);
- append_value_name (ivar, val, &str);
-
- tab_text (t,
- 1 + ivar_idx,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAT_TITLE | TAB_LEFT,
- ds_cstr (&str)
- );
-
- ds_destroy (&str);
- }
- }
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Weighted Average"), N_("Tukey's Hinges"));
- if ( diff_idx != -1 && diff_idx < iact->n_vars)
- {
- tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat
- );
- }
+ const struct interaction *iact = cmd->iacts[iact_idx];
+ struct pivot_footnote *missing_footnote = create_missing_footnote (table);
+ create_interaction_dimensions (table, cmd->cats, iact, missing_footnote);
- tab_text (t, heading_columns - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAT_TITLE | TAB_LEFT,
- gettext (ptile_alg_desc [cmd->pc_alg]));
+ struct pivot_dimension *dep_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- tukey_hinges_calculate (es->hinges, hinges);
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
- for (p = 0; p < cmd->n_percentiles; ++p)
- {
- tab_double (t, heading_columns + p,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- 0,
- percentile_calculate (es->percentiles[p], cmd->pc_alg),
- NULL, RC_OTHER);
+ size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
+ for (size_t v = 0; v < cmd->n_dep_vars; ++v)
+ {
+ indexes[table->n_dimensions - 1] = pivot_category_create_leaf (
+ dep_dim->root, pivot_value_new_variable (cmd->dep_vars[v]));
- if (cmd->ptiles[p] == 25.0)
- {
- tab_double (t, heading_columns + p,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- 0,
- hinges[0],
- NULL, RC_OTHER);
- }
- else if (cmd->ptiles[p] == 50.0)
- {
- tab_double (t, heading_columns + p,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- 0,
- hinges[1],
- NULL, RC_OTHER);
- }
- else if (cmd->ptiles[p] == 75.0)
- {
- tab_double (t, heading_columns + p,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- 0,
- hinges[2],
- NULL, RC_OTHER);
- }
- }
+ for (size_t i = 0; i < n_cats; ++i)
+ {
+ for (size_t j = 0; j < iact->n_vars; j++)
+ {
+ int idx = categoricals_get_value_index_by_category_real (
+ cmd->cats, iact_idx, i, j);
+ indexes[table->n_dimensions - 2 - j] = idx;
+ }
+ const struct exploratory_stats *ess
+ = categoricals_get_user_data_by_category_real (
+ cmd->cats, iact_idx, i);
+ const struct exploratory_stats *es = ess + v;
- tab_text (t, heading_columns - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- TAT_TITLE | TAB_LEFT,
- _("Tukey's Hinges"));
+ double hinges[3];
+ tukey_hinges_calculate (es->hinges, hinges);
- }
+ for (size_t pc_idx = 0; pc_idx < cmd->n_percentiles; ++pc_idx)
+ {
+ indexes[0] = pc_idx;
+
+ indexes[1] = 0;
+ double value = percentile_calculate (es->percentiles[pc_idx],
+ cmd->pc_alg);
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (value));
+
+ double hinge = (cmd->ptiles[pc_idx] == 25.0 ? hinges[0]
+ : cmd->ptiles[pc_idx] == 50.0 ? hinges[1]
+ : cmd->ptiles[pc_idx] == 75.0 ? hinges[2]
+ : SYSMIS);
+ if (hinge != SYSMIS)
+ {
+ indexes[1] = 1;
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (hinge));
+ }
+ }
+ }
- free (prev_vals);
- }
}
- tab_submit (t);
+ free (indexes);
+
+ pivot_table_submit (table);
}
static void
descriptives_report (const struct examine *cmd, int iact_idx)
{
- const struct interaction *iact = cmd->iacts[iact_idx];
- int i, v;
- const int heading_columns = 1 + iact->n_vars + 2;
- const int heading_rows = 1;
- struct tab_table *t;
-
- size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
-
- const int rows_per_cat = 13;
- const int rows_per_var = n_cats * rows_per_cat;
-
- const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
- const int nc = 2 + heading_columns;
-
- t = tab_create (nc, nr);
-
- tab_title (t, _("Descriptives"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ struct pivot_table *table = pivot_table_create (N_("Descriptives"));
+ table->omit_empty = true;
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Aspect"),
+ N_("Statistic"), N_("Std. Error"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"), N_("Mean"));
+ struct pivot_category *interval = pivot_category_create_group__ (
+ statistics->root,
+ pivot_value_new_text_format (N_("%g%% Confidence Interval for Mean"),
+ cmd->conf * 100.0));
+ pivot_category_create_leaves (interval, N_("Lower Bound"),
+ N_("Upper Bound"));
+ pivot_category_create_leaves (
+ statistics->root, N_("5% Trimmed Mean"), N_("Median"), N_("Variance"),
+ N_("Std. Deviation"), N_("Minimum"), N_("Maximum"), N_("Range"),
+ N_("Interquartile Range"), N_("Skewness"), N_("Kurtosis"));
- /* Internal Vertical lines */
- tab_box (t, -1, -1, -1, TAL_1,
- heading_columns, 0, nc - 1, nr - 1);
-
- /* External Frame */
- tab_box (t, TAL_2, TAL_2, -1, -1,
- 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-
- tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
- _("Statistic"));
+ const struct interaction *iact = cmd->iacts[iact_idx];
+ struct pivot_footnote *missing_footnote = create_missing_footnote (table);
+ create_interaction_dimensions (table, cmd->cats, iact, missing_footnote);
- tab_text (t, heading_columns + 1, 0, TAB_CENTER | TAT_TITLE,
- _("Std. Error"));
+ struct pivot_dimension *dep_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- for (i = 0; i < iact->n_vars; ++i)
- {
- tab_text (t,
- 1 + i, 0,
- TAT_TITLE,
- var_to_string (iact->vars[i])
- );
- }
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
- for (v = 0; v < cmd->n_dep_vars; ++v)
+ size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
+ for (size_t v = 0; v < cmd->n_dep_vars; ++v)
{
- const union value **prev_val = previous_value_alloc (iact);
-
- int ivar_idx;
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
+ indexes[table->n_dimensions - 1] = pivot_category_create_leaf (
+ dep_dim->root, pivot_value_new_variable (cmd->dep_vars[v]));
- tab_text (t,
- 0, heading_rows + v * rows_per_var,
- TAT_TITLE | TAB_LEFT,
- var_to_string (cmd->dep_vars[v])
- );
-
- for (i = 0; i < n_cats; ++i)
+ for (size_t i = 0; i < n_cats; ++i)
{
- const struct ccase *c =
- categoricals_get_case_by_category_real (cmd->cats,
- iact_idx, i);
-
- const struct exploratory_stats *ess =
- categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
+ for (size_t j = 0; j < iact->n_vars; j++)
+ {
+ int idx = categoricals_get_value_index_by_category_real (
+ cmd->cats, iact_idx, i, j);
+ indexes[table->n_dimensions - 2 - j] = idx;
+ }
+ const struct exploratory_stats *ess
+ = categoricals_get_user_data_by_category_real (cmd->cats,
+ iact_idx, i);
const struct exploratory_stats *es = ess + v;
- const int diff_idx = previous_value_record (iact, c, prev_val);
-
double m0, m1, m2, m3, m4;
- double tval;
-
moments_calculate (es->mom, &m0, &m1, &m2, &m3, &m4);
+ double tval = gsl_cdf_tdist_Qinv ((1.0 - cmd->conf) / 2.0, m0 - 1.0);
- tval = gsl_cdf_tdist_Qinv ((1.0 - cmd->conf) / 2.0, m0 - 1.0);
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
+ struct entry
{
- const struct variable *ivar = iact->vars[ivar_idx];
- const union value *val = case_data (c, ivar);
-
- if (( diff_idx != -1 && diff_idx <= ivar_idx)
- || i == 0)
- {
- struct string str;
- ds_init_empty (&str);
- append_value_name (ivar, val, &str);
-
- tab_text (t,
- 1 + ivar_idx,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAT_TITLE | TAB_LEFT,
- ds_cstr (&str)
- );
-
- ds_destroy (&str);
- }
+ int stat_idx;
+ int aspect_idx;
+ double x;
}
-
- if ( diff_idx != -1 && diff_idx < iact->n_vars)
+ entries[] = {
+ { 0, 0, m1 },
+ { 0, 1, calc_semean (m2, m0) },
+ { 1, 0, m1 - tval * calc_semean (m2, m0) },
+ { 2, 0, m1 + tval * calc_semean (m2, m0) },
+ { 3, 0, trimmed_mean_calculate (es->trimmed_mean) },
+ { 4, 0, percentile_calculate (es->quartiles[1], cmd->pc_alg) },
+ { 5, 0, m2 },
+ { 6, 0, sqrt (m2) },
+ { 7, 0, es->minima[0].val },
+ { 8, 0, es->maxima[0].val },
+ { 9, 0, es->maxima[0].val - es->minima[0].val },
+ { 10, 0, (percentile_calculate (es->quartiles[2], cmd->pc_alg) -
+ percentile_calculate (es->quartiles[0], cmd->pc_alg)) },
+ { 11, 0, m3 },
+ { 11, 1, calc_seskew (m0) },
+ { 12, 0, m4 },
+ { 12, 1, calc_sekurt (m0) },
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
{
- tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat
- );
+ const struct entry *e = &entries[j];
+ indexes[0] = e->aspect_idx;
+ indexes[1] = e->stat_idx;
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (e->x));
}
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAB_LEFT,
- _("Mean")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- 0, m1, NULL, RC_OTHER);
-
- tab_double (t,
- 1 + iact->n_vars + 3,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- 0, calc_semean (m2, m0), NULL, RC_OTHER);
-
- tab_text_format (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- TAB_LEFT,
- _("%g%% Confidence Interval for Mean"),
- cmd->conf * 100.0
- );
-
- tab_text (t,
- 1 + iact->n_vars + 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- TAB_LEFT,
- _("Lower Bound")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 1,
- 0, m1 - tval * calc_semean (m2, m0), NULL, RC_OTHER);
-
-
- tab_text (t,
- 1 + iact->n_vars + 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + 2,
- TAB_LEFT,
- _("Upper Bound")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 2,
- 0, m1 + tval * calc_semean (m2, m0), NULL, RC_OTHER);
-
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 3,
- TAB_LEFT,
- _("5% Trimmed Mean")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 3,
- 0,
- trimmed_mean_calculate (es->trimmed_mean),
- NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 4,
- TAB_LEFT,
- _("Median")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 4,
- 0,
- percentile_calculate (es->quartiles[1], cmd->pc_alg),
- NULL, RC_OTHER);
-
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 5,
- TAB_LEFT,
- _("Variance")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 5,
- 0, m2, NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 6,
- TAB_LEFT,
- _("Std. Deviation")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 6,
- 0, sqrt (m2), NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 7,
- TAB_LEFT,
- _("Minimum")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 7,
- 0,
- es->minima[0].val,
- NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 8,
- TAB_LEFT,
- _("Maximum")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 8,
- 0,
- es->maxima[0].val,
- NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 9,
- TAB_LEFT,
- _("Range")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 9,
- 0,
- es->maxima[0].val - es->minima[0].val,
- NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 10,
- TAB_LEFT,
- _("Interquartile Range")
- );
-
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 10,
- 0,
- percentile_calculate (es->quartiles[2], cmd->pc_alg) -
- percentile_calculate (es->quartiles[0], cmd->pc_alg),
- NULL, RC_OTHER);
-
-
-
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 11,
- TAB_LEFT,
- _("Skewness")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 11,
- 0, m3, NULL, RC_OTHER);
-
- tab_double (t,
- 1 + iact->n_vars + 3,
- heading_rows + v * rows_per_var + i * rows_per_cat + 11,
- 0, calc_seskew (m0), NULL, RC_OTHER);
-
- tab_text (t,
- 1 + iact->n_vars,
- heading_rows + v * rows_per_var + i * rows_per_cat + 12,
- TAB_LEFT,
- _("Kurtosis")
- );
-
- tab_double (t,
- 1 + iact->n_vars + 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + 12,
- 0, m4, NULL, RC_OTHER);
-
- tab_double (t,
- 1 + iact->n_vars + 3,
- heading_rows + v * rows_per_var + i * rows_per_cat + 12,
- 0, calc_sekurt (m0), NULL, RC_OTHER);
}
-
- free (prev_val);
}
- tab_submit (t);
+
+ free (indexes);
+
+ pivot_table_submit (table);
}
static void
extremes_report (const struct examine *cmd, int iact_idx)
{
- const struct interaction *iact = cmd->iacts[iact_idx];
- int i, v;
- const int heading_columns = 1 + iact->n_vars + 2;
- const int heading_rows = 1;
- struct tab_table *t;
-
- size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
-
- const int rows_per_cat = 2 * cmd->disp_extremes;
- const int rows_per_var = n_cats * rows_per_cat;
-
- const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
- const int nc = 2 + heading_columns;
-
- t = tab_create (nc, nr);
-
- tab_title (t, _("Extreme Values"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ struct pivot_table *table = pivot_table_create (N_("Extreme Values"));
+ table->omit_empty = true;
- /* Internal Vertical lines */
- tab_box (t, -1, -1, -1, TAL_1,
- heading_columns, 0, nc - 1, nr - 1);
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_leaf (statistics->root,
+ (cmd->id_var
+ ? pivot_value_new_variable (cmd->id_var)
+ : pivot_value_new_text (N_("Case Number"))));
+ pivot_category_create_leaves (statistics->root, N_("Value"));
- /* External Frame */
- tab_box (t, TAL_2, TAL_2, -1, -1,
- 0, 0, nc - 1, nr - 1);
+ struct pivot_dimension *order = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Order"));
+ for (size_t i = 0; i < cmd->disp_extremes; i++)
+ pivot_category_create_leaf (order->root, pivot_value_new_integer (i + 1));
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Extreme"),
+ N_("Highest"), N_("Lowest"));
+ const struct interaction *iact = cmd->iacts[iact_idx];
+ struct pivot_footnote *missing_footnote = create_missing_footnote (table);
+ create_interaction_dimensions (table, cmd->cats, iact, missing_footnote);
- if ( cmd->id_var )
- tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
- var_to_string (cmd->id_var));
- else
- tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
- _("Case Number"));
-
- tab_text (t, heading_columns + 1, 0, TAB_CENTER | TAT_TITLE,
- _("Value"));
+ struct pivot_dimension *dep_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- for (i = 0; i < iact->n_vars; ++i)
- {
- tab_text (t,
- 1 + i, 0,
- TAT_TITLE,
- var_to_string (iact->vars[i])
- );
- }
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
- for (v = 0; v < cmd->n_dep_vars; ++v)
+ size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
+ for (size_t v = 0; v < cmd->n_dep_vars; ++v)
{
- const union value **prev_val = previous_value_alloc (iact);
+ indexes[table->n_dimensions - 1] = pivot_category_create_leaf (
+ dep_dim->root, pivot_value_new_variable (cmd->dep_vars[v]));
- int ivar_idx;
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
-
- tab_text (t,
- 0, heading_rows + v * rows_per_var,
- TAT_TITLE,
- var_to_string (cmd->dep_vars[v])
- );
-
- for (i = 0; i < n_cats; ++i)
+ for (size_t i = 0; i < n_cats; ++i)
{
- int e;
- const struct ccase *c =
- categoricals_get_case_by_category_real (cmd->cats, iact_idx, i);
-
- const struct exploratory_stats *ess =
- categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
+ for (size_t j = 0; j < iact->n_vars; j++)
+ {
+ int idx = categoricals_get_value_index_by_category_real (
+ cmd->cats, iact_idx, i, j);
+ indexes[table->n_dimensions - 2 - j] = idx;
+ }
+ const struct exploratory_stats *ess
+ = categoricals_get_user_data_by_category_real (cmd->cats,
+ iact_idx, i);
const struct exploratory_stats *es = ess + v;
- int diff_idx = previous_value_record (iact, c, prev_val);
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
+ for (int e = 0 ; e < cmd->disp_extremes; ++e)
{
- const struct variable *ivar = iact->vars[ivar_idx];
- const union value *val = case_data (c, ivar);
+ indexes[1] = e;
- if (( diff_idx != -1 && diff_idx <= ivar_idx)
- || i == 0)
+ for (size_t j = 0; j < 2; j++)
{
- struct string str;
- ds_init_empty (&str);
- append_value_name (ivar, val, &str);
-
- tab_text (t,
- 1 + ivar_idx,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAT_TITLE | TAB_LEFT,
- ds_cstr (&str)
- );
-
- ds_destroy (&str);
+ const struct extremity *extremity
+ = j ? &es->minima[e] : &es->maxima[e];
+ indexes[2] = j;
+
+ indexes[0] = 0;
+ pivot_table_put (
+ table, indexes, table->n_dimensions,
+ (cmd->id_var
+ ? new_value_with_missing_footnote (cmd->id_var,
+ &extremity->identity,
+ missing_footnote)
+ : pivot_value_new_integer (extremity->identity.f)));
+
+ indexes[0] = 1;
+ union value val = { .f = extremity->val };
+ pivot_table_put (
+ table, indexes, table->n_dimensions,
+ new_value_with_missing_footnote (cmd->dep_vars[v], &val,
+ missing_footnote));
}
}
-
- if ( diff_idx != -1 && diff_idx < iact->n_vars)
- {
- tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat
- );
- }
-
- tab_text (t,
- heading_columns - 2,
- heading_rows + v * rows_per_var + i * rows_per_cat,
- TAB_RIGHT,
- _("Highest"));
-
-
- tab_hline (t, TAL_1, heading_columns - 2, nc - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes
- );
-
- tab_text (t,
- heading_columns - 2,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes,
- TAB_RIGHT,
- _("Lowest"));
-
- for (e = 0 ; e < cmd->disp_extremes; ++e)
- {
- tab_double (t,
- heading_columns - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + e,
- TAB_RIGHT,
- e + 1,
- NULL, RC_INTEGER);
-
- /* The casenumber */
- if (cmd->id_var)
- tab_value (t,
- heading_columns,
- heading_rows + v * rows_per_var + i * rows_per_cat + e,
- TAB_RIGHT,
- &es->maxima[e].identity,
- cmd->id_var,
- NULL);
- else
- tab_double (t,
- heading_columns,
- heading_rows + v * rows_per_var + i * rows_per_cat + e,
- TAB_RIGHT,
- es->maxima[e].identity.f,
- NULL, RC_INTEGER);
-
- tab_double (t,
- heading_columns + 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + e,
- 0,
- es->maxima[e].val,
- var_get_print_format (cmd->dep_vars[v]), RC_OTHER);
-
-
- tab_double (t,
- heading_columns - 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
- TAB_RIGHT,
- e + 1,
- NULL, RC_INTEGER);
-
- /* The casenumber */
- if (cmd->id_var)
- tab_value (t,
- heading_columns,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
- TAB_RIGHT,
- &es->minima[e].identity,
- cmd->id_var,
- NULL);
- else
- tab_double (t,
- heading_columns,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
- TAB_RIGHT,
- es->minima[e].identity.f,
- NULL, RC_INTEGER);
-
- tab_double (t,
- heading_columns + 1,
- heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
- 0,
- es->minima[e].val,
- var_get_print_format (cmd->dep_vars[v]), RC_OTHER);
- }
}
- free (prev_val);
}
+ free (indexes);
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
summary_report (const struct examine *cmd, int iact_idx)
{
- const struct interaction *iact = cmd->iacts[iact_idx];
- int i, v;
- const int heading_columns = 1 + iact->n_vars;
- const int heading_rows = 3;
- struct tab_table *t;
-
- const struct fmt_spec *wfmt = cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
-
- size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
-
- const int nr = heading_rows + n_cats * cmd->n_dep_vars;
- const int nc = 6 + heading_columns;
-
- t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_title (t, _("Case Processing Summary"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ struct pivot_table *table = pivot_table_create (
+ N_("Case Processing Summary"));
+ table->omit_empty = true;
+ pivot_table_set_weight_var (table, dict_get_weight (cmd->dict));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Cases"), N_("Valid"), N_("Missing"),
+ N_("Total"));
+ cases->root->show_label = true;
- /* Internal Vertical lines */
- tab_box (t, -1, -1, -1, TAL_1,
- heading_columns, 0, nc - 1, nr - 1);
-
- /* External Frame */
- tab_box (t, TAL_2, TAL_2, -1, -1,
- 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_joint_text (t, heading_columns, 0,
- nc - 1, 0, TAB_CENTER | TAT_TITLE, _("Cases"));
- tab_joint_text (t,
- heading_columns, 1,
- heading_columns + 1, 1,
- TAB_CENTER | TAT_TITLE, _("Valid"));
-
- tab_joint_text (t,
- heading_columns + 2, 1,
- heading_columns + 3, 1,
- TAB_CENTER | TAT_TITLE, _("Missing"));
+ const struct interaction *iact = cmd->iacts[iact_idx];
+ struct pivot_footnote *missing_footnote = create_missing_footnote (table);
+ create_interaction_dimensions (table, cmd->cats, iact, missing_footnote);
- tab_joint_text (t,
- heading_columns + 4, 1,
- heading_columns + 5, 1,
- TAB_CENTER | TAT_TITLE, _("Total"));
+ struct pivot_dimension *dep_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- for (i = 0; i < 3; ++i)
- {
- tab_text (t, heading_columns + i * 2, 2, TAB_CENTER | TAT_TITLE,
- _("N"));
- tab_text (t, heading_columns + i * 2 + 1, 2, TAB_CENTER | TAT_TITLE,
- _("Percent"));
- }
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
- for (i = 0; i < iact->n_vars; ++i)
+ size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
+ for (size_t v = 0; v < cmd->n_dep_vars; ++v)
{
- tab_text (t,
- 1 + i, 2,
- TAT_TITLE,
- var_to_string (iact->vars[i])
- );
- }
-
- if (n_cats > 0)
- for (v = 0; v < cmd->n_dep_vars; ++v)
- {
- int ivar_idx;
- const union value **prev_values = previous_value_alloc (iact);
-
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * n_cats);
+ indexes[table->n_dimensions - 1] = pivot_category_create_leaf (
+ dep_dim->root, pivot_value_new_variable (cmd->dep_vars[v]));
- tab_text (t,
- 0, heading_rows + n_cats * v,
- TAT_TITLE,
- var_to_string (cmd->dep_vars[v])
- );
+ for (size_t i = 0; i < n_cats; ++i)
+ {
+ for (size_t j = 0; j < iact->n_vars; j++)
+ {
+ int idx = categoricals_get_value_index_by_category_real (
+ cmd->cats, iact_idx, i, j);
+ indexes[table->n_dimensions - 2 - j] = idx;
+ }
+ const struct exploratory_stats *es
+ = categoricals_get_user_data_by_category_real (
+ cmd->cats, iact_idx, i);
- for (i = 0; i < n_cats; ++i)
- {
- double total;
- const struct exploratory_stats *es;
-
- const struct ccase *c =
- categoricals_get_case_by_category_real (cmd->cats,
- iact_idx, i);
- if (c)
- {
- int diff_idx = previous_value_record (iact, c, prev_values);
-
- if ( diff_idx != -1 && diff_idx < iact->n_vars - 1)
- tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
- heading_rows + n_cats * v + i );
-
- for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
- {
- const struct variable *ivar = iact->vars[ivar_idx];
- const union value *val = case_data (c, ivar);
-
- if (( diff_idx != -1 && diff_idx <= ivar_idx)
- || i == 0)
- {
- struct string str;
- ds_init_empty (&str);
- append_value_name (ivar, val, &str);
-
- tab_text (t,
- 1 + ivar_idx, heading_rows + n_cats * v + i,
- TAT_TITLE | TAB_LEFT,
- ds_cstr (&str)
- );
-
- ds_destroy (&str);
- }
- }
- }
-
-
- es = categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
-
-
- total = es[v].missing + es[v].non_missing;
- tab_double (t,
- heading_columns + 0,
- heading_rows + n_cats * v + i,
- 0,
- es[v].non_missing,
- NULL, RC_WEIGHT);
-
-
- tab_text_format (t,
- heading_columns + 1,
- heading_rows + n_cats * v + i,
- 0,
- "%g%%",
- 100.0 * es[v].non_missing / total
- );
-
-
- tab_double (t,
- heading_columns + 2,
- heading_rows + n_cats * v + i,
- 0,
- es[v].missing,
- NULL, RC_WEIGHT);
-
- tab_text_format (t,
- heading_columns + 3,
- heading_rows + n_cats * v + i,
- 0,
- "%g%%",
- 100.0 * es[v].missing / total
- );
- tab_double (t,
- heading_columns + 4,
- heading_rows + n_cats * v + i,
- 0,
- total,
- NULL, RC_WEIGHT);
-
- /* This can only be 100% can't it? */
- tab_text_format (t,
- heading_columns + 5,
- heading_rows + n_cats * v + i,
- 0,
- "%g%%",
- 100.0 * (es[v].missing + es[v].non_missing)/ total
- );
- }
- free (prev_values);
- }
+ double total = es[v].missing + es[v].non_missing;
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, es[v].non_missing },
+ { 1, 0, 100.0 * es[v].non_missing / total },
+ { 0, 1, es[v].missing },
+ { 1, 1, 100.0 * es[v].missing / total },
+ { 0, 2, total },
+ { 1, 2, 100.0 },
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ const struct entry *e = &entries[j];
+ indexes[0] = e->stat_idx;
+ indexes[1] = e->case_idx;
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (e->x));
+ }
+ }
+ }
- tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
- tab_hline (t, TAL_1, heading_columns, nc - 1, 2);
+ free (indexes);
- tab_submit (t);
+ pivot_table_submit (table);
}
/* Attempt to parse an interaction from LEXER */
#include "math/moments.h"
#include "output/chart-item.h"
#include "output/charts/scree.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
show_communalities (const struct cmd_factor * factor,
const gsl_vector *initial, const gsl_vector *extracted)
{
- int i;
- int c = 0;
- const int heading_columns = 1;
- int nc = heading_columns;
- const int heading_rows = 1;
- const int nr = heading_rows + factor->n_vars;
- struct tab_table *t;
-
- if (factor->print & PRINT_EXTRACTION)
- nc++;
-
- if (factor->print & PRINT_INITIAL)
- nc++;
-
- /* No point having a table with only headings */
- if (nc <= 1)
+ if (!(factor->print & (PRINT_INITIAL | PRINT_EXTRACTION)))
return;
- t = tab_create (nc, nr);
-
- tab_title (t, _("Communalities"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ struct pivot_table *table = pivot_table_create (N_("Communalities"));
- c = 1;
+ struct pivot_dimension *communalities = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Communalities"));
if (factor->print & PRINT_INITIAL)
- tab_text (t, c++, 0, TAB_CENTER | TAT_TITLE, _("Initial"));
-
+ pivot_category_create_leaves (communalities->root, N_("Initial"));
if (factor->print & PRINT_EXTRACTION)
- tab_text (t, c++, 0, TAB_CENTER | TAT_TITLE, _("Extraction"));
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- for (i = 0 ; i < factor->n_vars; ++i)
+ pivot_category_create_leaves (communalities->root, N_("Extraction"));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t i = 0 ; i < factor->n_vars; ++i)
{
- c = 0;
- tab_text (t, c++, i + heading_rows, TAT_TITLE, var_to_string (factor->vars[i]));
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (factor->vars[i]));
+ int col = 0;
if (factor->print & PRINT_INITIAL)
- tab_double (t, c++, i + heading_rows, 0, gsl_vector_get (initial, i), NULL, RC_OTHER);
-
+ pivot_table_put2 (table, col++, row, pivot_value_new_number (
+ gsl_vector_get (initial, i)));
if (factor->print & PRINT_EXTRACTION)
- tab_double (t, c++, i + heading_rows, 0, gsl_vector_get (extracted, i), NULL, RC_OTHER);
+ pivot_table_put2 (table, col++, row, pivot_value_new_number (
+ gsl_vector_get (extracted, i)));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
+static struct pivot_dimension *
+create_numeric_dimension (struct pivot_table *table,
+ enum pivot_axis_type axis_type, const char *name,
+ size_t n, bool show_label)
+{
+ struct pivot_dimension *d = pivot_dimension_create (table, axis_type, name);
+ d->root->show_label = show_label;
+ for (int i = 0 ; i < n; ++i)
+ pivot_category_create_leaf (d->root, pivot_value_new_integer (i + 1));
+ return d;
+}
static void
show_factor_matrix (const struct cmd_factor *factor, const struct idata *idata, const char *title, const gsl_matrix *fm)
{
- int i;
+ struct pivot_table *table = pivot_table_create (title);
const int n_factors = idata->n_extractions;
+ create_numeric_dimension (
+ table, PIVOT_AXIS_COLUMN,
+ factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"),
+ n_factors, true);
- const int heading_columns = 1;
- const int heading_rows = 2;
- const int nr = heading_rows + factor->n_vars;
- const int nc = heading_columns + n_factors;
- gsl_permutation *perm;
-
- struct tab_table *t = tab_create (nc, nr);
-
- /*
- if ( factor->extraction == EXTRACTION_PC )
- tab_title (t, _("Component Matrix"));
- else
- tab_title (t, _("Factor Matrix"));
- */
-
- tab_title (t, "%s", title);
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- if ( factor->extraction == EXTRACTION_PC )
- tab_joint_text (t,
- 1, 0,
- nc - 1, 0,
- TAB_CENTER | TAT_TITLE, _("Component"));
- else
- tab_joint_text (t,
- 1, 0,
- nc - 1, 0,
- TAB_CENTER | TAT_TITLE, _("Factor"));
-
-
- tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
-
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 1,
- nc - 1, nr - 1);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
/* Initialise to the identity permutation */
- perm = gsl_permutation_calloc (factor->n_vars);
+ gsl_permutation *perm = gsl_permutation_calloc (factor->n_vars);
if ( factor->sort)
sort_matrix_indirect (fm, perm);
- for (i = 0 ; i < n_factors; ++i)
- {
- tab_text_format (t, heading_columns + i, 1, TAB_CENTER | TAT_TITLE, _("%d"), i + 1);
- }
-
- for (i = 0 ; i < factor->n_vars; ++i)
+ for (size_t i = 0 ; i < factor->n_vars; ++i)
{
- int j;
const int matrix_row = perm->data[i];
- tab_text (t, 0, i + heading_rows, TAT_TITLE, var_to_string (factor->vars[matrix_row]));
- for (j = 0 ; j < n_factors; ++j)
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (factor->vars[matrix_row]));
+
+ for (size_t j = 0 ; j < n_factors; ++j)
{
double x = gsl_matrix_get (fm, matrix_row, j);
-
if ( fabs (x) < factor->blank)
continue;
- tab_double (t, heading_columns + j, heading_rows + i, 0, x, NULL, RC_OTHER);
+ pivot_table_put2 (table, j, var_idx, pivot_value_new_number (x));
}
}
gsl_permutation_free (perm);
- tab_submit (t);
+ pivot_table_submit (table);
}
+static void
+put_variance (struct pivot_table *table, int row, int phase_idx,
+ double lambda, double percent, double cum)
+{
+ double entries[] = { lambda, percent, cum };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put3 (table, i, phase_idx, row,
+ pivot_value_new_number (entries[i]));
+}
static void
show_explained_variance (const struct cmd_factor * factor,
const gsl_vector *extracted_eigenvalues,
const gsl_vector *rotated_loadings)
{
- size_t i;
- int c = 0;
- const int heading_columns = 1;
- const int heading_rows = 2;
- const int nr = heading_rows + factor->n_vars;
-
- struct tab_table *t ;
-
- double i_total = 0.0;
- double i_cum = 0.0;
-
- double e_total = 0.0;
- double e_cum = 0.0;
-
- double r_cum = 0.0;
-
- int nc = heading_columns;
-
- if (factor->print & PRINT_EXTRACTION)
- nc += 3;
-
- if (factor->print & PRINT_INITIAL)
- nc += 3;
-
- if (factor->print & PRINT_ROTATION)
- {
- nc += factor->rotation == ROT_PROMAX ? 1 : 3;
- }
-
- /* No point having a table with only headings */
- if ( nc <= heading_columns)
+ if (!(factor->print & (PRINT_INITIAL | PRINT_EXTRACTION | PRINT_ROTATION)))
return;
- t = tab_create (nc, nr);
-
- tab_title (t, _("Total Variance Explained"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_hline (t, TAL_1, 1, nc - 1, 1);
+ struct pivot_table *table = pivot_table_create (
+ N_("Total Variance Explained"));
+ table->omit_empty = true;
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ /* xgettext:no-c-format */
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Total"), PIVOT_RC_OTHER,
+ N_("% of Variance"), PIVOT_RC_PERCENT,
+ N_("Cumulative %"), PIVOT_RC_PERCENT);
-
- if ( factor->extraction == EXTRACTION_PC)
- tab_text (t, 0, 1, TAB_LEFT | TAT_TITLE, _("Component"));
- else
- tab_text (t, 0, 1, TAB_LEFT | TAT_TITLE, _("Factor"));
-
- c = 1;
+ struct pivot_dimension *phase = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Phase"));
if (factor->print & PRINT_INITIAL)
- {
- tab_joint_text (t, c, 0, c + 2, 0, TAB_CENTER | TAT_TITLE, _("Initial Eigenvalues"));
- c += 3;
- }
+ pivot_category_create_leaves (phase->root, N_("Initial Eigenvalues"));
if (factor->print & PRINT_EXTRACTION)
- {
- tab_joint_text (t, c, 0, c + 2, 0, TAB_CENTER | TAT_TITLE, _("Extraction Sums of Squared Loadings"));
- c += 3;
- }
+ pivot_category_create_leaves (phase->root,
+ N_("Extraction Sums of Squared Loadings"));
if (factor->print & PRINT_ROTATION)
- {
- const int width = factor->rotation == ROT_PROMAX ? 0 : 2;
- tab_joint_text (t, c, 0, c + width, 0, TAB_CENTER | TAT_TITLE, _("Rotation Sums of Squared Loadings"));
- c += width + 1;
- }
-
- for (i = 0; i < (nc - heading_columns + 2) / 3 ; ++i)
- {
- tab_text (t, i * 3 + 1, 1, TAB_CENTER | TAT_TITLE, _("Total"));
-
- tab_vline (t, TAL_2, heading_columns + i * 3, 0, nr - 1);
+ pivot_category_create_leaves (phase->root,
+ N_("Rotation Sums of Squared Loadings"));
- if (i == 2 && factor->rotation == ROT_PROMAX)
- continue;
+ struct pivot_dimension *components = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW,
+ factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"));
- /* xgettext:no-c-format */
- tab_text (t, i * 3 + 2, 1, TAB_CENTER | TAT_TITLE, _("% of Variance"));
- tab_text (t, i * 3 + 3, 1, TAB_CENTER | TAT_TITLE, _("Cumulative %"));
- }
-
- for (i = 0 ; i < initial_eigenvalues->size; ++i)
+ double i_total = 0.0;
+ for (size_t i = 0 ; i < initial_eigenvalues->size; ++i)
i_total += gsl_vector_get (initial_eigenvalues, i);
- if ( factor->extraction == EXTRACTION_PAF)
- {
- e_total = factor->n_vars;
- }
- else
- {
- e_total = i_total;
- }
+ double e_total = (factor->extraction == EXTRACTION_PAF
+ ? factor->n_vars
+ : i_total);
- for (i = 0 ; i < factor->n_vars; ++i)
+ double i_cum = 0.0;
+ double e_cum = 0.0;
+ double r_cum = 0.0;
+ for (size_t i = 0 ; i < factor->n_vars; ++i)
{
const double i_lambda = gsl_vector_get (initial_eigenvalues, i);
double i_percent = 100.0 * i_lambda / i_total ;
+ i_cum += i_percent;
const double e_lambda = gsl_vector_get (extracted_eigenvalues, i);
double e_percent = 100.0 * e_lambda / e_total ;
+ e_cum += e_percent;
- c = 0;
-
- tab_text_format (t, c++, i + heading_rows, TAB_LEFT | TAT_TITLE, _("%zu"), i + 1);
+ int row = pivot_category_create_leaf (
+ components->root, pivot_value_new_integer (i + 1));
- i_cum += i_percent;
- e_cum += e_percent;
+ int phase_idx = 0;
/* Initial Eigenvalues */
if (factor->print & PRINT_INITIAL)
- {
- tab_double (t, c++, i + heading_rows, 0, i_lambda, NULL, RC_OTHER);
- tab_double (t, c++, i + heading_rows, 0, i_percent, NULL, RC_OTHER);
- tab_double (t, c++, i + heading_rows, 0, i_cum, NULL, RC_OTHER);
- }
-
-
- if (factor->print & PRINT_EXTRACTION)
- {
- if (i < idata->n_extractions)
- {
- /* Sums of squared loadings */
- tab_double (t, c++, i + heading_rows, 0, e_lambda, NULL, RC_OTHER);
- tab_double (t, c++, i + heading_rows, 0, e_percent, NULL, RC_OTHER);
- tab_double (t, c++, i + heading_rows, 0, e_cum, NULL, RC_OTHER);
- }
- }
+ put_variance (table, row, phase_idx++, i_lambda, i_percent, i_cum);
- if (rotated_loadings != NULL)
+ if (i < idata->n_extractions)
{
- const double r_lambda = gsl_vector_get (rotated_loadings, i);
- double r_percent = 100.0 * r_lambda / e_total ;
+ if (factor->print & PRINT_EXTRACTION)
+ put_variance (table, row, phase_idx++, e_lambda, e_percent, e_cum);
- if (factor->print & PRINT_ROTATION)
+ if (rotated_loadings != NULL && factor->print & PRINT_ROTATION)
{
- if (i < idata->n_extractions)
- {
- r_cum += r_percent;
- tab_double (t, c++, i + heading_rows, 0, r_lambda, NULL, RC_OTHER);
- if (factor->rotation != ROT_PROMAX)
- {
- tab_double (t, c++, i + heading_rows, 0, r_percent, NULL, RC_OTHER);
- tab_double (t, c++, i + heading_rows, 0, r_cum, NULL, RC_OTHER);
- }
- }
+ double r_lambda = gsl_vector_get (rotated_loadings, i);
+ double r_percent = 100.0 * r_lambda / e_total ;
+ if (factor->rotation == ROT_PROMAX)
+ r_lambda = r_percent = SYSMIS;
+
+ r_cum += r_percent;
+ put_variance (table, row, phase_idx++, r_lambda, r_percent,
+ r_cum);
}
}
}
- tab_submit (t);
+ pivot_table_submit (table);
}
-
static void
show_factor_correlation (const struct cmd_factor * factor, const gsl_matrix *fcm)
{
- size_t i, j;
- const int heading_columns = 1;
- const int heading_rows = 1;
- const int nr = heading_rows + fcm->size2;
- const int nc = heading_columns + fcm->size1;
- struct tab_table *t = tab_create (nc, nr);
-
- tab_title (t, _("Factor Correlation Matrix"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_hline (t, TAL_1, 1, nc - 1, 1);
+ struct pivot_table *table = pivot_table_create (
+ N_("Factor Correlation Matrix"));
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ create_numeric_dimension (
+ table, PIVOT_AXIS_ROW,
+ factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"),
+ fcm->size2, true);
+ create_numeric_dimension (table, PIVOT_AXIS_COLUMN, N_("Factor 2"),
+ fcm->size1, false);
- if ( factor->extraction == EXTRACTION_PC)
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Component"));
- else
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Factor"));
+ for (size_t i = 0 ; i < fcm->size1; ++i)
+ for (size_t j = 0 ; j < fcm->size2; ++j)
+ pivot_table_put2 (table, j, i,
+ pivot_value_new_number (gsl_matrix_get (fcm, i, j)));
- for (i = 0 ; i < fcm->size1; ++i)
- {
- tab_text_format (t, heading_columns + i, 0, TAB_CENTER | TAT_TITLE, _("%zu"), i + 1);
- }
+ pivot_table_submit (table);
+}
- for (i = 0 ; i < fcm->size2; ++i)
+static void
+add_var_dims (struct pivot_table *table, const struct cmd_factor *factor)
+{
+ for (int i = 0; i < 2; i++)
{
- tab_text_format (t, 0, heading_rows + i, TAB_CENTER | TAT_TITLE, _("%zu"), i + 1);
- }
-
+ struct pivot_dimension *d = pivot_dimension_create (
+ table, i ? PIVOT_AXIS_ROW : PIVOT_AXIS_COLUMN,
+ N_("Variables"));
- for (i = 0 ; i < fcm->size1; ++i)
- {
- for (j = 0 ; j < fcm->size2; ++j)
- tab_double (t, heading_columns + j, heading_rows + i, 0,
- gsl_matrix_get (fcm, i, j), NULL, RC_OTHER);
+ for (size_t j = 0; j < factor->n_vars; j++)
+ pivot_category_create_leaf (
+ d->root, pivot_value_new_variable (factor->vars[j]));
}
-
- tab_submit (t);
}
static void
show_aic (const struct cmd_factor *factor, const struct idata *idata)
{
- struct tab_table *t ;
- size_t i;
-
- const int heading_rows = 1;
- const int heading_columns = 2;
-
- const int nc = heading_columns + factor->n_vars;
- const int nr = heading_rows + 2 * factor->n_vars;
-
if ((factor->print & PRINT_AIC) == 0)
return;
- t = tab_create (nc, nr);
-
- tab_title (t, _("Anti-Image Matrices"));
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
+ struct pivot_table *table = pivot_table_create (N_("Anti-Image Matrices"));
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ add_var_dims (table, factor);
- tab_vline (t, TAL_2, 2, 0, nr - 1);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
-
- for (i = 0; i < factor->n_vars; ++i)
- tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i]));
-
- tab_text (t, 0, heading_rows, TAT_TITLE, _("Anti-image Covariance"));
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + factor->n_vars);
- tab_text (t, 0, heading_rows + factor->n_vars, TAT_TITLE, _("Anti-image Correlation"));
-
- for (i = 0; i < factor->n_vars; ++i)
- {
- tab_text (t, 1, i + heading_rows, TAT_TITLE,
- var_to_string (factor->vars[i]));
-
- tab_text (t, 1, factor->n_vars + i + heading_rows, TAT_TITLE,
- var_to_string (factor->vars[i]));
- }
-
- for (i = 0; i < factor->n_vars; ++i)
- {
- int j;
- for (j = 0; j < factor->n_vars; ++j)
- {
- tab_double (t, heading_columns + i, heading_rows + j, 0,
- gsl_matrix_get (idata->ai_cov, i, j), NULL, RC_OTHER);
- }
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Anti-image Covariance"),
+ N_("Anti-image Correlation"));
+ for (size_t i = 0; i < factor->n_vars; ++i)
+ for (size_t j = 0; j < factor->n_vars; ++j)
+ {
+ double cov = gsl_matrix_get (idata->ai_cov, i, j);
+ pivot_table_put3 (table, i, j, 0, pivot_value_new_number (cov));
- for (j = 0; j < factor->n_vars; ++j)
- {
- tab_double (t, heading_columns + i, factor->n_vars + heading_rows + j, 0,
- gsl_matrix_get (idata->ai_cor, i, j), NULL, RC_OTHER);
- }
- }
+ double corr = gsl_matrix_get (idata->ai_cor, i, j);
+ pivot_table_put3 (table, i, j, 1, pivot_value_new_number (corr));
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
show_correlation_matrix (const struct cmd_factor *factor, const struct idata *idata)
{
- struct tab_table *t ;
- size_t i, j;
- int y_pos_corr = -1;
- int y_pos_sig = -1;
- int suffix_rows = 0;
-
- const int heading_rows = 1;
- const int heading_columns = 2;
-
- int nc = heading_columns ;
- int nr = heading_rows ;
- int n_data_sets = 0;
-
- if (factor->print & PRINT_CORRELATION)
- {
- y_pos_corr = n_data_sets;
- n_data_sets++;
- nc = heading_columns + factor->n_vars;
- }
-
- if (factor->print & PRINT_SIG)
- {
- y_pos_sig = n_data_sets;
- n_data_sets++;
- nc = heading_columns + factor->n_vars;
- }
-
- nr += n_data_sets * factor->n_vars;
-
- if (factor->print & PRINT_DETERMINANT)
- suffix_rows = 1;
-
- /* If the table would contain only headings, don't bother rendering it */
- if (nr <= heading_rows && suffix_rows == 0)
+ if (!(factor->print & (PRINT_CORRELATION | PRINT_SIG | PRINT_DETERMINANT)))
return;
- t = tab_create (nc, nr + suffix_rows);
-
- tab_title (t, _("Correlation Matrix"));
+ struct pivot_table *table = pivot_table_create (N_("Correlation Matrix"));
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
-
- if (nr > heading_rows)
+ if (factor->print & (PRINT_CORRELATION | PRINT_SIG))
{
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_vline (t, TAL_2, 2, 0, nr - 1);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
-
- for (i = 0; i < factor->n_vars; ++i)
- tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i]));
-
-
- for (i = 0 ; i < n_data_sets; ++i)
- {
- int y = heading_rows + i * factor->n_vars;
- size_t v;
- for (v = 0; v < factor->n_vars; ++v)
- tab_text (t, 1, y + v, TAT_TITLE, var_to_string (factor->vars[v]));
-
- tab_hline (t, TAL_1, 0, nc - 1, y);
- }
+ add_var_dims (table, factor);
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"));
if (factor->print & PRINT_CORRELATION)
- {
- const double y = heading_rows + y_pos_corr;
- tab_text (t, 0, y, TAT_TITLE, _("Correlations"));
-
- for (i = 0; i < factor->n_vars; ++i)
- {
- for (j = 0; j < factor->n_vars; ++j)
- tab_double (t, heading_columns + j, y + i, 0, gsl_matrix_get (idata->mm.corr, i, j), NULL, RC_OTHER);
- }
- }
-
+ pivot_category_create_leaves (statistics->root, N_("Correlation"),
+ PIVOT_RC_CORRELATION);
if (factor->print & PRINT_SIG)
- {
- const double y = heading_rows + y_pos_sig * factor->n_vars;
- tab_text (t, 0, y, TAT_TITLE, _("Sig. (1-tailed)"));
-
- for (i = 0; i < factor->n_vars; ++i)
- {
- for (j = 0; j < factor->n_vars; ++j)
- {
- double rho = gsl_matrix_get (idata->mm.corr, i, j);
- double w = gsl_matrix_get (idata->mm.n, i, j);
+ pivot_category_create_leaves (statistics->root, N_("Sig. (1-tailed)"),
+ PIVOT_RC_SIGNIFICANCE);
- if (i == j)
- continue;
+ int stat_idx = 0;
+ if (factor->print & PRINT_CORRELATION)
+ {
+ for (int i = 0; i < factor->n_vars; ++i)
+ for (int j = 0; j < factor->n_vars; ++j)
+ {
+ double corr = gsl_matrix_get (idata->mm.corr, i, j);
+ pivot_table_put3 (table, j, i, stat_idx,
+ pivot_value_new_number (corr));
+ }
+ stat_idx++;
+ }
- tab_double (t, heading_columns + j, y + i, 0, significance_of_correlation (rho, w), NULL, RC_PVALUE);
- }
- }
- }
+ if (factor->print & PRINT_SIG)
+ {
+ for (int i = 0; i < factor->n_vars; ++i)
+ for (int j = 0; j < factor->n_vars; ++j)
+ if (i != j)
+ {
+ double rho = gsl_matrix_get (idata->mm.corr, i, j);
+ double w = gsl_matrix_get (idata->mm.n, i, j);
+ double sig = significance_of_correlation (rho, w);
+ pivot_table_put3 (table, j, i, stat_idx,
+ pivot_value_new_number (sig));
+ }
+ stat_idx++;
+ }
}
if (factor->print & PRINT_DETERMINANT)
- {
- tab_text (t, 0, nr, TAB_LEFT | TAT_TITLE, _("Determinant"));
-
- tab_double (t, 1, nr, 0, idata->detR, NULL, RC_OTHER);
- }
+ table->caption = pivot_value_new_user_text_nocopy (
+ xasprintf ("%s: %.2f", _("Determinant"), idata->detR));
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
show_covariance_matrix (const struct cmd_factor *factor, const struct idata *idata)
{
- struct tab_table *t ;
- size_t i, j;
- int y_pos_corr = -1;
- int suffix_rows = 0;
-
- const int heading_rows = 1;
- const int heading_columns = 1;
-
- int nc = heading_columns ;
- int nr = heading_rows ;
- int n_data_sets = 0;
-
- if (factor->print & PRINT_COVARIANCE)
- {
- y_pos_corr = n_data_sets;
- n_data_sets++;
- nc = heading_columns + factor->n_vars;
- }
-
- nr += n_data_sets * factor->n_vars;
-
- /* If the table would contain only headings, don't bother rendering it */
- if (nr <= heading_rows && suffix_rows == 0)
+ if (!(factor->print & PRINT_COVARIANCE))
return;
- t = tab_create (nc, nr + suffix_rows);
-
- tab_title (t, _("Covariance Matrix"));
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
-
- if (nr > heading_rows)
- {
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ struct pivot_table *table = pivot_table_create (N_("Covariance Matrix"));
+ add_var_dims (table, factor);
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
-
- for (i = 0; i < factor->n_vars; ++i)
- tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i]));
-
-
- for (i = 0 ; i < n_data_sets; ++i)
- {
- int y = heading_rows + i * factor->n_vars;
- size_t v;
- for (v = 0; v < factor->n_vars; ++v)
- tab_text (t, heading_columns -1, y + v, TAT_TITLE, var_to_string (factor->vars[v]));
-
- tab_hline (t, TAL_1, 0, nc - 1, y);
- }
-
- if (factor->print & PRINT_COVARIANCE)
- {
- const double y = heading_rows + y_pos_corr;
-
- for (i = 0; i < factor->n_vars; ++i)
- {
- for (j = 0; j < factor->n_vars; ++j)
- tab_double (t, heading_columns + j, y + i, 0, gsl_matrix_get (idata->mm.cov, i, j), NULL, RC_OTHER);
- }
- }
- }
+ for (int i = 0; i < factor->n_vars; ++i)
+ for (int j = 0; j < factor->n_vars; ++j)
+ {
+ double cov = gsl_matrix_get (idata->mm.cov, i, j);
+ pivot_table_put2 (table, j, i, pivot_value_new_number (cov));
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
if ( factor->print & PRINT_UNIVARIATE)
{
- const struct fmt_spec *wfmt = factor->wv ? var_get_print_format (factor->wv) : & F_8_0;
- const int nc = 4;
- int i;
-
- const int heading_columns = 1;
- const int heading_rows = 1;
-
- const int nr = heading_rows + factor->n_vars;
-
- struct tab_table *t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_title (t, _("Descriptive Statistics"));
+ struct pivot_table *table = pivot_table_create (
+ N_("Descriptive Statistics"));
+ pivot_table_set_weight_var (table, factor->wv);
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("Analysis N"), PIVOT_RC_COUNT);
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Analysis N"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
for (i = 0 ; i < factor->n_vars; ++i)
{
const struct variable *v = factor->vars[i];
- tab_text (t, 0, i + heading_rows, TAB_LEFT | TAT_TITLE, var_to_string (v));
- tab_double (t, 1, i + heading_rows, 0, gsl_matrix_get (idata->mm.mean_matrix, i, i), NULL, RC_OTHER);
- tab_double (t, 2, i + heading_rows, 0, sqrt (gsl_matrix_get (idata->mm.var_matrix, i, i)), NULL, RC_OTHER);
- tab_double (t, 3, i + heading_rows, 0, gsl_matrix_get (idata->mm.n, i, i), NULL, RC_WEIGHT);
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (v));
+
+ double entries[] = {
+ gsl_matrix_get (idata->mm.mean_matrix, i, i),
+ sqrt (gsl_matrix_get (idata->mm.var_matrix, i, i)),
+ gsl_matrix_get (idata->mm.n, i, i),
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, row,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
if (factor->print & PRINT_KMO)
{
- int i;
- double df = factor->n_vars * (factor->n_vars - 1) / 2;
-
- double w = 0;
-
-
- double xsq;
-
- const int heading_columns = 2;
- const int heading_rows = 0;
-
- const int nr = heading_rows + 4;
- const int nc = heading_columns + 1;
-
-
-
- struct tab_table *t = tab_create (nc, nr);
- tab_title (t, _("KMO and Bartlett's Test"));
-
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
-
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 0, 0, TAT_TITLE | TAB_LEFT, _("Kaiser-Meyer-Olkin Measure of Sampling Adequacy"));
-
- tab_double (t, 2, 0, 0, sum_ssq_r / (sum_ssq_r + sum_ssq_a), NULL, RC_OTHER);
-
- tab_text (t, 0, 1, TAT_TITLE | TAB_LEFT, _("Bartlett's Test of Sphericity"));
-
- tab_text (t, 1, 1, TAT_TITLE, _("Approx. Chi-Square"));
- tab_text (t, 1, 2, TAT_TITLE, _("df"));
- tab_text (t, 1, 3, TAT_TITLE, _("Sig."));
-
+ struct pivot_table *table = pivot_table_create (
+ N_("KMO and Bartlett's Test"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Kaiser-Meyer-Olkin Measure of Sampling Adequacy"), PIVOT_RC_OTHER);
+ pivot_category_create_group (
+ statistics->root, N_("Bartlett's Test of Sphericity"),
+ N_("Approx. Chi-Square"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
/* The literature doesn't say what to do for the value of W when
missing values are involved. The best thing I can think of
is to take the mean average. */
- w = 0;
+ double w = 0;
for (i = 0; i < idata->mm.n->size1; ++i)
w += gsl_matrix_get (idata->mm.n, i, i);
w /= idata->mm.n->size1;
- xsq = w - 1 - (2 * factor->n_vars + 5) / 6.0;
- xsq *= -log (idata->detR);
-
- tab_double (t, 2, 1, 0, xsq, NULL, RC_OTHER);
- tab_double (t, 2, 2, 0, df, NULL, RC_INTEGER);
- tab_double (t, 2, 3, 0, gsl_cdf_chisq_Q (xsq, df), NULL, RC_PVALUE);
-
-
- tab_submit (t);
+ double xsq = ((w - 1 - (2 * factor->n_vars + 5) / 6.0)
+ * -log (idata->detR));
+ double df = factor->n_vars * (factor->n_vars - 1) / 2;
+ double entries[] = {
+ sum_ssq_r / (sum_ssq_r + sum_ssq_a),
+ xsq,
+ df,
+ gsl_cdf_chisq_Q (xsq, df)
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put1 (table, i, pivot_value_new_number (entries[i]));
+
+ pivot_table_submit (table);
}
show_correlation_matrix (factor, idata);
show_scree (factor, idata);
show_factor_matrix (factor, idata,
- factor->extraction == EXTRACTION_PC ? _("Component Matrix") : _("Factor Matrix"),
+ (factor->extraction == EXTRACTION_PC
+ ? N_("Component Matrix") : N_("Factor Matrix")),
factor_matrix);
if ( factor->rotation == ROT_PROMAX)
{
- show_factor_matrix (factor, idata, _("Pattern Matrix"), pattern_matrix);
+ show_factor_matrix (factor, idata, N_("Pattern Matrix"),
+ pattern_matrix);
gsl_matrix_free (pattern_matrix);
}
if ( factor->rotation != ROT_NONE)
{
show_factor_matrix (factor, idata,
- (factor->rotation == ROT_PROMAX) ? _("Structure Matrix") :
- (factor->extraction == EXTRACTION_PC ? _("Rotated Component Matrix") :
- _("Rotated Factor Matrix")),
+ (factor->rotation == ROT_PROMAX
+ ? N_("Structure Matrix")
+ : factor->extraction == EXTRACTION_PC
+ ? N_("Rotated Component Matrix")
+ : N_("Rotated Factor Matrix")),
rotated_factors);
gsl_matrix_free (rotated_factors);
#include "output/charts/barchart.h"
#include "output/charts/piechart.h"
#include "output/charts/plot-hist.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gl/xalloc.h"
/* Percentiles to calculate and possibly display. */
struct percentile *percentiles;
- int n_percentiles, n_show_percentiles;
+ const struct percentile *median;
+ int n_percentiles;
/* Frequency table display. */
long int max_categories; /* Maximum categories to show. */
bool ascending_value;
};
-static void calc_stats (const struct var_freqs *vf, double d[FRQ_ST_count]);
+static void calc_stats (const struct frq_proc *,
+ const struct var_freqs *, double d[FRQ_ST_count]);
static void do_piechart(const struct frq_chart *pie,
const struct variable *var,
const struct freq_tab *frq_tab);
static void dump_statistics (const struct frq_proc *frq,
- const struct var_freqs *vf,
const struct variable *wv);
static int
freq_tab_to_hist (const struct frq_proc *frq, const struct freq_tab *ft,
const struct variable *var);
+static void
+put_freq_row (struct pivot_table *table, int var_idx,
+ double frequency, double percent,
+ double valid_percent, double cum_percent)
+{
+ double entries[] = { frequency, percent, valid_percent, cum_percent };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ if (entries[i] != SYSMIS)
+ pivot_table_put2 (table, i, var_idx,
+ pivot_value_new_number (entries[i]));
+}
/* Displays a full frequency table for variable V. */
static void
dump_freq_table (const struct var_freqs *vf, const struct variable *wv)
{
- const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : &F_8_0;
const struct freq_tab *ft = &vf->tab;
- int n_categories;
- struct freq *f;
- struct tab_table *t;
- int r, x;
- double cum_total = 0.0;
- double cum_freq = 0.0;
- static const char *headings[] = {
- N_("Value Label"),
- N_("Value"),
- N_("Frequency"),
- N_("Percent"),
- N_("Valid Percent"),
- N_("Cum Percent")
- };
+ struct pivot_table *table = pivot_table_create__ (pivot_value_new_variable (
+ vf->var));
+ pivot_table_set_weight_var (table, wv);
- n_categories = ft->n_valid + ft->n_missing;
- t = tab_create (6, n_categories + 2);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, 1, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Frequency"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT,
+ N_("Valid Percent"), PIVOT_RC_PERCENT,
+ N_("Cumulative Percent"), PIVOT_RC_PERCENT);
- for (x = 0; x < 6; x++)
- tab_text (t, x, 0, TAB_CENTER | TAT_TITLE, gettext (headings[x]));
+ struct pivot_dimension *variable = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (vf->var));
- r = 1;
- for (f = ft->valid; f < ft->missing; f++)
+ double cum_freq = 0.0;
+ double cum_percent = 0.0;
+ struct pivot_category *valid = NULL;
+ for (const struct freq *f = ft->valid; f < ft->missing; f++)
{
- const char *label;
- double percent, valid_percent;
-
cum_freq += f->count;
-
- percent = f->count / ft->total_cases * 100.0;
- valid_percent = f->count / ft->valid_cases * 100.0;
- cum_total += valid_percent;
-
- label = var_lookup_value_label (vf->var, f->values);
- if (label != NULL)
- tab_text (t, 0, r, TAB_LEFT, label);
-
- tab_value (t, 1, r, TAB_NONE, f->values, vf->var, NULL);
- tab_double (t, 2, r, TAB_NONE, f->count, NULL, RC_WEIGHT);
- tab_double (t, 3, r, TAB_NONE, percent, NULL, RC_OTHER);
- tab_double (t, 4, r, TAB_NONE, valid_percent, NULL, RC_OTHER);
- tab_double (t, 5, r, TAB_NONE, cum_total, NULL, RC_OTHER);
- r++;
+ double valid_percent = f->count / ft->valid_cases * 100.0;
+ cum_percent += valid_percent;
+
+ if (!valid)
+ valid = pivot_category_create_group (variable->root, N_("Valid"));
+ int var_idx = pivot_category_create_leaf (
+ valid, pivot_value_new_var_value (vf->var, &f->values[0]));
+ put_freq_row (table, var_idx, f->count,
+ f->count / ft->total_cases * 100.0,
+ valid_percent, cum_percent);
}
- for (; f < &ft->valid[n_categories]; f++)
- {
- const char *label;
+ struct pivot_category *missing = NULL;
+ size_t n_categories = ft->n_valid + ft->n_missing;
+ for (const struct freq *f = ft->missing; f < &ft->valid[n_categories]; f++)
+ {
cum_freq += f->count;
- label = var_lookup_value_label (vf->var, f->values);
- if (label != NULL)
- tab_text (t, 0, r, TAB_LEFT, label);
-
- tab_value (t, 1, r, TAB_NONE, f->values, vf->var, NULL);
- tab_double (t, 2, r, TAB_NONE, f->count, NULL, RC_WEIGHT);
- tab_double (t, 3, r, TAB_NONE,
- f->count / ft->total_cases * 100.0, NULL, RC_OTHER);
- tab_text (t, 4, r, TAB_NONE, _("Missing"));
- r++;
+ if (!missing)
+ missing = pivot_category_create_group (variable->root, N_("Missing"));
+ int var_idx = pivot_category_create_leaf (
+ missing, pivot_value_new_var_value (vf->var, &f->values[0]));
+ put_freq_row (table, var_idx, f->count,
+ f->count / ft->total_cases * 100.0, SYSMIS, SYSMIS);
}
- tab_box (t, TAL_1, TAL_1, -1, TAL_1, 0, 0, 5, r);
- tab_hline (t, TAL_2, 0, 5, 1);
- tab_hline (t, TAL_2, 0, 5, r);
- tab_joint_text (t, 0, r, 1, r, TAB_RIGHT | TAT_TITLE, _("Total"));
- tab_vline (t, TAL_0, 1, r, r);
- tab_double (t, 2, r, TAB_NONE, cum_freq, NULL, RC_WEIGHT);
- tab_double (t, 3, r, TAB_NONE, 100.0, &F_5_1, RC_OTHER);
- tab_double (t, 4, r, TAB_NONE, 100.0, &F_5_1, RC_OTHER);
-
- tab_title (t, "%s", var_to_string (vf->var));
- tab_submit (t);
+ int var_idx = pivot_category_create_leaf (
+ variable->root, pivot_value_new_text (N_("Total")));
+ put_freq_row (table, var_idx, cum_freq, cum_percent, SYSMIS, SYSMIS);
+
+ pivot_table_submit (table);
}
\f
/* Statistical display. */
for (i = 0; i < frq->n_vars; i++)
{
struct var_freqs *vf = &frq->vars[i];
-
postprocess_freq_tab (frq, vf);
+ calc_percentiles (frq, vf);
+ }
+
+ if (frq->n_stats)
+ dump_statistics (frq, wv);
+
+ for (i = 0; i < frq->n_vars; i++)
+ {
+ struct var_freqs *vf = &frq->vars[i];
/* Frequencies tables. */
if (vf->tab.n_valid + vf->tab.n_missing <= frq->max_categories)
dump_freq_table (vf, wv);
- calc_percentiles (frq, vf);
-
- /* Statistics. */
- if (frq->n_stats)
- dump_statistics (frq, vf, wv);
if (frq->hist && var_is_numeric (vf->var) && vf->tab.n_valid > 0)
{
double d[FRQ_ST_count];
struct histogram *histogram;
- calc_stats (vf, d);
+ calc_stats (frq, vf, d);
histogram = freq_tab_to_hist (frq, &vf->tab, vf->var);
frq.percentiles = NULL;
frq.n_percentiles = 0;
- frq.n_show_percentiles = 0;
frq.hist = NULL;
frq.pie = NULL;
frq.percentiles[frq.n_percentiles].show = true;
lex_get (lexer);
frq.n_percentiles++;
- frq.n_show_percentiles++;
}
else
{
frq.percentiles[frq.n_percentiles].show = true;
frq.n_percentiles++;
- frq.n_show_percentiles++;
}
}
else
* sizeof (*frq.percentiles));
frq.percentiles[frq.n_percentiles].p = 0.50;
- frq.percentiles[frq.n_percentiles].show = true;
+ frq.percentiles[frq.n_percentiles].show = false;
frq.n_percentiles++;
- frq.n_show_percentiles++;
}
sizeof (*frq.percentiles),
ptile_3way);
- frq.n_show_percentiles = 0;
for (i = o = 0; i < frq.n_percentiles; ++i)
{
if (frq.percentiles[i].p != previous_p)
{
frq.percentiles[o].p = frq.percentiles[i].p;
frq.percentiles[o].show = frq.percentiles[i].show;
- if (frq.percentiles[i].show)
- frq.n_show_percentiles++;
o++;
}
else if (frq.percentiles[i].show &&
!frq.percentiles[o].show)
{
frq.percentiles[o].show = true;
- frq.n_show_percentiles++;
}
previous_p = frq.percentiles[i].p;
}
frq.n_percentiles = o;
+
+ frq.median = NULL;
+ for (i = 0; i < frq.n_percentiles; i++)
+ if (frq.percentiles[i].p == 0.5)
+ {
+ frq.median = &frq.percentiles[i];
+ break;
+ }
}
{
/* Calculates all the pertinent statistics for VF, putting them in array
D[]. */
static void
-calc_stats (const struct var_freqs *vf, double d[FRQ_ST_count])
+calc_stats (const struct frq_proc *frq, const struct var_freqs *vf,
+ double d[FRQ_ST_count])
{
const struct freq_tab *ft = &vf->tab;
double W = ft->valid_cases;
d[FRQ_ST_SEMEAN] = d[FRQ_ST_STDDEV] / sqrt (W);
d[FRQ_ST_SESKEWNESS] = calc_seskew (W);
d[FRQ_ST_SEKURTOSIS] = calc_sekurt (W);
+ d[FRQ_ST_MEDIAN] = frq->median ? frq->median->value : SYSMIS;
}
-/* Displays a table of all the statistics requested for variable V. */
-static void
-dump_statistics (const struct frq_proc *frq, const struct var_freqs *vf,
- const struct variable *wv)
+static bool
+all_string_variables (const struct frq_proc *frq)
{
- const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : &F_8_0;
- const struct freq_tab *ft = &vf->tab;
- double stat_value[FRQ_ST_count];
- struct tab_table *t;
- int i, r = 2; /* N missing and N valid are always dumped */
-
- if (var_is_alpha (vf->var))
- return;
+ for (size_t i = 0; i < frq->n_vars; i++)
+ if (var_is_numeric (frq->vars[i].var))
+ return false;
- calc_stats (vf, stat_value);
-
- t = tab_create (3, ((frq->stats & BIT_INDEX (FRQ_ST_MEDIAN)) ? frq->n_stats - 1 : frq->n_stats)
- + frq->n_show_percentiles + 2);
-
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_box (t, TAL_1, TAL_1, -1, -1 , 0 , 0 , 2, tab_nr(t) - 1) ;
+ return true;
+}
- tab_vline (t, TAL_1 , 2, 0, tab_nr(t) - 1);
+/* Displays a table of all the statistics requested. */
+static void
+dump_statistics (const struct frq_proc *frq, const struct variable *wv)
+{
+ if (all_string_variables (frq))
+ return;
- for (i = 0; i < FRQ_ST_count; i++)
+ struct pivot_table *table = pivot_table_create (N_("Statistics"));
+ pivot_table_set_weight_var (table, wv);
+
+ struct pivot_dimension *variables
+ = pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Variables"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"));
+ struct pivot_category *n = pivot_category_create_group (
+ statistics->root, N_("N"));
+ pivot_category_create_leaves (n,
+ N_("Valid"), PIVOT_RC_COUNT,
+ N_("Missing"), PIVOT_RC_COUNT);
+ for (int i = 0; i < FRQ_ST_count; i++)
+ if (frq->stats & BIT_INDEX (i))
+ pivot_category_create_leaf (statistics->root,
+ pivot_value_new_text (st_name[i]));
+ struct pivot_category *percentiles = NULL;
+ for (size_t i = 0; i < frq->n_percentiles; i++)
{
- if (FRQ_ST_MEDIAN == i)
- continue;
-
- if (frq->stats & BIT_INDEX (i))
- {
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE,
- gettext (st_name[i]));
-
- if (vf->tab.n_valid <= 0 && r >= 2)
- tab_text (t, 2, r, 0, ".");
- else
- tab_double (t, 2, r, TAB_NONE, stat_value[i], NULL, RC_OTHER);
- r++;
- }
- }
+ const struct percentile *pc = &frq->percentiles[i];
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("N"));
- tab_text (t, 1, 0, TAB_LEFT | TAT_TITLE, _("Valid"));
- tab_text (t, 1, 1, TAB_LEFT | TAT_TITLE, _("Missing"));
+ if (!pc->show)
+ continue;
- tab_double (t, 2, 0, TAB_NONE, ft->valid_cases, NULL, RC_WEIGHT);
- tab_double (t, 2, 1, TAB_NONE, ft->total_cases - ft->valid_cases, NULL, RC_WEIGHT);
+ if (!percentiles)
+ percentiles = pivot_category_create_group (
+ statistics->root, N_("Percentiles"));
+ pivot_category_create_leaf (percentiles, pivot_value_new_integer (
+ pc->p * 100.0));
+ }
- for (i = 0; i < frq->n_percentiles; i++)
+ for (size_t i = 0; i < frq->n_vars; i++)
{
- const struct percentile *pc = &frq->percentiles[i];
-
- if (!pc->show)
+ struct var_freqs *vf = &frq->vars[i];
+ if (var_is_alpha (vf->var))
continue;
- if ( i == 0 )
- {
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Percentiles"));
- }
+ const struct freq_tab *ft = &vf->tab;
- if (vf->tab.n_valid <= 0)
- {
- tab_text (t, 2, r, 0, ".");
- ++r;
- continue;
- }
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (vf->var));
- if (pc->p == 0.5)
- tab_text (t, 1, r, TAB_LEFT, _("50 (Median)"));
- else
- tab_double (t, 1, r, TAB_LEFT, pc->p * 100, NULL, RC_INTEGER);
- tab_double (t, 2, r, TAB_NONE, pc->value,
- var_get_print_format (vf->var), RC_OTHER);
+ int row = 0;
+ pivot_table_put2 (table, var_idx, row++,
+ pivot_value_new_number (ft->valid_cases));
+ pivot_table_put2 (table, var_idx, row++,
+ pivot_value_new_number (
+ ft->total_cases - ft->valid_cases));
- ++r;
- }
+ double stat_values[FRQ_ST_count];
+ calc_stats (frq, vf, stat_values);
+ for (int j = 0; j < FRQ_ST_count; j++)
+ {
+ if (!(frq->stats & BIT_INDEX (j)))
+ continue;
+
+ union value v = { .f = vf->tab.n_valid ? stat_values[j] : SYSMIS };
+ struct pivot_value *pv
+ = (j == FRQ_ST_MODE || j == FRQ_ST_MINIMUM || j == FRQ_ST_MAXIMUM
+ ? pivot_value_new_var_value (vf->var, &v)
+ : pivot_value_new_number (v.f));
+ pivot_table_put2 (table, var_idx, row++, pv);
+ }
+
+ for (size_t j = 0; j < frq->n_percentiles; j++)
+ {
+ const struct percentile *pc = &frq->percentiles[j];
+ if (!pc->show)
+ continue;
- tab_title (t, "%s", var_to_string (vf->var));
+ union value v = { .f = vf->tab.n_valid ? pc->value : SYSMIS };
+ pivot_table_put2 (table, var_idx, row++,
+ pivot_value_new_var_value (vf->var, &v));
+ }
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
-
#include "data/variable.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static void
show_ranks_box (const struct one_sample_test *ost, const struct friedman *fr)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 1;
- struct tab_table *table =
- tab_create (row_headers + 1, column_headers + ost->n_vars);
+ struct pivot_table *table = pivot_table_create (N_("Ranks"));
- tab_headers (table, row_headers, 0, column_headers, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Mean Rank"),
+ N_("Mean Rank"), PIVOT_RC_OTHER);
- tab_title (table, _("Ranks"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
-
- tab_text (table, 1, 0, 0, _("Mean Rank"));
-
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- for (i = 0 ; i < ost->n_vars ; ++i)
+ for (size_t i = 0 ; i < ost->n_vars ; ++i)
{
- tab_text (table, 0, row_headers + i,
- TAB_LEFT, var_to_string (ost->vars[i]));
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (ost->vars[i]));
- tab_double (table, 1, row_headers + i,
- 0, fr->rank_sum[i] / fr->cc, NULL, RC_OTHER);
+ pivot_table_put2 (table, 0, row,
+ pivot_value_new_number (fr->rank_sum[i] / fr->cc));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
{
const struct friedman_test *ft = UP_CAST (ost, const struct friedman_test, parent);
- int row = 0;
- const struct fmt_spec *wfmt = dict_get_weight_format (fr->dict);
-
- const int row_headers = 1;
- const int column_headers = 0;
- struct tab_table *table =
- tab_create (row_headers + 1, column_headers + (ft->kendalls_w ? 5 : 4));
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Test Statistics"));
-
- tab_text (table, 0, column_headers + row++,
- TAT_TITLE | TAB_LEFT , _("N"));
-
- if ( ft->kendalls_w)
- tab_text (table, 0, column_headers + row++,
- TAT_TITLE | TAB_LEFT , _("Kendall's W"));
-
- tab_text (table, 0, column_headers + row++,
- TAT_TITLE | TAB_LEFT , _("Chi-Square"));
-
- tab_text (table, 0, column_headers + row++,
- TAT_TITLE | TAB_LEFT, _("df"));
-
- tab_text (table, 0, column_headers + row++,
- TAT_TITLE | TAB_LEFT, _("Asymp. Sig."));
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- row = 0;
- tab_double (table, 1, column_headers + row++,
- 0, fr->cc, NULL, RC_WEIGHT);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
+ pivot_table_set_weight_var (table, dict_get_weight (fr->dict));
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT);
if (ft->kendalls_w)
- tab_double (table, 1, column_headers + row++,
- 0, fr->w, NULL, RC_OTHER);
+ pivot_category_create_leaves (statistics->root, N_("Kendall's W"),
+ PIVOT_RC_OTHER);
+ pivot_category_create_leaves (statistics->root,
+ N_("Chi-Square"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Asymp. Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_double (table, 1, column_headers + row++,
- 0, fr->chi_sq, NULL, RC_OTHER);
+ double entries[5];
+ int n = 0;
- tab_double (table, 1, column_headers + row++,
- 0, ost->n_vars - 1, NULL, RC_INTEGER);
+ entries[n++] = fr->cc;
+ if (ft->kendalls_w)
+ entries[n++] = fr->w;
+ entries[n++] = fr->chi_sq;
+ entries[n++] = ost->n_vars - 1;
+ entries[n++] = gsl_cdf_chisq_Q (fr->chi_sq, ost->n_vars - 1);
+ assert (n <= sizeof entries / sizeof *entries);
- tab_double (table, 1, column_headers + row++,
- 0, gsl_cdf_chisq_Q (fr->chi_sq, ost->n_vars - 1),
- NULL, RC_PVALUE);
+ for (size_t i = 0; i < n; i++)
+ pivot_table_put1 (table, i, pivot_value_new_number (entries[i]));
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "math/covariance.h"
#include "math/interaction.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
struct glm_spec
if (cmd->dump_coding)
{
- struct tab_table *t =
- covariance_dump_enc_header (cov,
- 1 + casereader_count_cases (input));
+ struct pivot_table *t = covariance_dump_enc_header (cov);
for (reader = input;
(c = casereader_read (reader)) != NULL; case_unref (c))
{
covariance_dump_enc (cov, c, t);
}
- casereader_destroy (reader);
- tab_submit (t);
+
+ pivot_table_submit (t);
}
{
taint_destroy (taint);
}
-static const char *roman[] =
- {
- "", /* The Romans had no concept of zero */
- "I",
- "II",
- "III",
- "IV"
- };
+static void
+put_glm_row (struct pivot_table *table, int row,
+ double a, double b, double c, double d, double e)
+{
+ double entries[] = { a, b, c, d, e };
+
+ for (size_t col = 0; col < sizeof entries / sizeof *entries; col++)
+ if (entries[col] != SYSMIS)
+ pivot_table_put2 (table, col, row,
+ pivot_value_new_number (entries[col]));
+}
static void
output_glm (const struct glm_spec *cmd, const struct glm_workspace *ws)
{
- const struct fmt_spec *wfmt =
- cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
+ struct pivot_table *table = pivot_table_create (
+ N_("Tests of Between-Subjects Effects"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ (cmd->ss_type == 1 ? N_("Type I Sum Of Squares")
+ : cmd->ss_type == 2 ? N_("Type II Sum Of Squares")
+ : N_("Type III Sum Of Squares")), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Mean Square"), PIVOT_RC_OTHER,
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *source = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Source"),
+ cmd->intercept ? N_("Corrected Model") : N_("Model"));
- double intercept_ssq;
- double ssq_effects;
double n_total, mean;
- double df_corr = 1.0;
- double mse = 0;
-
- int f;
- int r;
- const int heading_columns = 1;
- const int heading_rows = 1;
- struct tab_table *t;
-
- const int nc = 6;
- int nr = heading_rows + 3 + cmd->n_interactions;
- if (cmd->intercept)
- nr += 2;
-
- t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_title (t, _("Tests of Between-Subjects Effects"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Source"));
-
- /* TRANSLATORS: The parameter is a roman numeral */
- tab_text_format (t, 1, 0, TAB_CENTER | TAT_TITLE,
- _("Type %s Sum of Squares"),
- roman[cmd->ss_type]);
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean Square"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("F"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
-
moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
- df_corr += categoricals_df_total (ws->cats);
+ double df_corr = 1.0 + categoricals_df_total (ws->cats);
- r = heading_rows;
- if (cmd->intercept)
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
- else
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Model"));
-
- r++;
-
- mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
-
- intercept_ssq = pow2 (mean * n_total) / n_total;
-
- ssq_effects = 0.0;
+ double mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
+ double intercept_ssq = pow2 (mean * n_total) / n_total;
if (cmd->intercept)
{
- const double df = 1.0;
- const double F = intercept_ssq / df / mse;
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Intercept"));
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_text (N_("Intercept")));
+
/* The intercept for unbalanced models is of limited use and
nobody knows how to calculate it properly */
if (categoricals_isbalanced (ws->cats))
- {
- tab_double (t, 1, r, 0, intercept_ssq, NULL, RC_OTHER);
- tab_double (t, 2, r, 0, 1.00, NULL, RC_WEIGHT);
- tab_double (t, 3, r, 0, intercept_ssq / df, NULL, RC_OTHER);
- tab_double (t, 4, r, 0, F, NULL, RC_OTHER);
- tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
- NULL, RC_PVALUE);
- }
- r++;
+ {
+ const double df = 1.0;
+ const double F = intercept_ssq / df / mse;
+ put_glm_row (table, row, intercept_ssq, 1.0, intercept_ssq / df,
+ F, gsl_cdf_fdist_Q (F, df, n_total - df_corr));
+ }
}
- for (f = 0; f < cmd->n_interactions; ++f)
+ double ssq_effects = 0.0;
+ for (int f = 0; f < cmd->n_interactions; ++f)
{
- struct string str = DS_EMPTY_INITIALIZER;
double df = categoricals_df (ws->cats, f);
-
double ssq = gsl_vector_get (ws->ssq, f + 1);
- double F;
-
ssq_effects += ssq;
-
- if (! cmd->intercept)
+ if (!cmd->intercept)
{
df++;
ssq += intercept_ssq;
}
+ double F = ssq / df / mse;
- F = ssq / df / mse;
+ struct string str = DS_EMPTY_INITIALIZER;
interaction_to_string (cmd->interactions[f], &str);
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, ds_cstr (&str));
- ds_destroy (&str);
-
- tab_double (t, 1, r, 0, ssq, NULL, RC_OTHER);
- tab_double (t, 2, r, 0, df, NULL, RC_WEIGHT);
- tab_double (t, 3, r, 0, ssq / df, NULL, RC_OTHER);
- tab_double (t, 4, r, 0, F, NULL, RC_OTHER);
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
- tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
- NULL, RC_PVALUE);
- r++;
+ put_glm_row (table, row, ssq, df, ssq / df, F,
+ gsl_cdf_fdist_Q (F, df, n_total - df_corr));
}
{
/* Model / Corrected Model */
double df = df_corr;
double ssq = ws->total_ssq - gsl_vector_get (ws->ssq, 0);
- double F;
-
- if ( cmd->intercept )
- df --;
+ if (cmd->intercept)
+ df--;
else
ssq += intercept_ssq;
-
- F = ssq / df / mse;
- tab_double (t, 1, heading_rows, 0, ssq, NULL, RC_OTHER);
- tab_double (t, 2, heading_rows, 0, df, NULL, RC_WEIGHT);
- tab_double (t, 3, heading_rows, 0, ssq / df, NULL, RC_OTHER);
- tab_double (t, 4, heading_rows, 0, F, NULL, RC_OTHER);
-
- tab_double (t, 5, heading_rows, 0,
- gsl_cdf_fdist_Q (F, df, n_total - df_corr), NULL, RC_PVALUE);
+ double F = ssq / df / mse;
+ put_glm_row (table, 0, ssq, df, ssq / df, F,
+ gsl_cdf_fdist_Q (F, df, n_total - df_corr));
}
{
+ int row = pivot_category_create_leaf (source->root,
+ pivot_value_new_text (N_("Error")));
const double df = n_total - df_corr;
const double ssq = gsl_vector_get (ws->ssq, 0);
const double mse = ssq / df;
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Error"));
- tab_double (t, 1, r, 0, ssq, NULL, RC_OTHER);
- tab_double (t, 2, r, 0, df, NULL, RC_WEIGHT);
- tab_double (t, 3, r++, 0, mse, NULL, RC_OTHER);
+ put_glm_row (table, row, ssq, df, mse, SYSMIS, SYSMIS);
}
{
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Total"));
- tab_double (t, 1, r, 0, ws->total_ssq + intercept_ssq, NULL, RC_OTHER);
- tab_double (t, 2, r, 0, n_total, NULL, RC_WEIGHT);
-
- r++;
+ int row = pivot_category_create_leaf (source->root,
+ pivot_value_new_text (N_("Total")));
+ put_glm_row (table, row, ws->total_ssq + intercept_ssq, n_total,
+ SYSMIS, SYSMIS, SYSMIS);
}
if (cmd->intercept)
{
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Total"));
- tab_double (t, 1, r, 0, ws->total_ssq, NULL, RC_OTHER);
- tab_double (t, 2, r, 0, n_total - 1.0, NULL, RC_WEIGHT);
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_text (N_("Corrected Total")));
+ put_glm_row (table, row, ws->total_ssq, n_total - 1.0, SYSMIS,
+ SYSMIS, SYSMIS);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
#if 0
#include "language/stats/freq.h"
#include "language/stats/chart-category.h"
-#include "output/tab.h"
-
#include "gettext.h"
#define _(msgid) gettext (msgid)
#define N_(msgid) msgid
#include "libpspp/message.h"
#include "libpspp/misc.h"
#include "math/sort.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gl/xalloc.h"
+#include "gettext.h"
+#define N_(msgid) msgid
+#define _(msgid) gettext (msgid)
+
+
/* Returns true iff the independent variable lies in the
between val1 and val2. Regardless of which is the greater value.
*/
double stddev;
};
-static void show_jt (const struct n_sample_test *nst, const struct jt *jt, const struct variable *wv);
+static void show_jt (const struct n_sample_test *, const struct jt *,
+ const struct fmt_spec *wfmt);
void
jt.mean = (pow2 (jt.n) - ccsq_sum) / 4.0;
- show_jt (nst, &jt, dict_get_weight (dict));
+ show_jt (nst, &jt, dict_get_weight_format (dict));
}
casereader_destroy (input);
caseproto_unref (proto);
}
-
\f
-
-#include "gettext.h"
-#define _(msgid) gettext (msgid)
-
static void
-show_jt (const struct n_sample_test *nst, const struct jt *jt, const struct variable *wv)
+show_jt (const struct n_sample_test *nst, const struct jt *jt,
+ const struct fmt_spec *wfmt)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 1;
- const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : & F_8_0;
-
- struct tab_table *table =
- tab_create (row_headers + 7, column_headers + nst->n_vars);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Jonckheere-Terpstra Test"));
-
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- tab_text_format (table, 1, 0, TAT_TITLE | TAB_CENTER,
- _("Number of levels in %s"),
- var_to_string (nst->indep_var));
- tab_text (table, 2, 0, TAT_TITLE | TAB_CENTER, _("N"));
- tab_text (table, 3, 0, TAT_TITLE | TAB_CENTER, _("Observed J-T Statistic"));
- tab_text (table, 4, 0, TAT_TITLE | TAB_CENTER, _("Mean J-T Statistic"));
- tab_text (table, 5, 0, TAT_TITLE | TAB_CENTER, _("Std. Deviation of J-T Statistic"));
- tab_text (table, 6, 0, TAT_TITLE | TAB_CENTER, _("Std. J-T Statistic"));
- tab_text (table, 7, 0, TAT_TITLE | TAB_CENTER, _("Asymp. Sig. (2-tailed)"));
-
-
- for (i = 0; i < nst->n_vars; ++i)
+ struct pivot_table *table = pivot_table_create (
+ N_("Jonckheere-Terpstra Test"));
+ pivot_table_set_weight_format (table, wfmt);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_leaf_rc (
+ statistics->root,
+ pivot_value_new_text_format (N_("Number of levels in %s"),
+ var_to_string (nst->indep_var)),
+ PIVOT_RC_INTEGER);
+ pivot_category_create_leaves (
+ statistics->root,
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Observed J-T Statistic"), PIVOT_RC_OTHER,
+ N_("Mean J-T Statistic"), PIVOT_RC_OTHER,
+ N_("Std. Deviation of J-T Statistic"), PIVOT_RC_OTHER,
+ N_("Std. J-T Statistic"), PIVOT_RC_OTHER,
+ N_("Asymp. Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+
+ for (size_t i = 0; i < nst->n_vars; ++i)
{
- double std_jt;
-
- tab_text (table, 0, i + row_headers, TAT_TITLE,
- var_to_string (nst->vars[i]) );
-
- tab_double (table, 1, i + row_headers, TAT_TITLE,
- jt[0].levels, NULL, RC_INTEGER);
-
- tab_double (table, 2, i + row_headers, TAT_TITLE,
- jt[0].n, NULL, RC_WEIGHT);
-
- tab_double (table, 3, i + row_headers, TAT_TITLE,
- jt[0].obs, NULL, RC_OTHER);
-
- tab_double (table, 4, i + row_headers, TAT_TITLE,
- jt[0].mean, NULL, RC_OTHER);
-
- tab_double (table, 5, i + row_headers, TAT_TITLE,
- jt[0].stddev, NULL, RC_OTHER);
-
- std_jt = (jt[0].obs - jt[0].mean) / jt[0].stddev;
- tab_double (table, 6, i + row_headers, TAT_TITLE,
- std_jt, NULL, RC_OTHER);
-
- tab_double (table, 7, i + row_headers, TAT_TITLE,
- 2.0 * ((std_jt > 0) ? gsl_cdf_ugaussian_Q (std_jt) : gsl_cdf_ugaussian_P (std_jt)), NULL, RC_PVALUE);
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (nst->vars[i]));
+
+ double std_jt = (jt[0].obs - jt[0].mean) / jt[0].stddev;
+ double sig = (2.0 * (std_jt > 0
+ ? gsl_cdf_ugaussian_Q (std_jt)
+ : gsl_cdf_ugaussian_P (std_jt)));
+ double entries[] = {
+ jt[0].levels,
+ jt[0].n,
+ jt[0].obs,
+ jt[0].mean,
+ jt[0].stddev,
+ std_jt,
+ sig,
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, row, pivot_value_new_number (entries[j]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "libpspp/message.h"
#include "libpspp/misc.h"
#include "math/sort.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gl/xalloc.h"
+#include "gettext.h"
+#define N_(msgid) msgid
+#define _(msgid) gettext (msgid)
/* Returns true iff the independent variable lies in the range [nst->val1, nst->val2] */
static bool
double h;
};
-static void show_ranks_box (const struct n_sample_test *nst, const struct kw *kw, int n_groups);
-static void show_sig_box (const struct n_sample_test *nst, const struct kw *kw);
+static void show_ranks_box (const struct n_sample_test *, const struct kw *);
+static void show_sig_box (const struct n_sample_test *, const struct kw *);
void
kruskal_wallis_execute (const struct dataset *ds,
casereader_destroy (input);
- show_ranks_box (nst, kw, total_n_groups);
+ show_ranks_box (nst, kw);
show_sig_box (nst, kw);
/* Cleanup allocated memory */
free (kw);
}
-
\f
-#include "gettext.h"
-#define _(msgid) gettext (msgid)
-
-
static void
-show_ranks_box (const struct n_sample_test *nst, const struct kw *kw, int n_groups)
+show_ranks_box (const struct n_sample_test *nst, const struct kw *kw)
{
- int row;
- int i;
- const int row_headers = 2;
- const int column_headers = 1;
- struct tab_table *table =
- tab_create (row_headers + 2, column_headers + n_groups + nst->n_vars);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
+ struct pivot_table *table = pivot_table_create (N_("Ranks"));
- tab_title (table, _("Ranks"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_INTEGER,
+ N_("Mean Rank"), PIVOT_RC_OTHER);
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_text (table, 1, 0, TAT_TITLE,
- var_to_string (nst->indep_var)
- );
-
- tab_text (table, 3, 0, 0, _("Mean Rank"));
- tab_text (table, 2, 0, 0, _("N"));
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
-
- row = column_headers;
- for (i = 0 ; i < nst->n_vars ; ++i)
+ for (size_t i = 0 ; i < nst->n_vars ; ++i)
{
- int tot = 0;
- struct rank_entry *re_x;
- struct bt bt;
-
- if (i > 0)
- tab_hline (table, TAL_1, 0, tab_nc (table) -1, row);
-
- tab_text (table, 0, row,
- TAT_TITLE, var_to_string (nst->vars[i]));
-
/* Sort the rank entries, by iteratin the hash and putting the entries
into a binary tree. */
- bt_init (&bt, compare_rank_entries_3way, nst->vars[i]);
+ struct bt bt = BT_INITIALIZER(compare_rank_entries_3way, nst->vars[i]);
+ struct rank_entry *re_x;
HMAP_FOR_EACH (re_x, struct rank_entry, node, &kw[i].map)
- {
- bt_insert (&bt, &re_x->btn);
- }
+ bt_insert (&bt, &re_x->btn);
/* Report the rank entries in sorted order. */
+ struct pivot_category *group = pivot_category_create_group__ (
+ variables->root, pivot_value_new_variable (nst->vars[i]));
+ int tot = 0;
const struct rank_entry *re;
BT_FOR_EACH (re, struct rank_entry, btn, &bt)
{
- struct string str;
- ds_init_empty (&str);
-
+ struct string str = DS_EMPTY_INITIALIZER;
var_append_value_name (nst->indep_var, &re->group, &str);
+ int row = pivot_category_create_leaf (
+ group, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
- tab_text (table, 1, row, TAB_LEFT, ds_cstr (&str));
- tab_double (table, 2, row, TAB_LEFT, re->n, NULL, RC_INTEGER);
- tab_double (table, 3, row, TAB_LEFT, re->sum_of_ranks / re->n, NULL, RC_OTHER);
+ double entries[] = { re->n, re->sum_of_ranks / re->n };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, row,
+ pivot_value_new_number (entries[j]));
tot += re->n;
- row++;
- ds_destroy (&str);
}
- tab_double (table, 2, row, TAB_LEFT,
- tot, NULL, RC_INTEGER);
- tab_text (table, 1, row++, TAB_LEFT, _("Total"));
+ int row = pivot_category_create_leaves (group, N_("Total"));
+ pivot_table_put2 (table, 0, row, pivot_value_new_number (tot));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
-
static void
show_sig_box (const struct n_sample_test *nst, const struct kw *kw)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 1;
- struct tab_table *table =
- tab_create (row_headers + nst->n_vars * 2, column_headers + 3);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Test Statistics"));
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
- tab_text (table, 0, column_headers,
- TAT_TITLE | TAB_LEFT , _("Chi-Square"));
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Chi-Square"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Asymp. Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_text (table, 0, 1 + column_headers,
- TAT_TITLE | TAB_LEFT, _("df"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Variables"));
- tab_text (table, 0, 2 + column_headers,
- TAT_TITLE | TAB_LEFT, _("Asymp. Sig."));
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- for (i = 0 ; i < nst->n_vars; ++i)
+ for (size_t i = 0 ; i < nst->n_vars; ++i)
{
- const double df = hmap_count (&kw[i].map) - 1;
- tab_text (table, column_headers + 1 + i, 0, TAT_TITLE,
- var_to_string (nst->vars[i])
- );
-
- tab_double (table, column_headers + 1 + i, 1, 0,
- kw[i].h, NULL, RC_OTHER);
-
- tab_double (table, column_headers + 1 + i, 2, 0,
- df, NULL, RC_INTEGER);
-
- tab_double (table, column_headers + 1 + i, 3, 0,
- gsl_cdf_chisq_Q (kw[i].h, df),
- NULL, RC_PVALUE);
+ int col = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (nst->vars[i]));
+
+ double df = hmap_count (&kw[i].map) - 1;
+ double sig = gsl_cdf_chisq_Q (kw[i].h, df);
+ double entries[] = { kw[i].h, df, sig };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, col, pivot_value_new_number (entries[j]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "libpspp/hash-functions.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
const struct ks_one_sample_test *kst,
const struct fmt_spec *wfmt)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 2;
- const int nc = kst->parent.n_vars + column_headers;
- const int nr = 8 + row_headers;
- struct tab_table *table = tab_create (nc, nr);
- tab_set_format (table, RC_WEIGHT, wfmt);
- tab_headers (table, row_headers, 0, column_headers, 0);
+ struct pivot_table *table = pivot_table_create (
+ N_("One-Sample Kolmogorov-Smirnov Test"));
+ pivot_table_set_weight_format (table, wfmt);
- tab_title (table, _("One-Sample Kolmogorov-Smirnov Test"));
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, nc - 1, nr - 1 );
-
- tab_hline (table, TAL_2, 0, nc - 1, row_headers);
-
- tab_vline (table, TAL_1, column_headers, 0, nr - 1);
-
- tab_text (table, 0, 1,
- TAT_TITLE | TAB_LEFT , _("N"));
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT);
switch (kst->dist)
{
- case KS_NORMAL:
- tab_text (table, 0, 2,
- TAT_TITLE | TAB_LEFT , _("Normal Parameters"));
-
- tab_text (table, 1, 2,
- TAT_TITLE | TAB_LEFT , _("Mean"));
- tab_text (table, 1, 3,
- TAT_TITLE | TAB_LEFT , _("Std. Deviation"));
- break;
case KS_UNIFORM:
- tab_text (table, 0, 2,
- TAT_TITLE | TAB_LEFT , _("Uniform Parameters"));
+ pivot_category_create_group (statistics->root, N_("Uniform Parameters"),
+ N_("Minimum"), N_("Maximum"));
+ break;
- tab_text (table, 1, 2,
- TAT_TITLE | TAB_LEFT , _("Minimum"));
- tab_text (table, 1, 3,
- TAT_TITLE | TAB_LEFT , _("Maximum"));
+ case KS_NORMAL:
+ pivot_category_create_group (statistics->root, N_("Normal Parameters"),
+ N_("Mean"), N_("Std. Deviation"));
break;
- case KS_POISSON:
- tab_text (table, 0, 2,
- TAT_TITLE | TAB_LEFT , _("Poisson Parameters"));
- tab_text (table, 1, 2,
- TAT_TITLE | TAB_LEFT , _("Lambda"));
+ case KS_POISSON:
+ pivot_category_create_group (statistics->root, N_("Poisson Parameters"),
+ N_("Lambda"));
break;
- case KS_EXPONENTIAL:
- tab_text (table, 0, 2,
- TAT_TITLE | TAB_LEFT , _("Exponential Parameters"));
- tab_text (table, 1, 2,
- TAT_TITLE | TAB_LEFT , _("Scale"));
+ case KS_EXPONENTIAL:
+ pivot_category_create_group (statistics->root,
+ N_("Exponential Parameters"), N_("Scale"));
break;
default:
NOT_REACHED ();
}
- /* The variable columns */
- for (i = 0; i < kst->parent.n_vars; ++i)
+ pivot_category_create_group (
+ statistics->root, N_("Most Extreme Differences"),
+ N_("Absolute"), N_("Positive"), N_("Negative"));
+
+ pivot_category_create_leaves (
+ statistics->root, N_("Kolmogorov-Smirnov Z"),
+ _("Asymp. Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Variables"));
+
+ for (size_t i = 0; i < kst->parent.n_vars; ++i)
{
- double abs = 0;
- double z = 0;
- const int col = 2 + i;
- tab_text (table, col, 0,
- TAT_TITLE | TAB_CENTER ,
- var_to_string (kst->parent.vars[i]));
+ int col = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (kst->parent.vars[i]));
+
+ double values[10];
+ size_t n = 0;
+
+ values[n++] = ks[i].obs_cc;
switch (kst->dist)
{
case KS_UNIFORM:
- tab_double (table, col, 1, 0, ks[i].obs_cc, NULL, RC_WEIGHT);
- tab_double (table, col, 2, 0, ks[i].test_min, NULL, RC_OTHER);
- tab_double (table, col, 3, 0, ks[i].test_max, NULL, RC_OTHER);
+ values[n++] = ks[i].test_min;
+ values[n++] = ks[i].test_max;
break;
case KS_NORMAL:
- tab_double (table, col, 1, 0, ks[i].obs_cc, NULL, RC_WEIGHT);
- tab_double (table, col, 2, 0, ks[i].mu, NULL, RC_OTHER);
- tab_double (table, col, 3, 0, ks[i].sigma, NULL, RC_OTHER);
+ values[n++] = ks[i].mu;
+ values[n++] = ks[i].sigma;
break;
case KS_POISSON:
case KS_EXPONENTIAL:
- tab_double (table, col, 1, 0, ks[i].obs_cc, NULL, RC_WEIGHT);
- tab_double (table, col, 2, 0, ks[i].mu, NULL, RC_OTHER);
+ values[n++] = ks[i].mu;
break;
default:
NOT_REACHED ();
}
- abs = ks[i].diff_pos;
+ double abs = ks[i].diff_pos;
maximize (&abs, -ks[i].diff_neg);
- z = sqrt (ks[i].obs_cc) * abs;
-
- tab_double (table, col, 5, 0, ks[i].diff_pos, NULL, RC_OTHER);
- tab_double (table, col, 6, 0, ks[i].diff_neg, NULL, RC_OTHER);
+ double z = sqrt (ks[i].obs_cc) * abs;
- tab_double (table, col, 4, 0, abs, NULL, RC_OTHER);
+ values[n++] = abs;
+ values[n++] = ks[i].diff_pos;
+ values[n++] = ks[i].diff_neg;
+ values[n++] = z;
+ values[n++] = ks_asymp_sig (z);
- tab_double (table, col, 7, 0, z, NULL, RC_OTHER);
- tab_double (table, col, 8, 0, ks_asymp_sig (z), NULL, RC_PVALUE);
+ for (size_t j = 0; j < n; j++)
+ pivot_table_put2 (table, j, col, pivot_value_new_number (values[j]));
}
-
- tab_text (table, 0, 4,
- TAT_TITLE | TAB_LEFT , _("Most Extreme Differences"));
-
- tab_text (table, 1, 4,
- TAT_TITLE | TAB_LEFT , _("Absolute"));
-
- tab_text (table, 1, 5,
- TAT_TITLE | TAB_LEFT , _("Positive"));
-
- tab_text (table, 1, 6,
- TAT_TITLE | TAB_LEFT , _("Negative"));
-
- tab_text (table, 0, 7,
- TAT_TITLE | TAB_LEFT , _("Kolmogorov-Smirnov Z"));
-
- tab_text (table, 0, 8,
- TAT_TITLE | TAB_LEFT , _("Asymp. Sig. (2-tailed)"));
-
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "language/lexer/value-parser.h"
#include "language/lexer/variable-parser.h"
#include "libpspp/assertion.h"
+#include "libpspp/hash-functions.h"
+#include "libpspp/hmap.h"
#include "libpspp/ll.h"
#include "libpspp/message.h"
#include "libpspp/misc.h"
#include "math/categoricals.h"
#include "math/interaction.h"
-#include "libpspp/hmap.h"
-#include "libpspp/hash-functions.h"
-
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static void
output_depvarmap (const struct lr_spec *cmd, const struct lr_result *res)
{
- const int heading_columns = 0;
- const int heading_rows = 1;
- struct tab_table *t;
- struct string str;
-
- const int nc = 2;
- int nr = heading_rows + 2;
-
- t = tab_create (nc, nr);
- tab_title (t, _("Dependent Variable Encoding"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ struct pivot_table *table = pivot_table_create (
+ N_("Dependent Variable Encoding"));
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Original Value"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Internal Value"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Mapping"),
+ N_("Internal Value"));
+ struct pivot_dimension *original = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Original Value"));
+ original->root->show_label = true;
+ for (int i = 0; i < 2; i++)
+ {
+ const union value *v = i ? &res->y1 : &res->y0;
+ int orig_idx = pivot_category_create_leaf (
+ original->root, pivot_value_new_var_value (cmd->dep_var, v));
+ pivot_table_put2 (table, 0, orig_idx, pivot_value_new_number (
+ map_dependent_var (cmd, res, v)));
+ }
- ds_init_empty (&str);
- var_append_value_name (cmd->dep_var, &res->y0, &str);
- tab_text (t, 0, 0 + heading_rows, 0, ds_cstr (&str));
-
- ds_clear (&str);
- var_append_value_name (cmd->dep_var, &res->y1, &str);
- tab_text (t, 0, 1 + heading_rows, 0, ds_cstr (&str));
-
-
- tab_double (t, 1, 0 + heading_rows, 0, map_dependent_var (cmd, res, &res->y0), NULL, RC_INTEGER);
- tab_double (t, 1, 1 + heading_rows, 0, map_dependent_var (cmd, res, &res->y1), NULL, RC_INTEGER);
- ds_destroy (&str);
-
- tab_submit (t);
+ pivot_table_submit (table);
}
output_variables (const struct lr_spec *cmd,
const struct lr_result *res)
{
- int row = 0;
- const int heading_columns = 1;
- int heading_rows = 1;
- struct tab_table *t;
+ struct pivot_table *table = pivot_table_create (
+ N_("Variables in the Equation"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("B"), PIVOT_RC_OTHER,
+ N_("S.E."), PIVOT_RC_OTHER,
+ N_("Wald"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE,
+ N_("Exp(B)"), PIVOT_RC_OTHER);
+ if (cmd->print & PRINT_CI)
+ {
+ struct pivot_category *group = pivot_category_create_group__ (
+ statistics->root,
+ pivot_value_new_text_format (N_("%d%% CI for Exp(B)"),
+ cmd->confidence));
+ pivot_category_create_leaves (group, N_("Lower"), N_("Upper"));
+ }
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+ struct pivot_category *step1 = pivot_category_create_group (
+ variables->root, N_("Step 1"));
- int nc = 8;
- int nr ;
- int i = 0;
int ivar = 0;
int idx_correction = 0;
+ int i = 0;
- if (cmd->print & PRINT_CI)
- {
- nc += 2;
- heading_rows += 1;
- row++;
- }
- nr = heading_rows + cmd->n_predictor_vars;
+ int nr = cmd->n_predictor_vars;
if (cmd->constant)
nr++;
-
if (res->cats)
nr += categoricals_df_total (res->cats) + cmd->n_cat_predictors;
- t = tab_create (nc, nr);
- tab_title (t, _("Variables in the Equation"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 0, row + 1, TAB_CENTER | TAT_TITLE, _("Step 1"));
-
- tab_text (t, 2, row, TAB_CENTER | TAT_TITLE, _("B"));
- tab_text (t, 3, row, TAB_CENTER | TAT_TITLE, _("S.E."));
- tab_text (t, 4, row, TAB_CENTER | TAT_TITLE, _("Wald"));
- tab_text (t, 5, row, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 6, row, TAB_CENTER | TAT_TITLE, _("Sig."));
- tab_text (t, 7, row, TAB_CENTER | TAT_TITLE, _("Exp(B)"));
-
- if (cmd->print & PRINT_CI)
- {
- tab_joint_text_format (t, 8, 0, 9, 0,
- TAB_CENTER | TAT_TITLE, _("%d%% CI for Exp(B)"), cmd->confidence);
-
- tab_text (t, 8, row, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 9, row, TAB_CENTER | TAT_TITLE, _("Upper"));
- }
-
- for (row = heading_rows ; row < nr; ++row)
+ for (int row = 0; row < nr; row++)
{
- const int idx = row - heading_rows - idx_correction;
-
- const double b = gsl_vector_get (res->beta_hat, idx);
- const double sigma2 = gsl_matrix_get (res->hessian, idx, idx);
- const double wald = pow2 (b) / sigma2;
- const double df = 1;
+ const int idx = row - idx_correction;
+ int var_idx;
if (idx < cmd->n_predictor_vars)
- {
- tab_text (t, 1, row, TAB_LEFT | TAT_TITLE,
- var_to_string (cmd->predictor_vars[idx]));
- }
+ var_idx = pivot_category_create_leaf (
+ step1, pivot_value_new_variable (cmd->predictor_vars[idx]));
else if (i < cmd->n_cat_predictors)
{
- double wald;
- bool summary = false;
- struct string str;
const struct interaction *cat_predictors = cmd->cat_predictors[i];
- const int df = categoricals_df (res->cats, i);
-
- ds_init_empty (&str);
+ struct string str = DS_EMPTY_INITIALIZER;
interaction_to_string (cat_predictors, &str);
-
- if (ivar == 0)
+ if (ivar != 0)
+ ds_put_format (&str, "(%d)", ivar);
+ var_idx = pivot_category_create_leaf (
+ step1, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
+
+ int df = categoricals_df (res->cats, i);
+ bool summary = ivar == 0;
+ if (summary)
{
/* Calculate the Wald statistic,
which is \beta' C^-1 \beta .
gsl_linalg_cholesky_invert (subhessian);
gsl_blas_dgemv (CblasTrans, 1.0, subhessian, &vv.vector, 0, temp);
+ double wald;
gsl_blas_ddot (temp, &vv.vector, &wald);
- tab_double (t, 4, row, 0, wald, NULL, RC_OTHER);
- tab_double (t, 5, row, 0, df, NULL, RC_INTEGER);
- tab_double (t, 6, row, 0, gsl_cdf_chisq_Q (wald, df), NULL, RC_PVALUE);
+ double entries[] = { wald, df, gsl_cdf_chisq_Q (wald, df) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j + 2, var_idx,
+ pivot_value_new_number (entries[j]));
- idx_correction ++;
- summary = true;
+ idx_correction++;
gsl_matrix_free (subhessian);
gsl_vector_free (temp);
}
- else
- {
- ds_put_format (&str, "(%d)", ivar);
- }
- tab_text (t, 1, row, TAB_LEFT | TAT_TITLE, ds_cstr (&str));
if (ivar++ == df)
{
++i; /* next interaction */
ivar = 0;
}
- ds_destroy (&str);
-
if (summary)
continue;
}
else
- {
- tab_text (t, 1, row, TAB_LEFT | TAT_TITLE, _("Constant"));
- }
-
- tab_double (t, 2, row, 0, b, NULL, RC_OTHER);
- tab_double (t, 3, row, 0, sqrt (sigma2), NULL, RC_OTHER);
- tab_double (t, 4, row, 0, wald, NULL, RC_OTHER);
- tab_double (t, 5, row, 0, df, NULL, RC_INTEGER);
- tab_double (t, 6, row, 0, gsl_cdf_chisq_Q (wald, df), NULL, RC_PVALUE);
- tab_double (t, 7, row, 0, exp (b), NULL, RC_OTHER);
-
- if (cmd->print & PRINT_CI)
- {
- int last_ci = nr;
- double wc = gsl_cdf_ugaussian_Pinv (0.5 + cmd->confidence / 200.0);
- wc *= sqrt (sigma2);
-
- if (cmd->constant)
- last_ci--;
-
- if (row < last_ci)
- {
- tab_double (t, 8, row, 0, exp (b - wc), NULL, RC_OTHER);
- tab_double (t, 9, row, 0, exp (b + wc), NULL, RC_OTHER);
- }
- }
+ var_idx = pivot_category_create_leaves (step1, N_("Constant"));
+
+ double b = gsl_vector_get (res->beta_hat, idx);
+ double sigma2 = gsl_matrix_get (res->hessian, idx, idx);
+ double wald = pow2 (b) / sigma2;
+ double df = 1;
+ double wc = (gsl_cdf_ugaussian_Pinv (0.5 + cmd->confidence / 200.0)
+ * sqrt (sigma2));
+ bool show_ci = cmd->print & PRINT_CI && row < nr - cmd->constant;
+
+ double entries[] = {
+ b,
+ sqrt (sigma2),
+ wald,
+ df,
+ gsl_cdf_chisq_Q (wald, df),
+ exp (b),
+ show_ci ? exp (b - wc) : SYSMIS,
+ show_ci ? exp (b + wc) : SYSMIS,
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ if (entries[j] != SYSMIS)
+ pivot_table_put2 (table, j, var_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
output_model_summary (const struct lr_result *res,
double initial_log_likelihood, double log_likelihood)
{
- const int heading_columns = 0;
- const int heading_rows = 1;
- struct tab_table *t;
-
- const int nc = 4;
- int nr = heading_rows + 1;
- double cox;
-
- t = tab_create (nc, nr);
- tab_title (t, _("Model Summary"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Step 1"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("-2 Log likelihood"));
- tab_double (t, 1, 1, 0, -2 * log_likelihood, NULL, RC_OTHER);
-
-
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Cox & Snell R Square"));
- cox = 1.0 - exp((initial_log_likelihood - log_likelihood) * (2 / res->cc));
- tab_double (t, 2, 1, 0, cox, NULL, RC_OTHER);
-
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Nagelkerke R Square"));
- tab_double (t, 3, 1, 0, cox / ( 1.0 - exp(initial_log_likelihood * (2 / res->cc))), NULL, RC_OTHER);
-
-
- tab_submit (t);
+ struct pivot_table *table = pivot_table_create (N_("Model Summary"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("-2 Log likelihood"), PIVOT_RC_OTHER,
+ N_("Cox & Snell R Square"), PIVOT_RC_OTHER,
+ N_("Nagelkerke R Square"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *step = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Step"));
+ step->root->show_label = true;
+ pivot_category_create_leaf (step->root, pivot_value_new_integer (1));
+
+ double cox = (1.0 - exp ((initial_log_likelihood - log_likelihood)
+ * (2 / res->cc)));
+ double entries[] = {
+ -2 * log_likelihood,
+ cox,
+ cox / ( 1.0 - exp(initial_log_likelihood * (2 / res->cc)))
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, 0, pivot_value_new_number (entries[i]));
+
+ pivot_table_submit (table);
}
/* Show the case processing summary box */
static void
case_processing_summary (const struct lr_result *res)
{
- const int heading_columns = 1;
- const int heading_rows = 1;
- struct tab_table *t;
-
- const int nc = 3;
- const int nr = heading_rows + 3;
- casenumber total;
-
- t = tab_create (nc, nr);
- tab_title (t, _("Case Processing Summary"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
+ struct pivot_table *table = pivot_table_create (
+ N_("Case Processing Summary"));
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Unweighted Cases"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Percent"));
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Unweighted Cases"),
+ N_("Included in Analysis"), N_("Missing Cases"), N_("Total"));
+ cases->root->show_label = true;
-
- tab_text (t, 0, 1, TAB_LEFT | TAT_TITLE, _("Included in Analysis"));
- tab_text (t, 0, 2, TAB_LEFT | TAT_TITLE, _("Missing Cases"));
- tab_text (t, 0, 3, TAB_LEFT | TAT_TITLE, _("Total"));
-
- tab_double (t, 1, 1, 0, res->n_nonmissing, NULL, RC_INTEGER);
- tab_double (t, 1, 2, 0, res->n_missing, NULL, RC_INTEGER);
-
- total = res->n_nonmissing + res->n_missing;
- tab_double (t, 1, 3, 0, total , NULL, RC_INTEGER);
-
- tab_double (t, 2, 1, 0, 100 * res->n_nonmissing / (double) total, NULL, RC_OTHER);
- tab_double (t, 2, 2, 0, 100 * res->n_missing / (double) total, NULL, RC_OTHER);
- tab_double (t, 2, 3, 0, 100 * total / (double) total, NULL, RC_OTHER);
-
- tab_submit (t);
+ double total = res->n_nonmissing + res->n_missing;
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, res->n_nonmissing },
+ { 0, 1, res->n_missing },
+ { 0, 2, total },
+ { 1, 0, 100.0 * res->n_nonmissing / total },
+ { 1, 1, 100.0 * res->n_missing / total },
+ { 1, 2, 100.0 },
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, entries[i].stat_idx, entries[i].case_idx,
+ pivot_value_new_number (entries[i].x));
+
+ pivot_table_submit (table);
}
static void
output_categories (const struct lr_spec *cmd, const struct lr_result *res)
{
- const struct fmt_spec *wfmt =
- cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
-
- int cumulative_df;
- int i = 0;
- const int heading_columns = 2;
- const int heading_rows = 2;
- struct tab_table *t;
-
- int nc ;
- int nr ;
-
- int v;
- int r = 0;
+ struct pivot_table *table = pivot_table_create (
+ N_("Categorical Variables' Codings"));
+ pivot_table_set_weight_var (table, dict_get_weight (cmd->dict));
int max_df = 0;
int total_cats = 0;
- for (i = 0; i < cmd->n_cat_predictors; ++i)
+ for (int i = 0; i < cmd->n_cat_predictors; ++i)
{
size_t n = categoricals_n_count (res->cats, i);
size_t df = categoricals_df (res->cats, i);
total_cats += n;
}
- nc = heading_columns + 1 + max_df;
- nr = heading_rows + total_cats;
-
- t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
-
- tab_title (t, _("Categorical Variables' Codings"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-
- tab_text (t, heading_columns, 1, TAB_CENTER | TAT_TITLE, _("Frequency"));
-
- tab_joint_text_format (t, heading_columns + 1, 0, nc - 1, 0,
- TAB_CENTER | TAT_TITLE, _("Parameter coding"));
-
-
- for (i = 0; i < max_df; ++i)
- {
- int c = heading_columns + 1 + i;
- tab_text_format (t, c, 1, TAB_CENTER | TAT_TITLE, _("(%d)"), i + 1);
- }
-
- cumulative_df = 0;
- for (v = 0; v < cmd->n_cat_predictors; ++v)
+ struct pivot_dimension *codings = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Codings"),
+ N_("Frequency"), PIVOT_RC_COUNT);
+ struct pivot_category *coding_group = pivot_category_create_group (
+ codings->root, N_("Parameter coding"));
+ for (int i = 0; i < max_df; ++i)
+ pivot_category_create_leaf_rc (
+ coding_group,
+ pivot_value_new_user_text_nocopy (xasprintf ("(%d)", i + 1)),
+ PIVOT_RC_INTEGER);
+
+ struct pivot_dimension *categories = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Categories"));
+
+ int cumulative_df = 0;
+ for (int v = 0; v < cmd->n_cat_predictors; ++v)
{
int cat;
const struct interaction *cat_predictors = cmd->cat_predictors[v];
- int df = categoricals_df (res->cats, v);
- struct string str;
- ds_init_empty (&str);
+ int df = categoricals_df (res->cats, v);
+ struct string str = DS_EMPTY_INITIALIZER;
interaction_to_string (cat_predictors, &str);
-
- tab_text (t, 0, heading_rows + r, TAB_LEFT | TAT_TITLE, ds_cstr (&str) );
-
- ds_destroy (&str);
+ struct pivot_category *var_group = pivot_category_create_group__ (
+ categories->root,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
for (cat = 0; cat < categoricals_n_count (res->cats, v) ; ++cat)
{
- struct string str;
- const struct ccase *c = categoricals_get_case_by_category_real (res->cats, v, cat);
- const double *freq = categoricals_get_user_data_by_category_real (res->cats, v, cat);
-
- int x;
- ds_init_empty (&str);
-
- for (x = 0; x < cat_predictors->n_vars; ++x)
+ const struct ccase *c = categoricals_get_case_by_category_real (
+ res->cats, v, cat);
+ struct string label = DS_EMPTY_INITIALIZER;
+ for (int x = 0; x < cat_predictors->n_vars; ++x)
{
- const union value *val = case_data (c, cat_predictors->vars[x]);
- var_append_value_name (cat_predictors->vars[x], val, &str);
+ if (!ds_is_empty (&label))
+ ds_put_byte (&label, ' ');
- if (x < cat_predictors->n_vars - 1)
- ds_put_cstr (&str, " ");
+ const union value *val = case_data (c, cat_predictors->vars[x]);
+ var_append_value_name (cat_predictors->vars[x], val, &label);
}
+ int cat_idx = pivot_category_create_leaf (
+ var_group,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&label)));
- tab_text (t, 1, heading_rows + r, 0, ds_cstr (&str));
- ds_destroy (&str);
- tab_double (t, 2, heading_rows + r, 0, *freq, NULL, RC_WEIGHT);
+ double *freq = categoricals_get_user_data_by_category_real (
+ res->cats, v, cat);
+ pivot_table_put2 (table, 0, cat_idx, pivot_value_new_number (*freq));
- for (x = 0; x < df; ++x)
- {
- tab_double (t, heading_columns + 1 + x, heading_rows + r, 0, (cat == x), NULL, RC_INTEGER);
- }
- ++r;
+ for (int x = 0; x < df; ++x)
+ pivot_table_put2 (table, x + 1, cat_idx,
+ pivot_value_new_number (cat == x));
}
cumulative_df += df;
}
- tab_submit (t);
-
+ pivot_table_submit (table);
}
+static void
+create_classification_dimension (const struct lr_spec *cmd,
+ const struct lr_result *res,
+ struct pivot_table *table,
+ enum pivot_axis_type axis_type,
+ const char *label, const char *total)
+{
+ struct pivot_dimension *d = pivot_dimension_create (
+ table, axis_type, label);
+ d->root->show_label = true;
+ struct pivot_category *pred_group = pivot_category_create_group__ (
+ d->root, pivot_value_new_variable (cmd->dep_var));
+ for (int i = 0; i < 2; i++)
+ {
+ const union value *y = i ? &res->y1 : &res->y0;
+ pivot_category_create_leaf_rc (
+ pred_group, pivot_value_new_var_value (cmd->dep_var, y),
+ PIVOT_RC_COUNT);
+ }
+ pivot_category_create_leaves (d->root, total, PIVOT_RC_PERCENT);
+}
static void
output_classification_table (const struct lr_spec *cmd, const struct lr_result *res)
{
- const struct fmt_spec *wfmt =
- cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
-
- const int heading_columns = 3;
- const int heading_rows = 3;
-
- struct string sv0, sv1;
-
- const int nc = heading_columns + 3;
- const int nr = heading_rows + 3;
-
- struct tab_table *t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
-
- ds_init_empty (&sv0);
- ds_init_empty (&sv1);
-
- tab_title (t, _("Classification Table"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, -1, 0, 0, nc - 1, nr - 1);
- tab_box (t, -1, -1, -1, TAL_1, heading_columns, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- tab_text (t, 0, heading_rows, TAB_CENTER | TAT_TITLE, _("Step 1"));
-
-
- tab_joint_text (t, heading_columns, 0, nc - 1, 0,
- TAB_CENTER | TAT_TITLE, _("Predicted"));
-
- tab_joint_text (t, heading_columns, 1, heading_columns + 1, 1,
- 0, var_to_string (cmd->dep_var) );
+ struct pivot_table *table = pivot_table_create (N_("Classification Table"));
+ pivot_table_set_weight_var (table, cmd->wv);
- tab_joint_text (t, 1, 2, 2, 2,
- TAB_LEFT | TAT_TITLE, _("Observed"));
+ create_classification_dimension (cmd, res, table, PIVOT_AXIS_COLUMN,
+ N_("Predicted"), N_("Percentage Correct"));
+ create_classification_dimension (cmd, res, table, PIVOT_AXIS_ROW,
+ N_("Observed"), N_("Overall Percentage"));
- tab_text (t, 1, 3, TAB_LEFT, var_to_string (cmd->dep_var) );
-
-
- tab_joint_text (t, nc - 1, 1, nc - 1, 2,
- TAB_CENTER | TAT_TITLE, _("Percentage\nCorrect"));
-
-
- tab_joint_text (t, 1, nr - 1, 2, nr - 1,
- TAB_LEFT | TAT_TITLE, _("Overall Percentage"));
-
-
- tab_hline (t, TAL_1, 1, nc - 1, nr - 1);
-
- var_append_value_name (cmd->dep_var, &res->y0, &sv0);
- var_append_value_name (cmd->dep_var, &res->y1, &sv1);
-
- tab_text (t, 2, heading_rows, TAB_LEFT, ds_cstr (&sv0));
- tab_text (t, 2, heading_rows + 1, TAB_LEFT, ds_cstr (&sv1));
-
- tab_text (t, heading_columns, 2, 0, ds_cstr (&sv0));
- tab_text (t, heading_columns + 1, 2, 0, ds_cstr (&sv1));
-
- ds_destroy (&sv0);
- ds_destroy (&sv1);
-
- tab_double (t, heading_columns, 3, 0, res->tn, NULL, RC_WEIGHT);
- tab_double (t, heading_columns + 1, 4, 0, res->tp, NULL, RC_WEIGHT);
-
- tab_double (t, heading_columns + 1, 3, 0, res->fp, NULL, RC_WEIGHT);
- tab_double (t, heading_columns, 4, 0, res->fn, NULL, RC_WEIGHT);
-
- tab_double (t, heading_columns + 2, 3, 0, 100 * res->tn / (res->tn + res->fp), NULL, RC_OTHER);
- tab_double (t, heading_columns + 2, 4, 0, 100 * res->tp / (res->tp + res->fn), NULL, RC_OTHER);
-
- tab_double (t, heading_columns + 2, 5, 0,
- 100 * (res->tp + res->tn) / (res->tp + res->tn + res->fp + res->fn), NULL, RC_OTHER);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Step"), N_("Step 1"));
+ struct entry
+ {
+ int pred_idx;
+ int obs_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, res->tn },
+ { 0, 1, res->fn },
+ { 1, 0, res->fp },
+ { 1, 1, res->tp },
+ { 2, 0, 100 * res->tn / (res->tn + res->fp) },
+ { 2, 1, 100 * res->tp / (res->tp + res->fn) },
+ { 2, 2,
+ 100 * (res->tp + res->tn) / (res->tp + res->tn + res->fp + res->fn)},
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put3 (table, e->pred_idx, e->obs_idx, 0,
+ pivot_value_new_number (e->x));
+ }
- tab_submit (t);
+ pivot_table_submit (table);
}
#include "libpspp/cast.h"
#include "libpspp/misc.h"
#include "math/sort.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
+
+#include "gettext.h"
+#define N_(msgid) msgid
+#define _(msgid) gettext (msgid)
/* Calculates the adjustment necessary for tie compensation */
static void
double z;
};
-static void show_ranks_box (const struct n_sample_test *nst, const struct mw *mw);
-static void show_statistics_box (const struct n_sample_test *nst, const struct mw *mw, bool exact);
+static void show_ranks_box (const struct n_sample_test *, const struct mw *);
+static void show_statistics_box (const struct n_sample_test *,
+ const struct mw *);
struct casereader *input,
enum mv_class exclude,
const struct npar_test *test,
- bool exact,
+ bool exact UNUSED,
double timer UNUSED)
{
int i;
casereader_destroy (input);
show_ranks_box (nst, mw);
- show_statistics_box (nst, mw, exact);
+ show_statistics_box (nst, mw);
free (mw);
}
-
\f
-
-#include "gettext.h"
-#define _(msgid) gettext (msgid)
-
static void
show_ranks_box (const struct n_sample_test *nst, const struct mw *mwv)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 2;
- struct tab_table *table =
- tab_create (row_headers + 7, column_headers + nst->n_vars);
-
- struct string g1str, g2str;;
- ds_init_empty (&g1str);
- var_append_value_name (nst->indep_var, &nst->val1, &g1str);
-
- ds_init_empty (&g2str);
- var_append_value_name (nst->indep_var, &nst->val2, &g2str);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Ranks"));
-
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- tab_hline (table, TAL_1, row_headers, tab_nc (table) -1, 1);
-
- tab_text (table, 1, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g1str));
- tab_text (table, 2, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g2str));
- tab_text (table, 3, 1, TAT_TITLE | TAB_CENTER, _("Total"));
- tab_joint_text (table, 1, 0, 3, 0,
- TAT_TITLE | TAB_CENTER, _("N"));
- tab_vline (table, TAL_2, 4, 0, tab_nr (table) - 1);
-
- tab_text (table, 4, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g1str));
- tab_text (table, 5, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g2str));
- tab_joint_text (table, 4, 0, 5, 0,
- TAT_TITLE | TAB_CENTER, _("Mean Rank"));
- tab_vline (table, TAL_2, 6, 0, tab_nr (table) - 1);
-
- tab_text (table, 6, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g1str));
- tab_text (table, 7, 1, TAT_TITLE | TAB_CENTER, ds_cstr (&g2str));
- tab_joint_text (table, 6, 0, 7, 0,
- TAT_TITLE | TAB_CENTER, _("Sum of Ranks"));
-
- ds_destroy (&g1str);
- ds_destroy (&g2str);
-
- for (i = 0 ; i < nst->n_vars ; ++i)
+ struct pivot_table *table = pivot_table_create (N_("Ranks"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean Rank"), PIVOT_RC_OTHER,
+ N_("Sum of Ranks"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *indep = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (nst->indep_var));
+ pivot_category_create_leaf (indep->root,
+ pivot_value_new_var_value (nst->indep_var,
+ &nst->val1));
+ pivot_category_create_leaf (indep->root,
+ pivot_value_new_var_value (nst->indep_var,
+ &nst->val2));
+ pivot_category_create_leaves (indep->root, N_("Total"));
+
+ struct pivot_dimension *dep = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (size_t i = 0 ; i < nst->n_vars ; ++i)
{
const struct mw *mw = &mwv[i];
- tab_text (table, 0, column_headers + i, TAT_TITLE,
- var_to_string (nst->vars[i]));
-
- tab_double (table, 1, column_headers + i, 0,
- mw->n[0], NULL, RC_OTHER);
-
- tab_double (table, 2, column_headers + i, 0,
- mw->n[1], NULL, RC_OTHER);
-
- tab_double (table, 3, column_headers + i, 0,
- mw->n[1] + mw->n[0], NULL, RC_OTHER);
- /* Mean Ranks */
- tab_double (table, 4, column_headers + i, 0,
- mw->rank_sum[0] / mw->n[0], NULL, RC_OTHER);
-
- tab_double (table, 5, column_headers + i, 0,
- mw->rank_sum[1] / mw->n[1], NULL, RC_OTHER);
-
- /* Sum of Ranks */
- tab_double (table, 6, column_headers + i, 0,
- mw->rank_sum[0], NULL, RC_OTHER);
-
- tab_double (table, 7, column_headers + i, 0,
- mw->rank_sum[1], NULL, RC_OTHER);
+ int dep_idx = pivot_category_create_leaf (
+ dep->root, pivot_value_new_variable (nst->vars[i]));
+
+ struct entry
+ {
+ int stat_idx;
+ int indep_idx;
+ double x;
+ }
+ entries[] = {
+ /* N. */
+ { 0, 0, mw->n[0] },
+ { 0, 1, mw->n[1] },
+ { 0, 2, mw->n[0] + mw->n[1] },
+
+ /* Mean Rank. */
+ { 1, 0, mw->rank_sum[0] / mw->n[0] },
+ { 1, 1, mw->rank_sum[1] / mw->n[1] },
+
+ /* Sum of Ranks. */
+ { 2, 0, mw->rank_sum[0] },
+ { 2, 1, mw->rank_sum[1] },
+ };
+
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ const struct entry *e = &entries[j];
+ pivot_table_put3 (table, e->stat_idx, e->indep_idx, dep_idx,
+ pivot_value_new_number (e->x));
+ }
}
- tab_submit (table);
+ pivot_table_submit (table);
}
static void
-show_statistics_box (const struct n_sample_test *nst, const struct mw *mwv, bool exact)
+show_statistics_box (const struct n_sample_test *nst, const struct mw *mwv)
{
- int i;
- const int row_headers = 1;
- const int column_headers = 1;
- struct tab_table *table =
- tab_create (row_headers + (exact ? 6 : 4), column_headers + nst->n_vars);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
- tab_title (table, _("Test Statistics"));
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ _("Mann-Whitney U"), PIVOT_RC_OTHER,
+ _("Wilcoxon W"), PIVOT_RC_OTHER,
+ _("Z"), PIVOT_RC_OTHER,
+ _("Asymp. Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
- /* Vertical lines inside the box */
- tab_box (table, 1, 0, -1, TAL_1,
- row_headers, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- /* Box around the table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- tab_text (table, 1, 0, TAT_TITLE | TAB_CENTER, _("Mann-Whitney U"));
- tab_text (table, 2, 0, TAT_TITLE | TAB_CENTER, _("Wilcoxon W"));
- tab_text (table, 3, 0, TAT_TITLE | TAB_CENTER, _("Z"));
- tab_text (table, 4, 0, TAT_TITLE | TAB_CENTER, _("Asymp. Sig. (2-tailed)"));
-
- if (exact)
- {
- tab_text (table, 5, 0, TAT_TITLE | TAB_CENTER, _("Exact Sig. (2-tailed)"));
- tab_text (table, 6, 0, TAT_TITLE | TAB_CENTER, _("Point Probability"));
- }
-
- for (i = 0 ; i < nst->n_vars ; ++i)
+ for (size_t i = 0 ; i < nst->n_vars ; ++i)
{
const struct mw *mw = &mwv[i];
- tab_text (table, 0, column_headers + i, TAT_TITLE,
- var_to_string (nst->vars[i]));
-
- tab_double (table, 1, column_headers + i, 0,
- mw->u, NULL, RC_OTHER);
-
- tab_double (table, 2, column_headers + i, 0,
- mw->w, NULL, RC_OTHER);
-
- tab_double (table, 3, column_headers + i, 0,
- mw->z, NULL, RC_OTHER);
-
- tab_double (table, 4, column_headers + i, 0,
- 2.0 * gsl_cdf_ugaussian_P (mw->z), NULL, RC_PVALUE);
+ int row = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (nst->vars[i]));
+
+ double entries[] = {
+ mw->u,
+ mw->w,
+ mw->z,
+ 2.0 * gsl_cdf_ugaussian_P (mw->z),
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, row, pivot_value_new_number (entries[i]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "data/variable.h"
#include "language/stats/npar.h"
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "libpspp/message.h"
#include "gl/minmax.h"
#include "data/value.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
free (mc);
}
+static char *
+make_pair_name (const variable_pair *pair)
+{
+ return xasprintf ("%s & %s", var_to_string ((*pair)[0]),
+ var_to_string ((*pair)[1]));
+}
static void
output_freq_table (variable_pair *vp,
const struct mcnemar *param,
const struct dictionary *dict)
{
- const int header_rows = 2;
- const int header_cols = 1;
-
- struct tab_table *table = tab_create (header_cols + 2, header_rows + 2);
-
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
-
- struct string pair_name;
- struct string val1str ;
- struct string val0str ;
-
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- ds_init_empty (&val0str);
- ds_init_empty (&val1str);
-
- var_append_value_name ((*vp)[0], ¶m->val0, &val0str);
- var_append_value_name ((*vp)[1], ¶m->val1, &val1str);
-
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " & ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
-
- tab_title (table, "%s", ds_cstr (&pair_name));
-
- ds_destroy (&pair_name);
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_user_text_nocopy (make_pair_name (vp)));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- tab_headers (table, header_cols, 0, header_rows, 0);
-
- /* Vertical lines inside the box */
- tab_box (table, 0, 0, -1, TAL_1,
- 1, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_vline (table, TAL_2, header_cols, 0, tab_nr (table) - 1);
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, header_rows);
-
- tab_text (table, 0, 0, TAB_CENTER, var_to_string ((*vp)[0]));
-
- tab_joint_text (table, 1, 0, 2, 0, TAB_CENTER, var_to_string ((*vp)[1]));
- tab_hline (table, TAL_1, 1, tab_nc (table) - 1, 1);
-
-
- tab_text (table, 0, header_rows + 0, TAB_LEFT, ds_cstr (&val0str));
- tab_text (table, 0, header_rows + 1, TAB_LEFT, ds_cstr (&val1str));
-
- tab_text (table, header_cols + 0, 1, TAB_LEFT, ds_cstr (&val0str));
- tab_text (table, header_cols + 1, 1, TAB_LEFT, ds_cstr (&val1str));
-
- tab_double (table, header_cols + 0, header_rows + 0, TAB_RIGHT, param->n00, NULL, RC_WEIGHT);
- tab_double (table, header_cols + 0, header_rows + 1, TAB_RIGHT, param->n01, NULL, RC_WEIGHT);
- tab_double (table, header_cols + 1, header_rows + 0, TAB_RIGHT, param->n10, NULL, RC_WEIGHT);
- tab_double (table, header_cols + 1, header_rows + 1, TAB_RIGHT, param->n11, NULL, RC_WEIGHT);
+ struct pivot_dimension *vars[2];
+ for (int i = 0; i < 2; i++)
+ {
+ vars[i] = pivot_dimension_create__ (
+ table, i ? PIVOT_AXIS_COLUMN : PIVOT_AXIS_ROW,
+ pivot_value_new_variable ((*vp)[i]));
+ vars[i]->root->show_label = true;
+
+ for (int j = 0; j < 2; j++)
+ {
+ const union value *val = j ? ¶m->val1 : ¶m->val0;
+ pivot_category_create_leaf_rc (
+ vars[i]->root, pivot_value_new_var_value ((*vp)[0], val),
+ PIVOT_RC_COUNT);
+ }
+ }
- tab_submit (table);
+ struct entry
+ {
+ int idx0;
+ int idx1;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, param->n00 },
+ { 1, 0, param->n01 },
+ { 0, 1, param->n10 },
+ { 1, 1, param->n11 },
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put2 (table, e->idx0, e->idx1,
+ pivot_value_new_number (e->x));
+ }
- ds_destroy (&val0str);
- ds_destroy (&val1str);
+ pivot_table_submit (table);
}
-
static void
output_statistics_table (const struct two_sample_test *t2s,
const struct mcnemar *mc,
const struct dictionary *dict)
{
- int i;
-
- struct tab_table *table = tab_create (5, t2s->n_pairs + 1);
-
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- tab_title (table, _("Test Statistics"));
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, 0, 1, 0, 1);
-
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, 1);
- tab_vline (table, TAL_2, 1, 0, tab_nr (table) - 1);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Exact Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Exact Sig. (1-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Point Probability"), PIVOT_RC_OTHER);
- /* Vertical lines inside the box */
- tab_box (table, -1, -1, -1, TAL_1,
- 0, 0,
- tab_nc (table) - 1, tab_nr (table) - 1);
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Pairs"));
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1,
- tab_nr (table) - 1);
-
- tab_text (table, 1, 0, TAT_TITLE | TAB_CENTER,
- _("N"));
-
- tab_text (table, 2, 0, TAT_TITLE | TAB_CENTER,
- _("Exact Sig. (2-tailed)"));
-
- tab_text (table, 3, 0, TAT_TITLE | TAB_CENTER,
- _("Exact Sig. (1-tailed)"));
-
- tab_text (table, 4, 0, TAT_TITLE | TAB_CENTER,
- _("Point Probability"));
-
- for (i = 0 ; i < t2s->n_pairs; ++i)
+ for (size_t i = 0 ; i < t2s->n_pairs; ++i)
{
- double sig;
variable_pair *vp = &t2s->pairs[i];
-
- struct string pair_name;
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " & ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
-
- tab_text (table, 0, 1 + i, TAB_LEFT, ds_cstr (&pair_name));
- ds_destroy (&pair_name);
-
- tab_double (table, 1, 1 + i, TAB_RIGHT, mc[i].n00 + mc[i].n01 + mc[i].n10 + mc[i].n11, NULL, RC_WEIGHT);
-
- sig = gsl_cdf_binomial_P (mc[i].n01, 0.5, mc[i].n01 + mc[i].n10);
-
- tab_double (table, 2, 1 + i, TAB_RIGHT, 2 * sig, NULL, RC_PVALUE);
- tab_double (table, 3, 1 + i, TAB_RIGHT, sig, NULL, RC_PVALUE);
-
- tab_double (table, 4, 1 + i, TAB_RIGHT, gsl_ran_binomial_pdf (mc[i].n01, 0.5, mc[i].n01 + mc[i].n10),
- NULL, RC_OTHER);
+ int pair_idx = pivot_category_create_leaf (
+ pairs->root, pivot_value_new_user_text_nocopy (make_pair_name (vp)));
+
+ double n = mc[i].n00 + mc[i].n01 + mc[i].n10 + mc[i].n11;
+ double sig = gsl_cdf_binomial_P (mc[i].n01, 0.5, mc[i].n01 + mc[i].n10);
+ double point = gsl_ran_binomial_pdf (mc[i].n01, 0.5,
+ mc[i].n01 + mc[i].n10);
+ double entries[] = { n, 2.0 * sig, sig, point };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, pair_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "math/interaction.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include <math.h>
return false;
}
-static void output_case_processing_summary (const struct mtable *);
+static void output_case_processing_summary (const struct mtable *,
+ const struct variable *wv);
static void output_report (const struct means *, int, const struct mtable *);
int i;
const struct mtable *table = &cmd->table[t];
- output_case_processing_summary (table);
+ output_case_processing_summary (table, wv);
for (i = 0; i < table->n_layers; ++i)
{
static void
-output_case_processing_summary (const struct mtable *table)
+output_case_processing_summary (const struct mtable *mt,
+ const struct variable *wv)
{
- int i, v;
- const int heading_columns = 1;
- const int heading_rows = 3;
- struct tab_table *t;
-
- const int nr = heading_rows + table->n_layers * table->n_dep_vars;
- const int nc = 7;
-
- t = tab_create (nc, nr);
- tab_title (t, _("Case Processing Summary"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-
- tab_joint_text (t, heading_columns, 0,
- nc - 1, 0, TAB_CENTER | TAT_TITLE, _("Cases"));
-
- tab_joint_text (t, 1, 1, 2, 1, TAB_CENTER | TAT_TITLE, _("Included"));
- tab_joint_text (t, 3, 1, 4, 1, TAB_CENTER | TAT_TITLE, _("Excluded"));
- tab_joint_text (t, 5, 1, 6, 1, TAB_CENTER | TAT_TITLE, _("Total"));
+ struct pivot_table *table = pivot_table_create (
+ N_("Case Processing Summary"));
+ pivot_table_set_weight_var (table, wv);
- tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
- tab_hline (t, TAL_1, heading_columns, nc - 1, 2);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Cases"),
+ N_("Included"), N_("Excluded"), N_("Total"))
+ ->root->show_label = true;
+ struct pivot_dimension *tables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Tables"));
- for (i = 0; i < 3; ++i)
- {
- tab_text (t, heading_columns + i * 2, 2, TAB_CENTER | TAT_TITLE,
- _("N"));
- tab_text (t, heading_columns + i * 2 + 1, 2, TAB_CENTER | TAT_TITLE,
- _("Percent"));
- }
-
- for (v = 0; v < table->n_dep_vars; ++v)
+ for (size_t v = 0; v < mt->n_dep_vars; ++v)
{
- const struct variable *var = table->dep_vars[v];
- const char *dv_name = var_to_string (var);
- for (i = 0; i < table->n_layers; ++i)
+ const struct variable *var = mt->dep_vars[v];
+ for (size_t i = 0; i < mt->n_layers; ++i)
{
- const int row = v * table->n_layers + i;
- const struct interaction *iact = table->interactions[i];
- casenumber n_total;
-
- struct string str;
- ds_init_cstr (&str, dv_name);
- ds_put_cstr (&str, ": ");
+ const int row = v * mt->n_layers + i;
+ const struct interaction *iact = mt->interactions[i];
+ struct string str = DS_EMPTY_INITIALIZER;
+ ds_put_format (&str, "%s: ", var_to_string (var));
interaction_to_string (iact, &str);
-
- tab_text (t, 0, row + heading_rows,
- TAB_LEFT | TAT_TITLE, ds_cstr (&str));
-
-
- n_total = table->summary[row].missing +
- table->summary[row].non_missing;
-
- tab_double (t, 1, row + heading_rows,
- 0, table->summary[row].non_missing, NULL, RC_INTEGER);
-
- tab_text_format (t, 2, row + heading_rows,
- 0, _("%g%%"),
- table->summary[row].non_missing / (double) n_total * 100.0);
-
-
- tab_double (t, 3, row + heading_rows,
- 0, table->summary[row].missing, NULL, RC_INTEGER);
-
-
- tab_text_format (t, 4, row + heading_rows,
- 0, _("%g%%"),
- table->summary[row].missing / (double) n_total * 100.0);
-
-
- tab_double (t, 5, row + heading_rows,
- 0, table->summary[row].missing +
- table->summary[row].non_missing, NULL, RC_INTEGER);
-
- tab_text_format (t, 6, row + heading_rows,
- 0, _("%g%%"),
- n_total / (double) n_total * 100.0);
-
-
- ds_destroy (&str);
+ int table_idx = pivot_category_create_leaf (
+ tables->root, pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&str)));
+
+ const struct summary *s = &mt->summary[row];
+ double n_total = s->missing + s->non_missing;
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] =
+ {
+ { 0, 0, s->non_missing },
+ { 1, 0, s->non_missing / n_total * 100.0 },
+ { 0, 1, s->missing },
+ { 1, 1, s->missing / n_total * 100.0 },
+ { 0, 2, n_total },
+ { 1, 2, 100.0 },
+ };
+
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ const struct entry *e = &entries[j];
+ pivot_table_put3 (table, e->stat_idx, e->case_idx, table_idx,
+ pivot_value_new_number (e->x));
+ }
}
}
- tab_submit (t);
+ pivot_table_submit (table);
}
-
static void
-output_report (const struct means *cmd, int iact_idx,
- const struct mtable *table)
+create_interaction_dimensions (struct pivot_table *table,
+ const struct categoricals *cats,
+ const struct interaction *iact)
{
- int grp;
- int i;
-
- const struct interaction *iact = table->interactions[iact_idx];
-
- const int heading_columns = 1 + iact->n_vars;
- const int heading_rows = 1;
- struct tab_table *t;
-
- const int n_cats = categoricals_n_count (table->cats, iact_idx);
-
- const int nr = n_cats * table->n_dep_vars + heading_rows;
-
- const int nc = heading_columns + cmd->n_cells;
-
- t = tab_create (nc, nr);
- tab_title (t, _("Report"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
- tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
- for (i = 0; i < iact->n_vars; ++i)
- {
- tab_text (t, 1 + i, 0, TAB_CENTER | TAT_TITLE,
- var_to_string (iact->vars[i]));
- }
-
- for (i = 0; i < cmd->n_cells; ++i)
+ for (size_t i = iact->n_vars; i-- > 0; )
{
- tab_text (t, heading_columns + i, 0,
- TAB_CENTER | TAT_TITLE,
- gettext (cell_spec[cmd->cells[i]].title));
+ const struct variable *var = iact->vars[i];
+ struct pivot_dimension *d = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (var));
+ d->root->show_label = true;
+
+ size_t n;
+ union value *values = categoricals_get_var_values (cats, var, &n);
+ for (size_t j = 0; j < n; j++)
+ pivot_category_create_leaf (
+ d->root, pivot_value_new_var_value (var, &values[j]));
}
+}
+static void
+output_report (const struct means *cmd, int iact_idx,
+ const struct mtable *mt)
+{
+ struct pivot_table *table = pivot_table_create (N_("Report"));
+ table->omit_empty = true;
- for (i = 0; i < n_cats; ++i)
- {
- int v, dv;
- const struct ccase *c =
- categoricals_get_case_by_category_real (table->cats, iact_idx, i);
-
- for (dv = 0; dv < table->n_dep_vars; ++dv)
- {
- tab_text (t, 0,
- heading_rows + dv * n_cats,
- TAB_RIGHT | TAT_TITLE,
- var_to_string (table->dep_vars[dv])
- );
-
- if ( dv > 0)
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows + dv * n_cats);
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ for (int i = 0; i < cmd->n_cells; ++i)
+ pivot_category_create_leaf (
+ statistics->root, pivot_value_new_text (cell_spec[cmd->cells[i]].title));
- for (v = 0; v < iact->n_vars; ++v)
- {
- const struct variable *var = iact->vars[v];
- const union value *val = case_data (c, var);
- struct string str;
- ds_init_empty (&str);
- var_append_value_name (var, val, &str);
+ const struct interaction *iact = mt->interactions[iact_idx];
+ create_interaction_dimensions (table, mt->cats, iact);
- tab_text (t, 1 + v, heading_rows + dv * n_cats + i,
- TAB_RIGHT | TAT_TITLE, ds_cstr (&str));
+ struct pivot_dimension *dep_dim = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- ds_destroy (&str);
- }
- }
- }
+ size_t *indexes = xnmalloc (table->n_dimensions, sizeof *indexes);
- for (grp = 0; grp < n_cats; ++grp)
+ size_t n_cats = categoricals_n_count (mt->cats, iact_idx);
+ for (size_t v = 0; v < mt->n_dep_vars; ++v)
{
- int dv;
- struct per_cat_data *per_cat_data =
- categoricals_get_user_data_by_category_real (table->cats, iact_idx, grp);
-
- for (dv = 0; dv < table->n_dep_vars; ++dv)
- {
- const struct per_var_data *pvd = &per_cat_data->pvd[dv];
- for (i = 0; i < cmd->n_cells; ++i)
- {
- const int csi = cmd->cells[i];
- const struct cell_spec *cs = &cell_spec[csi];
-
- double result = cs->sd (pvd, pvd->cell_stats[i]);
-
- tab_double (t, heading_columns + i,
- heading_rows + grp + dv * n_cats,
- 0, result, NULL, RC_OTHER);
- }
- }
+ indexes[table->n_dimensions - 1] = pivot_category_create_leaf (
+ dep_dim->root, pivot_value_new_variable (mt->dep_vars[v]));
+
+ for (size_t i = 0; i < n_cats; ++i)
+ {
+ for (size_t j = 0; j < iact->n_vars; j++)
+ {
+ int idx = categoricals_get_value_index_by_category_real (
+ mt->cats, iact_idx, i, j);
+ indexes[table->n_dimensions - 2 - j] = idx;
+ }
+
+ struct per_cat_data *per_cat_data
+ = categoricals_get_user_data_by_category_real (
+ mt->cats, iact_idx, i);
+
+ const struct per_var_data *pvd = &per_cat_data->pvd[v];
+ for (int stat_idx = 0; stat_idx < cmd->n_cells; ++stat_idx)
+ {
+ indexes[0] = stat_idx;
+ const int csi = cmd->cells[stat_idx];
+ const struct cell_spec *cs = &cell_spec[csi];
+
+ double result = cs->sd (pvd, pvd->cell_stats[stat_idx]);
+ pivot_table_put (table, indexes, table->n_dimensions,
+ pivot_value_new_number (result));
+ }
+ }
}
+ free (indexes);
- tab_submit (t);
+ pivot_table_submit (table);
}
+
#include "libpspp/str.h"
#include "libpspp/misc.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static void
show_frequencies (const struct n_sample_test *nst, const struct results *results, int n_vals, const struct dictionary *dict)
{
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- int i;
- int v;
-
- const int row_headers = 2;
- const int column_headers = 2;
- const int nc = row_headers + n_vals;
- const int nr = column_headers + nst->n_vars * 2;
-
- struct tab_table *table = tab_create (nc, nr);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Frequencies"));
-
- /* Box around the table and vertical lines inside*/
- tab_box (table, TAL_2, TAL_2, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- tab_joint_text (table,
- row_headers, 0, row_headers + n_vals - 1, 0,
- TAT_TITLE | TAB_CENTER, var_to_string (nst->indep_var));
-
-
- tab_hline (table, TAL_1, row_headers, tab_nc (table) - 1, 1);
-
-
- for (i = 0; i < n_vals; ++i)
- {
- const struct results *rs = results + 0;
- struct string label;
- ds_init_empty (&label);
-
- var_append_value_name (nst->indep_var, &rs->sorted_array[i]->val,
- &label);
-
- tab_text (table, row_headers + i, 1,
- TAT_TITLE | TAB_LEFT, ds_cstr (&label));
-
- ds_destroy (&label);
- }
-
- for (v = 0; v < nst->n_vars; ++v)
+ struct pivot_table *table = pivot_table_create (N_("Frequencies"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+
+ struct pivot_dimension *indep = pivot_dimension_create__ (
+ table, PIVOT_AXIS_COLUMN, pivot_value_new_variable (nst->indep_var));
+ indep->root->show_label = true;
+ for (int i = 0; i < n_vals; ++i)
+ pivot_category_create_leaf_rc (
+ indep->root, pivot_value_new_var_value (
+ nst->indep_var, &results->sorted_array[i]->val), PIVOT_RC_COUNT);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("> Median"), N_("≤ Median"));
+
+ struct pivot_dimension *dep = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (int v = 0; v < nst->n_vars; ++v)
{
const struct results *rs = &results[v];
- tab_text (table, 0, column_headers + v * 2,
- TAT_TITLE | TAB_LEFT, var_to_string (rs->var) );
-
- tab_text (table, 1, column_headers + v * 2,
- TAT_TITLE | TAB_LEFT, _("> Median") );
-
- tab_text (table, 1, column_headers + v * 2 + 1,
- TAT_TITLE | TAB_LEFT, _("≤ Median") );
- if ( v > 0)
- tab_hline (table, TAL_1, 0, tab_nc (table) - 1, column_headers + v * 2);
- }
-
- for (v = 0; v < nst->n_vars; ++v)
- {
- int i;
- const struct results *rs = &results[v];
+ int dep_idx = pivot_category_create_leaf (
+ dep->root, pivot_value_new_variable (rs->var));
- for (i = 0; i < n_vals; ++i)
+ for (int indep_idx = 0; indep_idx < n_vals; indep_idx++)
{
- const struct val_node *vn = rs->sorted_array[i];
- tab_double (table, row_headers + i, column_headers + v * 2,
- 0, vn->gt, NULL, RC_WEIGHT);
-
- tab_double (table, row_headers + i, column_headers + v * 2 + 1,
- 0, vn->le, NULL, RC_WEIGHT);
+ const struct val_node *vn = rs->sorted_array[indep_idx];
+ pivot_table_put3 (table, indep_idx, 0, dep_idx,
+ pivot_value_new_number (vn->gt));
+ pivot_table_put3 (table, indep_idx, 1, dep_idx,
+ pivot_value_new_number (vn->le));
}
}
- tab_submit (table);
+ pivot_table_submit (table);
}
-
static void
show_test_statistics (const struct n_sample_test *nst,
const struct results *results,
int n_vals,
const struct dictionary *dict)
{
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- int v;
-
- const int row_headers = 1;
- const int column_headers = 1;
- const int nc = row_headers + 5;
- const int nr = column_headers + nst->n_vars;
-
- struct tab_table *table = tab_create (nc, nr);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Test Statistics"));
-
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- tab_box (table, TAL_2, TAL_2, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Median"),
+ N_("Chi-Square"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Asymp. Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- tab_text (table, row_headers + 0, 0,
- TAT_TITLE | TAB_CENTER, _("N"));
-
- tab_text (table, row_headers + 1, 0,
- TAT_TITLE | TAB_CENTER, _("Median"));
-
- tab_text (table, row_headers + 2, 0,
- TAT_TITLE | TAB_CENTER, _("Chi-Square"));
-
- tab_text (table, row_headers + 3, 0,
- TAT_TITLE | TAB_CENTER, _("df"));
-
- tab_text (table, row_headers + 4, 0,
- TAT_TITLE | TAB_CENTER, _("Asymp. Sig."));
-
-
- for (v = 0; v < nst->n_vars; ++v)
+ for (int v = 0; v < nst->n_vars; ++v)
{
double df = n_vals - 1;
const struct results *rs = &results[v];
- tab_text (table, 0, column_headers + v,
- TAT_TITLE | TAB_LEFT, var_to_string (rs->var));
-
-
- tab_double (table, row_headers + 0, column_headers + v,
- 0, rs->n, NULL, RC_WEIGHT);
-
- tab_double (table, row_headers + 1, column_headers + v,
- 0, rs->median, NULL, RC_OTHER);
-
- tab_double (table, row_headers + 2, column_headers + v,
- 0, rs->chisq, NULL, RC_OTHER);
-
- tab_double (table, row_headers + 3, column_headers + v,
- 0, df, NULL, RC_WEIGHT);
- tab_double (table, row_headers + 4, column_headers + v,
- 0, gsl_cdf_chisq_Q (rs->chisq, df), NULL, RC_PVALUE);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (rs->var));
+
+ double entries[] = {
+ rs->n,
+ rs->median,
+ rs->chisq,
+ df,
+ gsl_cdf_chisq_Q (rs->chisq, df),
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ struct pivot_value *value
+ = pivot_value_new_number (entries[i]);
+ if (i == 1)
+ value->numeric.format = *var_get_print_format (rs->var);
+ pivot_table_put2 (table, i, var_idx, value);
+ }
}
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "data/format.h"
#include "data/variable.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
void
do_summary_box (const struct descriptives *desc,
const struct variable *const *vv,
- int n_vars)
+ int n_vars,
+ const struct fmt_spec *wfmt)
{
- int v;
- bool quartiles = false;
+ if (!desc)
+ return;
- int col;
- int columns = 1 ;
- struct tab_table *table ;
+ struct pivot_table *table = pivot_table_create (
+ N_("Descriptive Statistics"));
+ pivot_table_set_weight_format (table, wfmt);
- if ( desc ) columns += 5;
- if ( quartiles ) columns += 3;
+ pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("Minimum"), N_("Maximum"));
- table = tab_create (columns, 2 + n_vars);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
-
- tab_title (table, _("Descriptive Statistics"));
-
- tab_headers (table, 1, 0, 1, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr(table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, 2);
- tab_vline (table, TAL_2, 1, 0, tab_nr (table) - 1);
-
- col = 1;
- if ( desc )
+ for (int v = 0; v < n_vars; ++v)
{
- tab_joint_text (table, col, 0, col, 1, TAT_TITLE | TAB_CENTER,
- _("N"));
- col++;
- tab_joint_text (table, col, 0, col, 1, TAT_TITLE | TAB_CENTER,
- _("Mean"));
- col++;
- tab_joint_text (table, col, 0, col, 1, TAT_TITLE | TAB_CENTER,
- _("Std. Deviation"));
- col++;
- tab_joint_text (table, col, 0, col, 1, TAT_TITLE | TAB_CENTER,
- _("Minimum"));
- col++;
- tab_joint_text (table, col, 0, col, 1, TAT_TITLE | TAB_CENTER,
- _("Maximum"));
- col++;
- }
+ const struct variable *var = vv[v];
- if ( quartiles )
- {
- tab_joint_text (table, col, 0, col + 2, 0, TAT_TITLE | TAB_CENTER,
- _("Percentiles"));
- tab_hline (table, TAL_1, col, col + 2, 1);
-
- tab_text (table, col, 1, TAT_TITLE | TAB_CENTER,
- _("25th"));
- col++;
- tab_text (table, col, 1, TAT_TITLE | TAB_CENTER,
- _("50th (Median)"));
- col++;
- tab_text (table, col, 1, TAT_TITLE | TAB_CENTER,
- _("75th"));
- col++;
- }
+ int row = pivot_category_create_leaf (variables->root,
+ pivot_value_new_variable (var));
+ double entries[] = { desc[v].n, desc[v].mean, desc[v].std_dev };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, row, pivot_value_new_number (entries[j]));
- for ( v = 0 ; v < n_vars ; ++v )
- {
- const struct variable *var = vv[v];
- const struct fmt_spec *fmt = var_get_print_format (var);
-
- tab_text (table, 0, 2 + v, 0, var_to_string (var));
-
- col = 1;
- if (desc != NULL)
- {
- tab_double (table, col++, 2 + v, 0, desc[v].n, fmt, RC_OTHER);
- tab_double (table, col++, 2 + v, 0, desc[v].mean, fmt, RC_OTHER);
- tab_double (table, col++, 2 + v, 0, desc[v].std_dev, fmt, RC_OTHER);
- tab_double (table, col++, 2 + v, 0, desc[v].min, fmt, RC_OTHER);
- tab_double (table, col++, 2 + v, 0, desc[v].max, fmt, RC_OTHER);
- }
+ union value extrema[2] = { { .f = desc[v].min }, { .f = desc[v].max } };
+ for (size_t j = 0; j < 2; j++)
+ pivot_table_put2 (table, 3 + j, row,
+ pivot_value_new_var_value (var, &extrema[j]));
}
-
- tab_submit (table);
+ pivot_table_submit (table);
}
struct variable ;
struct casereader ;
struct dictionary;
+struct fmt_spec;
struct descriptives
{
void
do_summary_box (const struct descriptives *desc,
const struct variable *const *vv,
- int n_vars);
+ int n_vars,
+ const struct fmt_spec *wfmt);
void npar_summary_calc_descriptives (struct descriptives *desc,
struct casereader *input,
if ( (specs->descriptives || specs->quartiles)
&& !taint_has_tainted_successor (casereader_get_taint (input)) )
- do_summary_box (summary_descriptives, specs->vv, specs->n_vars );
+ do_summary_box (summary_descriptives, specs->vv, specs->n_vars,
+ dict_get_weight_format (dataset_dict (ds)));
free (summary_descriptives);
casereader_destroy (input);
#include "math/covariance.h"
#include "math/levene.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
/* The weight variable */
const struct variable *wv;
+ const struct fmt_spec *wfmt;
/* The confidence level for multiple comparisons */
double alpha;
oneway.missing_type = MISS_ANALYSIS;
oneway.exclude = MV_ANY;
oneway.wv = dict_get_weight (dict);
+ oneway.wfmt = dict_get_weight_format (dict);
oneway.alpha = 0.05;
oneway.posthoc = NULL;
oneway.n_posthoc = 0;
static void
show_anova_table (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
{
- size_t i;
- int n_cols =7;
- size_t n_rows = cmd->n_vars * 3 + 1;
+ struct pivot_table *table = pivot_table_create (N_("ANOVA"));
- struct tab_table *t = tab_create (n_cols, n_rows);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Sum of Squares"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Mean Square"), PIVOT_RC_OTHER,
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_headers (t, 2, 0, 1, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Type"),
+ N_("Between Groups"), N_("Within Groups"),
+ N_("Total"));
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1, n_rows - 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- tab_hline (t, TAL_2, 0, n_cols - 1, 1 );
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
- tab_vline (t, TAL_0, 1, 0, 0);
-
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Sum of Squares"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Mean Square"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("F"));
- tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
-
-
- for (i = 0; i < cmd->n_vars; ++i)
+ for (size_t i = 0; i < cmd->n_vars; ++i)
{
- double n;
- double df1, df2;
- double msa;
- const char *s = var_to_string (cmd->vars[i]);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (cmd->vars[i]));
+
const struct per_var_ws *pvw = &ws->vws[i];
+ double n;
moments1_calculate (ws->dd_total[i]->mom, &n, NULL, NULL, NULL, NULL);
- df1 = pvw->n_groups - 1;
- df2 = n - pvw->n_groups;
- msa = pvw->ssa / df1;
-
- tab_text (t, 0, i * 3 + 1, TAB_LEFT | TAT_TITLE, s);
- tab_text (t, 1, i * 3 + 1, TAB_LEFT | TAT_TITLE, _("Between Groups"));
- tab_text (t, 1, i * 3 + 2, TAB_LEFT | TAT_TITLE, _("Within Groups"));
- tab_text (t, 1, i * 3 + 3, TAB_LEFT | TAT_TITLE, _("Total"));
-
- if (i > 0)
- tab_hline (t, TAL_1, 0, n_cols - 1, i * 3 + 1);
-
-
- /* Sums of Squares */
- tab_double (t, 2, i * 3 + 1, 0, pvw->ssa, NULL, RC_OTHER);
- tab_double (t, 2, i * 3 + 3, 0, pvw->sst, NULL, RC_OTHER);
- tab_double (t, 2, i * 3 + 2, 0, pvw->sse, NULL, RC_OTHER);
-
-
- /* Degrees of freedom */
- tab_double (t, 3, i * 3 + 1, 0, df1, NULL, RC_INTEGER);
- tab_double (t, 3, i * 3 + 2, 0, df2, NULL, RC_INTEGER);
- tab_double (t, 3, i * 3 + 3, 0, n - 1, NULL, RC_INTEGER);
+ double df1 = pvw->n_groups - 1;
+ double df2 = n - pvw->n_groups;
+ double msa = pvw->ssa / df1;
+ double F = msa / pvw->mse ;
- /* Mean Squares */
- tab_double (t, 4, i * 3 + 1, TAB_RIGHT, msa, NULL, RC_OTHER);
- tab_double (t, 4, i * 3 + 2, TAB_RIGHT, pvw->mse, NULL, RC_OTHER);
-
- {
- const double F = msa / pvw->mse ;
-
- /* The F value */
- tab_double (t, 5, i * 3 + 1, 0, F, NULL, RC_OTHER);
-
- /* The significance */
- tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL, RC_PVALUE);
- }
+ struct entry
+ {
+ int stat_idx;
+ int type_idx;
+ double x;
+ }
+ entries[] = {
+ /* Sums of Squares. */
+ { 0, 0, pvw->ssa },
+ { 0, 1, pvw->sse },
+ { 0, 2, pvw->sst },
+ /* Degrees of Freedom. */
+ { 1, 0, df1 },
+ { 1, 1, df2 },
+ { 1, 2, n - 1 },
+ /* Mean Squares. */
+ { 2, 0, msa },
+ { 2, 1, pvw->mse },
+ /* F. */
+ { 3, 0, F },
+ /* Significance. */
+ { 4, 0, gsl_cdf_fdist_Q (F, df1, df2) },
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ const struct entry *e = &entries[j];
+ pivot_table_put3 (table, e->stat_idx, e->type_idx, var_idx,
+ pivot_value_new_number (e->x));
+ }
}
- tab_title (t, _("ANOVA"));
- tab_submit (t);
+ pivot_table_submit (table);
}
-
/* Show the descriptives table */
static void
show_descriptives (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
{
- size_t v;
- int n_cols = 10;
- struct tab_table *t;
- int row;
-
- const double confidence = 0.95;
- const double q = (1.0 - confidence) / 2.0;
-
- const struct fmt_spec *wfmt = cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
-
- int n_rows = 2;
-
- for (v = 0; v < cmd->n_vars; ++v)
- n_rows += ws->actual_number_of_groups + 1;
-
- t = tab_create (n_cols, n_rows);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 2, 0, 2, 0);
-
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
- /* Underline headers */
- tab_hline (t, TAL_2, 0, n_cols - 1, 2);
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
-
- tab_text (t, 2, 1, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 3, 1, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 4, 1, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("Std. Error"));
+ if (!cmd->n_vars)
+ return;
+ const struct categoricals *cats = covariance_get_categoricals (
+ ws->vws[0].cov);
+ struct pivot_table *table = pivot_table_create (N_("Descriptives"));
+ pivot_table_set_weight_format (table, cmd->wfmt);
- tab_vline (t, TAL_0, 7, 0, 0);
- tab_hline (t, TAL_1, 6, 7, 1);
- tab_joint_text_format (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE,
- _("%g%% Confidence Interval for Mean"),
- confidence*100.0);
-
- tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
- tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
-
- tab_text (t, 8, 1, TAB_CENTER | TAT_TITLE, _("Minimum"));
- tab_text (t, 9, 1, TAB_CENTER | TAT_TITLE, _("Maximum"));
+ const double confidence = 0.95;
- tab_title (t, _("Descriptives"));
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT, N_("Mean"), N_("Std. Deviation"),
+ N_("Std. Error"));
+ struct pivot_category *interval = pivot_category_create_group__ (
+ statistics->root,
+ pivot_value_new_text_format (N_("%g%% Confidence Interval for Mean"),
+ confidence * 100.0));
+ pivot_category_create_leaves (interval, N_("Lower Bound"),
+ N_("Upper Bound"));
+ pivot_category_create_leaves (statistics->root,
+ N_("Minimum"), N_("Maximum"));
+
+ struct pivot_dimension *indep_var = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (cmd->indep_var));
+ indep_var->root->show_label = true;
+ size_t n;
+ union value *values = categoricals_get_var_values (cats, cmd->indep_var, &n);
+ for (size_t j = 0; j < n; j++)
+ pivot_category_create_leaf (
+ indep_var->root, pivot_value_new_var_value (cmd->indep_var, &values[j]));
+ pivot_category_create_leaf (
+ indep_var->root, pivot_value_new_text_format (N_("Total")));
+
+ struct pivot_dimension *dep_var = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variable"));
- row = 2;
- for (v = 0; v < cmd->n_vars; ++v)
+ const double q = (1.0 - confidence) / 2.0;
+ for (int v = 0; v < cmd->n_vars; ++v)
{
- const char *s = var_to_string (cmd->vars[v]);
- const struct fmt_spec *fmt = var_get_print_format (cmd->vars[v]);
-
- int count = 0;
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_var->root, pivot_value_new_variable (cmd->vars[v]));
struct per_var_ws *pvw = &ws->vws[v];
const struct categoricals *cats = covariance_get_categoricals (pvw->cov);
- tab_text (t, 0, row, TAB_LEFT | TAT_TITLE, s);
- if ( v > 0)
- tab_hline (t, TAL_1, 0, n_cols - 1, row);
-
+ int count;
for (count = 0; count < categoricals_n_total (cats); ++count)
{
- double T;
- double n, mean, variance;
- double std_dev, std_error ;
-
- struct string vstr;
-
- const struct ccase *gcc = categoricals_get_case_by_category (cats, count);
- const struct descriptive_data *dd = categoricals_get_user_data_by_category (cats, count);
+ const struct descriptive_data *dd
+ = categoricals_get_user_data_by_category (cats, count);
+ double n, mean, variance;
moments1_calculate (dd->mom, &n, &mean, &variance, NULL, NULL);
- std_dev = sqrt (variance);
- std_error = std_dev / sqrt (n) ;
-
- ds_init_empty (&vstr);
-
- var_append_value_name (cmd->indep_var, case_data (gcc, cmd->indep_var), &vstr);
-
- tab_text (t, 1, row + count,
- TAB_LEFT | TAT_TITLE,
- ds_cstr (&vstr));
-
- ds_destroy (&vstr);
-
- /* Now fill in the numbers ... */
-
- tab_double (t, 2, row + count, 0, n, NULL, RC_WEIGHT);
-
- tab_double (t, 3, row + count, 0, mean, NULL, RC_OTHER);
-
- tab_double (t, 4, row + count, 0, std_dev, NULL, RC_OTHER);
-
-
- tab_double (t, 5, row + count, 0, std_error, NULL, RC_OTHER);
-
- /* Now the confidence interval */
-
- T = gsl_cdf_tdist_Qinv (q, n - 1);
-
- tab_double (t, 6, row + count, 0,
- mean - T * std_error, NULL, RC_OTHER);
-
- tab_double (t, 7, row + count, 0,
- mean + T * std_error, NULL, RC_OTHER);
-
- /* Min and Max */
-
- tab_double (t, 8, row + count, 0, dd->minimum, fmt, RC_OTHER);
- tab_double (t, 9, row + count, 0, dd->maximum, fmt, RC_OTHER);
+ double std_dev = sqrt (variance);
+ double std_error = std_dev / sqrt (n) ;
+ double T = gsl_cdf_tdist_Qinv (q, n - 1);
+
+ double entries[] = {
+ n,
+ mean,
+ std_dev,
+ std_error,
+ mean - T * std_error,
+ mean + T * std_error,
+ dd->minimum,
+ dd->maximum,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put3 (table, i, count, dep_var_idx,
+ pivot_value_new_number (entries[i]));
}
if (categoricals_is_complete (cats))
- {
- double T;
- double n, mean, variance;
- double std_dev;
- double std_error;
-
- moments1_calculate (ws->dd_total[v]->mom, &n, &mean, &variance, NULL, NULL);
-
- std_dev = sqrt (variance);
- std_error = std_dev / sqrt (n) ;
-
- tab_text (t, 1, row + count,
- TAB_LEFT | TAT_TITLE, _("Total"));
-
- tab_double (t, 2, row + count, 0, n, NULL, RC_WEIGHT);
-
- tab_double (t, 3, row + count, 0, mean, NULL, RC_OTHER);
-
- tab_double (t, 4, row + count, 0, std_dev, NULL, RC_OTHER);
-
- tab_double (t, 5, row + count, 0, std_error, NULL, RC_OTHER);
-
- /* Now the confidence interval */
- T = gsl_cdf_tdist_Qinv (q, n - 1);
-
- tab_double (t, 6, row + count, 0,
- mean - T * std_error, NULL, RC_OTHER);
-
- tab_double (t, 7, row + count, 0,
- mean + T * std_error, NULL, RC_OTHER);
-
-
- /* Min and Max */
- tab_double (t, 8, row + count, 0, ws->dd_total[v]->minimum, fmt, RC_OTHER);
- tab_double (t, 9, row + count, 0, ws->dd_total[v]->maximum, fmt, RC_OTHER);
- }
-
- row += categoricals_n_total (cats) + 1;
+ {
+ double n, mean, variance;
+ moments1_calculate (ws->dd_total[v]->mom, &n, &mean, &variance,
+ NULL, NULL);
+
+ double std_dev = sqrt (variance);
+ double std_error = std_dev / sqrt (n) ;
+ double T = gsl_cdf_tdist_Qinv (q, n - 1);
+
+ double entries[] = {
+ n,
+ mean,
+ std_dev,
+ std_error,
+ mean - T * std_error,
+ mean + T * std_error,
+ ws->dd_total[v]->minimum,
+ ws->dd_total[v]->maximum,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put3 (table, i, count, dep_var_idx,
+ pivot_value_new_number (entries[i]));
+ }
}
- tab_submit (t);
+ pivot_table_submit (table);
}
/* Show the homogeneity table */
static void
show_homogeneity (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
{
- size_t v;
- int n_cols = 5;
- size_t n_rows = cmd->n_vars + 1;
-
- struct tab_table *t = tab_create (n_cols, n_rows);
- tab_headers (t, 1, 0, 1, 0);
-
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1, n_rows - 1);
+ struct pivot_table *table = pivot_table_create (
+ N_("Test of Homogeneity of Variances"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Levene Statistic"), PIVOT_RC_OTHER,
+ N_("df1"), PIVOT_RC_INTEGER,
+ N_("df2"), PIVOT_RC_INTEGER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 1, 0, n_rows - 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Levene Statistic"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("df1"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("df2"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
-
- tab_title (t, _("Test of Homogeneity of Variances"));
-
- for (v = 0; v < cmd->n_vars; ++v)
+ for (int v = 0; v < cmd->n_vars; ++v)
{
- double n;
- const struct per_var_ws *pvw = &ws->vws[v];
- double F = levene_calculate (pvw->nl);
-
- const struct variable *var = cmd->vars[v];
- const char *s = var_to_string (var);
- double df1, df2;
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (cmd->vars[v]));
+ double n;
moments1_calculate (ws->dd_total[v]->mom, &n, NULL, NULL, NULL, NULL);
- df1 = pvw->n_groups - 1;
- df2 = n - pvw->n_groups;
-
- tab_text (t, 0, v + 1, TAB_LEFT | TAT_TITLE, s);
-
- tab_double (t, 1, v + 1, TAB_RIGHT, F, NULL, RC_OTHER);
- tab_double (t, 2, v + 1, TAB_RIGHT, df1, NULL, RC_INTEGER);
- tab_double (t, 3, v + 1, TAB_RIGHT, df2, NULL, RC_INTEGER);
+ const struct per_var_ws *pvw = &ws->vws[v];
+ double df1 = pvw->n_groups - 1;
+ double df2 = n - pvw->n_groups;
+ double F = levene_calculate (pvw->nl);
- /* Now the significance */
- tab_double (t, 4, v + 1, TAB_RIGHT, gsl_cdf_fdist_Q (F, df1, df2), NULL, RC_PVALUE);
+ double entries[] =
+ {
+ F,
+ df1,
+ df2,
+ gsl_cdf_fdist_Q (F, df1, df2),
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, var_idx,
+ pivot_value_new_number (entries[i]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
show_contrast_coeffs (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
{
- int c_num = 0;
- struct ll *cli;
-
- int n_contrasts = ll_count (&cmd->contrast_list);
- int n_cols = 2 + ws->actual_number_of_groups;
- int n_rows = 2 + n_contrasts;
-
- struct tab_table *t;
-
- const struct covariance *cov = ws->vws[0].cov ;
-
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 2, 0, 2, 0);
+ struct pivot_table *table = pivot_table_create (N_("Contrast Coefficients"));
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1, n_rows - 1);
+ struct pivot_dimension *indep_var = pivot_dimension_create__ (
+ table, PIVOT_AXIS_COLUMN, pivot_value_new_variable (cmd->indep_var));
+ indep_var->root->show_label = true;
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 2, 0,
- n_cols - 1, 0);
+ struct pivot_dimension *contrast = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Contrast"));
+ contrast->root->show_label = true;
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 0, 0,
- 1, 1);
+ const struct covariance *cov = ws->vws[0].cov;
- tab_hline (t, TAL_1, 2, n_cols - 1, 1);
- tab_hline (t, TAL_2, 0, n_cols - 1, 2);
-
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
-
- tab_title (t, _("Contrast Coefficients"));
-
- tab_text (t, 0, 2, TAB_LEFT | TAT_TITLE, _("Contrast"));
-
-
- tab_joint_text (t, 2, 0, n_cols - 1, 0, TAB_CENTER | TAT_TITLE,
- var_to_string (cmd->indep_var));
-
- for ( cli = ll_head (&cmd->contrast_list);
- cli != ll_null (&cmd->contrast_list);
- cli = ll_next (cli))
+ const struct contrasts_node *cn;
+ int c_num = 1;
+ ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list)
{
- int count = 0;
- struct contrasts_node *cn = ll_data (cli, struct contrasts_node, ll);
- struct ll *coeffi ;
+ int contrast_idx = pivot_category_create_leaf (
+ contrast->root, pivot_value_new_integer (c_num++));
- tab_text_format (t, 1, c_num + 2, TAB_CENTER, "%d", c_num + 1);
-
- for (coeffi = ll_head (&cn->coefficient_list);
- coeffi != ll_null (&cn->coefficient_list);
- ++count, coeffi = ll_next (coeffi))
+ const struct coeff_node *coeffn;
+ int indep_idx = 0;
+ ll_for_each (coeffn, struct coeff_node, ll, &cn->coefficient_list)
{
const struct categoricals *cats = covariance_get_categoricals (cov);
- const struct ccase *gcc = categoricals_get_case_by_category (cats, count);
- struct coeff_node *coeffn = ll_data (coeffi, struct coeff_node, ll);
- struct string vstr;
-
- ds_init_empty (&vstr);
-
- var_append_value_name (cmd->indep_var, case_data (gcc, cmd->indep_var), &vstr);
+ const struct ccase *gcc = categoricals_get_case_by_category (
+ cats, indep_idx);
- tab_text (t, count + 2, 1, TAB_CENTER | TAT_TITLE, ds_cstr (&vstr));
+ if (!contrast_idx)
+ pivot_category_create_leaf (
+ indep_var->root, pivot_value_new_var_value (
+ cmd->indep_var, case_data (gcc, cmd->indep_var)));
- ds_destroy (&vstr);
-
- tab_text_format (t, count + 2, c_num + 2, TAB_RIGHT, "%.*g",
- DBL_DIG + 1, coeffn->coeff);
+ pivot_table_put2 (table, indep_idx++, contrast_idx,
+ pivot_value_new_integer (coeffn->coeff));
}
- ++c_num;
}
- tab_submit (t);
+ pivot_table_submit (table);
}
-
/* Show the results of the contrast tests */
static void
show_contrast_tests (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
{
+ struct pivot_table *table = pivot_table_create (N_("Contrast Tests"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Value of Contrast"), PIVOT_RC_OTHER,
+ N_("Std. Error"), PIVOT_RC_OTHER,
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_OTHER,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *contrasts = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Contrast"));
+ contrasts->root->show_label = true;
int n_contrasts = ll_count (&cmd->contrast_list);
- size_t v;
- int n_cols = 8;
- size_t n_rows = 1 + cmd->n_vars * 2 * n_contrasts;
-
- struct tab_table *t;
+ for (int i = 1; i <= n_contrasts; i++)
+ pivot_category_create_leaf (contrasts->root, pivot_value_new_integer (i));
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 3, 0, 1, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumption"),
+ N_("Assume equal variances"),
+ N_("Does not assume equal variances"));
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1, n_rows - 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variable"));
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 0, 0,
- 2, 0);
-
- tab_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 3, 0, n_rows - 1);
-
- tab_title (t, _("Contrast Tests"));
-
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Contrast"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Value of Contrast"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Error"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 7, 0, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
-
- for (v = 0; v < cmd->n_vars; ++v)
+ for (int v = 0; v < cmd->n_vars; ++v)
{
const struct per_var_ws *pvw = &ws->vws[v];
const struct categoricals *cats = covariance_get_categoricals (pvw->cov);
if (!categoricals_is_complete (cats))
continue;
- struct ll *cli;
- int i = 0;
- int lines_per_variable = 2 * n_contrasts;
- tab_text (t, 0, (v * lines_per_variable) + 1, TAB_LEFT | TAT_TITLE,
- var_to_string (cmd->vars[v]));
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (cmd->vars[v]));
- for ( cli = ll_head (&cmd->contrast_list);
- cli != ll_null (&cmd->contrast_list);
- ++i, cli = ll_next (cli))
+ struct contrasts_node *cn;
+ int contrast_idx = 0;
+ ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list)
{
- struct contrasts_node *cn = ll_data (cli, struct contrasts_node, ll);
- struct ll *coeffi ;
- int ci = 0;
- double contrast_value = 0.0;
- double coef_msq = 0.0;
-
- double T;
- double std_error_contrast;
- double df;
- double sec_vneq = 0.0;
/* Note: The calculation of the degrees of freedom in the
"variances not equal" case is painfull!!
}
*/
- double df_denominator = 0.0;
- double df_numerator = 0.0;
-
double grand_n;
- moments1_calculate (ws->dd_total[v]->mom, &grand_n, NULL, NULL, NULL, NULL);
- df = grand_n - pvw->n_groups;
+ moments1_calculate (ws->dd_total[v]->mom, &grand_n, NULL, NULL,
+ NULL, NULL);
+ double df = grand_n - pvw->n_groups;
- if ( i == 0 )
+ double contrast_value = 0.0;
+ double coef_msq = 0.0;
+ double sec_vneq = 0.0;
+ double df_denominator = 0.0;
+ double df_numerator = 0.0;
+ struct coeff_node *coeffn;
+ int ci = 0;
+ ll_for_each (coeffn, struct coeff_node, ll, &cn->coefficient_list)
{
- tab_text (t, 1, (v * lines_per_variable) + i + 1,
- TAB_LEFT | TAT_TITLE,
- _("Assume equal variances"));
-
- tab_text (t, 1, (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_LEFT | TAT_TITLE,
- _("Does not assume equal"));
- }
-
- tab_text_format (t, 2, (v * lines_per_variable) + i + 1,
- TAB_CENTER | TAT_TITLE, "%d", i + 1);
-
+ const struct descriptive_data *dd
+ = categoricals_get_user_data_by_category (cats, ci);
+ const double coef = coeffn->coeff;
- tab_text_format (t, 2,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_CENTER | TAT_TITLE, "%d", i + 1);
-
- for (coeffi = ll_head (&cn->coefficient_list);
- coeffi != ll_null (&cn->coefficient_list);
- ++ci, coeffi = ll_next (coeffi))
- {
double n, mean, variance;
- const struct descriptive_data *dd = categoricals_get_user_data_by_category (cats, ci);
- struct coeff_node *cn = ll_data (coeffi, struct coeff_node, ll);
- const double coef = cn->coeff;
- double winv ;
-
moments1_calculate (dd->mom, &n, &mean, &variance, NULL, NULL);
- winv = variance / n;
-
+ double winv = variance / n;
contrast_value += coef * mean;
+ coef_msq += pow2 (coef) / n;
+ sec_vneq += pow2 (coef) * variance / n;
+ df_numerator += pow2 (coef) * winv;
+ df_denominator += pow2(pow2 (coef) * winv) / (n - 1);
- coef_msq += (pow2 (coef)) / n;
-
- sec_vneq += (pow2 (coef)) * variance / n;
-
- df_numerator += (pow2 (coef)) * winv;
- df_denominator += pow2((pow2 (coef)) * winv) / (n - 1);
+ ci++;
}
-
sec_vneq = sqrt (sec_vneq);
-
df_numerator = pow2 (df_numerator);
- tab_double (t, 3, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, contrast_value, NULL, RC_OTHER);
-
- tab_double (t, 3, (v * lines_per_variable) + i + 1 +
- n_contrasts,
- TAB_RIGHT, contrast_value, NULL, RC_OTHER);
-
- std_error_contrast = sqrt (pvw->mse * coef_msq);
-
- /* Std. Error */
- tab_double (t, 4, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, std_error_contrast,
- NULL, RC_OTHER);
+ double std_error_contrast = sqrt (pvw->mse * coef_msq);
+ double T = fabs (contrast_value / std_error_contrast);
+ double T_ne = contrast_value / sec_vneq;
+ double df_ne = df_numerator / df_denominator;
+ double p_ne = gsl_cdf_tdist_P (T_ne, df_ne);
+ double q_ne = gsl_cdf_tdist_Q (T_ne, df_ne);
- T = fabs (contrast_value / std_error_contrast);
-
- /* T Statistic */
-
- tab_double (t, 5, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, T,
- NULL, RC_OTHER);
-
-
- /* Degrees of Freedom */
- tab_double (t, 6, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, df, NULL, RC_INTEGER);
-
-
- /* Significance TWO TAILED !!*/
- tab_double (t, 7, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df),
- NULL, RC_PVALUE);
-
- /* Now for the Variances NOT Equal case */
-
- /* Std. Error */
- tab_double (t, 4,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, sec_vneq,
- NULL, RC_OTHER);
-
- T = contrast_value / sec_vneq;
- tab_double (t, 5,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, T,
- NULL, RC_OTHER);
-
- df = df_numerator / df_denominator;
-
- tab_double (t, 6,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, df,
- NULL, RC_OTHER);
-
- {
- double p = gsl_cdf_tdist_P (T, df);
- double q = gsl_cdf_tdist_Q (T, df);
+ struct entry
+ {
+ int stat_idx;
+ int assumption_idx;
+ double x;
+ }
+ entries[] =
+ {
+ /* Assume equal. */
+ { 0, 0, contrast_value },
+ { 1, 0, std_error_contrast },
+ { 2, 0, T },
+ { 3, 0, df },
+ { 4, 0, 2 * gsl_cdf_tdist_Q (T, df) },
+ /* Do not assume equal. */
+ { 0, 1, contrast_value },
+ { 1, 1, sec_vneq },
+ { 2, 1, T_ne },
+ { 3, 1, df_ne },
+ { 4, 1, 2 * (T > 0 ? q_ne : p_ne) },
+ };
+
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put4 (
+ table, e->stat_idx, contrast_idx, e->assumption_idx, var_idx,
+ pivot_value_new_number (e->x));
+ }
- /* The Significance */
- tab_double (t, 7, (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, 2 * ((T > 0) ? q : p),
- NULL, RC_PVALUE);
- }
+ contrast_idx++;
}
-
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, n_cols - 1, (v * lines_per_variable) + 1);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
-
-
static void
show_comparisons (const struct oneway_spec *cmd, const struct oneway_workspace *ws, int v)
{
- const int n_cols = 8;
- const int heading_rows = 2;
- const int heading_cols = 3;
-
- int p;
- int r = heading_rows ;
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_user_text_nocopy (xasprintf (
+ _("Multiple Comparisons (%s)"),
+ var_to_string (cmd->vars[v]))));
+ table->omit_empty = true;
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Mean Difference (I - J)"), PIVOT_RC_OTHER,
+ N_("Std. Error"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+ struct pivot_category *interval = pivot_category_create_group__ (
+ statistics->root,
+ pivot_value_new_text_format (N_("%g%% Confidence Interval"),
+ (1 - cmd->alpha) * 100.0));
+ pivot_category_create_leaves (interval,
+ N_("Lower Bound"), PIVOT_RC_OTHER,
+ N_("Upper Bound"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *j_family = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("(J) Family"));
+ j_family->root->show_label = true;
+
+ struct pivot_dimension *i_family = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("(J) Family"));
+ i_family->root->show_label = true;
const struct per_var_ws *pvw = &ws->vws[v];
const struct categoricals *cat = pvw->cat;
- const int n_rows = heading_rows + cmd->n_posthoc * pvw->n_groups * (pvw->n_groups - 1);
-
- struct tab_table *t = tab_create (n_cols, n_rows);
-
- tab_headers (t, heading_cols, 0, heading_rows, 0);
-
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_cols, 0,
- n_cols - 1, n_rows - 1);
-
- tab_vline (t, TAL_2, heading_cols, 0, n_rows - 1);
-
- tab_title (t, _("Multiple Comparisons (%s)"), var_to_string (cmd->vars[v]));
-
- tab_text_format (t, 1, 1, TAB_LEFT | TAT_TITLE, _("(I) %s"), var_to_string (cmd->indep_var));
- tab_text_format (t, 2, 1, TAB_LEFT | TAT_TITLE, _("(J) %s"), var_to_string (cmd->indep_var));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 3, 1, TAB_CENTER | TAT_TITLE, _("(I - J)"));
- tab_text (t, 4, 1, TAB_CENTER | TAT_TITLE, _("Std. Error"));
- tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("Sig."));
-
- tab_joint_text_format (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE,
- _("%g%% Confidence Interval"),
- (1 - cmd->alpha) * 100.0);
-
- tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
- tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
+ for (int i = 0; i < pvw->n_groups; i++)
+ {
+ const struct ccase *gcc = categoricals_get_case_by_category (cat, i);
+ for (int j = 0; j < 2; j++)
+ pivot_category_create_leaf (
+ j ? j_family->root : i_family->root,
+ pivot_value_new_var_value (cmd->indep_var,
+ case_data (gcc, cmd->indep_var)));
+ }
+ struct pivot_dimension *test = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Test"));
- for (p = 0; p < cmd->n_posthoc; ++p)
+ for (int p = 0; p < cmd->n_posthoc; ++p)
{
- int i;
const struct posthoc *ph = &ph_tests[cmd->posthoc[p]];
- tab_hline (t, TAL_2, 0, n_cols - 1, r);
-
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, gettext (ph->label));
+ int test_idx = pivot_category_create_leaf (
+ test->root, pivot_value_new_text (ph->label));
- for (i = 0; i < pvw->n_groups ; ++i)
+ for (int i = 0; i < pvw->n_groups ; ++i)
{
+ struct descriptive_data *dd_i
+ = categoricals_get_user_data_by_category (cat, i);
double weight_i, mean_i, var_i;
- int rx = 0;
- struct string vstr;
- int j;
- struct descriptive_data *dd_i = categoricals_get_user_data_by_category (cat, i);
- const struct ccase *gcc = categoricals_get_case_by_category (cat, i);
-
-
- ds_init_empty (&vstr);
- var_append_value_name (cmd->indep_var, case_data (gcc, cmd->indep_var), &vstr);
-
- if ( i != 0)
- tab_hline (t, TAL_1, 1, n_cols - 1, r);
- tab_text (t, 1, r, TAB_LEFT | TAT_TITLE, ds_cstr (&vstr));
-
moments1_calculate (dd_i->mom, &weight_i, &mean_i, &var_i, 0, 0);
- for (j = 0 ; j < pvw->n_groups; ++j)
+ for (int j = 0 ; j < pvw->n_groups; ++j)
{
- double std_err;
- double weight_j, mean_j, var_j;
- double half_range;
- const struct ccase *cc;
- struct descriptive_data *dd_j = categoricals_get_user_data_by_category (cat, j);
if (j == i)
continue;
- ds_clear (&vstr);
- cc = categoricals_get_case_by_category (cat, j);
- var_append_value_name (cmd->indep_var, case_data (cc, cmd->indep_var), &vstr);
- tab_text (t, 2, r + rx, TAB_LEFT | TAT_TITLE, ds_cstr (&vstr));
-
+ struct descriptive_data *dd_j
+ = categoricals_get_user_data_by_category (cat, j);
+ double weight_j, mean_j, var_j;
moments1_calculate (dd_j->mom, &weight_j, &mean_j, &var_j, 0, 0);
- tab_double (t, 3, r + rx, 0, mean_i - mean_j, NULL, RC_OTHER);
-
- std_err = pvw->mse;
+ double std_err = pvw->mse;
std_err *= weight_i + weight_j;
std_err /= weight_i * weight_j;
std_err = sqrt (std_err);
- tab_double (t, 4, r + rx, 0, std_err, NULL, RC_OTHER);
-
- tab_double (t, 5, r + rx, 0, 2 * multiple_comparison_sig (std_err, pvw, dd_i, dd_j, ph), NULL, RC_PVALUE);
-
- half_range = mc_half_range (cmd, pvw, std_err, dd_i, dd_j, ph);
-
- tab_double (t, 6, r + rx, 0,
- (mean_i - mean_j) - half_range, NULL, RC_OTHER);
-
- tab_double (t, 7, r + rx, 0,
- (mean_i - mean_j) + half_range, NULL, RC_OTHER);
-
- rx++;
+ double sig = 2 * multiple_comparison_sig (std_err, pvw,
+ dd_i, dd_j, ph);
+ double half_range = mc_half_range (cmd, pvw, std_err,
+ dd_i, dd_j, ph);
+ double entries[] = {
+ mean_i - mean_j,
+ std_err,
+ sig,
+ (mean_i - mean_j) - half_range,
+ (mean_i - mean_j) + half_range,
+ };
+ for (size_t k = 0; k < sizeof entries / sizeof *entries; k++)
+ pivot_table_put4 (table, k, j, i, test_idx,
+ pivot_value_new_number (entries[k]));
}
- ds_destroy (&vstr);
- r += pvw->n_groups - 1;
}
}
- tab_submit (t);
+ pivot_table_submit (table);
}
#include "libpspp/assertion.h"
#include "libpspp/str.h"
#include "math/random.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "output/text-item.h"
#include "gettext.h"
static void
quick_cluster_show_centers (struct Kmeans *kmeans, bool initial, const struct qc *qc)
{
- struct tab_table *t;
- int nc, nr, currow;
- int i, j;
- nc = qc->ngroups + 1;
- nr = qc->n_vars + 4;
- t = tab_create (nc, nr);
- tab_headers (t, 0, nc - 1, 0, 1);
- currow = 0;
- if (!initial)
- {
- tab_title (t, _("Final Cluster Centers"));
- }
- else
- {
- tab_title (t, _("Initial Cluster Centers"));
- }
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, nc - 1, nr - 1);
- tab_joint_text (t, 1, 0, nc - 1, 0, TAB_CENTER, _("Cluster"));
- tab_hline (t, TAL_1, 1, nc - 1, 2);
- currow += 2;
-
- for (i = 0; i < qc->ngroups; i++)
- {
- tab_text_format (t, (i + 1), currow, TAB_CENTER, "%d", (i + 1));
- }
- currow++;
- tab_hline (t, TAL_1, 1, nc - 1, currow);
- currow++;
- for (i = 0; i < qc->n_vars; i++)
- {
- tab_text (t, 0, currow + i, TAB_LEFT,
- var_to_string (qc->vars[i]));
+ struct pivot_table *table = pivot_table_create (
+ initial ? N_("Initial Cluster Centers") : N_("Final Cluster Centers"));
+
+ struct pivot_dimension *clusters = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Cluster"));
+ clusters->root->show_label = true;
+ for (size_t i = 0; i < qc->ngroups; i++)
+ pivot_category_create_leaf (clusters->root,
+ pivot_value_new_integer (i + 1));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable"));
+ for (size_t i = 0; i < qc->n_vars; i++)
+ pivot_category_create_leaf (variables->root,
+ pivot_value_new_variable (qc->vars[i]));
+
+ const gsl_matrix *matrix = (initial
+ ? kmeans->initial_centers
+ : kmeans->centers);
+ for (size_t i = 0; i < qc->ngroups; i++)
+ for (size_t j = 0; j < qc->n_vars; j++)
+ {
+ double x = gsl_matrix_get (matrix, kmeans->group_order->data[i], j);
+ union value v = { .f = x };
+ pivot_table_put2 (table, i, j,
+ pivot_value_new_var_value (qc->vars[j], &v));
}
- for (i = 0; i < qc->ngroups; i++)
- {
- for (j = 0; j < qc->n_vars; j++)
- {
- if (!initial)
- {
- tab_double (t, i + 1, j + 4, TAB_CENTER,
- gsl_matrix_get (kmeans->centers,
- kmeans->group_order->data[i], j),
- var_get_print_format (qc->vars[j]), RC_OTHER);
- }
- else
- {
- tab_double (t, i + 1, j + 4, TAB_CENTER,
- gsl_matrix_get (kmeans->initial_centers,
- kmeans->group_order->data[i], j),
- var_get_print_format (qc->vars[j]), RC_OTHER);
- }
- }
- }
- tab_submit (t);
+ pivot_table_submit (table);
}
/* Reports cluster membership for each case. */
static void
quick_cluster_show_membership (struct Kmeans *kmeans, const struct casereader *reader, const struct qc *qc)
{
- struct tab_table *t;
- int nc, nr, i;
+ struct pivot_table *table = pivot_table_create (N_("Cluster Membership"));
- struct ccase *c;
- struct casereader *cs = casereader_clone (reader);
- nc = 2;
- nr = kmeans->n + 1;
- t = tab_create (nc, nr);
- tab_headers (t, 0, nc - 1, 0, 0);
- tab_title (t, _("Cluster Membership"));
- tab_text (t, 0, 0, TAB_CENTER, _("Case Number"));
- tab_text (t, 1, 0, TAB_CENTER, _("Cluster"));
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, nc - 1, nr - 1);
- tab_hline (t, TAL_1, 0, nc - 1, 1);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Cluster"),
+ N_("Cluster"));
+
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Case Number"));
+ cases->root->show_label = true;
gsl_permutation *ip = gsl_permutation_alloc (qc->ngroups);
gsl_permutation_inverse (ip, kmeans->group_order);
- for (i = 0; (c = casereader_read (cs)) != NULL; i++, case_unref (c))
+ struct casereader *cs = casereader_clone (reader);
+ struct ccase *c;
+ for (int i = 0; (c = casereader_read (cs)) != NULL; i++, case_unref (c))
{
- int clust = -1;
assert (i < kmeans->n);
+ int clust;
kmeans_get_nearest_group (kmeans, c, qc, &clust, NULL, NULL, NULL);
- clust = ip->data[clust];
- tab_text_format (t, 0, i+1, TAB_CENTER, "%d", (i + 1));
- tab_text_format (t, 1, i+1, TAB_CENTER, "%d", (clust + 1));
+ int cluster = ip->data[clust];
+
+ int case_idx = pivot_category_create_leaf (
+ cases->root, pivot_value_new_integer (i + 1));
+ pivot_table_put2 (table, 0, case_idx,
+ pivot_value_new_integer (cluster + 1));
}
gsl_permutation_free (ip);
- assert (i == kmeans->n);
- tab_submit (t);
+ pivot_table_submit (table);
casereader_destroy (cs);
}
static void
quick_cluster_show_number_cases (struct Kmeans *kmeans, const struct qc *qc)
{
- struct tab_table *t;
- int nc, nr;
- int i, numelem;
- long int total;
- nc = 3;
- nr = qc->ngroups + 1;
- t = tab_create (nc, nr);
- tab_headers (t, 0, nc - 1, 0, 0);
- tab_title (t, _("Number of Cases in each Cluster"));
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, nc - 1, nr - 1);
- tab_text (t, 0, 0, TAB_LEFT, _("Cluster"));
-
- total = 0;
- for (i = 0; i < qc->ngroups; i++)
+ struct pivot_table *table = pivot_table_create (
+ N_("Number of Cases in each Cluster"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Count"));
+
+ struct pivot_dimension *clusters = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Clusters"));
+ struct pivot_category *group = pivot_category_create_group (
+ clusters->root, N_("Cluster"));
+
+ long int total = 0;
+ for (int i = 0; i < qc->ngroups; i++)
{
- tab_text_format (t, 1, i, TAB_CENTER, "%d", (i + 1));
- numelem =
- kmeans->num_elements_groups->data[kmeans->group_order->data[i]];
- tab_text_format (t, 2, i, TAB_CENTER, "%d", numelem);
- total += numelem;
+ int cluster_idx = pivot_category_create_leaf (
+ group, pivot_value_new_integer (i + 1));
+ int count = kmeans->num_elements_groups->data[
+ kmeans->group_order->data[i]];
+ pivot_table_put2 (table, 0, cluster_idx,
+ pivot_value_new_integer (count));
+ total += count;
}
- tab_text (t, 0, qc->ngroups, TAB_LEFT, _("Valid"));
- tab_text_format (t, 2, qc->ngroups, TAB_LEFT, "%ld", total);
- tab_submit (t);
+ int cluster_idx = pivot_category_create_leaf (
+ clusters->root, pivot_value_new_text (N_("Valid")));
+ pivot_table_put2 (table, 0, cluster_idx, pivot_value_new_integer (total));
+ pivot_table_submit (table);
}
/* Reports. */
#include "libpspp/pool.h"
#include "libpspp/string-set.h"
#include "libpspp/taint.h"
-
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
struct string_set new_names;
struct rank rank;
struct rank_spec *rs;
- int i;
subcase_init_empty (&rank.sc);
created with INTO. */
for (rs = rank.rs; rs < &rank.rs[rank.n_rs]; rs++)
{
- int v;
-
rs->dest_labels = pool_calloc (rank.pool, rank.n_vars,
sizeof *rs->dest_labels);
- for ( v = 0 ; v < rank.n_vars ; v ++ )
+ for (int v = 0 ; v < rank.n_vars ; v ++ )
{
const char **dst_name = &rs->dest_names[v];
if ( *dst_name == NULL )
if ( rank.print )
{
- int v;
+ struct pivot_table *table = pivot_table_create (
+ N_("Variables Created by RANK"));
+ table->omit_empty = true;
- tab_output_text_format (0, _("Variables Created By %s"), "RANK");
- tab_output_text (0, "");
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("New Variable"),
+ N_("New Variable"), N_("Function"),
+ N_("Fraction"), N_("Grouping Variables"));
- for (i = 0 ; i < rank.n_rs ; ++i )
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Existing Variable"),
+ N_("Existing Variable"));
+ variables->root->show_label = true;
+
+ for (size_t i = 0 ; i < rank.n_rs ; ++i )
{
- for ( v = 0 ; v < rank.n_vars ; v ++ )
+ for (size_t v = 0 ; v < rank.n_vars ; v ++ )
{
- if ( rank.n_group_vars > 0 )
- {
- struct string varlist;
- int g;
-
- ds_init_empty (&varlist);
- for ( g = 0 ; g < rank.n_group_vars ; ++g )
- {
- ds_put_cstr (&varlist, var_get_name (rank.group_vars[g]));
-
- if ( g < rank.n_group_vars - 1)
- ds_put_cstr (&varlist, " ");
- }
-
- if ( rank.rs[i].rfunc == NORMAL ||
- rank.rs[i].rfunc == PROPORTION )
- tab_output_text_format (0,
- _("%s into %s(%s of %s using %s BY %s)"),
- var_get_name (rank.vars[v]),
- rank.rs[i].dest_names[v],
- function_name[rank.rs[i].rfunc],
- var_get_name (rank.vars[v]),
- fraction_name (&rank),
- ds_cstr (&varlist));
-
- else
- tab_output_text_format (0,
- _("%s into %s(%s of %s BY %s)"),
- var_get_name (rank.vars[v]),
- rank.rs[i].dest_names[v],
- function_name[rank.rs[i].rfunc],
- var_get_name (rank.vars[v]),
- ds_cstr (&varlist));
- ds_destroy (&varlist);
- }
- else
- {
- if ( rank.rs[i].rfunc == NORMAL ||
- rank.rs[i].rfunc == PROPORTION )
- tab_output_text_format (0,
- _("%s into %s(%s of %s using %s)"),
- var_get_name (rank.vars[v]),
- rank.rs[i].dest_names[v],
- function_name[rank.rs[i].rfunc],
- var_get_name (rank.vars[v]),
- fraction_name (&rank));
-
- else
- tab_output_text_format (0,
- _("%s into %s(%s of %s)"),
- var_get_name (rank.vars[v]),
- rank.rs[i].dest_names[v],
- function_name[rank.rs[i].rfunc],
- var_get_name (rank.vars[v]));
- }
+ int row_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (rank.vars[v]));
+
+ struct string group_vars = DS_EMPTY_INITIALIZER;
+ for (int g = 0 ; g < rank.n_group_vars ; ++g )
+ {
+ if (g)
+ ds_put_byte (&group_vars, ' ');
+ ds_put_cstr (&group_vars, var_get_name (rank.group_vars[g]));
+ }
+
+ enum rank_func rfunc = rank.rs[i].rfunc;
+ bool has_fraction = rfunc == NORMAL || rfunc == PROPORTION;
+ const char *entries[] =
+ {
+ rank.rs[i].dest_names[v],
+ function_name[rank.rs[i].rfunc],
+ has_fraction ? fraction_name (&rank) : NULL,
+ rank.n_group_vars ? ds_cstr (&group_vars) : NULL,
+ };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ {
+ const char *entry = entries[j];
+ if (entry)
+ pivot_table_put2 (table, j, row_idx,
+ pivot_value_new_user_text (entry, -1));
+ }
}
}
+
+ pivot_table_submit (table);
}
/* Do the ranking */
#include "libpspp/message.h"
#include "libpspp/taint.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
+
+#include "gl/intprops.h"
+#include "gl/minmax.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
#define N_(msgid) msgid
-#include <gl/intprops.h>
-
#define STATS_R 1
#define STATS_COEFF 2
#define STATS_ANOVA 4
static void
reg_stats_r (const struct linreg * c, const struct variable *var)
{
- struct tab_table *t;
- int n_rows = 2;
- int n_cols = 5;
- double rsq;
- double adjrsq;
- double std_error;
-
- assert (c != NULL);
- rsq = linreg_ssreg (c) / linreg_sst (c);
- adjrsq = rsq -
- (1.0 - rsq) * linreg_n_coeffs (c) / (linreg_n_obs (c) -
- linreg_n_coeffs (c) - 1);
- std_error = sqrt (linreg_mse (c));
- t = tab_create (n_cols, n_rows);
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
- tab_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
- tab_vline (t, TAL_0, 1, 0, 0);
-
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("R"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("R Square"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Adjusted R Square"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Error of the Estimate"));
- tab_double (t, 1, 1, TAB_RIGHT, sqrt (rsq), NULL, RC_OTHER);
- tab_double (t, 2, 1, TAB_RIGHT, rsq, NULL, RC_OTHER);
- tab_double (t, 3, 1, TAB_RIGHT, adjrsq, NULL, RC_OTHER);
- tab_double (t, 4, 1, TAB_RIGHT, std_error, NULL, RC_OTHER);
- tab_title (t, _("Model Summary (%s)"), var_to_string (var));
- tab_submit (t);
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("Model Summary (%s)"),
+ var_to_string (var)));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("R"), N_("R Square"), N_("Adjusted R Square"),
+ N_("Std. Error of the Estimate"));
+
+ double rsq = linreg_ssreg (c) / linreg_sst (c);
+ double adjrsq = (rsq -
+ (1.0 - rsq) * linreg_n_coeffs (c)
+ / (linreg_n_obs (c) - linreg_n_coeffs (c) - 1));
+ double std_error = sqrt (linreg_mse (c));
+
+ double entries[] = {
+ sqrt (rsq), rsq, adjrsq, std_error
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put1 (table, i, pivot_value_new_number (entries[i]));
+
+ pivot_table_submit (table);
}
/*
static void
reg_stats_coeff (const struct linreg * c, const gsl_matrix *cov, const struct variable *var, const struct regression *cmd)
{
- size_t j;
- int n_cols = 7;
- const int heading_rows = 2;
- int n_rows;
- int this_row = heading_rows;
- double pval;
- double std_err;
- double beta;
- const char *label;
-
- const struct variable *v;
- struct tab_table *t;
-
- const double df = linreg_n_obs (c) - linreg_n_coeffs (c) - 1;
- double q = (1 - cmd->ci) / 2.0; /* 2-tailed test */
- double tval = gsl_cdf_tdist_Qinv (q, df);
-
- assert (c != NULL);
- n_rows = linreg_n_coeffs (c) + heading_rows + 1;
-
- if (cmd->stats & STATS_CI)
- n_cols += 2;
-
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 2, 0, 1, 0);
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
- tab_hline (t, TAL_2, 0, n_cols - 1, heading_rows);
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
- tab_vline (t, TAL_0, 1, 0, 0);
-
-
- tab_hline (t, TAL_1, 2, 4, 1);
- tab_joint_text (t, 2, 0, 3, 0, TAB_CENTER | TAT_TITLE, _("Unstandardized Coefficients"));
- tab_text (t, 2, 1, TAB_CENTER | TAT_TITLE, _("B"));
- tab_text (t, 3, 1, TAB_CENTER | TAT_TITLE, _("Std. Error"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Standardized Coefficients"));
- tab_text (t, 4, 1, TAB_CENTER | TAT_TITLE, _("Beta"));
- tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Sig."));
-
- std_err = sqrt (gsl_matrix_get (linreg_cov (c), 0, 0));
-
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("Coefficients (%s)"),
+ var_to_string (var)));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_group (statistics->root,
+ N_("Unstandardized Coefficients"),
+ N_("B"), N_("Std. Error"));
+ pivot_category_create_group (statistics->root,
+ N_("Standardized Coefficients"), N_("Beta"));
+ pivot_category_create_leaves (statistics->root, N_("t"),
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
if (cmd->stats & STATS_CI)
{
- double lower = linreg_intercept (c) - tval * std_err ;
- double upper = linreg_intercept (c) + tval * std_err ;
- tab_double (t, 7, heading_rows, 0, lower, NULL, RC_OTHER);
- tab_double (t, 8, heading_rows, 0, upper, NULL, RC_OTHER);
-
- tab_joint_text_format (t, 7, 0, 8, 0, TAB_CENTER | TAT_TITLE, _("%g%% Confidence Interval for B"), cmd->ci * 100);
- tab_hline (t, TAL_1, 7, 8, 1);
- tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
- tab_text (t, 8, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
+ struct pivot_category *interval = pivot_category_create_group__ (
+ statistics->root, pivot_value_new_text_format (
+ N_("%g%% Confidence Interval for B"),
+ cmd->ci * 100.0));
+ pivot_category_create_leaves (interval, N_("Lower Bound"),
+ N_("Upper Bound"));
}
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ double df = linreg_n_obs (c) - linreg_n_coeffs (c) - 1;
+ double q = (1 - cmd->ci) / 2.0; /* 2-tailed test */
+ double tval = gsl_cdf_tdist_Qinv (q, df);
+
if (!cmd->origin)
{
- tab_text (t, 1, this_row, TAB_LEFT | TAT_TITLE, _("(Constant)"));
- tab_double (t, 2, this_row, 0, linreg_intercept (c), NULL, RC_OTHER);
- tab_double (t, 3, this_row, 0, std_err, NULL, RC_OTHER);
- tab_double (t, 4, this_row, 0, 0.0, NULL, RC_OTHER);
- double t_stat = linreg_intercept (c) / std_err;
- tab_double (t, 5, this_row, 0, t_stat, NULL, RC_OTHER);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_text (N_("(Constant)")));
- double pval =
- 2 * gsl_cdf_tdist_Q (fabs (t_stat),
- (double) (linreg_n_obs (c) - linreg_n_coeffs (c)));
- tab_double (t, 6, this_row, 0, pval, NULL, RC_PVALUE);
- this_row++;
+ double std_err = sqrt (gsl_matrix_get (linreg_cov (c), 0, 0));
+ double t_stat = linreg_intercept (c) / std_err;
+ double entries[] = {
+ linreg_intercept (c),
+ std_err,
+ 0.0,
+ t_stat,
+ 2.0 * gsl_cdf_tdist_Q (fabs (t_stat),
+ linreg_n_obs (c) - linreg_n_coeffs (c)),
+ linreg_intercept (c) - tval * std_err,
+ linreg_intercept (c) + tval * std_err,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, var_idx,
+ pivot_value_new_number (entries[i]));
}
- for (j = 0; j < linreg_n_coeffs (c); j++, this_row++)
+ for (size_t j = 0; j < linreg_n_coeffs (c); j++)
{
- struct string tstr;
- ds_init_empty (&tstr);
-
- v = linreg_indep_var (c, j);
- label = var_to_string (v);
- /* Do not overwrite the variable's name. */
- ds_put_cstr (&tstr, label);
- tab_text (t, 1, this_row, TAB_LEFT, ds_cstr (&tstr));
- /*
- Regression coefficients.
- */
- tab_double (t, 2, this_row, 0, linreg_coeff (c, j), NULL, RC_OTHER);
- /*
- Standard error of the coefficients.
- */
- std_err = sqrt (gsl_matrix_get (linreg_cov (c), j + 1, j + 1));
- tab_double (t, 3, this_row, 0, std_err, NULL, RC_OTHER);
- /*
- Standardized coefficient, i.e., regression coefficient
- if all variables had unit variance.
- */
- beta = sqrt (gsl_matrix_get (cov, j, j));
- beta *= linreg_coeff (c, j) /
- sqrt (gsl_matrix_get (cov, cov->size1 - 1, cov->size2 - 1));
- tab_double (t, 4, this_row, 0, beta, NULL, RC_OTHER);
+ const struct variable *v = linreg_indep_var (c, j);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (v));
- /*
- Test statistic for H0: coefficient is 0.
- */
+ double std_err = sqrt (gsl_matrix_get (linreg_cov (c), j + 1, j + 1));
double t_stat = linreg_coeff (c, j) / std_err;
- tab_double (t, 5, this_row, 0, t_stat, NULL, RC_OTHER);
- /*
- P values for the test statistic above.
- */
- pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), df);
- tab_double (t, 6, this_row, 0, pval, NULL, RC_PVALUE);
- ds_destroy (&tstr);
-
- if (cmd->stats & STATS_CI)
- {
- double lower = linreg_coeff (c, j) - tval * std_err ;
- double upper = linreg_coeff (c, j) + tval * std_err ;
-
- tab_double (t, 7, this_row, 0, lower, NULL, RC_OTHER);
- tab_double (t, 8, this_row, 0, upper, NULL, RC_OTHER);
- }
+ double entries[] = {
+ linreg_coeff (c, j),
+ sqrt (gsl_matrix_get (linreg_cov (c), j + 1, j + 1)),
+ (sqrt (gsl_matrix_get (cov, j, j)) * linreg_coeff (c, j) /
+ sqrt (gsl_matrix_get (cov, cov->size1 - 1, cov->size2 - 1))),
+ t_stat,
+ 2 * gsl_cdf_tdist_Q (fabs (t_stat), df),
+ linreg_coeff (c, j) - tval * std_err,
+ linreg_coeff (c, j) + tval * std_err,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, var_idx,
+ pivot_value_new_number (entries[i]));
}
- tab_title (t, _("Coefficients (%s)"), var_to_string (var));
- tab_submit (t);
+
+ pivot_table_submit (table);
}
/*
static void
reg_stats_anova (const struct linreg * c, const struct variable *var)
{
- int n_cols = 7;
- int n_rows = 4;
- const double msm = linreg_ssreg (c) / linreg_dfmodel (c);
- const double mse = linreg_mse (c);
- const double F = msm / mse;
- const double pval = gsl_cdf_fdist_Q (F, linreg_dfmodel (c),
- linreg_dferror (c));
-
- struct tab_table *t;
-
- assert (c != NULL);
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 2, 0, 1, 0);
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("ANOVA (%s)"), var_to_string (var)));
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Sum of Squares"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_INTEGER,
+ N_("Mean Square"), PIVOT_RC_OTHER,
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
- tab_vline (t, TAL_0, 1, 0, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Source"),
+ N_("Regression"), N_("Residual"), N_("Total"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Sum of Squares"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Mean Square"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("F"));
- tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
+ double msm = linreg_ssreg (c) / linreg_dfmodel (c);
+ double mse = linreg_mse (c);
+ double F = msm / mse;
- tab_text (t, 1, 1, TAB_LEFT | TAT_TITLE, _("Regression"));
- tab_text (t, 1, 2, TAB_LEFT | TAT_TITLE, _("Residual"));
- tab_text (t, 1, 3, TAB_LEFT | TAT_TITLE, _("Total"));
-
- /* Sums of Squares */
- tab_double (t, 2, 1, 0, linreg_ssreg (c), NULL, RC_OTHER);
- tab_double (t, 2, 3, 0, linreg_sst (c), NULL, RC_OTHER);
- tab_double (t, 2, 2, 0, linreg_sse (c), NULL, RC_OTHER);
-
-
- /* Degrees of freedom */
- tab_text_format (t, 3, 1, TAB_RIGHT, "%.*g", DBL_DIG + 1, linreg_dfmodel (c));
- tab_text_format (t, 3, 2, TAB_RIGHT, "%.*g", DBL_DIG + 1, linreg_dferror (c));
- tab_text_format (t, 3, 3, TAB_RIGHT, "%.*g", DBL_DIG + 1, linreg_dftotal (c));
-
- /* Mean Squares */
- tab_double (t, 4, 1, TAB_RIGHT, msm, NULL, RC_OTHER);
- tab_double (t, 4, 2, TAB_RIGHT, mse, NULL, RC_OTHER);
-
- tab_double (t, 5, 1, 0, F, NULL, RC_OTHER);
-
- tab_double (t, 6, 1, 0, pval, NULL, RC_PVALUE);
+ struct entry
+ {
+ int stat_idx;
+ int source_idx;
+ double x;
+ }
+ entries[] = {
+ /* Sums of Squares. */
+ { 0, 0, linreg_ssreg (c) },
+ { 0, 1, linreg_sse (c) },
+ { 0, 2, linreg_sst (c) },
+ /* Degrees of freedom. */
+ { 1, 0, linreg_dfmodel (c) },
+ { 1, 1, linreg_dferror (c) },
+ { 1, 2, linreg_dftotal (c) },
+ /* Mean Squares. */
+ { 2, 0, msm },
+ { 2, 1, mse },
+ /* F */
+ { 3, 0, F },
+ /* Significance. */
+ { 4, 0, gsl_cdf_fdist_Q (F, linreg_dfmodel (c), linreg_dferror (c)) },
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put2 (table, e->stat_idx, e->source_idx,
+ pivot_value_new_number (e->x));
+ }
- tab_title (t, _("ANOVA (%s)"), var_to_string (var));
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
reg_stats_bcov (const struct linreg * c, const struct variable *var)
{
- int n_cols;
- int n_rows;
- int i;
- int k;
- int row;
- int col;
- const char *label;
- struct tab_table *t;
-
- assert (c != NULL);
- n_cols = linreg_n_indeps (c) + 1 + 2;
- n_rows = 2 * (linreg_n_indeps (c) + 1);
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 2, 0, 1, 0);
- tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
- tab_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 2, 0, n_rows - 1);
- tab_vline (t, TAL_0, 1, 0, 0);
- tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Model"));
- tab_text (t, 1, 1, TAB_CENTER | TAT_TITLE, _("Covariances"));
- for (i = 0; i < linreg_n_coeffs (c); i++)
+ struct pivot_table *table = pivot_table_create__ (
+ pivot_value_new_text_format (N_("Coefficient Correlations (%s)"),
+ var_to_string (var)));
+
+ for (size_t i = 0; i < 2; i++)
{
- const struct variable *v = linreg_indep_var (c, i);
- label = var_to_string (v);
- tab_text (t, 2, i, TAB_CENTER, label);
- tab_text (t, i + 2, 0, TAB_CENTER, label);
- for (k = 1; k < linreg_n_coeffs (c); k++)
- {
- col = (i <= k) ? k : i;
- row = (i <= k) ? i : k;
- tab_double (t, k + 2, i, TAB_CENTER,
- gsl_matrix_get (linreg_cov (c), row, col), NULL, RC_OTHER);
- }
+ struct pivot_dimension *models = pivot_dimension_create (
+ table, i ? PIVOT_AXIS_ROW : PIVOT_AXIS_COLUMN, N_("Models"));
+ for (size_t j = 0; j < linreg_n_coeffs (c); j++)
+ pivot_category_create_leaf (
+ models->root, pivot_value_new_variable (
+ linreg_indep_var (c, j)));
}
- tab_title (t, _("Coefficient Correlations (%s)"), var_to_string (var));
- tab_submit (t);
+
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Covariances"));
+
+ for (size_t i = 0; i < linreg_n_coeffs (c); i++)
+ for (size_t k = 0; k < linreg_n_coeffs (c); k++)
+ {
+ double cov = gsl_matrix_get (linreg_cov (c), MIN (i, k), MAX (i, k));
+ pivot_table_put3 (table, k, i, 0, pivot_value_new_number (cov));
+ }
+
+ pivot_table_submit (table);
}
#include "libpspp/misc.h"
#include "libpspp/str.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "output/text-item.h"
#include "gettext.h"
case_processing_summary (casenumber n_valid, casenumber n_missing,
const struct dictionary *dict)
{
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
+ struct pivot_table *table = pivot_table_create (
+ N_("Case Processing Summary"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- casenumber total;
- int n_cols = 4;
- int n_rows = 4;
- int heading_columns = 2;
- int heading_rows = 1;
- struct tab_table *tbl;
- tbl = tab_create (n_cols, n_rows);
- tab_set_format (tbl, RC_WEIGHT, wfmt);
- tab_headers (tbl, heading_columns, 0, heading_rows, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
- tab_title (tbl, _("Case Processing Summary"));
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Cases"), N_("Valid"), N_("Excluded"),
+ N_("Total"));
+ cases->root->show_label = true;
- /* Vertical lines for the data only */
- tab_box (tbl,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- n_cols - 1, n_rows - 1);
+ casenumber total = n_missing + n_valid;
- /* Box around table */
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, heading_rows);
-
- tab_vline (tbl, TAL_2, heading_columns, 0, n_rows - 1);
-
-
- tab_text (tbl, 0, heading_rows, TAB_LEFT | TAT_TITLE,
- _("Cases"));
-
- tab_text (tbl, 1, heading_rows, TAB_LEFT | TAT_TITLE,
- _("Valid"));
-
- tab_text (tbl, 1, heading_rows + 1, TAB_LEFT | TAT_TITLE,
- _("Excluded"));
-
- tab_text (tbl, 1, heading_rows + 2, TAB_LEFT | TAT_TITLE,
- _("Total"));
-
- tab_text (tbl, heading_columns, 0, TAB_CENTER | TAT_TITLE,
- _("N"));
-
- tab_text (tbl, heading_columns + 1, 0, TAB_CENTER | TAT_TITLE, _("%"));
-
- total = n_missing + n_valid;
-
- tab_double (tbl, 2, heading_rows, TAB_RIGHT,
- n_valid, NULL, RC_WEIGHT);
-
-
- tab_double (tbl, 2, heading_rows + 1, TAB_RIGHT,
- n_missing, NULL, RC_WEIGHT);
-
-
- tab_double (tbl, 2, heading_rows + 2, TAB_RIGHT,
- total, NULL, RC_WEIGHT);
-
-
- tab_double (tbl, 3, heading_rows, TAB_RIGHT,
- 100 * n_valid / (double) total, NULL, RC_OTHER);
-
-
- tab_double (tbl, 3, heading_rows + 1, TAB_RIGHT,
- 100 * n_missing / (double) total, NULL, RC_OTHER);
-
-
- tab_double (tbl, 3, heading_rows + 2, TAB_RIGHT,
- 100 * total / (double) total, NULL, RC_OTHER);
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, n_valid },
+ { 0, 1, n_missing },
+ { 0, 2, total },
+ { 1, 0, 100.0 * n_valid / total },
+ { 1, 1, 100.0 * n_missing / total },
+ { 1, 2, 100.0 }
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put2 (table, e->stat_idx, e->case_idx,
+ pivot_value_new_number (e->x));
+ }
- tab_submit (tbl);
+ pivot_table_submit (table);
}
-
-
static void
reliability_summary_total (const struct reliability *rel)
{
- int i;
- const int n_cols = 5;
- const int heading_columns = 1;
- const int heading_rows = 1;
- const int n_rows = rel->sc[0].n_items + heading_rows ;
- const struct variable *wv = rel->wv;
- const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : & F_8_0;
- struct tab_table *tbl = tab_create (n_cols, n_rows);
- tab_set_format (tbl, RC_WEIGHT, wfmt);
- tab_headers (tbl, heading_columns, 0, heading_rows, 0);
-
- tab_title (tbl, _("Item-Total Statistics"));
-
- /* Vertical lines for the data only */
- tab_box (tbl,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- n_cols - 1, n_rows - 1);
-
- /* Box around table */
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, heading_rows);
-
- tab_vline (tbl, TAL_2, heading_columns, 0, n_rows - 1);
-
- tab_text (tbl, 1, 0, TAB_CENTER | TAT_TITLE,
- _("Scale Mean if Item Deleted"));
+ struct pivot_table *table = pivot_table_create (N_("Item-Total Statistics"));
- tab_text (tbl, 2, 0, TAB_CENTER | TAT_TITLE,
- _("Scale Variance if Item Deleted"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Scale Mean if Item Deleted"),
+ N_("Scale Variance if Item Deleted"),
+ N_("Corrected Item-Total Correlation"),
+ N_("Cronbach's Alpha if Item Deleted"));
- tab_text (tbl, 3, 0, TAB_CENTER | TAT_TITLE,
- _("Corrected Item-Total Correlation"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- tab_text (tbl, 4, 0, TAB_CENTER | TAT_TITLE,
- _("Cronbach's Alpha if Item Deleted"));
-
-
- for (i = 0 ; i < rel->sc[0].n_items; ++i)
+ for (size_t i = 0 ; i < rel->sc[0].n_items; ++i)
{
- double cov, item_to_total_r;
- double mean, weight, var;
-
const struct cronbach *s = &rel->sc[rel->total_start + i];
- tab_text (tbl, 0, heading_rows + i, TAB_LEFT| TAT_TITLE,
- var_to_string (rel->sc[0].items[i]));
-
- moments1_calculate (s->total, &weight, &mean, &var, 0, 0);
-
- tab_double (tbl, 1, heading_rows + i, TAB_RIGHT,
- mean, NULL, RC_OTHER);
-
- tab_double (tbl, 2, heading_rows + i, TAB_RIGHT,
- s->variance_of_sums, NULL, RC_OTHER);
-
- tab_double (tbl, 4, heading_rows + i, TAB_RIGHT,
- s->alpha, NULL, RC_OTHER);
-
- moments1_calculate (rel->sc[0].m[i], &weight, &mean, &var, 0,0);
- cov = rel->sc[0].variance_of_sums + var - s->variance_of_sums;
- cov /= 2.0;
-
- item_to_total_r = (cov - var) / (sqrt(var) * sqrt (s->variance_of_sums));
-
-
- tab_double (tbl, 3, heading_rows + i, TAB_RIGHT,
- item_to_total_r, NULL, RC_OTHER);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (rel->sc[0].items[i]));
+
+ double mean;
+ moments1_calculate (s->total, NULL, &mean, NULL, NULL, NULL);
+
+ double var;
+ moments1_calculate (rel->sc[0].m[i], NULL, NULL, &var, NULL, NULL);
+ double cov
+ = (rel->sc[0].variance_of_sums + var - s->variance_of_sums) / 2.0;
+
+ double entries[] = {
+ mean,
+ s->variance_of_sums,
+ (cov - var) / sqrt (var * s->variance_of_sums),
+ s->alpha,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, var_idx,
+ pivot_value_new_number (entries[i]));
}
-
- tab_submit (tbl);
+ pivot_table_submit (table);
}
-static void reliability_statistics_model_alpha (struct tab_table *tbl,
- const struct reliability *rel);
-
-static void reliability_statistics_model_split (struct tab_table *tbl,
- const struct reliability *rel);
-
-
-struct reliability_output_table
-{
- int n_cols;
- int n_rows;
- int heading_cols;
- int heading_rows;
- void (*populate) (struct tab_table *, const struct reliability *);
-};
-
-
-static struct reliability_output_table rol[2] =
- {
- { 2, 2, 1, 1, reliability_statistics_model_alpha},
- { 4, 9, 3, 0, reliability_statistics_model_split}
- };
-
static void
reliability_statistics (const struct reliability *rel)
{
- int n_cols = rol[rel->model].n_cols;
- int n_rows = rol[rel->model].n_rows;
- int heading_columns = rol[rel->model].heading_cols;
- int heading_rows = rol[rel->model].heading_rows;
- const struct variable *wv = rel->wv;
- const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : & F_8_0;
- struct tab_table *tbl = tab_create (n_cols, n_rows);
- tab_set_format (tbl, RC_WEIGHT, wfmt);
-
- tab_headers (tbl, heading_columns, 0, heading_rows, 0);
-
- tab_title (tbl, _("Reliability Statistics"));
-
- /* Vertical lines for the data only */
- tab_box (tbl,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- n_cols - 1, n_rows - 1);
-
- /* Box around table */
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, heading_rows);
-
- tab_vline (tbl, TAL_2, heading_columns, 0, n_rows - 1);
-
- if ( rel->model == MODEL_ALPHA )
- reliability_statistics_model_alpha (tbl, rel);
- else if (rel->model == MODEL_SPLIT )
- reliability_statistics_model_split (tbl, rel);
-
- tab_submit (tbl);
-}
-
-
-static void
-reliability_statistics_model_alpha (struct tab_table *tbl,
- const struct reliability *rel)
-{
- const struct cronbach *s = &rel->sc[0];
-
- tab_text (tbl, 0, 0, TAB_CENTER | TAT_TITLE,
- _("Cronbach's Alpha"));
-
- tab_text (tbl, 1, 0, TAB_CENTER | TAT_TITLE,
- _("N of Items"));
-
- tab_double (tbl, 0, 1, TAB_RIGHT, s->alpha, NULL, RC_OTHER);
-
- tab_double (tbl, 1, 1, TAB_RIGHT, s->n_items, NULL, RC_WEIGHT);
-}
-
-
-static void
-reliability_statistics_model_split (struct tab_table *tbl,
- const struct reliability *rel)
-{
- tab_text (tbl, 0, 0, TAB_LEFT,
- _("Cronbach's Alpha"));
-
- tab_text (tbl, 1, 0, TAB_LEFT,
- _("Part 1"));
-
- tab_text (tbl, 2, 0, TAB_LEFT,
- _("Value"));
-
- tab_text (tbl, 2, 1, TAB_LEFT,
- _("N of Items"));
-
- tab_text (tbl, 1, 2, TAB_LEFT,
- _("Part 2"));
-
- tab_text (tbl, 2, 2, TAB_LEFT,
- _("Value"));
+ struct pivot_table *table = pivot_table_create (
+ N_("Reliability Statistics"));
+ pivot_table_set_weight_var (table, rel->wv);
- tab_text (tbl, 2, 3, TAB_LEFT,
- _("N of Items"));
-
- tab_text (tbl, 1, 4, TAB_LEFT,
- _("Total N of Items"));
-
- tab_text (tbl, 0, 5, TAB_LEFT,
- _("Correlation Between Forms"));
-
- tab_text (tbl, 0, 6, TAB_LEFT,
- _("Spearman-Brown Coefficient"));
-
- tab_text (tbl, 1, 6, TAB_LEFT,
- _("Equal Length"));
-
- tab_text (tbl, 1, 7, TAB_LEFT,
- _("Unequal Length"));
-
-
- tab_text (tbl, 0, 8, TAB_LEFT,
- _("Guttman Split-Half Coefficient"));
-
-
-
- tab_double (tbl, 3, 0, TAB_RIGHT, rel->sc[1].alpha, NULL, RC_OTHER);
- tab_double (tbl, 3, 2, TAB_RIGHT, rel->sc[2].alpha, NULL, RC_OTHER);
-
- tab_double (tbl, 3, 1, TAB_RIGHT, rel->sc[1].n_items, NULL, RC_WEIGHT);
- tab_double (tbl, 3, 3, TAB_RIGHT, rel->sc[2].n_items, NULL, RC_WEIGHT);
-
- tab_double (tbl, 3, 4, TAB_RIGHT,
- rel->sc[1].n_items + rel->sc[2].n_items, NULL, RC_WEIGHT);
-
- {
- /* R is the correlation between the two parts */
- double r = rel->sc[0].variance_of_sums -
- rel->sc[1].variance_of_sums -
- rel->sc[2].variance_of_sums ;
-
- /* Guttman Split Half Coefficient */
- double g = 2 * r / rel->sc[0].variance_of_sums;
-
- /* Unequal Length Spearman Brown Coefficient, and
- intermediate value used in the computation thereof */
- double uly, tmp;
-
- r /= sqrt (rel->sc[1].variance_of_sums);
- r /= sqrt (rel->sc[2].variance_of_sums);
- r /= 2.0;
-
- tab_double (tbl, 3, 5, TAB_RIGHT, r, NULL, RC_OTHER);
-
- /* Equal length Spearman-Brown Coefficient */
- tab_double (tbl, 3, 6, TAB_RIGHT, 2 * r / (1.0 + r), NULL, RC_OTHER);
-
- tab_double (tbl, 3, 8, TAB_RIGHT, g, NULL, RC_OTHER);
-
- tmp = (1.0 - r*r) * rel->sc[1].n_items * rel->sc[2].n_items /
- pow2 (rel->sc[0].n_items);
-
- uly = sqrt( pow4 (r) + 4 * pow2 (r) * tmp);
- uly -= pow2 (r);
- uly /= 2 * tmp;
+ if (rel->model == MODEL_ALPHA)
+ {
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN,
+ N_("Statistics"),
+ N_("Cronbach's Alpha"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+
+ const struct cronbach *s = &rel->sc[0];
+ pivot_table_put1 (table, 0, pivot_value_new_number (s->alpha));
+ pivot_table_put1 (table, 1, pivot_value_new_number (s->n_items));
+ }
+ else
+ {
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"));
+ struct pivot_category *alpha = pivot_category_create_group (
+ statistics->root, N_("Cronbach's Alpha"));
+ pivot_category_create_group (alpha, N_("Part 1"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_group (alpha, N_("Part 2"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_leaves (alpha,
+ N_("Total N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_leaves (statistics->root,
+ N_("Correlation Between Forms"),
+ PIVOT_RC_OTHER);
+ pivot_category_create_group (statistics->root,
+ N_("Spearman-Brown Coefficient"),
+ N_("Equal Length"), PIVOT_RC_OTHER,
+ N_("Unequal Length"), PIVOT_RC_OTHER);
+ pivot_category_create_leaves (statistics->root,
+ N_("Guttman Split-Half Coefficient"),
+ PIVOT_RC_OTHER);
+
+ /* R is the correlation between the two parts */
+ double r0 = rel->sc[0].variance_of_sums -
+ rel->sc[1].variance_of_sums -
+ rel->sc[2].variance_of_sums ;
+ double r1 = (r0 / sqrt (rel->sc[1].variance_of_sums)
+ / sqrt (rel->sc[2].variance_of_sums)
+ / 2.0);
+
+ /* Guttman Split Half Coefficient */
+ double g = 2 * r0 / rel->sc[0].variance_of_sums;
+
+ double tmp = (1.0 - r1*r1) * rel->sc[1].n_items * rel->sc[2].n_items /
+ pow2 (rel->sc[0].n_items);
+
+ double entries[] = {
+ rel->sc[1].alpha,
+ rel->sc[1].n_items,
+ rel->sc[2].alpha,
+ rel->sc[2].n_items,
+ rel->sc[1].n_items + rel->sc[2].n_items,
+ r1,
+ 2 * r1 / (1.0 + r1),
+ (sqrt ( pow4 (r1) + 4 * pow2 (r1) * tmp) - pow2 (r1)) / (2 * tmp),
+ g,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put1 (table, i, pivot_value_new_number (entries[i]));
+ }
- tab_double (tbl, 3, 7, TAB_RIGHT, uly, NULL, RC_OTHER);
- }
+ pivot_table_submit (table);
}
-
#include "math/sort.h"
#include "output/chart-item.h"
#include "output/charts/roc-chart.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
static void
show_auc (struct roc_state *rs, const struct cmd_roc *roc)
{
- int i;
- const int n_fields = roc->print_se ? 5 : 1;
- const int n_cols = roc->n_vars > 1 ? n_fields + 1: n_fields;
- const int n_rows = 2 + roc->n_vars;
- struct tab_table *tbl = tab_create (n_cols, n_rows);
-
- if ( roc->n_vars > 1)
- tab_title (tbl, _("Area Under the Curve"));
- else
- tab_title (tbl, _("Area Under the Curve (%s)"), var_to_string (roc->vars[0]));
-
- tab_headers (tbl, n_cols - n_fields, 0, 1, 0);
-
-
- tab_text (tbl, n_cols - n_fields, 1, TAT_TITLE, _("Area"));
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, 2);
+ struct pivot_table *table = pivot_table_create (N_("Area Under the Curve"));
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1,
- n_rows - 1);
-
- if ( roc->print_se )
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Area"), PIVOT_RC_OTHER);
+ if (roc->print_se)
{
- tab_text (tbl, n_cols - 4, 1, TAT_TITLE, _("Std. Error"));
- tab_text (tbl, n_cols - 3, 1, TAT_TITLE, _("Asymptotic Sig."));
-
- tab_text (tbl, n_cols - 2, 1, TAT_TITLE, _("Lower Bound"));
- tab_text (tbl, n_cols - 1, 1, TAT_TITLE, _("Upper Bound"));
-
- tab_joint_text_format (tbl, n_cols - 2, 0, 4, 0,
- TAT_TITLE | TAB_CENTER,
- _("Asymp. %g%% Confidence Interval"), roc->ci);
- tab_vline (tbl, 0, n_cols - 1, 0, 0);
- tab_hline (tbl, TAL_1, n_cols - 2, n_cols - 1, 1);
+ pivot_category_create_leaves (
+ statistics->root,
+ N_("Std. Error"), PIVOT_RC_OTHER,
+ N_("Asymptotic Sig."), PIVOT_RC_SIGNIFICANCE);
+ struct pivot_category *interval = pivot_category_create_group__ (
+ statistics->root,
+ pivot_value_new_text_format (N_("Asymp. %g%% Confidence Interval"),
+ roc->ci));
+ pivot_category_create_leaves (interval,
+ N_("Lower Bound"), PIVOT_RC_OTHER,
+ N_("Upper Bound"), PIVOT_RC_OTHER);
}
- if ( roc->n_vars > 1)
- tab_text (tbl, 0, 1, TAT_TITLE, _("Variable under test"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variable under test"));
+ variables->root->show_label = true;
- if ( roc->n_vars > 1)
- tab_vline (tbl, TAL_2, 1, 0, n_rows - 1);
-
-
- for ( i = 0 ; i < roc->n_vars ; ++i )
+ for (size_t i = 0 ; i < roc->n_vars ; ++i )
{
- tab_text (tbl, 0, 2 + i, TAT_TITLE, var_to_string (roc->vars[i]));
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (roc->vars[i]));
- tab_double (tbl, n_cols - n_fields, 2 + i, 0, rs[i].auc, NULL, RC_OTHER);
+ pivot_table_put2 (table, 0, var_idx, pivot_value_new_number (rs[i].auc));
if ( roc->print_se )
{
- double se ;
- const double sd_0_5 = sqrt ((rs[i].n1 + rs[i].n2 + 1) /
- (12 * rs[i].n1 * rs[i].n2));
- double ci ;
- double yy ;
-
- se = rs[i].auc * (1 - rs[i].auc) + (rs[i].n1 - 1) * (rs[i].q1hat - pow2 (rs[i].auc)) +
- (rs[i].n2 - 1) * (rs[i].q2hat - pow2 (rs[i].auc));
-
+ double se = (rs[i].auc * (1 - rs[i].auc)
+ + (rs[i].n1 - 1) * (rs[i].q1hat - pow2 (rs[i].auc))
+ + (rs[i].n2 - 1) * (rs[i].q2hat - pow2 (rs[i].auc)));
se /= rs[i].n1 * rs[i].n2;
-
se = sqrt (se);
- tab_double (tbl, n_cols - 4, 2 + i, 0,
- se,
- NULL, RC_OTHER);
-
- ci = 1 - roc->ci / 100.0;
- yy = gsl_cdf_gaussian_Qinv (ci, se) ;
-
- tab_double (tbl, n_cols - 2, 2 + i, 0,
- rs[i].auc - yy,
- NULL, RC_OTHER);
-
- tab_double (tbl, n_cols - 1, 2 + i, 0,
- rs[i].auc + yy,
- NULL, RC_OTHER);
-
- tab_double (tbl, n_cols - 3, 2 + i, 0,
- 2.0 * gsl_cdf_ugaussian_Q (fabs ((rs[i].auc - 0.5 ) / sd_0_5)),
- NULL, RC_PVALUE);
+ double ci = 1 - roc->ci / 100.0;
+ double yy = gsl_cdf_gaussian_Qinv (ci, se);
+
+ double sd_0_5 = sqrt ((rs[i].n1 + rs[i].n2 + 1) /
+ (12 * rs[i].n1 * rs[i].n2));
+ double sig = 2.0 * gsl_cdf_ugaussian_Q (fabs ((rs[i].auc - 0.5)
+ / sd_0_5));
+ double entries[] = { se, sig, rs[i].auc - yy, rs[i].auc + yy };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i + 1, var_idx,
+ pivot_value_new_number (entries[i]));
}
}
- tab_submit (tbl);
+ pivot_table_submit (table);
}
static void
show_summary (const struct cmd_roc *roc)
{
- const int n_cols = 3;
- const int n_rows = 4;
- struct tab_table *tbl = tab_create (n_cols, n_rows);
-
- tab_title (tbl, _("Case Summary"));
-
- tab_headers (tbl, 1, 0, 2, 0);
-
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1,
- n_rows - 1);
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, 2);
- tab_vline (tbl, TAL_2, 1, 0, n_rows - 1);
-
-
- tab_hline (tbl, TAL_2, 1, n_cols - 1, 1);
- tab_vline (tbl, TAL_1, 2, 1, n_rows - 1);
-
+ struct pivot_table *table = pivot_table_create (N_("Case Summary"));
- tab_text (tbl, 0, 1, TAT_TITLE | TAB_LEFT, var_to_string (roc->state_var));
- tab_text (tbl, 1, 1, TAT_TITLE, _("Unweighted"));
- tab_text (tbl, 2, 1, TAT_TITLE, _("Weighted"));
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Valid N (listwise)"),
+ N_("Unweighted"), PIVOT_RC_INTEGER,
+ N_("Weighted"), PIVOT_RC_OTHER);
+ statistics->root->show_label = true;
- tab_joint_text (tbl, 1, 0, 2, 0,
- TAT_TITLE | TAB_CENTER,
- _("Valid N (listwise)"));
+ struct pivot_dimension *cases = pivot_dimension_create__ (
+ table, PIVOT_AXIS_ROW, pivot_value_new_variable (roc->state_var));
+ cases->root->show_label = true;
+ pivot_category_create_leaves (cases->root, N_("Positive"), N_("Negative"));
-
- tab_text (tbl, 0, 2, TAB_LEFT, _("Positive"));
- tab_text (tbl, 0, 3, TAB_LEFT, _("Negative"));
-
-
- tab_double (tbl, 1, 2, 0, roc->pos, NULL, RC_INTEGER);
- tab_double (tbl, 1, 3, 0, roc->neg, NULL, RC_INTEGER);
-
- tab_double (tbl, 2, 2, 0, roc->pos_weighted, NULL, RC_OTHER);
- tab_double (tbl, 2, 3, 0, roc->neg_weighted, NULL, RC_OTHER);
-
- tab_submit (tbl);
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, roc->pos },
+ { 0, 1, roc->neg },
+ { 1, 0, roc->pos_weighted },
+ { 1, 1, roc->neg_weighted },
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put2 (table, e->stat_idx, e->case_idx,
+ pivot_value_new_number (e->x));
+ }
+ pivot_table_submit (table);
}
-
static void
show_coords (struct roc_state *rs, const struct cmd_roc *roc)
{
- int x = 1;
- int i;
- const int n_cols = roc->n_vars > 1 ? 4 : 3;
- int n_rows = 1;
- struct tab_table *tbl ;
-
- for (i = 0; i < roc->n_vars; ++i)
- n_rows += casereader_count_cases (rs[i].cutpoint_rdr);
-
- tbl = tab_create (n_cols, n_rows);
+ struct pivot_table *table = pivot_table_create (
+ N_("Coordinates of the Curve"));
+ table->omit_empty = true;
- if ( roc->n_vars > 1)
- tab_title (tbl, _("Coordinates of the Curve"));
- else
- tab_title (tbl, _("Coordinates of the Curve (%s)"), var_to_string (roc->vars[0]));
-
-
- tab_headers (tbl, 1, 0, 1, 0);
-
- tab_hline (tbl, TAL_2, 0, n_cols - 1, 1);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Positive if greater than or equal to"),
+ N_("Sensitivity"), N_("1 - Specificity"));
- if ( roc->n_vars > 1)
- tab_text (tbl, 0, 0, TAT_TITLE, _("Test variable"));
+ struct pivot_dimension *coordinates = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Coordinates"));
+ coordinates->hide_all_labels = true;
- tab_text (tbl, n_cols - 3, 0, TAT_TITLE, _("Positive if greater than or equal to"));
- tab_text (tbl, n_cols - 2, 0, TAT_TITLE, _("Sensitivity"));
- tab_text (tbl, n_cols - 1, 0, TAT_TITLE, _("1 - Specificity"));
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Test variable"));
+ variables->root->show_label = true;
- tab_box (tbl,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- n_cols - 1,
- n_rows - 1);
- if ( roc->n_vars > 1)
- tab_vline (tbl, TAL_2, 1, 0, n_rows - 1);
-
- for (i = 0; i < roc->n_vars; ++i)
+ int n_coords = 0;
+ for (size_t i = 0; i < roc->n_vars; ++i)
{
- struct ccase *cc;
struct casereader *r = casereader_clone (rs[i].cutpoint_rdr);
- if ( roc->n_vars > 1)
- tab_text (tbl, 0, x, TAT_TITLE, var_to_string (roc->vars[i]));
-
- if ( i > 0)
- tab_hline (tbl, TAL_1, 0, n_cols - 1, x);
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (roc->vars[i]));
-
- for (; (cc = casereader_read (r)) != NULL;
- case_unref (cc), x++)
+ struct ccase *cc;
+ int coord_idx = 0;
+ for (; (cc = casereader_read (r)) != NULL; case_unref (cc))
{
const double se = case_data_idx (cc, ROC_TP)->f /
- (
- case_data_idx (cc, ROC_TP)->f
- +
- case_data_idx (cc, ROC_FN)->f
- );
+ (case_data_idx (cc, ROC_TP)->f + case_data_idx (cc, ROC_FN)->f);
const double sp = case_data_idx (cc, ROC_TN)->f /
- (
- case_data_idx (cc, ROC_TN)->f
- +
- case_data_idx (cc, ROC_FP)->f
- );
-
- tab_double (tbl, n_cols - 3, x, 0, case_data_idx (cc, ROC_CUTPOINT)->f,
- var_get_print_format (roc->vars[i]), RC_OTHER);
-
- tab_double (tbl, n_cols - 2, x, 0, se, NULL, RC_OTHER);
- tab_double (tbl, n_cols - 1, x, 0, 1 - sp, NULL, RC_OTHER);
+ (case_data_idx (cc, ROC_TN)->f + case_data_idx (cc, ROC_FP)->f);
+
+ pivot_table_put3 (
+ table, 0, coord_idx, var_idx,
+ pivot_value_new_var_value (roc->vars[i],
+ case_data_idx (cc, ROC_CUTPOINT)));
+
+ pivot_table_put3 (table, 1, coord_idx, var_idx,
+ pivot_value_new_number (se));
+ pivot_table_put3 (table, 2, coord_idx, var_idx,
+ pivot_value_new_number (1 - sp));
+ coord_idx++;
}
+ if (coord_idx > n_coords)
+ n_coords = coord_idx;
+
casereader_destroy (r);
}
- tab_submit (tbl);
+ for (size_t i = 0; i < n_coords; i++)
+ pivot_category_create_leaf (coordinates->root,
+ pivot_value_new_integer (i + 1));
+
+ pivot_table_submit (table);
}
#include "libpspp/misc.h"
#include "math/percentiles.h"
#include "math/sort.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static void
show_runs_result (const struct runs_test *rt, const struct run_state *rs, const struct dictionary *dict)
{
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
const struct one_sample_test *otp = &rt->parent;
- int i;
- const int row_headers = 1;
- const int column_headers = 1;
- struct tab_table *table =
- tab_create (row_headers + otp->n_vars, column_headers + 7);
- tab_set_format (table, RC_WEIGHT, wfmt);
-
- tab_headers (table, row_headers, 0, column_headers, 0);
-
- tab_title (table, _("Runs Test"));
-
- /* Box around the table and vertical lines inside*/
- tab_box (table, TAL_2, TAL_2, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- tab_hline (table, TAL_2, 0, tab_nc (table) -1, column_headers);
- tab_vline (table, TAL_2, row_headers, 0, tab_nr (table) - 1);
-
- for (i = 0 ; i < otp->n_vars; ++i)
+ struct pivot_table *table = pivot_table_create (N_("Runs Test"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+
+ pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ (rt->cp_mode == CP_CUSTOM ? N_("Test Value")
+ : rt->cp_mode == CP_MODE ? N_("Test Value (mode)")
+ : rt->cp_mode == CP_MEAN ? N_("Test Value (mean)")
+ : N_("Test Value (median)")), PIVOT_RC_OTHER,
+ N_("Cases < Test Value"), PIVOT_RC_COUNT,
+ N_("Cases ≥ Test Value"), PIVOT_RC_COUNT,
+ N_("Total Cases"), PIVOT_RC_COUNT,
+ N_("Number of Runs"), PIVOT_RC_INTEGER,
+ N_("Z"), PIVOT_RC_OTHER,
+ N_("Asymp. Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Variable"));
+
+ for (size_t i = 0 ; i < otp->n_vars; ++i)
{
const struct run_state *run = &rs[i];
- double z = runs_statistic (run);
-
- tab_text (table, row_headers + i, 0,
- TAT_TITLE | TAB_CENTER ,
- var_to_string (otp->vars[i]));
-
- tab_double (table, row_headers +i, 1, 0,
- run->cutpoint, NULL, RC_OTHER);
+ int col = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (otp->vars[i]));
- tab_double (table, row_headers +i, 2, 0,
- run->nn, NULL, RC_WEIGHT);
-
- tab_double (table, row_headers +i, 3, 0,
- run->np, NULL, RC_WEIGHT);
-
- tab_double (table, row_headers +i, 4, 0,
- run->n, NULL, RC_WEIGHT);
-
- tab_double (table, row_headers +i, 5, 0,
- run->runs, NULL, RC_INTEGER);
-
- tab_double (table, row_headers +i, 6, 0,
- z, NULL, RC_OTHER);
-
- tab_double (table, row_headers +i, 7, 0,
- 2.0 * (1.0 - gsl_cdf_ugaussian_P (z)), NULL, RC_PVALUE);
- }
+ double z = runs_statistic (run);
- switch ( rt->cp_mode)
- {
- case CP_CUSTOM:
- tab_text (table, 0, column_headers ,
- TAT_TITLE | TAB_LEFT , _("Test Value"));
- break;
- case CP_MODE:
- tab_text (table, 0, column_headers ,
- TAT_TITLE | TAB_LEFT , _("Test Value (mode)"));
- break;
- case CP_MEAN:
- tab_text (table, 0, column_headers ,
- TAT_TITLE | TAB_LEFT , _("Test Value (mean)"));
- break;
- case CP_MEDIAN:
- tab_text (table, 0, column_headers ,
- TAT_TITLE | TAB_LEFT , _("Test Value (median)"));
- break;
+ double rows[] = {
+ run->cutpoint,
+ run->nn,
+ run->np,
+ run->n,
+ run->runs,
+ z,
+ 2.0 * (1.0 - gsl_cdf_ugaussian_P (z)),
+ };
+
+ for (int row = 0; row < sizeof rows / sizeof *rows; row++)
+ pivot_table_put2 (table, row, col, pivot_value_new_number (rows[row]));
}
- tab_text (table, 0, column_headers + 1,
- TAT_TITLE | TAB_LEFT , _("Cases < Test Value"));
-
- tab_text (table, 0, column_headers + 2,
- TAT_TITLE | TAB_LEFT , _("Cases ≥ Test Value"));
-
- tab_text (table, 0, column_headers + 3,
- TAT_TITLE | TAB_LEFT , _("Total Cases"));
-
- tab_text (table, 0, column_headers + 4,
- TAT_TITLE | TAB_LEFT , _("Number of Runs"));
-
- tab_text (table, 0, column_headers + 5,
- TAT_TITLE | TAB_LEFT , _("Z"));
-
- tab_text (table, 0, column_headers + 6,
- TAT_TITLE | TAB_LEFT , _("Asymp. Sig. (2-tailed)"));
-
- tab_submit (table);
+ pivot_table_submit (table);
}
-
-
#include "data/variable.h"
#include "language/stats/npar.h"
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gl/xalloc.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
struct sign_test_params
double point_prob;
};
+static int
+add_pair_leaf (struct pivot_dimension *dimension, variable_pair *pair)
+{
+ char *label = xasprintf ("%s - %s", var_to_string ((*pair)[0]),
+ var_to_string ((*pair)[1]));
+ return pivot_category_create_leaf (
+ dimension->root,
+ pivot_value_new_user_text_nocopy (label));
+}
static void
output_frequency_table (const struct two_sample_test *t2s,
const struct sign_test_params *param,
const struct dictionary *dict)
{
- int i;
- struct tab_table *table = tab_create (3, 1 + 4 * t2s->n_pairs);
-
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
-
- tab_set_format (table, RC_WEIGHT, wfmt);
- tab_title (table, _("Frequencies"));
-
- tab_headers (table, 2, 0, 1, 0);
+ struct pivot_table *table = pivot_table_create (N_("Frequencies"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- /* Vertical lines inside the box */
- tab_box (table, 0, 0, -1, TAL_1,
- 1, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("N"),
+ N_("N"), PIVOT_RC_COUNT);
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Differences"),
+ N_("Negative Differences"),
+ N_("Positive Differences"),
+ N_("Ties"), N_("Total"));
- tab_text (table, 2, 0, TAB_CENTER, _("N"));
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Pairs"));
- for (i = 0 ; i < t2s->n_pairs; ++i)
+ for (size_t i = 0 ; i < t2s->n_pairs; ++i)
{
variable_pair *vp = &t2s->pairs[i];
- struct string pair_name;
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " - ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
+ int pair_idx = add_pair_leaf (pairs, vp);
-
- tab_text (table, 0, 1 + i * 4, TAB_LEFT, ds_cstr (&pair_name));
-
- ds_destroy (&pair_name);
-
- tab_hline (table, TAL_1, 0, tab_nc (table) - 1, 1 + i * 4);
-
- tab_text (table, 1, 1 + i * 4, TAB_LEFT, _("Negative Differences"));
- tab_text (table, 1, 2 + i * 4, TAB_LEFT, _("Positive Differences"));
- tab_text (table, 1, 3 + i * 4, TAB_LEFT, _("Ties"));
- tab_text (table, 1, 4 + i * 4, TAB_LEFT, _("Total"));
-
- tab_double (table, 2, 1 + i * 4, TAB_RIGHT, param[i].neg, NULL, RC_WEIGHT);
- tab_double (table, 2, 2 + i * 4, TAB_RIGHT, param[i].pos, NULL, RC_WEIGHT);
- tab_double (table, 2, 3 + i * 4, TAB_RIGHT, param[i].ties, NULL, RC_WEIGHT);
- tab_double (table, 2, 4 + i * 4, TAB_RIGHT,
- param[i].ties + param[i].neg + param[i].pos, NULL, RC_WEIGHT);
+ const struct sign_test_params *p = ¶m[i];
+ double values[] = { p->neg, p->pos, p->ties, p->ties + p->neg + p->pos };
+ for (size_t j = 0; j < sizeof values / sizeof *values; j++)
+ pivot_table_put3 (table, 0, j, pair_idx,
+ pivot_value_new_number (values[j]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
static void
output_statistics_table (const struct two_sample_test *t2s,
const struct sign_test_params *param)
{
- int i;
- struct tab_table *table = tab_create (1 + t2s->n_pairs, 4);
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
- tab_title (table, _("Test Statistics"));
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Exact Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Exact Sig. (1-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Point Probability"), PIVOT_RC_SIGNIFICANCE);
- tab_headers (table, 0, 1, 0, 1);
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Pairs"));
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, 1);
- tab_vline (table, TAL_2, 1, 0, tab_nr (table) - 1);
-
-
- /* Vertical lines inside the box */
- tab_box (table, -1, -1, -1, TAL_1,
- 0, 0,
- tab_nc (table) - 1, tab_nr (table) - 1);
-
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1,
- tab_nr (table) - 1);
-
- tab_text (table, 0, 1, TAT_TITLE | TAB_LEFT,
- _("Exact Sig. (2-tailed)"));
-
- tab_text (table, 0, 2, TAT_TITLE | TAB_LEFT,
- _("Exact Sig. (1-tailed)"));
-
- tab_text (table, 0, 3, TAT_TITLE | TAB_LEFT,
- _("Point Probability"));
-
- for (i = 0 ; i < t2s->n_pairs; ++i)
+ for (size_t i = 0 ; i < t2s->n_pairs; ++i)
{
variable_pair *vp = &t2s->pairs[i];
-
- struct string pair_name;
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " - ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
-
- tab_text (table, 1 + i, 0, TAB_LEFT, ds_cstr (&pair_name));
- ds_destroy (&pair_name);
-
- tab_double (table, 1 + i, 1, TAB_RIGHT,
- param[i].one_tailed_sig * 2, NULL, RC_PVALUE);
-
- tab_double (table, 1 + i, 2, TAB_RIGHT, param[i].one_tailed_sig, NULL, RC_PVALUE);
- tab_double (table, 1 + i, 3, TAB_RIGHT, param[i].point_prob, NULL, RC_PVALUE);
+ int pair_idx = add_pair_leaf (pairs, vp);
+
+ const struct sign_test_params *p = ¶m[i];
+ double values[] = { p->one_tailed_sig * 2,
+ p->one_tailed_sig,
+ p->point_prob };
+ for (size_t j = 0; j < sizeof values / sizeof *values; j++)
+ pivot_table_put2 (table, j, pair_idx,
+ pivot_value_new_number (values[j]));
}
- tab_submit (table);
+ pivot_table_submit (table);
}
void
#include "data/dictionary.h"
#include "data/format.h"
#include "data/variable.h"
-
#include "math/moments.h"
#include "math/levene.h"
+#include "output/pivot-table.h"
-#include <output/tab.h>
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
static void
indep_summary (const struct tt *tt, struct indep_samples *is, const struct pair_stats *ps)
{
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
-
- int v;
- int cols = 6;
- const int heading_rows = 1;
- int rows = tt->n_vars * 2 + heading_rows;
-
- struct string vallab0 ;
- struct string vallab1 ;
- struct tab_table *t = tab_create (cols, rows);
- tab_set_format (t, RC_WEIGHT, wfmt);
- ds_init_empty (&vallab0);
- ds_init_empty (&vallab1);
-
- tab_headers (t, 0, 0, 1, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_title (t, _("Group Statistics"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, var_to_string (is->gvar));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("S.E. Mean"));
-
+ struct pivot_table *table = pivot_table_create (N_("Group Statistics"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *group = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Group"));
+ group->root->show_label = true;
if (is->cut)
{
+ struct string vallab0 = DS_EMPTY_INITIALIZER;
ds_put_cstr (&vallab0, "≥");
- ds_put_cstr (&vallab1, "<");
-
var_append_value_name (is->gvar, is->gval0, &vallab0);
+ pivot_category_create_leaf (group->root,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&vallab0)));
+
+ struct string vallab1 = DS_EMPTY_INITIALIZER;
+ ds_put_cstr (&vallab1, "<");
var_append_value_name (is->gvar, is->gval0, &vallab1);
+ pivot_category_create_leaf (group->root,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&vallab1)));
}
else
{
- var_append_value_name (is->gvar, is->gval0, &vallab0);
- var_append_value_name (is->gvar, is->gval1, &vallab1);
+ pivot_category_create_leaf (
+ group->root, pivot_value_new_var_value (is->gvar, is->gval0));
+ pivot_category_create_leaf (
+ group->root, pivot_value_new_var_value (is->gvar, is->gval1));
}
- tab_vline (t, TAL_1, 1, heading_rows, rows - 1);
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- for (v = 0; v < tt->n_vars; ++v)
+ for (size_t v = 0; v < tt->n_vars; ++v)
{
- int i;
const struct variable *var = tt->vars[v];
- tab_text (t, 0, v * 2 + heading_rows, TAB_LEFT,
- var_to_string (var));
-
- tab_text (t, 1, v * 2 + heading_rows, TAB_LEFT,
- ds_cstr (&vallab0));
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (var));
- tab_text (t, 1, v * 2 + 1 + heading_rows, TAB_LEFT,
- ds_cstr (&vallab1));
-
- for (i = 0 ; i < 2; ++i)
+ for (int i = 0 ; i < 2; ++i)
{
double cc, mean, sigma;
moments_calculate (ps[v].mom[i], &cc, &mean, &sigma, NULL, NULL);
- tab_double (t, 2, v * 2 + i + heading_rows, TAB_RIGHT, cc, NULL, RC_WEIGHT);
- tab_double (t, 3, v * 2 + i + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 4, v * 2 + i + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 5, v * 2 + i + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL, RC_OTHER);
+ double entries[] = { cc, mean, sqrt (sigma), sqrt (sigma / cc) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put3 (table, j, i, dep_var_idx,
+ pivot_value_new_number (entries[j]));
}
}
- tab_submit (t);
-
- ds_destroy (&vallab0);
- ds_destroy (&vallab1);
+ pivot_table_submit (table);
}
static void
indep_test (const struct tt *tt, const struct pair_stats *ps)
{
- int v;
- const int heading_rows = 3;
- const int rows= tt->n_vars * 2 + heading_rows;
-
- const size_t cols = 11;
-
- struct tab_table *t = tab_create (cols, rows);
- tab_headers (t, 0, 0, 3, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 3);
-
- tab_title (t, _("Independent Samples Test"));
-
- tab_hline (t, TAL_1, 2, cols - 1, 1);
- tab_vline (t, TAL_2, 2, 0, rows - 1);
- tab_vline (t, TAL_1, 4, 0, rows - 1);
- tab_box (t, -1, -1, -1, TAL_1, 2, 1, cols - 2, rows - 1);
- tab_hline (t, TAL_1, cols - 2, cols - 1, 2);
- tab_box (t, -1, -1, -1, TAL_1, cols - 2, 2, cols - 1, rows - 1);
- tab_joint_text (t, 2, 0, 3, 0, TAB_CENTER, _("Levene's Test for Equality of Variances"));
- tab_joint_text (t, 4, 0, cols - 1, 0, TAB_CENTER, _("t-test for Equality of Means"));
-
- tab_text (t, 2, 2, TAB_CENTER | TAT_TITLE, _("F"));
- tab_text (t, 3, 2, TAB_CENTER | TAT_TITLE, _("Sig."));
- tab_text (t, 4, 2, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 5, 2, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 6, 2, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
- tab_text (t, 7, 2, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 8, 2, TAB_CENTER | TAT_TITLE, _("Std. Error Difference"));
- tab_text (t, 9, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 10, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
-
- tab_joint_text_format (t, 9, 1, 10, 1, TAB_CENTER,
- _("%g%% Confidence Interval of the Difference"),
- tt->confidence * 100.0);
-
- tab_vline (t, TAL_1, 1, heading_rows, rows - 1);
-
- for (v = 0; v < tt->n_vars; ++v)
+ struct pivot_table *table = pivot_table_create (
+ N_("Independent Samples Test"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_group (
+ statistics->root, N_("Levene's Test for Equality of Variances"),
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+ struct pivot_category *group = pivot_category_create_group (
+ statistics->root, N_("T-Test for Equality of Means"),
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_OTHER,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Mean Difference"), PIVOT_RC_OTHER,
+ N_("Std. Error Difference"), PIVOT_RC_OTHER);
+ pivot_category_create_group (
+ group, N_("95% Confidence Interval of the Difference"),
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumptions"),
+ N_("Equal variances assumed"),
+ N_("Equal variances not assumed"));
+
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (size_t v = 0; v < tt->n_vars; ++v)
{
- double df, pooled_variance, mean_diff, tval;
- double se2, std_err_diff;
- double p, q;
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (tt->vars[v]));
+
double cc0, mean0, sigma0;
double cc1, mean1, sigma1;
moments_calculate (ps[v].mom[0], &cc0, &mean0, &sigma0, NULL, NULL);
moments_calculate (ps[v].mom[1], &cc1, &mean1, &sigma1, NULL, NULL);
- tab_text (t, 0, v * 2 + heading_rows, TAB_LEFT, var_to_string (tt->vars[v]));
- tab_text (t, 1, v * 2 + heading_rows, TAB_LEFT, _("Equal variances assumed"));
-
- df = cc0 + cc1 - 2.0;
- tab_double (t, 5, v * 2 + heading_rows, TAB_RIGHT, df, NULL, RC_OTHER);
-
- pooled_variance = ((cc0 - 1)* sigma0 + (cc1 - 1) * sigma1) / df ;
-
- tval = (mean0 - mean1) / sqrt (pooled_variance);
- tval /= sqrt ((cc0 + cc1) / (cc0 * cc1));
-
- tab_double (t, 4, v * 2 + heading_rows, TAB_RIGHT, tval, NULL, RC_OTHER);
+ double mean_diff = mean0 - mean1;
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
- mean_diff = mean0 - mean1;
-
- tab_double (t, 6, v * 2 + heading_rows, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL, RC_PVALUE);
- tab_double (t, 7, v * 2 + heading_rows, TAB_RIGHT, mean_diff, NULL, RC_OTHER);
-
- std_err_diff = sqrt (pooled_variance * (1.0/cc0 + 1.0/cc1));
- tab_double (t, 8, v * 2 + heading_rows, TAB_RIGHT, std_err_diff, NULL, RC_OTHER);
-
-
- /* Now work out the confidence interval */
- q = (1 - tt->confidence)/2.0; /* 2-tailed test */
-
- tval = gsl_cdf_tdist_Qinv (q, df);
- tab_double (t, 9, v * 2 + heading_rows, TAB_RIGHT, mean_diff - tval * std_err_diff, NULL, RC_OTHER);
- tab_double (t, 10, v * 2 + heading_rows, TAB_RIGHT, mean_diff + tval * std_err_diff, NULL, RC_OTHER);
+ /* Equal variances assumed. */
+ double e_df = cc0 + cc1 - 2.0;
+ double e_pooled_variance = ((cc0 - 1)* sigma0 + (cc1 - 1) * sigma1) / e_df;
+ double e_tval = ((mean0 - mean1) / sqrt (e_pooled_variance)
+ / sqrt ((cc0 + cc1) / (cc0 * cc1)));
+ double e_p = gsl_cdf_tdist_P (e_tval, e_df);
+ double e_q = gsl_cdf_tdist_Q (e_tval, e_df);
+ double e_sig = 2.0 * (e_tval > 0 ? e_q : e_p);
+ double e_std_err_diff = sqrt (e_pooled_variance * (1.0/cc0 + 1.0/cc1));
+ double e_tval_qinv = gsl_cdf_tdist_Qinv ((1 - tt->confidence) / 2.0, e_df);
/* Equal variances not assumed */
- tab_text (t, 1, v * 2 + heading_rows + 1, TAB_LEFT, _("Equal variances not assumed"));
- std_err_diff = sqrt ((sigma0 / cc0) + (sigma1 / cc1));
-
- se2 = sigma0 / cc0 + sigma1 / cc1;
- tval = mean_diff / sqrt (se2);
- tab_double (t, 4, v * 2 + heading_rows + 1, TAB_RIGHT, tval, NULL, RC_OTHER);
-
- {
- double p, q;
- const double s0 = sigma0 / (cc0);
- const double s1 = sigma1 / (cc1);
- double df = pow2 (s0 + s1) ;
- df /= pow2 (s0) / (cc0 - 1) + pow2 (s1) / (cc1 - 1);
-
- tab_double (t, 5, v * 2 + heading_rows + 1, TAB_RIGHT, df, NULL, RC_OTHER);
-
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
-
- tab_double (t, 6, v * 2 + heading_rows + 1, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL, RC_PVALUE);
-
- /* Now work out the confidence interval */
- q = (1 - tt->confidence) / 2.0; /* 2-tailed test */
-
- tval = gsl_cdf_tdist_Qinv (q, df);
- }
-
- tab_double (t, 7, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff, NULL, RC_OTHER);
- tab_double (t, 8, v * 2 + heading_rows + 1, TAB_RIGHT, std_err_diff, NULL, RC_OTHER);
- tab_double (t, 9, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff - tval * std_err_diff, NULL, RC_OTHER);
- tab_double (t, 10, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff + tval * std_err_diff, NULL, RC_OTHER);
-
- tab_double (t, 2, v * 2 + heading_rows, TAB_CENTER, ps[v].lev, NULL, RC_OTHER);
-
-
- {
- /* Now work out the significance of the Levene test */
- double df1 = 1;
- double df2 = cc0 + cc1 - 2;
- double q = gsl_cdf_fdist_Q (ps[v].lev, df1, df2);
- tab_double (t, 3, v * 2 + heading_rows, TAB_CENTER, q, NULL, RC_PVALUE);
- }
+ const double s0 = sigma0 / cc0;
+ const double s1 = sigma1 / cc1;
+ double d_df = (pow2 (s0 + s1) / (pow2 (s0) / (cc0 - 1)
+ + pow2 (s1) / (cc1 - 1)));
+ double d_tval = mean_diff / sqrt (sigma0 / cc0 + sigma1 / cc1);
+ double d_p = gsl_cdf_tdist_P (d_tval, d_df);
+ double d_q = gsl_cdf_tdist_Q (d_tval, d_df);
+ double d_sig = 2.0 * (d_tval > 0 ? d_q : d_p);
+ double d_std_err_diff = sqrt ((sigma0 / cc0) + (sigma1 / cc1));
+ double d_tval_qinv = gsl_cdf_tdist_Qinv ((1 - tt->confidence) / 2.0, d_df);
+
+ struct entry
+ {
+ int assumption_idx;
+ int stat_idx;
+ double x;
+ }
+ entries[] =
+ {
+ { 0, 0, ps[v].lev },
+ { 0, 1, gsl_cdf_fdist_Q (ps[v].lev, 1, cc0 + cc1 - 2) },
+
+ { 0, 2, e_tval },
+ { 0, 3, e_df },
+ { 0, 4, e_sig },
+ { 0, 5, mean_diff },
+ { 0, 6, e_std_err_diff },
+ { 0, 7, mean_diff - e_tval_qinv * e_std_err_diff },
+ { 0, 8, mean_diff + e_tval_qinv * e_std_err_diff },
+
+ { 1, 2, d_tval },
+ { 1, 3, d_df },
+ { 1, 4, d_sig },
+ { 1, 5, mean_diff },
+ { 1, 6, d_std_err_diff },
+ { 1, 7, mean_diff - d_tval_qinv * d_std_err_diff },
+ { 1, 8, mean_diff + d_tval_qinv * d_std_err_diff },
+ };
+
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put3 (table, e->stat_idx, e->assumption_idx,
+ dep_var_idx, pivot_value_new_number (e->x));
+ }
}
- tab_submit (t);
+ pivot_table_submit (table);
}
#include "libpspp/hmapx.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
{
const struct variable *var;
- /* The position for reporting purposes */
- int posn;
-
/* N, Mean, Variance */
struct moments *mom;
struct one_samp
{
- struct hmapx hmap;
+ struct per_var_stats *stats;
+ size_t n_stats;
double testval;
};
static void
one_sample_test (const struct tt *tt, const struct one_samp *os)
{
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
- const int heading_rows = 3;
- const size_t rows = heading_rows + tt->n_vars;
- const size_t cols = 7;
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
-
- struct tab_table *t = tab_create (cols, rows);
- tab_set_format (t, RC_WEIGHT, wfmt);
-
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 3);
-
- tab_title (t, _("One-Sample Test"));
- tab_hline (t, TAL_1, 1, cols - 1, 1);
- tab_vline (t, TAL_2, 1, 0, rows - 1);
-
- tab_joint_text_format (t, 1, 0, cols - 1, 0, TAB_CENTER,
- _("Test Value = %f"), os->testval);
-
- tab_box (t, -1, -1, -1, TAL_1, 1, 1, cols - 1, rows - 1);
-
- tab_joint_text_format (t, 5, 1, 6, 1, TAB_CENTER,
- _("%g%% Confidence Interval of the Difference"),
- tt->confidence * 100.0);
-
- tab_hline (t, TAL_1, 5, 6, 2);
- tab_text (t, 1, 2, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 2, 2, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 3, 2, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
- tab_text (t, 4, 2, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 5, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 6, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
-
- HMAPX_FOR_EACH (per_var_stats, node, &os->hmap)
+ struct pivot_table *table = pivot_table_create (N_("One-Sample Test"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ struct pivot_category *group = pivot_category_create_group__ (
+ statistics->root, pivot_value_new_user_text_nocopy (
+ xasprintf (_("Test Value = %.*g"), DBL_DIG + 1, os->testval)));
+ pivot_category_create_leaves (
+ group,
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Mean Difference"), PIVOT_RC_OTHER);
+ struct pivot_category *subgroup = pivot_category_create_group__ (
+ group, pivot_value_new_user_text_nocopy (
+ xasprintf (_("%g%% Confidence Interval of the Difference"),
+ tt->confidence * 100.0)));
+ pivot_category_create_leaves (subgroup,
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (size_t i = 0; i < os->n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os->stats[i];
const struct moments *m = per_var_stats->mom;
- double cc, mean, sigma;
- double tval, df;
- double p, q;
- double mean_diff;
- double se_mean ;
- const int v = per_var_stats->posn;
-
- moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
-
- tval = (mean - os->testval) * sqrt (cc / sigma);
-
- mean_diff = per_var_stats->sum_diff / cc;
- se_mean = sqrt (sigma / cc);
- df = cc - 1.0;
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
-
- tab_text (t, 0, v + heading_rows, TAB_LEFT, var_to_string (per_var_stats->var));
- tab_double (t, 1, v + heading_rows, TAB_RIGHT, tval, NULL, RC_OTHER);
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, df, NULL, RC_WEIGHT);
- /* Multiply by 2 to get 2-tailed significance, makeing sure we've got
- the correct tail*/
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL, RC_PVALUE);
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (per_var_stats->var));
- tab_double (t, 4, v + heading_rows, TAB_RIGHT, mean_diff, NULL, RC_OTHER);
-
- tval = gsl_cdf_tdist_Qinv ( (1.0 - tt->confidence) / 2.0, df);
-
- tab_double (t, 5, v + heading_rows, TAB_RIGHT, mean_diff - tval * se_mean, NULL, RC_OTHER);
- tab_double (t, 6, v + heading_rows, TAB_RIGHT, mean_diff + tval * se_mean, NULL, RC_OTHER);
+ double cc, mean, sigma;
+ moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
+ double tval = (mean - os->testval) * sqrt (cc / sigma);
+ double mean_diff = per_var_stats->sum_diff / cc;
+ double se_mean = sqrt (sigma / cc);
+ double df = cc - 1.0;
+ double p = gsl_cdf_tdist_P (tval, df);
+ double q = gsl_cdf_tdist_Q (tval, df);
+ double sig = 2.0 * (tval > 0 ? q : p);
+ double tval_qinv = gsl_cdf_tdist_Qinv ((1.0 - tt->confidence) / 2.0, df);
+ double lower = mean_diff - tval_qinv * se_mean;
+ double upper = mean_diff + tval_qinv * se_mean;
+
+ double entries[] = { tval, df, sig, mean_diff, lower, upper };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, dep_var_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
one_sample_summary (const struct tt *tt, const struct one_samp *os)
{
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
- const int cols = 5;
- const int heading_rows = 1;
- const int rows = tt->n_vars + heading_rows;
- struct tab_table *t = tab_create (cols, rows);
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_title (t, _("One-Sample Statistics"));
- tab_vline (t, TAL_2, 1, 0, rows - 1);
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("S.E. Mean"));
-
- HMAPX_FOR_EACH (per_var_stats, node, &os->hmap)
+ struct pivot_table *table = pivot_table_create (N_("One-Sample Statistics"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t i = 0; i < os->n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os->stats[i];
const struct moments *m = per_var_stats->mom;
- const int v = per_var_stats->posn;
+
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (per_var_stats->var));
+
double cc, mean, sigma;
moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
- tab_text (t, 0, v + heading_rows, TAB_LEFT, var_to_string (per_var_stats->var));
- tab_double (t, 1, v + heading_rows, TAB_RIGHT, cc, NULL, RC_WEIGHT);
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 4, v + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL, RC_OTHER);
+ double entries[] = { cc, mean, sqrt (sigma), sqrt (sigma / cc) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, var_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
void
one_sample_run (const struct tt *tt, double testval, struct casereader *reader)
{
- int i;
- struct ccase *c;
struct one_samp os;
- struct casereader *r;
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
os.testval = testval;
- hmapx_init (&os.hmap);
-
- /* Insert all the variables into the map */
- for (i = 0; i < tt->n_vars; ++i)
+ os.stats = xcalloc (tt->n_vars, sizeof *os.stats);
+ os.n_stats = tt->n_vars;
+ for (size_t i = 0; i < tt->n_vars; ++i)
{
- struct per_var_stats *per_var_stats = xzalloc (sizeof (*per_var_stats));
-
- per_var_stats->posn = i;
+ struct per_var_stats *per_var_stats = &os.stats[i];
per_var_stats->var = tt->vars[i];
per_var_stats->mom = moments_create (MOMENT_VARIANCE);
-
- hmapx_insert (&os.hmap, per_var_stats, hash_pointer (per_var_stats->var, 0));
}
- r = casereader_clone (reader);
+ struct casereader *r = casereader_clone (reader);
+ struct ccase *c;
for ( ; (c = casereader_read (r) ); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
- {
+ for (size_t i = 0; i < os.n_stats; i++)
+ {
+ const struct per_var_stats *per_var_stats = &os.stats[i];
const struct variable *var = per_var_stats->var;
const union value *val = case_data (c, var);
if (var_is_value_missing (var, val, tt->exclude))
for ( ; (c = casereader_read (r) ); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
- {
+ for (size_t i = 0; i < os.n_stats; i++)
+ {
+ struct per_var_stats *per_var_stats = &os.stats[i];
const struct variable *var = per_var_stats->var;
const union value *val = case_data (c, var);
if (var_is_value_missing (var, val, tt->exclude))
one_sample_summary (tt, &os);
one_sample_test (tt, &os);
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
+ for (size_t i = 0; i < os.n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os.stats[i];
moments_destroy (per_var_stats->mom);
- free (per_var_stats);
}
-
- hmapx_destroy (&os.hmap);
+ free (os.stats);
}
#include "data/dictionary.h"
#include "data/format.h"
#include "data/variable.h"
-#include "libpspp/hmapx.h"
-#include "libpspp/hash-functions.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
struct pair_stats
{
- int posn;
double sum_of_prod;
struct moments *mom0;
const struct variable *var0;
struct paired_samp
{
- struct hmapx hmap;
+ struct pair_stats *ps;
+ size_t n_ps;
};
static void paired_summary (const struct tt *tt, struct paired_samp *os);
void
paired_run (const struct tt *tt, size_t n_pairs, vp *pairs, struct casereader *reader)
{
- int i;
struct ccase *c;
struct paired_samp ps;
struct casereader *r;
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
- hmapx_init (&ps.hmap);
-
- for (i = 0; i < n_pairs; ++i)
+ ps.ps = xcalloc (n_pairs, sizeof *ps.ps);
+ ps.n_ps = n_pairs;
+ for (size_t i = 0; i < n_pairs; ++i)
{
vp *pair = &pairs[i];
- unsigned int hash;
- struct pair_stats *pp = xzalloc (sizeof *pp);
- pp->posn = i;
+ struct pair_stats *pp = &ps.ps[i];
pp->var0 = (*pair)[0];
pp->var1 = (*pair)[1];
pp->mom0 = moments_create (MOMENT_VARIANCE);
pp->mom1 = moments_create (MOMENT_VARIANCE);
pp->mom_diff = moments_create (MOMENT_VARIANCE);
-
- hash = hash_pointer ((*pair)[0], 0);
- hash = hash_pointer ((*pair)[1], hash);
-
- hmapx_insert (&ps.hmap, pp, hash);
}
r = casereader_clone (reader);
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
- HMAPX_FOR_EACH (pp, node, &ps.hmap)
+ for (int i = 0; i < ps.n_ps; i++)
{
+ struct pair_stats *pp = &ps.ps[i];
const union value *val0 = case_data (c, pp->var0);
const union value *val1 = case_data (c, pp->var1);
if (var_is_value_missing (pp->var0, val0, tt->exclude))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
- HMAPX_FOR_EACH (pp, node, &ps.hmap)
+ for (int i = 0; i < ps.n_ps; i++)
{
+ struct pair_stats *pp = &ps.ps[i];
const union value *val0 = case_data (c, pp->var0);
const union value *val1 = case_data (c, pp->var1);
if (var_is_value_missing (pp->var0, val0, tt->exclude))
paired_test (tt, &ps);
/* Clean up */
- HMAPX_FOR_EACH (pp, node, &ps.hmap)
+
+ for (int i = 0; i < ps.n_ps; i++)
{
+ struct pair_stats *pp = &ps.ps[i];
moments_destroy (pp->mom0);
moments_destroy (pp->mom1);
moments_destroy (pp->mom_diff);
- free (pp);
}
-
- hmapx_destroy (&ps.hmap);
+ free (ps.ps);
}
static void
paired_summary (const struct tt *tt, struct paired_samp *os)
{
- size_t n_pairs = hmapx_count (&os->hmap);
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
-
- const int heading_rows = 1;
- const int heading_cols = 2;
-
- const int cols = 4 + heading_cols;
- const int rows = n_pairs * 2 + heading_rows;
- struct tab_table *t = tab_create (cols, rows);
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_box (t, -1, -1, TAL_0, TAL_1, heading_cols, 0, cols - 1, rows - 1);
-
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_title (t, _("Paired Sample Statistics"));
- tab_vline (t, TAL_2, heading_cols, 0, rows - 1);
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("S.E. Mean"));
-
- HMAPX_FOR_EACH (pp, node, &os->hmap)
- {
- int v = pp->posn;
- double cc, mean, sigma;
+ struct pivot_table *table = pivot_table_create (
+ N_("Paired Sample Statistics"));
+ pivot_table_set_weight_var (table, tt->wv);
- tab_text_format (t, 0, v * 2 + heading_rows, TAB_LEFT, _("Pair %d"), pp->posn + 1);
-
- /* first var */
- moments_calculate (pp->mom0, &cc, &mean, &sigma, NULL, NULL);
- tab_text (t, 1, v * 2 + heading_rows, TAB_LEFT, var_to_string (pp->var0));
- tab_double (t, 3, v * 2 + heading_rows, TAB_RIGHT, cc, NULL, RC_WEIGHT);
- tab_double (t, 2, v * 2 + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 4, v * 2 + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 5, v * 2 + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL, RC_OTHER);
-
- /* second var */
- moments_calculate (pp->mom1, &cc, &mean, &sigma, NULL, NULL);
- tab_text (t, 1, v * 2 + 1 + heading_rows, TAB_LEFT, var_to_string (pp->var1));
- tab_double (t, 3, v * 2 + 1 + heading_rows, TAB_RIGHT, cc, NULL, RC_WEIGHT);
- tab_double (t, 2, v * 2 + 1 + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 4, v * 2 + 1 + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 5, v * 2 + 1 + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL, RC_OTHER);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t i = 0; i < os->n_ps; i++)
+ {
+ struct pair_stats *pp = &os->ps[i];
+ struct pivot_category *pair = pivot_category_create_group__ (
+ variables->root, pivot_value_new_text_format (N_("Pair %d"), i + 1));
+
+ for (int j = 0; j < 2; j++)
+ {
+ const struct variable *var = j ? pp->var1 : pp->var0;
+ const struct moments *mom = j ? pp->mom1 : pp->mom0;
+ double cc, mean, sigma;
+ moments_calculate (mom, &cc, &mean, &sigma, NULL, NULL);
+
+ int var_idx = pivot_category_create_leaf (
+ pair, pivot_value_new_variable (var));
+
+ double entries[] = { cc, mean, sqrt (sigma), sqrt (sigma / cc) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, var_idx,
+ pivot_value_new_number (entries[j]));
+ }
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
paired_correlations (const struct tt *tt, struct paired_samp *os)
{
- size_t n_pairs = hmapx_count (&os->hmap);
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
- const int heading_rows = 1;
- const int heading_cols = 2;
-
- const int cols = 5;
- const int rows = n_pairs + heading_rows;
- struct tab_table *t = tab_create (cols, rows);
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols - 1, rows - 1);
-
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_title (t, _("Paired Samples Correlations"));
- tab_vline (t, TAL_2, heading_cols, 0, rows - 1);
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Correlation"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
-
- HMAPX_FOR_EACH (pp, node, &os->hmap)
- {
- double corr;
- double cc0, mean0, sigma0;
- double cc1, mean1, sigma1;
- int v = pp->posn;
+ struct pivot_table *table = pivot_table_create (
+ N_("Paired Samples Correlations"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Correlation"), PIVOT_RC_CORRELATION,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
- tab_text_format (t, 0, v + heading_rows, TAB_LEFT, _("Pair %d"), pp->posn + 1);
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Pairs"));
- tab_text_format (t, 1, v + heading_rows, TAB_LEFT, _("%s & %s"),
- var_to_string (pp->var0),
- var_to_string (pp->var1));
+ for (size_t i = 0; i < os->n_ps; i++)
+ {
+ struct pair_stats *pp = &os->ps[i];
+ struct pivot_category *group = pivot_category_create_group__ (
+ pairs->root, pivot_value_new_text_format (N_("Pair %d"), i + 1));
+
+ int row = pivot_category_create_leaf (
+ group, pivot_value_new_text_format (N_("%s & %s"),
+ var_to_string (pp->var0),
+ var_to_string (pp->var1)));
+ double cc0, mean0, sigma0;
+ double cc1, mean1, sigma1;
moments_calculate (pp->mom0, &cc0, &mean0, &sigma0, NULL, NULL);
moments_calculate (pp->mom1, &cc1, &mean1, &sigma1, NULL, NULL);
-
/* If this fails, then we're not dealing with missing values properly */
assert (cc0 == cc1);
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, cc0, NULL, RC_WEIGHT);
-
- corr = pp->sum_of_prod / cc0 - (mean0 * mean1);
- corr /= sqrt (sigma0 * sigma1);
- corr *= cc0 / (cc0 - 1);
-
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, corr, NULL, RC_OTHER);
- tab_double (t, 4, v + heading_rows, TAB_RIGHT,
- 2.0 * significance_of_correlation (corr, cc0), NULL, RC_PVALUE);
+ double corr = ((pp->sum_of_prod / cc0 - mean0 * mean1)
+ / sqrt (sigma0 * sigma1) * cc0 / (cc0 - 1));
+ double sig = 2.0 * significance_of_correlation (corr, cc0);
+ double entries[] = { cc0, corr, sig };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, row, pivot_value_new_number (entries[i]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
paired_test (const struct tt *tt, const struct paired_samp *os)
{
- size_t n_pairs = hmapx_count (&os->hmap);
- struct hmapx_node *node;
- struct pair_stats *pp = NULL;
-
- const int heading_rows = 3;
- const int heading_cols = 2;
- const size_t rows = heading_rows + n_pairs;
- const size_t cols = 10;
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
-
- struct tab_table *t = tab_create (cols, rows);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 3);
-
- tab_title (t, _("Paired Samples Test"));
- tab_hline (t, TAL_1, heading_cols, 6, 1);
- tab_vline (t, TAL_2, heading_cols, 0, rows - 1);
-
- tab_box (t, -1, -1, -1, TAL_1, heading_cols, 0, cols - 1, rows - 1);
-
- tab_joint_text (t, 2, 0, 6, 0, TAB_CENTER,
- _("Paired Differences"));
-
- tab_joint_text_format (t, 5, 1, 6, 1, TAB_CENTER,
- _("%g%% Confidence Interval of the Difference"),
- tt->confidence * 100.0);
-
- tab_hline (t, TAL_1, 5, 6, 2);
- tab_text (t, 7, 2, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 8, 2, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 9, 2, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
- tab_text (t, 4, 2, TAB_CENTER | TAT_TITLE, _("Std. Error Mean"));
- tab_text (t, 3, 2, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 2, 2, TAB_CENTER | TAT_TITLE, _("Mean"));
-
- tab_text (t, 5, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 6, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
-
- HMAPX_FOR_EACH (pp, node, &os->hmap)
+ struct pivot_table *table = pivot_table_create (N_("Paired Samples Test"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ struct pivot_category *group = pivot_category_create_group (
+ statistics->root, N_("Paired Differences"),
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+ struct pivot_category *interval = pivot_category_create_group__ (
+ group, pivot_value_new_text_format (
+ N_("%g%% Confidence Interval of the Difference"),
+ tt->confidence * 100.0));
+ pivot_category_create_leaves (interval,
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+ pivot_category_create_leaves (statistics->root,
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Pairs"));
+
+ for (size_t i = 0; i < os->n_ps; i++)
{
- int v = pp->posn;
- double cc, mean, sigma;
- double df ;
- double tval;
- double p, q;
- double se_mean;
-
- moments_calculate (pp->mom_diff, &cc, &mean, &sigma, NULL, NULL);
-
- df = cc - 1.0;
- tab_text_format (t, 0, v + heading_rows, TAB_LEFT, _("Pair %d"), v + 1);
+ struct pair_stats *pp = &os->ps[i];
+ struct pivot_category *group = pivot_category_create_group__ (
+ pairs->root, pivot_value_new_text_format (N_("Pair %d"), i + 1));
- tab_text_format (t, 1, v + heading_rows, TAB_LEFT, _("%s - %s"),
- var_to_string (pp->var0),
- var_to_string (pp->var1));
+ int row = pivot_category_create_leaf (
+ group, pivot_value_new_text_format (N_("%s - %s"),
+ var_to_string (pp->var0),
+ var_to_string (pp->var1)));
- tval = mean * sqrt (cc / sigma);
- se_mean = sqrt (sigma / cc);
-
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 4, v + heading_rows, TAB_RIGHT, se_mean, NULL, RC_OTHER);
+ double cc, mean, sigma;
+ moments_calculate (pp->mom_diff, &cc, &mean, &sigma, NULL, NULL);
- tab_double (t, 7, v + heading_rows, TAB_RIGHT, tval, NULL, RC_OTHER);
- tab_double (t, 8, v + heading_rows, TAB_RIGHT, df, NULL, RC_WEIGHT);
+ double df = cc - 1.0;
+ double t = mean * sqrt (cc / sigma);
+ double se_mean = sqrt (sigma / cc);
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
+ double p = gsl_cdf_tdist_P (t, df);
+ double q = gsl_cdf_tdist_Q (t, df);
+ double sig = 2.0 * (t > 0 ? q : p);
- tab_double (t, 9, v + heading_rows, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL, RC_PVALUE);
+ double t_qinv = gsl_cdf_tdist_Qinv ((1.0 - tt->confidence) / 2.0, df);
- tval = gsl_cdf_tdist_Qinv ( (1.0 - tt->confidence) / 2.0, df);
+ double entries[] = {
+ mean,
+ sqrt (sigma),
+ se_mean,
+ mean - t_qinv * se_mean,
+ mean + t_qinv * se_mean,
+ t,
+ df,
+ sig,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put2 (table, i, row, pivot_value_new_number (entries[i]));
- tab_double (t, 5, v + heading_rows, TAB_RIGHT, mean - tval * se_mean, NULL, RC_OTHER);
- tab_double (t, 6, v + heading_rows, TAB_RIGHT, mean + tval * se_mean, NULL, RC_OTHER);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
#include "libpspp/misc.h"
#include "math/sort.h"
#include "math/wilcoxon-sig.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/minmax.h"
#include "gl/xalloc.h"
+#include "gettext.h"
+#define N_(msgid) msgid
+#define _(msgid) gettext (msgid)
+
static double
append_difference (const struct ccase *c, casenumber n UNUSED, void *aux)
{
free (ws);
}
-
-
\f
+static void
+put_row (struct pivot_table *table, int var_idx, int sign_idx,
+ double n, double sum)
+{
+ pivot_table_put3 (table, 0, sign_idx, var_idx, pivot_value_new_number (n));
+ if (sum != SYSMIS)
+ {
+ pivot_table_put3 (table, 1, sign_idx, var_idx,
+ pivot_value_new_number (sum / n));
+ pivot_table_put3 (table, 2, sign_idx, var_idx,
+ pivot_value_new_number (sum));
+ }
+}
-#include "gettext.h"
-#define _(msgid) gettext (msgid)
+static int
+add_pair_leaf (struct pivot_dimension *dimension, variable_pair *pair)
+{
+ char *label = xasprintf ("%s - %s", var_to_string ((*pair)[0]),
+ var_to_string ((*pair)[1]));
+ return pivot_category_create_leaf (
+ dimension->root,
+ pivot_value_new_user_text_nocopy (label));
+}
static void
show_ranks_box (const struct wilcoxon_state *ws,
const struct two_sample_test *t2s,
const struct dictionary *dict)
{
- size_t i;
-
- const struct fmt_spec *wfmt = dict_get_weight_format (dict);
+ struct pivot_table *table = pivot_table_create (N_("Ranks"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
- struct tab_table *table = tab_create (5, 1 + 4 * t2s->n_pairs);
- tab_set_format (table, RC_WEIGHT, wfmt);
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean Rank"), PIVOT_RC_OTHER,
+ N_("Sum of Ranks"), PIVOT_RC_OTHER);
- tab_title (table, _("Ranks"));
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Sign"),
+ N_("Negative Ranks"), N_("Positive Ranks"),
+ N_("Ties"), N_("Total"));
- tab_headers (table, 2, 0, 1, 0);
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Pairs"));
- /* Vertical lines inside the box */
- tab_box (table, 0, 0, -1, TAL_1,
- 1, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
-
- tab_text (table, 2, 0, TAB_CENTER, _("N"));
- tab_text (table, 3, 0, TAB_CENTER, _("Mean Rank"));
- tab_text (table, 4, 0, TAB_CENTER, _("Sum of Ranks"));
-
-
- for (i = 0 ; i < t2s->n_pairs; ++i)
+ for (size_t i = 0 ; i < t2s->n_pairs; ++i)
{
variable_pair *vp = &t2s->pairs[i];
-
- struct string pair_name;
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " - ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
-
- tab_text (table, 1, 1 + i * 4, TAB_LEFT, _("Negative Ranks"));
- tab_text (table, 1, 2 + i * 4, TAB_LEFT, _("Positive Ranks"));
- tab_text (table, 1, 3 + i * 4, TAB_LEFT, _("Ties"));
- tab_text (table, 1, 4 + i * 4, TAB_LEFT, _("Total"));
-
- tab_hline (table, TAL_1, 0, tab_nc (table) - 1, 1 + i * 4);
-
-
- tab_text (table, 0, 1 + i * 4, TAB_LEFT, ds_cstr (&pair_name));
- ds_destroy (&pair_name);
-
-
- /* N */
- tab_double (table, 2, 1 + i * 4, TAB_RIGHT, ws[i].negatives.n, NULL, RC_WEIGHT);
- tab_double (table, 2, 2 + i * 4, TAB_RIGHT, ws[i].positives.n, NULL, RC_WEIGHT);
- tab_double (table, 2, 3 + i * 4, TAB_RIGHT, ws[i].n_zeros, NULL, RC_WEIGHT);
-
- tab_double (table, 2, 4 + i * 4, TAB_RIGHT,
- ws[i].n_zeros + ws[i].positives.n + ws[i].negatives.n, NULL, RC_WEIGHT);
-
- /* Sums */
- tab_double (table, 4, 1 + i * 4, TAB_RIGHT, ws[i].negatives.sum, NULL, RC_OTHER);
- tab_double (table, 4, 2 + i * 4, TAB_RIGHT, ws[i].positives.sum, NULL, RC_OTHER);
-
-
- /* Means */
- tab_double (table, 3, 1 + i * 4, TAB_RIGHT,
- ws[i].negatives.sum / (double) ws[i].negatives.n, NULL, RC_OTHER);
-
- tab_double (table, 3, 2 + i * 4, TAB_RIGHT,
- ws[i].positives.sum / (double) ws[i].positives.n, NULL, RC_OTHER);
-
+ int pair_idx = add_pair_leaf (pairs, vp);
+
+ const struct wilcoxon_state *w = &ws[i];
+ put_row (table, pair_idx, 0, w->negatives.n, w->negatives.sum);
+ put_row (table, pair_idx, 1, w->positives.n, w->positives.sum);
+ put_row (table, pair_idx, 2, w->n_zeros, SYSMIS);
+ put_row (table, pair_idx, 3,
+ w->n_zeros + w->positives.n + w->negatives.n, SYSMIS);
}
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, 1);
- tab_vline (table, TAL_2, 2, 0, tab_nr (table) - 1);
-
-
- tab_submit (table);
+ pivot_table_submit (table);
}
double timer UNUSED
)
{
- size_t i;
- struct tab_table *table = tab_create (1 + t2s->n_pairs, exact ? 5 : 3);
-
- tab_title (table, _("Test Statistics"));
-
- tab_headers (table, 1, 0, 1, 0);
-
- /* Vertical lines inside the box */
- tab_box (table, 0, 0, -1, TAL_1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
- /* Box around entire table */
- tab_box (table, TAL_2, TAL_2, -1, -1,
- 0, 0, tab_nc (table) - 1, tab_nr (table) - 1 );
-
-
- tab_text (table, 0, 1, TAB_LEFT, _("Z"));
- tab_text (table, 0, 2, TAB_LEFT, _("Asymp. Sig. (2-tailed)"));
-
- if ( exact )
+ struct pivot_table *table = pivot_table_create (N_("Test Statistics"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Z"), PIVOT_RC_OTHER,
+ N_("Asymp. Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE);
+ if (exact)
+ pivot_category_create_leaves (
+ statistics->root,
+ N_("Exact Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Exact Sig. (1-tailed)"), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *pairs = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Pairs"));
+
+ struct pivot_footnote *too_many_pairs = pivot_table_create_footnote (
+ table, pivot_value_new_text (
+ N_("Too many pairs to calculate exact significance")));
+
+ for (size_t i = 0 ; i < t2s->n_pairs; ++i)
{
- tab_text (table, 0, 3, TAB_LEFT, _("Exact Sig. (2-tailed)"));
- tab_text (table, 0, 4, TAB_LEFT, _("Exact Sig. (1-tailed)"));
-
-#if 0
- tab_text (table, 0, 5, TAB_LEFT, _("Point Probability"));
-#endif
- }
-
- for (i = 0 ; i < t2s->n_pairs; ++i)
- {
- double z;
- double n = ws[i].positives.n + ws[i].negatives.n;
variable_pair *vp = &t2s->pairs[i];
+ int pair_idx = add_pair_leaf (pairs, vp);
- struct string pair_name;
- ds_init_cstr (&pair_name, var_to_string ((*vp)[0]));
- ds_put_cstr (&pair_name, " - ");
- ds_put_cstr (&pair_name, var_to_string ((*vp)[1]));
-
-
- tab_text (table, 1 + i, 0, TAB_CENTER, ds_cstr (&pair_name));
- ds_destroy (&pair_name);
-
- z = MIN (ws[i].positives.sum, ws[i].negatives.sum);
+ double n = ws[i].positives.n + ws[i].negatives.n;
+ double z = MIN (ws[i].positives.sum, ws[i].negatives.sum);
z -= n * (n + 1)/ 4.0;
-
z /= sqrt (n * (n + 1) * (2*n + 1)/24.0 - ws[i].tiebreaker / 48.0);
- tab_double (table, 1 + i, 1, TAB_RIGHT, z, NULL, RC_OTHER);
-
- tab_double (table, 1 + i, 2, TAB_RIGHT,
- 2.0 * gsl_cdf_ugaussian_P (z),
- NULL, RC_PVALUE);
+ double entries[4];
+ int n_entries = 0;
+ entries[n_entries++] = z;
+ entries[n_entries++] = 2.0 * gsl_cdf_ugaussian_P (z);
+ int footnote_idx = -1;
if (exact)
{
double p = LevelOfSignificanceWXMPSR (ws[i].positives.sum, n);
if (p < 0)
{
- msg (MW, _("Too many pairs to calculate exact significance."));
+ footnote_idx = n_entries;
+ entries[n_entries++] = SYSMIS;
}
else
- {
- tab_double (table, 1 + i, 3, TAB_RIGHT, p, NULL, RC_PVALUE);
- tab_double (table, 1 + i, 4, TAB_RIGHT, p / 2.0, NULL, RC_PVALUE);
- }
- }
+ {
+ entries[n_entries++] = p;
+ entries[n_entries++] = p / 2.0;
+ }
+ }
+
+ for (int j = 0; j < n_entries; j++)
+ {
+ struct pivot_value *value = pivot_value_new_number (entries[j]);
+ if (j == footnote_idx)
+ pivot_value_add_footnote (value, too_many_pairs);
+ pivot_table_put2 (table, j, pair_idx, value);
+ }
}
- tab_hline (table, TAL_2, 0, tab_nc (table) - 1, 1);
- tab_vline (table, TAL_2, 1, 0, tab_nr (table) - 1);
-
-
- tab_submit (table);
+ pivot_table_submit (table);
}
#include "language/lexer/lexer.h"
#include "language/lexer/format-parser.h"
#include "libpspp/message.h"
+#include "libpspp/string-set.h"
#include "libpspp/version.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gl/xalloc.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
-struct thing
-{
- const char *identifier;
- enum result_class rc;
-};
-
-extern struct fmt_spec ugly [n_RC];
-
-static const struct thing things[] =
- {
- {"SIGNIFICANCE", RC_PVALUE},
- {"COUNT" ,RC_WEIGHT}
- };
-
-#define N_THINGS (sizeof (things) / sizeof (struct thing))
-
-struct output_spec
-{
- /* An array of classes */
- enum result_class *rc;
-
- int n_rc;
-
- /* The format to be applied to these classes */
- struct fmt_spec fmt;
-};
-
int
cmd_output (struct lexer *lexer, struct dataset *ds UNUSED)
{
- int j, i;
- struct output_spec *output_specs = NULL;
- int n_os = 0;
+ struct string_set rc_names = STRING_SET_INITIALIZER (rc_names);
if (!lex_force_match_id (lexer, "MODIFY"))
{
}
else if (lex_match_id (lexer, "TABLECELLS"))
{
- struct output_spec *os;
- output_specs = xrealloc (output_specs, sizeof (*output_specs) * ++n_os);
- os = &output_specs[n_os - 1];
- os->n_rc = 0;
- os->rc = NULL;
- bool format = false;
+ string_set_clear (&rc_names);
+ struct fmt_spec fmt = { 0, 0, 0 };
while (lex_token (lexer) != T_SLASH &&
lex_token (lexer) != T_ENDCMD)
if (! lex_force_match (lexer, T_LBRACK))
goto error;
- while (lex_token (lexer) != T_RBRACK &&
- lex_token (lexer) != T_ENDCMD)
- {
- int i;
- for (i = 0 ; i < N_THINGS; ++i)
- {
- if (lex_match_id (lexer, things[i].identifier))
- {
- os->rc = xrealloc (os->rc, sizeof (*os->rc) * ++os->n_rc);
- os->rc[os->n_rc - 1] = things[i].rc;
- break;
- }
- }
- if (i >= N_THINGS)
- {
- lex_error (lexer, _("Unknown TABLECELLS class"));
- goto error;
- }
- }
+ while (lex_token (lexer) == T_ID)
+ {
+ string_set_insert (&rc_names, lex_tokcstr (lexer));
+ lex_get (lexer);
+ }
+
if (! lex_force_match (lexer, T_RBRACK))
goto error;
}
else if (lex_match_id (lexer, "FORMAT"))
{
- struct fmt_spec fmt;
char type[FMT_TYPE_LEN_MAX + 1];
int width = -1;
int decimals = -1;
fmt.w = width;
fmt.d = decimals;
-
- os->fmt = fmt;
- format = true;
}
else
{
goto error;
}
}
- if (!format)
- goto error;
+
+ if (fmt.w)
+ {
+ const struct string_set_node *node;
+ const char *s;
+ STRING_SET_FOR_EACH (s, node, &rc_names)
+ if (!pivot_result_class_change (s, &fmt))
+ lex_error (lexer, _("Unknown cell class %s."), s);
+ }
}
else
{
}
}
- /* Populate the global table, with the values we parsed */
- for (i = 0; i < n_os; ++i)
- {
- for (j = 0; j < output_specs[i].n_rc; ++j)
- {
- ugly [output_specs[i].rc[j]] = output_specs[i].fmt;
- }
- }
-
- for (j = 0; j < n_os; ++j)
- free (output_specs[j].rc);
- free (output_specs);
return CMD_SUCCESS;
- error:
- for (j = 0; j < n_os; ++j)
- free (output_specs[j].rc);
- free (output_specs);
+ error:
+ string_set_destroy (&rc_names);
return CMD_SUCCESS;
}
lex_match (lexer, T_EQUALS);
if (lex_match_id (lexer, "VALUES"))
- {
- settings_set_value_style (SETTINGS_VAL_STYLE_VALUES);
- }
+ settings_set_show_values (SETTINGS_VALUE_SHOW_VALUE);
else if (lex_match_id (lexer, "LABELS"))
- {
- settings_set_value_style (SETTINGS_VAL_STYLE_LABELS);
- }
+ settings_set_show_values (SETTINGS_VALUE_SHOW_LABEL);
else if (lex_match_id (lexer, "BOTH"))
- {
- settings_set_value_style (SETTINGS_VAL_STYLE_BOTH);
- }
+ settings_set_show_values (SETTINGS_VALUE_SHOW_BOTH);
else
{
lex_error_expecting (lexer, "VALUES", "LABELS", "BOTH", NULL_SENTINEL);
lex_match (lexer, T_EQUALS);
if (lex_match_id (lexer, "NAMES"))
- {
- settings_set_var_style (SETTINGS_VAR_STYLE_NAMES);
- }
+ settings_set_show_variables (SETTINGS_VALUE_SHOW_VALUE);
else if (lex_match_id (lexer, "LABELS"))
- {
- settings_set_var_style (SETTINGS_VAR_STYLE_LABELS);
- }
+ settings_set_show_variables (SETTINGS_VALUE_SHOW_LABEL);
else if (lex_match_id (lexer, "BOTH"))
- {
- settings_set_var_style (SETTINGS_VAR_STYLE_BOTH);
- }
+ settings_set_show_variables (SETTINGS_VALUE_SHOW_BOTH);
else
{
lex_error_expecting (lexer, "NAMES", "LABELS", "BOTH", NULL_SENTINEL);
struct hmap_node node; /* In struct categorical's 'varmap'. */
const struct variable *var; /* The variable. */
struct hmap valmap; /* Contains "struct value_node"s. */
+ union value *values; /* Values in valmap, as a sorted array. */
};
static int
}
static struct variable_node *
-lookup_variable (const struct hmap *map, const struct variable *var, unsigned int hash)
+lookup_variable (const struct hmap *map, const struct variable *var)
{
struct variable_node *vn;
- HMAP_FOR_EACH_WITH_HASH (vn, struct variable_node, node, hash, map)
+ HMAP_FOR_EACH_WITH_HASH (vn, struct variable_node, node,
+ hash_pointer (var, 0), map)
if (vn->var == var)
return vn;
return NULL;
for (size_t v = 0; v < inter[i]->n_vars; ++v)
{
const struct variable *var = inter[i]->vars[v];
- unsigned int hash = hash_pointer (var, 0);
- struct variable_node *vn = lookup_variable (&cat->varmap, var, hash);
+ struct variable_node *vn = lookup_variable (&cat->varmap, var);
if (!vn)
{
vn = pool_malloc (cat->pool, sizeof *vn);
vn->var = var;
+ vn->values = NULL;
hmap_init (&vn->valmap);
- hmap_insert (&cat->varmap, &vn->node, hash);
+ hmap_insert (&cat->varmap, &vn->node, hash_pointer (var, 0));
}
iap->varnodes[v] = vn;
}
cat->sane = true;
}
+union value *
+categoricals_get_var_values (const struct categoricals *cat,
+ const struct variable *var, size_t *np)
+{
+ struct variable_node *vn = lookup_variable (&cat->varmap, var);
+ *np = hmap_count (&vn->valmap);
+ if (!vn->values)
+ {
+ vn->values = pool_nalloc (cat->pool, *np, sizeof *vn->values);
+
+ struct value_node *valnd;
+ HMAP_FOR_EACH (valnd, struct value_node, node, &vn->valmap)
+ vn->values[valnd->index] = valnd->val;
+ }
+ return vn->values;
+}
+
static struct interact_params *
df_to_iap (const struct categoricals *cat, int subscript)
{
return n < hmap_count (&iap->ivmap) ? iap->ivs[n]->user_data : NULL;
}
+int
+categoricals_get_value_index_by_category_real (const struct categoricals *cat,
+ int iact_idx, int cat_idx,
+ int var_idx)
+{
+ const struct interact_params *iap = &cat->iap[iact_idx];
+ const struct interaction_value *ivn = iap->ivs[cat_idx];
+ const struct variable *var = iap->iact->vars[var_idx];
+ const struct variable_node *vn = iap->varnodes[var_idx];
+ const union value *val = case_data (ivn->ccase, var);
+ int width = var_get_width (var);
+ unsigned int hash = value_hash (val, width, 0);
+ return lookup_value (&vn->valmap, val, hash, width)->index;
+}
+
/* Return a case containing the set of values corresponding to CAT_INDEX. */
const struct ccase *
categoricals_get_case_by_category (const struct categoricals *cat,
void categoricals_done (const struct categoricals *);
bool categoricals_is_complete (const struct categoricals *);
-/* Counting categories.
+/* Categories.
A variable's number of categories is the number of unique values observed in
the data passed to categoricals_update().
size_t categoricals_n_count (const struct categoricals *, size_t idx);
size_t categoricals_n_total (const struct categoricals *);
+union value *categoricals_get_var_values (const struct categoricals *,
+ const struct variable *, size_t *n);
+
/* Degrees of freedom.
A categorical variable with N_CATS categories has N_CATS - 1 degrees of
void *categoricals_get_user_data_by_category_real (
const struct categoricals *, int iact, int n);
+int categoricals_get_value_index_by_category_real (
+ const struct categoricals *, int iact_idx, int cat_idx, int var_idx);
+
void *categoricals_get_user_data_by_category (const struct categoricals *,
int category);
const struct ccase *categoricals_get_case_by_category (
*/
#include "libpspp/str.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "data/format.h"
/* Create a table which can be populated with the encodings for
the covariance matrix COV */
-struct tab_table *
-covariance_dump_enc_header (const struct covariance *cov, int length)
+struct pivot_table *
+covariance_dump_enc_header (const struct covariance *cov)
{
- struct tab_table *t = tab_create (cov->dim, length);
- int n;
- int i;
-
- tab_title (t, "Covariance Encoding");
-
- tab_box (t,
- TAL_2, TAL_2, 0, 0,
- 0, 0, tab_nc (t) - 1, tab_nr (t) - 1);
-
- tab_hline (t, TAL_2, 0, tab_nc (t) - 1, 1);
-
-
- for (i = 0 ; i < cov->n_vars; ++i)
- {
- tab_text (t, i, 0, TAT_TITLE, var_get_name (cov->vars[i]));
- tab_vline (t, TAL_1, i + 1, 0, tab_nr (t) - 1);
- }
-
- n = 0;
- while (i < cov->dim)
+ struct pivot_table *table = pivot_table_create ("Covariance Encoding");
+
+ struct pivot_dimension *factors = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, "Factor");
+ for (size_t i = 0 ; i < cov->n_vars; ++i)
+ pivot_category_create_leaf (factors->root,
+ pivot_value_new_variable (cov->vars[i]));
+ for (size_t i = 0, n = 0; i < cov->dim - cov->n_vars; n++)
{
- struct string str;
- int idx = i - cov->n_vars;
const struct interaction *iact =
- categoricals_get_interaction_by_subscript (cov->categoricals, idx);
- int df;
+ categoricals_get_interaction_by_subscript (cov->categoricals, i);
- ds_init_empty (&str);
+ struct string str = DS_EMPTY_INITIALIZER;
interaction_to_string (iact, &str);
+ struct pivot_category *group = pivot_category_create_group__ (
+ factors->root,
+ pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
- df = categoricals_df (cov->categoricals, n);
-
- tab_joint_text (t,
- i, 0,
- i + df - 1, 0,
- TAT_TITLE, ds_cstr (&str));
-
- if (i + df < tab_nr (t) - 1)
- tab_vline (t, TAL_1, i + df, 0, tab_nr (t) - 1);
+ int df = categoricals_df (cov->categoricals, n);
+ for (int j = 0; j < df; j++)
+ pivot_category_create_leaf_rc (group, pivot_value_new_integer (j),
+ PIVOT_RC_INTEGER);
i += df;
- n++;
- ds_destroy (&str);
}
- return t;
+ struct pivot_dimension *matrix = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, "Matrix", "Matrix");
+ matrix->hide_all_labels = true;
+
+ return table;
}
*/
void
covariance_dump_enc (const struct covariance *cov, const struct ccase *c,
- struct tab_table *t)
+ struct pivot_table *table)
{
- static int row = 0;
- int i;
- ++row;
- for (i = 0 ; i < cov->dim; ++i)
- {
- double v = get_val (cov, i, c);
- tab_double (t, i, row, 0, v, i < cov->n_vars ? NULL : &F_8_0, RC_OTHER);
- }
+ int row = pivot_category_create_leaf (
+ table->dimensions[1]->root,
+ pivot_value_new_integer (table->dimensions[1]->n_leaves));
+
+ for (int i = 0 ; i < cov->dim; ++i)
+ pivot_table_put2 (
+ table, i, row, pivot_value_new_number (get_val (cov, i, c)));
}
const struct categoricals * covariance_get_categoricals (const struct covariance *cov);
size_t covariance_dim (const struct covariance * cov);
-struct tab_table ;
-void
-covariance_dump_enc (const struct covariance *cov, const struct ccase *c,
- struct tab_table *t);
-
-struct tab_table *
-covariance_dump_enc_header (const struct covariance *cov, int length);
-
-
+struct pivot_table *covariance_dump_enc_header (const struct covariance *);
+void covariance_dump_enc (const struct covariance *, const struct ccase *,
+ struct pivot_table *);
#endif
{
ds_put_cstr (str, var_to_string (iact->vars[v]));
if (v + 1 < iact->n_vars)
- ds_put_cstr (str, " * ");
+ ds_put_cstr (str, " × ");
}
}
#include "output/message-item.h"
#include "output/options.h"
#include "output/render.h"
-#include "output/tab.h"
#include "output/table-item.h"
#include "output/text-item.h"
return;
struct area_style style = {
+ .cell_style.halign = TABLE_HALIGN_LEFT,
.font_style.bold = bold,
.font_style.underline = underline,
};
struct table_cell cell = {
- .options = TAB_LEFT,
.text = CONST_CAST (char *, s),
.style = &style,
};
src/output/output-item.h \
src/output/page-setup-item.c \
src/output/page-setup-item.h \
+ src/output/pivot-output.c \
+ src/output/pivot-table.c \
+ src/output/pivot-table.h \
src/output/render.c \
src/output/render.h \
src/output/tab.c \
src/output/tab.h \
- src/output/table-casereader.c \
src/output/table-item.c \
src/output/table-item.h \
src/output/table-paste.c \
#include "output/options.h"
#include "output/page-setup-item.h"
#include "output/render.h"
-#include "output/tab.h"
#include "output/table-item.h"
#include "output/table.h"
#include "output/text-item.h"
int R = options & TAB_ROTATE ? 0 : 1;
struct xr_font *font = (options & TAB_FIX ? &xr->fonts[XR_FONT_FIXED]
- : options & TAB_EMPH ? &xr->fonts[XR_FONT_EMPHASIS]
: &xr->fonts[XR_FONT_PROPORTIONAL]);
struct xr_font local_font;
if (font_style->typeface)
dump_line (xr, -xr->left_margin, best,
xr->width + xr->right_margin, best,
RENDER_LINE_SINGLE,
- &(struct cell_color) CELL_COLOR (0, 255, 0));
+ &CELL_COLOR (0, 255, 0));
}
}
/* Output cell contents. */
const char *s = cell.text;
- if (cell.options & TAB_EMPH)
- fputs ("<EM>", html->file);
if (cell.options & TAB_FIX)
{
fputs ("<TT>", html->file);
s += strspn (s, CC_SPACES);
escape_string (html->file, s, strlen (s), " ", "<BR>");
}
- if (cell.options & TAB_EMPH)
- fputs ("</EM>", html->file);
html_put_footnote_markers (html, cell.footnotes, cell.n_footnotes);
#include "output/driver-provider.h"
#include "output/message-item.h"
#include "output/options.h"
-#include "output/tab.h"
#include "output/table-item.h"
#include "output/table-provider.h"
#include "output/text-item.h"
--- /dev/null
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2018 Free Software Foundation, Inc.
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see <http://www.gnu.org/licenses/>. */
+
+#include <config.h>
+
+#include <stdlib.h>
+
+#include "output/pivot-table.h"
+
+#include "data/settings.h"
+#include "libpspp/assertion.h"
+#include "libpspp/pool.h"
+#include "output/tab.h"
+#include "output/table.h"
+#include "output/table-item.h"
+#include "output/text-item.h"
+#include "output/table-provider.h"
+
+#include "gl/minmax.h"
+#include "gl/xalloc.h"
+
+#define H TABLE_HORZ
+#define V TABLE_VERT
+
+static const struct pivot_category *
+find_category (const struct pivot_dimension *d, int dim_index,
+ const size_t *indexes, int row_ofs)
+{
+ size_t index = indexes[dim_index];
+ assert (index < d->n_leaves);
+ for (const struct pivot_category *c = d->presentation_leaves[index];
+ c; c = c->parent)
+ {
+ if (!row_ofs)
+ return c;
+
+ row_ofs -= 1 + c->extra_depth;
+ if (row_ofs < 0)
+ return NULL;
+ }
+ return NULL;
+}
+
+static struct area_style *
+area_style_override (struct pool *pool,
+ const struct area_style *in,
+ const struct cell_style *cell_,
+ const struct font_style *font_)
+{
+ const struct cell_style *cell = cell_ ? cell_ : &in->cell_style;
+ const struct font_style *font = font_ ? font_ : &in->font_style;
+
+ struct area_style *out = (pool
+ ? pool_alloc (pool, sizeof *out)
+ : xmalloc (sizeof *out));
+ *out = (struct area_style) {
+ .cell_style.halign = cell->halign,
+ .cell_style.valign = cell->valign,
+ .cell_style.decimal_offset = cell->decimal_offset,
+ .cell_style.margin[H][0] = cell->margin[H][0],
+ .cell_style.margin[H][1] = cell->margin[H][1],
+ .cell_style.margin[V][0] = cell->margin[V][0],
+ .cell_style.margin[V][1] = cell->margin[V][1],
+ .font_style.fg[0] = font->fg[0],
+ .font_style.fg[1] = font->fg[1],
+ .font_style.bg[0] = font->bg[0],
+ .font_style.bg[1] = font->bg[1],
+ .font_style.typeface = (font->typeface
+ ? pool_strdup (pool, font->typeface)
+ : NULL),
+ .font_style.size = font->size,
+ .font_style.bold = font->bold,
+ .font_style.italic = font->italic,
+ .font_style.underline = font->underline,
+ .font_style.markup = font->markup,
+ };
+ return out;
+}
+
+static void
+fill_cell (struct tab_table *t, int x1, int y1, int x2, int y2,
+ const struct area_style *style, int style_idx,
+ const struct pivot_value *value, struct footnote **footnotes,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ bool rotate_label)
+{
+
+ struct string s = DS_EMPTY_INITIALIZER;
+ int opts = style_idx << TAB_STYLE_SHIFT;
+ if (value)
+ {
+ bool numeric = pivot_value_format_body (value, show_values,
+ show_variables, &s);
+ if (numeric)
+ opts |= TAB_NUMERIC;
+ if (value->font_style && value->font_style->markup)
+ opts |= TAB_MARKUP;
+ if (rotate_label)
+ opts |= TAB_ROTATE;
+ }
+ tab_joint_text (t, x1, y1, x2, y2, opts, ds_cstr (&s));
+ ds_destroy (&s);
+
+ if (value)
+ {
+ if (value->cell_style || value->font_style)
+ tab_add_style (t, x1, y1,
+ area_style_override (t->container, style,
+ value->cell_style,
+ value->font_style));
+
+ for (size_t i = 0; i < value->n_footnotes; i++)
+ tab_add_footnote (t, x1, y1, footnotes[value->footnotes[i]->idx]);
+ }
+}
+
+static struct table_item_text *
+pivot_value_to_table_item_text (const struct pivot_value *value,
+ const struct area_style *area,
+ struct footnote **footnotes,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables)
+{
+ if (!value)
+ return NULL;
+
+ struct string s = DS_EMPTY_INITIALIZER;
+ pivot_value_format_body (value, show_values, show_variables, &s);
+
+ struct table_item_text *text = xmalloc (sizeof *text);
+ *text = (struct table_item_text) {
+ .content = ds_steal_cstr (&s),
+ .footnotes = xnmalloc (value->n_footnotes, sizeof *text->footnotes),
+ .n_footnotes = value->n_footnotes,
+ .style = area_style_override (
+ NULL, area, value->cell_style, value->font_style),
+ };
+
+ for (size_t i = 0; i < value->n_footnotes; i++)
+ text->footnotes[i] = footnotes[value->footnotes[i]->idx];
+
+ return text;
+}
+
+static int
+get_table_rule (const struct table_border_style *styles,
+ enum pivot_border style_idx)
+{
+ return styles[style_idx].stroke | (style_idx << TAB_RULE_STYLE_SHIFT);
+}
+
+static void
+draw_line (struct tab_table *t, const struct table_border_style *styles,
+ enum pivot_border style_idx,
+ enum table_axis axis, int a, int b0, int b1)
+{
+ int rule = get_table_rule (styles, style_idx);
+ if (axis == H)
+ tab_hline (t, rule, b0, b1, a);
+ else
+ tab_vline (t, rule, a, b0, b1);
+}
+
+static void
+compose_headings (struct tab_table *t,
+ const struct pivot_axis *a_axis, enum table_axis a,
+ const struct pivot_axis *b_axis,
+ const struct table_border_style *borders,
+ enum pivot_border dim_col_horz,
+ enum pivot_border dim_col_vert,
+ enum pivot_border cat_col_horz,
+ enum pivot_border cat_col_vert,
+ const size_t *column_enumeration, size_t n_columns,
+ const struct area_style *label_style, int label_style_idx,
+ const struct area_style *corner_style,
+ struct footnote **footnotes,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ bool rotate_inner_labels, bool rotate_outer_labels)
+{
+ enum table_axis b = !a;
+ int b_size = a_axis->label_depth;
+ int a_ofs = b_axis->label_depth;
+
+ if (!a_axis->n_dimensions || !n_columns || !b_size)
+ return;
+
+ int bottom_row = b_size - 1;
+ const int stride = MAX (1, a_axis->n_dimensions);
+ for (int dim_index = 0; dim_index < a_axis->n_dimensions; dim_index++)
+ {
+ const struct pivot_dimension *d = a_axis->dimensions[dim_index];
+ if (d->hide_all_labels)
+ continue;
+
+ for (int row_ofs = 0; row_ofs < d->label_depth; row_ofs++)
+ {
+ for (size_t x1 = 0; x1 < n_columns; )
+ {
+ const struct pivot_category *c = find_category (
+ d, dim_index, column_enumeration + x1 * stride, row_ofs);
+ if (!c)
+ {
+ x1++;
+ continue;
+ }
+
+ size_t x2;
+ for (x2 = x1 + 1; x2 < n_columns; x2++)
+ {
+ const struct pivot_category *c2 = find_category (
+ d, dim_index, column_enumeration + x2 * stride, row_ofs);
+ if (c != c2)
+ break;
+ }
+
+ int y1 = bottom_row - row_ofs - c->extra_depth;
+ int y2 = bottom_row - row_ofs + 1;
+ bool is_outer_row = y1 == 0;
+ bool is_inner_row = y2 == b_size;
+ if (pivot_category_is_leaf (c) || c->show_label)
+ {
+ int bb[TABLE_N_AXES][2];
+ bb[a][0] = x1 + a_ofs;
+ bb[a][1] = x2 + a_ofs - 1;
+ bb[b][0] = y1;
+ bb[b][1] = y2 - 1;
+ bool rotate = ((rotate_inner_labels && is_inner_row)
+ || (rotate_outer_labels && is_outer_row));
+ fill_cell (t, bb[H][0], bb[V][0], bb[H][1], bb[V][1],
+ label_style, label_style_idx, c->name, footnotes,
+ show_values, show_variables, rotate);
+
+ if (pivot_category_is_leaf (c) && x2 + 1 <= n_columns)
+ {
+ enum pivot_border style
+ = (y1 == 0 && a_axis->label_depth > d->label_depth
+ ? dim_col_vert
+ : cat_col_vert);
+ draw_line (t, borders, style, b, x2 + a_ofs, y1,
+ t->table.n[b] - 1);
+ }
+ if (pivot_category_is_leaf (c) && x1 > 0)
+ {
+ enum pivot_border style
+ = (y1 == 0 && a_axis->label_depth > d->label_depth
+ ? dim_col_vert
+ : cat_col_vert);
+ draw_line (t, borders, style, b, x1 + a_ofs, y1,
+ t->table.n[b] - 1);
+ }
+ }
+ if (c->parent && c->parent->show_label)
+ draw_line (t, borders, cat_col_horz, a, y1,
+ x1 + a_ofs, x2 + a_ofs - 1);
+
+ x1 = x2;
+ }
+ }
+
+ if (d->root->show_label_in_corner && a_ofs > 0)
+ {
+ int bb[TABLE_N_AXES][2];
+ bb[a][0] = a_ofs - 1;
+ bb[a][1] = a_ofs - 1;
+ bb[b][0] = bottom_row - d->label_depth + 1;
+ bb[b][1] = bottom_row;
+ fill_cell (t, bb[H][0], bb[V][0], bb[H][1], bb[V][1],
+ corner_style, PIVOT_AREA_CORNER, d->root->name, footnotes,
+ show_values, show_variables, false);
+ }
+
+ if (dim_index > 1)
+ draw_line (t, borders, dim_col_horz, a, bottom_row + 1, a_ofs,
+ t->table.n[a] - 1);
+
+ bottom_row -= d->label_depth;
+ }
+}
+
+static void
+pivot_table_submit_layer (const struct pivot_table *st,
+ const size_t *layer_indexes)
+{
+ const size_t *pindexes[PIVOT_N_AXES]
+ = { [PIVOT_AXIS_LAYER] = layer_indexes };
+
+ struct string layer_label = DS_EMPTY_INITIALIZER;
+ const struct pivot_axis *layer_axis = &st->axes[PIVOT_AXIS_LAYER];
+ for (size_t i = 0; i < layer_axis->n_dimensions; i++)
+ {
+ const struct pivot_dimension *d = layer_axis->dimensions[i];
+ if (d->n_leaves)
+ {
+ if (!ds_is_empty (&layer_label))
+ ds_put_byte (&layer_label, '\n');
+ pivot_value_format (d->root->name, st->show_values,
+ st->show_variables, &layer_label);
+ ds_put_cstr (&layer_label, ": ");
+ pivot_value_format (d->data_leaves[layer_indexes[i]]->name,
+ st->show_values, st->show_variables,
+ &layer_label);
+ }
+ }
+
+ size_t body[TABLE_N_AXES];
+ size_t *column_enumeration = pivot_table_enumerate_axis (
+ st, PIVOT_AXIS_COLUMN, layer_indexes, st->omit_empty, &body[H]);
+ size_t *row_enumeration = pivot_table_enumerate_axis (
+ st, PIVOT_AXIS_ROW, layer_indexes, st->omit_empty, &body[V]);
+
+ int stub[TABLE_N_AXES] = {
+ [H] = st->axes[PIVOT_AXIS_ROW].label_depth,
+ [V] = st->axes[PIVOT_AXIS_COLUMN].label_depth,
+ };
+ struct tab_table *table = tab_create (body[H] + stub[H],
+ body[V] + stub[V]);
+ tab_headers (table, stub[H], 0, stub[V], 0);
+
+ for (size_t i = 0; i < PIVOT_N_AREAS; i++)
+ table->styles[i] = area_style_override (table->container, &st->areas[i],
+ NULL, NULL);
+
+ for (size_t i = 0; i < PIVOT_N_BORDERS; i++)
+ {
+ const struct table_border_style *in = &st->borders[i];
+ table->rule_colors[i] = pool_alloc (table->container,
+ sizeof *table->rule_colors[i]);
+ struct cell_color *out = table->rule_colors[i];
+ out->alpha = in->color.alpha;
+ out->r = in->color.r;
+ out->g = in->color.g;
+ out->b = in->color.b;
+ }
+
+ struct footnote **footnotes = xcalloc (st->n_footnotes, sizeof *footnotes);
+ for (size_t i = 0; i < st->n_footnotes; i++)
+ footnotes[i] = tab_create_footnote (
+ table, i,
+ pivot_value_to_string (st->footnotes[i]->content,
+ st->show_values, st->show_variables),
+ pivot_value_to_string (st->footnotes[i]->marker,
+ st->show_values, st->show_variables),
+ area_style_override (table->container, &st->areas[PIVOT_AREA_FOOTER],
+ st->footnotes[i]->content->cell_style,
+ st->footnotes[i]->content->font_style));
+
+ compose_headings (table,
+ &st->axes[PIVOT_AXIS_COLUMN], H, &st->axes[PIVOT_AXIS_ROW],
+ st->borders,
+ PIVOT_BORDER_DIM_COL_HORZ,
+ PIVOT_BORDER_DIM_COL_VERT,
+ PIVOT_BORDER_CAT_COL_HORZ,
+ PIVOT_BORDER_CAT_COL_VERT,
+ column_enumeration, body[H],
+ &st->areas[PIVOT_AREA_COLUMN_LABELS],
+ PIVOT_AREA_COLUMN_LABELS,
+ &st->areas[PIVOT_AREA_CORNER], footnotes,
+ st->rotate_inner_column_labels,
+ st->show_values, st->show_variables, false);
+
+ compose_headings (table,
+ &st->axes[PIVOT_AXIS_ROW], V, &st->axes[PIVOT_AXIS_COLUMN],
+ st->borders,
+ PIVOT_BORDER_DIM_ROW_VERT,
+ PIVOT_BORDER_DIM_ROW_HORZ,
+ PIVOT_BORDER_CAT_ROW_VERT,
+ PIVOT_BORDER_CAT_ROW_HORZ,
+ row_enumeration, body[V],
+ &st->areas[PIVOT_AREA_ROW_LABELS],
+ PIVOT_AREA_ROW_LABELS,
+ &st->areas[PIVOT_AREA_CORNER], footnotes,
+ false, st->show_values, st->show_variables,
+ st->rotate_outer_row_labels);
+
+ size_t *dindexes = xcalloc (st->n_dimensions, sizeof *dindexes);
+ size_t y = 0;
+ PIVOT_ENUMERATION_FOR_EACH (pindexes[PIVOT_AXIS_ROW], row_enumeration,
+ &st->axes[PIVOT_AXIS_ROW])
+ {
+ size_t x = 0;
+ PIVOT_ENUMERATION_FOR_EACH (pindexes[PIVOT_AXIS_COLUMN],
+ column_enumeration,
+ &st->axes[PIVOT_AXIS_COLUMN])
+ {
+ pivot_table_convert_indexes_ptod (st, pindexes, dindexes);
+ const struct pivot_value *value = pivot_table_get (st, dindexes);
+ fill_cell (table,
+ x + stub[H], y + stub[V],
+ x + stub[H], y + stub[V],
+ &st->areas[PIVOT_AREA_DATA], PIVOT_AREA_DATA,
+ value, footnotes,
+ st->show_values, st->show_variables, false);
+
+ x++;
+ }
+
+ y++;
+ }
+ free (dindexes);
+
+ if (st->corner_text && stub[H] && stub[V])
+ fill_cell (table, 0, 0, stub[H] - 1, stub[V] - 1,
+ &st->areas[PIVOT_AREA_CORNER], PIVOT_AREA_CORNER,
+ st->corner_text, footnotes,
+ st->show_values, st->show_variables, false);
+
+ if (tab_nc (table) && tab_nr (table))
+ {
+ tab_hline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_INNER_TOP),
+ 0, tab_nc (table) - 1, 0);
+ tab_hline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_INNER_BOTTOM),
+ 0, tab_nc (table) - 1, tab_nr (table));
+ tab_vline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_INNER_LEFT),
+ 0, 0, tab_nr (table) - 1);
+ tab_vline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_INNER_RIGHT),
+ tab_nc (table), 0, tab_nr (table) - 1);
+
+ if (stub[V])
+ tab_hline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_DATA_TOP),
+ 0, tab_nc (table) - 1, stub[V]);
+ if (stub[H])
+ tab_vline (
+ table, get_table_rule (st->borders, PIVOT_BORDER_DATA_LEFT),
+ stub[H], 0, tab_nr (table) - 1);
+
+ }
+ free (column_enumeration);
+ free (row_enumeration);
+
+ struct table_item *ti = table_item_create (&table->table, NULL, NULL);
+
+ if (st->title)
+ {
+ struct table_item_text *title = pivot_value_to_table_item_text (
+ st->title, &st->areas[PIVOT_AREA_TITLE], footnotes,
+ st->show_values, st->show_variables);
+ table_item_set_title (ti, title);
+ table_item_text_destroy (title);
+ }
+
+ if (!ds_is_empty (&layer_label))
+ {
+ struct table_item_text *layers = table_item_text_create (
+ ds_cstr (&layer_label));
+ layers->style = area_style_override (NULL, &st->areas[PIVOT_AREA_LAYERS],
+ NULL, NULL);
+ table_item_set_layers (ti, layers);
+ table_item_text_destroy (layers);
+
+ ds_destroy (&layer_label);
+ }
+
+ if (st->caption)
+ {
+ struct table_item_text *caption = pivot_value_to_table_item_text (
+ st->caption, &st->areas[PIVOT_AREA_CAPTION], footnotes,
+ st->show_values, st->show_variables);
+ table_item_set_caption (ti, caption);
+ table_item_text_destroy (caption);
+ }
+
+ table_item_submit (ti);
+}
+
+void
+pivot_table_submit (const struct pivot_table *st)
+{
+ pivot_table_assign_label_depth (CONST_CAST (struct pivot_table *, st));
+
+ int old_decimal = settings_get_decimal_char (FMT_COMMA);
+ if (st->decimal == '.' || st->decimal == ',')
+ settings_set_decimal_char (st->decimal);
+
+ if (st->print_all_layers)
+ {
+ size_t *layer_indexes;
+
+ PIVOT_AXIS_FOR_EACH (layer_indexes, &st->axes[PIVOT_AXIS_LAYER])
+ {
+ if (st->paginate_layers)
+ text_item_submit (text_item_create (TEXT_ITEM_EJECT_PAGE, ""));
+ pivot_table_submit_layer (st, layer_indexes);
+ }
+ }
+ else
+ pivot_table_submit_layer (st, st->current_layer);
+
+ settings_set_decimal_char (old_decimal);
+}
--- /dev/null
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2017, 2018 Free Software Foundation, Inc.
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see <http://www.gnu.org/licenses/>. */
+
+#include <config.h>
+
+#include "output/pivot-table.h"
+
+#include <stdlib.h>
+
+#include "data/data-out.h"
+#include "data/settings.h"
+#include "data/value.h"
+#include "data/variable.h"
+#include "libpspp/hash-functions.h"
+#include "libpspp/i18n.h"
+
+#include "gl/c-ctype.h"
+#include "gl/intprops.h"
+#include "gl/minmax.h"
+#include "gl/xalloc.h"
+#include "gl/xmemdup0.h"
+#include "gl/xsize.h"
+
+#include "gettext.h"
+#define _(msgid) gettext (msgid)
+#define N_(msgid) msgid
+
+static const struct fmt_spec *pivot_table_get_format (
+ const struct pivot_table *, const char *s);
+\f
+/* Pivot table display styling. */
+
+/* Returns the name of AREA. */
+const char *
+pivot_area_to_string (enum pivot_area area)
+{
+ switch (area)
+ {
+ case PIVOT_AREA_TITLE: return "title";
+ case PIVOT_AREA_CAPTION: return "caption";
+ case PIVOT_AREA_FOOTER: return "footer";
+ case PIVOT_AREA_CORNER: return "corner";
+ case PIVOT_AREA_COLUMN_LABELS: return "column labels";
+ case PIVOT_AREA_ROW_LABELS: return "row labels";
+ case PIVOT_AREA_DATA: return "data";
+ case PIVOT_AREA_LAYERS: return "layers";
+ case PIVOT_N_AREAS: default: return "**error**";
+ }
+}
+
+/* Returns the name of BORDER. */
+const char *
+pivot_border_to_string (enum pivot_border border)
+{
+ switch (border)
+ {
+ case PIVOT_BORDER_TITLE:
+ return "title";
+
+ case PIVOT_BORDER_OUTER_LEFT:
+ return "left outer frame";
+ case PIVOT_BORDER_OUTER_TOP:
+ return "top outer frame";
+ case PIVOT_BORDER_OUTER_RIGHT:
+ return "right outer frame";
+ case PIVOT_BORDER_OUTER_BOTTOM:
+ return "bottom outer frame";
+
+ case PIVOT_BORDER_INNER_LEFT:
+ return "left inner frame";
+ case PIVOT_BORDER_INNER_TOP:
+ return "top inner frame";
+ case PIVOT_BORDER_INNER_RIGHT:
+ return "right inner frame";
+ case PIVOT_BORDER_INNER_BOTTOM:
+ return "bottom inner frame";
+
+ case PIVOT_BORDER_DATA_LEFT:
+ return "data area left";
+ case PIVOT_BORDER_DATA_TOP:
+ return "data area top";
+
+ case PIVOT_BORDER_DIM_ROW_HORZ:
+ return "row label horizontal dimension border";
+ case PIVOT_BORDER_DIM_ROW_VERT:
+ return "row label vertical dimension border";
+ case PIVOT_BORDER_DIM_COL_HORZ:
+ return "column label horizontal dimension border";
+ case PIVOT_BORDER_DIM_COL_VERT:
+ return "column label vertical dimension border";
+
+ case PIVOT_BORDER_CAT_ROW_HORZ:
+ return "row label horizontal category border";
+ case PIVOT_BORDER_CAT_ROW_VERT:
+ return "row label vertical category border";
+ case PIVOT_BORDER_CAT_COL_HORZ:
+ return "column label horizontal category border";
+ case PIVOT_BORDER_CAT_COL_VERT:
+ return "column label vertical category border";
+
+ case PIVOT_N_BORDERS:
+ default:
+ return "**error**";
+ }
+}
+
+void
+pivot_table_sizing_uninit (struct pivot_table_sizing *sizing)
+{
+ if (sizing)
+ {
+ free (sizing->widths);
+ free (sizing->breaks);
+ free (sizing->keeps);
+ }
+}
+\f
+/* Axes. */
+
+/* Returns the name of AXIS_TYPE. */
+const char *
+pivot_axis_type_to_string (enum pivot_axis_type axis_type)
+{
+ switch (axis_type)
+ {
+ case PIVOT_AXIS_LAYER:
+ return "layer";
+
+ case PIVOT_AXIS_ROW:
+ return "row";
+
+ case PIVOT_AXIS_COLUMN:
+ return "column";
+
+ default:
+ return "<error>";
+ }
+}
+
+static enum pivot_axis_type
+pivot_axis_type_transpose (enum pivot_axis_type axis_type)
+{
+ assert (axis_type == PIVOT_AXIS_ROW || axis_type == PIVOT_AXIS_COLUMN);
+ return (axis_type == PIVOT_AXIS_ROW ? PIVOT_AXIS_COLUMN : PIVOT_AXIS_ROW);
+}
+
+/* Implementation of PIVOT_AXIS_FOR_EACH. */
+size_t *
+pivot_axis_iterator_next (size_t *indexes, const struct pivot_axis *axis)
+{
+ if (!indexes)
+ {
+ if (axis->n_dimensions)
+ for (size_t i = 0; i < axis->n_dimensions; i++)
+ if (axis->dimensions[i]->n_leaves == 0)
+ return NULL;
+
+ return xcalloc (axis->n_dimensions, sizeof *indexes);
+ }
+
+ for (size_t i = 0; i < axis->n_dimensions; i++)
+ {
+ const struct pivot_dimension *d = axis->dimensions[i];
+ if (++indexes[i] < d->n_leaves)
+ return indexes;
+
+ indexes[i] = 0;
+ }
+
+ free (indexes);
+ return NULL;
+}
+\f
+/* Dimensions. */
+
+static void
+pivot_category_set_rc (struct pivot_category *category, const char *s)
+{
+ const struct fmt_spec *format = pivot_table_get_format (
+ category->dimension->table, s);
+ if (format)
+ category->format = *format;
+}
+
+static void
+pivot_category_create_leaves_valist (struct pivot_category *parent,
+ va_list args)
+{
+ const char *s;
+ while ((s = va_arg (args, const char *)))
+ {
+ if (!strncmp (s, "RC_", 3))
+ {
+ assert (parent->n_subs);
+ pivot_category_set_rc (parent->subs[parent->n_subs - 1], s);
+ }
+ else
+ pivot_category_create_leaf (parent, pivot_value_new_text (s));
+ }
+}
+
+/* Creates a new dimension with the given NAME in TABLE and returns it. The
+ dimension is added to axis AXIS_TYPE, becoming the outermost dimension on
+ that axis.
+
+ NAME should be a translatable name, but not actually translated yet,
+ e.g. enclosed in N_(). To use a different kind of value for a name, use
+ pivot_dimension_create__() instead.
+
+ The optional varargs parameters may be used to add an initial set of
+ categories to the dimension. Each string should be a translatable category
+ name, but not actually translated yet, e.g. enclosed in N_(). Each string
+ may optionally be followod by a PIVOT_RC_* string that specifies the default
+ numeric format for cells in this category. */
+struct pivot_dimension * SENTINEL (0)
+(pivot_dimension_create) (struct pivot_table *table,
+ enum pivot_axis_type axis_type,
+ const char *name, ...)
+{
+ struct pivot_dimension *d = pivot_dimension_create__ (
+ table, axis_type, pivot_value_new_text (name));
+
+ va_list args;
+ va_start (args, name);
+ pivot_category_create_leaves_valist (d->root, args);
+ va_end (args);
+
+ return d;
+}
+
+/* Creates a new dimension with the given NAME in TABLE and returns it. The
+ dimension is added to axis AXIS_TYPE, becoming the outermost dimension on
+ that axis. */
+struct pivot_dimension *
+pivot_dimension_create__ (struct pivot_table *table,
+ enum pivot_axis_type axis_type,
+ struct pivot_value *name)
+{
+ assert (pivot_table_is_empty (table));
+
+ struct pivot_dimension *d = xmalloc (sizeof *d);
+ *d = (struct pivot_dimension) {
+ .table = table,
+ .axis_type = axis_type,
+ .level = table->axes[axis_type].n_dimensions,
+ .top_index = table->n_dimensions,
+ .root = xmalloc (sizeof *d->root),
+ };
+
+ struct pivot_category *root = d->root;
+ *root = (struct pivot_category) {
+ .name = name,
+ .parent = NULL,
+ .dimension = d,
+ .show_label = false,
+ .data_index = SIZE_MAX,
+ .presentation_index = SIZE_MAX,
+ };
+
+ table->dimensions = xrealloc (
+ table->dimensions, (table->n_dimensions + 1) * sizeof *table->dimensions);
+ table->dimensions[table->n_dimensions++] = d;
+
+ struct pivot_axis *axis = &table->axes[axis_type];
+ axis->dimensions = xrealloc (
+ axis->dimensions, (axis->n_dimensions + 1) * sizeof *axis->dimensions);
+ axis->dimensions[axis->n_dimensions++] = d;
+
+ /* XXX extent and label_depth need to be calculated later. */
+
+ return d;
+}
+
+void
+pivot_dimension_destroy (struct pivot_dimension *d)
+{
+ if (!d)
+ return;
+
+ pivot_category_destroy (d->root);
+ free (d->data_leaves);
+ free (d->presentation_leaves);
+}
+
+/* Returns the first leaf node in an in-order traversal that is a child of
+ CAT. */
+static const struct pivot_category * UNUSED
+pivot_category_first_leaf (const struct pivot_category *cat)
+{
+ if (pivot_category_is_leaf (cat))
+ return cat;
+
+ for (size_t i = 0; i < cat->n_subs; i++)
+ {
+ const struct pivot_category *first
+ = pivot_category_first_leaf (cat->subs[i]);
+ if (first)
+ return first;
+ }
+
+ return NULL;
+}
+
+/* Returns the next leaf node in an in-order traversal starting at CAT, which
+ must be a leaf. */
+static const struct pivot_category * UNUSED
+pivot_category_next_leaf (const struct pivot_category *cat)
+{
+ assert (pivot_category_is_leaf (cat));
+
+ for (;;)
+ {
+ const struct pivot_category *parent = cat->parent;
+ if (!parent)
+ return NULL;
+ for (size_t i = cat->group_index + 1; i < parent->n_subs; i++)
+ {
+ const struct pivot_category *next
+ = pivot_category_first_leaf (parent->subs[i]);
+ if (next)
+ return next;
+ }
+
+ cat = cat->parent;
+ }
+}
+
+static void
+pivot_category_add_child (struct pivot_category *child)
+{
+ struct pivot_category *parent = child->parent;
+
+ assert (pivot_category_is_group (parent));
+ if (parent->n_subs >= parent->allocated_subs)
+ parent->subs = x2nrealloc (parent->subs, &parent->allocated_subs,
+ sizeof *parent->subs);
+ parent->subs[parent->n_subs++] = child;
+}
+
+/* Adds leaf categories as a child of PARENT. To create top-level categories
+ within dimension 'd', pass 'd->root' for PARENT.
+
+ Each of the varargs parameters should be a string, each of which should be a
+ translatable category name, but not actually translated yet, e.g. enclosed
+ in N_(). Each string may optionally be followod by a PIVOT_RC_* string that
+ specifies the default numeric format for cells in this category.
+
+ Returns the category index, which is just a 0-based array index, for the
+ first new category.
+
+ Leaves have to be created in in-order, that is, don't create a group and add
+ some leaves, then add leaves outside the group and try to add more leaves
+ inside it. */
+int SENTINEL (0)
+(pivot_category_create_leaves) (struct pivot_category *parent, ...)
+{
+ int retval = parent->dimension->n_leaves;
+
+ va_list args;
+ va_start (args, parent);
+ pivot_category_create_leaves_valist (parent, args);
+ va_end (args);
+
+ return retval;
+}
+
+/* Creates a new leaf category with the given NAME as a child of PARENT. To
+ create a top-level category within dimension 'd', pass 'd->root' for PARENT.
+ Returns the category index, which is just a 0-based array index, for the new
+ category.
+
+ Leaves have to be created in in-order, that is, don't create a group and add
+ some leaves, then add leaves outside the group and try to add more leaves
+ inside it. */
+int
+pivot_category_create_leaf (struct pivot_category *parent,
+ struct pivot_value *name)
+{
+ return pivot_category_create_leaf_rc (parent, name, NULL);
+}
+
+/* Creates a new leaf category with the given NAME as a child of PARENT. To
+ create a top-level category within dimension 'd', pass 'd->root' for PARENT.
+ Returns the category index, which is just a 0-based array index, for the new
+ category.
+
+ If RC is nonnull and the name of a result category, the category is assigned
+ that result category.
+
+ Leaves have to be created in in-order, that is, don't create a group and add
+ some leaves, then add leaves outside the group and try to add more leaves
+ inside it. */
+int
+pivot_category_create_leaf_rc (struct pivot_category *parent,
+ struct pivot_value *name, const char *rc)
+{
+ struct pivot_dimension *d = parent->dimension;
+
+ struct pivot_category *leaf = xmalloc (sizeof *leaf);
+ *leaf = (struct pivot_category) {
+ .name = name,
+ .parent = parent,
+ .dimension = d,
+ .group_index = parent->n_subs,
+ .data_index = d->n_leaves,
+ .presentation_index = d->n_leaves,
+ };
+
+ if (d->n_leaves >= d->allocated_leaves)
+ {
+ d->data_leaves = x2nrealloc (d->data_leaves, &d->allocated_leaves,
+ sizeof *d->data_leaves);
+ d->presentation_leaves = xrealloc (
+ d->presentation_leaves,
+ d->allocated_leaves * sizeof *d->presentation_leaves);
+ }
+
+ d->data_leaves[d->n_leaves] = leaf;
+ d->presentation_leaves[d->n_leaves] = leaf;
+ d->n_leaves++;
+
+ pivot_category_add_child (leaf);
+
+ /* Make sure that the new child is the last in in-order. */
+ assert (!pivot_category_next_leaf (leaf));
+
+ pivot_category_set_rc (leaf, rc);
+
+ return leaf->data_index;
+}
+
+/* Adds a new category group named NAME as a child of PARENT. To create a
+ top-level group within dimension 'd', pass 'd->root' for PARENT.
+
+ NAME should be a translatable name, but not actually translated yet,
+ e.g. enclosed in N_(). To use a different kind of value for a name, use
+ pivot_category_create_group__() instead.
+
+ The optional varargs parameters may be used to add an initial set of
+ categories to the group. Each string should be a translatable category
+ name, but not actually translated yet, e.g. enclosed in N_(). Each string
+ may optionally be followod by a PIVOT_RC_* string that specifies the default
+ numeric format for cells in this category.
+
+ Returns the new group. */
+struct pivot_category * SENTINEL (0)
+(pivot_category_create_group) (struct pivot_category *parent,
+ const char *name, ...)
+{
+ struct pivot_category *group = pivot_category_create_group__ (
+ parent, pivot_value_new_text (name));
+
+ va_list args;
+ va_start (args, name);
+ pivot_category_create_leaves_valist (group, args);
+ va_end (args);
+
+ return group;
+}
+
+/* Adds a new category group named NAME as a child of PARENT. To create a
+ top-level group within dimension 'd', pass 'd->root' for PARENT. Returns
+ the new group. */
+struct pivot_category *
+pivot_category_create_group__ (struct pivot_category *parent,
+ struct pivot_value *name)
+{
+ struct pivot_dimension *d = parent->dimension;
+
+ struct pivot_category *group = xmalloc (sizeof *group);
+ *group = (struct pivot_category) {
+ .name = name,
+ .parent = parent,
+ .dimension = d,
+ .show_label = true,
+ .group_index = parent->n_subs,
+ .data_index = SIZE_MAX,
+ .presentation_index = SIZE_MAX,
+ };
+
+ pivot_category_add_child (group);
+
+ return group;
+}
+
+void
+pivot_category_destroy (struct pivot_category *c)
+{
+ if (!c)
+ return;
+
+ pivot_value_destroy (c->name);
+ for (size_t i = 0; i < c->n_subs; i++)
+ pivot_category_destroy (c->subs[i]);
+ free (c);
+}
+\f
+/* Result classes.
+
+ These are usually the easiest way to control the formatting of numeric data
+ in a pivot table. See pivot_dimension_create() for an explanation of their
+ use. */
+struct result_class
+ {
+ const char *name; /* "RC_*". */
+ struct fmt_spec format;
+ };
+
+/* Formats for most of the result classes. */
+static struct result_class result_classes[] =
+ {
+ { PIVOT_RC_INTEGER, { FMT_F, 40, 0 } },
+ { PIVOT_RC_PERCENT, { FMT_PCT, 40, 1 } },
+ { PIVOT_RC_CORRELATION, { FMT_F, 40, 3 } },
+ { PIVOT_RC_SIGNIFICANCE, { FMT_F, 40, 3 } },
+ { PIVOT_RC_RESIDUAL, { FMT_F, 40, 2 } },
+ { PIVOT_RC_COUNT, { 0, 0, 0 } },
+ { PIVOT_RC_OTHER, { 0, 0, 0 } },
+ };
+
+/* Has PIVOT_RC_COUNT been overridden by the user? */
+static bool overridden_count_format;
+
+static struct result_class *
+pivot_result_class_find (const char *s)
+{
+ for (size_t i = 0; i < sizeof result_classes / sizeof *result_classes; i++)
+ if (!strcmp (s, result_classes[i].name))
+ return &result_classes[i];
+ return NULL;
+}
+
+static const struct fmt_spec *
+pivot_table_get_format (const struct pivot_table *table, const char *s)
+{
+ if (!s)
+ return NULL;
+ else if (!strcmp (s, PIVOT_RC_OTHER))
+ return settings_get_format ();
+ else if (!strcmp (s, PIVOT_RC_COUNT) && !overridden_count_format)
+ return &table->weight_format;
+ else
+ {
+ const struct result_class *rc = pivot_result_class_find (s);
+ return rc ? &rc->format : NULL;
+ }
+}
+
+/* Sets the format specification for the result class named S (which should not
+ include the RC_ prefix) to *FORMAT. Returns true if successful, false if S
+ does not name a known result class. */
+bool
+pivot_result_class_change (const char *s_, const struct fmt_spec *format)
+{
+ char *s = xasprintf ("RC_%s", s_);
+ struct result_class *rc = pivot_result_class_find (s);
+ if (rc)
+ {
+ rc->format = *format;
+ if (!strcmp (s, PIVOT_RC_COUNT))
+ overridden_count_format = true;
+ }
+ free (s);
+
+ return rc != NULL;
+}
+\f
+/* One piece of data within a pivot table. */
+struct pivot_cell
+ {
+ struct hmap_node hmap_node; /* In struct pivot_table's 'cells' hmap. */
+ struct pivot_value *value;
+ unsigned int idx[]; /* One index per table dimension. */
+ };
+
+/* Pivot tables. */
+
+/* Creates and returns a new pivot table with the given TITLE. TITLE should be
+ a text string marked for translation but not actually translated yet,
+ e.g. N_("Descriptive Statistics").
+
+ Operations commonly performed on the new pivot_table:
+
+ - If empty rows or columns should not be displayed, set ->omit_empty to
+ true.
+
+ - Set the format to use for "count" values with pivot_table_set_weight_var()
+ or pivot_table_set_weight_format().
+
+ This function is a shortcut for pivot_table_create__() for the most common
+ case. Use pivot_table_create__() directly if the title should be some kind
+ of value other than an ordinary text string.
+
+ See the large comment at the top of pivot-table.h for general advice on
+ creating pivot tables. */
+struct pivot_table *
+pivot_table_create (const char *title)
+{
+ return pivot_table_create__ (pivot_value_new_text (title));
+}
+
+/* Creates and returns a new pivot table with the given TITLE.
+
+ Operations commonly performed on the new pivot_table:
+
+ - If empty rows or columns should not be displayed, set ->omit_empty to
+ true.
+
+ - Set the format to use for "count" values with pivot_table_set_weight_var()
+ or pivot_table_set_weight_format().
+
+ See the large comment at the top of pivot-table.h for general advice on
+ creating pivot tables. */
+struct pivot_table *
+pivot_table_create__ (struct pivot_value *title)
+{
+ struct pivot_table *table = xzalloc (sizeof *table);
+ table->weight_format = (struct fmt_spec) { FMT_F, 40, 0 };
+ table->title = title;
+
+ /* Set default area styles. */
+#define STYLE(BOLD, H, V, L, R, T, B) { \
+ .cell_style = { \
+ .halign = TABLE_HALIGN_##H, \
+ .valign = TABLE_VALIGN_##V, \
+ .margin = { [TABLE_HORZ][0] = L, [TABLE_HORZ][1] = R, \
+ [TABLE_VERT][0] = T, [TABLE_VERT][1] = B }, \
+ }, \
+ .font_style = { \
+ .bold = BOLD, \
+ .fg = { [0] = CELL_COLOR_BLACK, [1] = CELL_COLOR_BLACK}, \
+ .bg = { [0] = CELL_COLOR_WHITE, [1] = CELL_COLOR_WHITE}, \
+ }, \
+ }
+ static const struct area_style default_area_styles[PIVOT_N_AREAS] = {
+ [PIVOT_AREA_TITLE] = STYLE( true, CENTER, CENTER, 8,11,1,8),
+ [PIVOT_AREA_CAPTION] = STYLE(false, LEFT, TOP, 8,11,1,1),
+ [PIVOT_AREA_FOOTER] = STYLE(false, LEFT, TOP, 11, 8,2,3),
+ [PIVOT_AREA_CORNER] = STYLE(false, LEFT, BOTTOM, 8,11,1,1),
+ [PIVOT_AREA_COLUMN_LABELS] = STYLE(false, CENTER, BOTTOM, 8,11,1,3),
+ [PIVOT_AREA_ROW_LABELS] = STYLE(false, LEFT, TOP, 8,11,1,3),
+ [PIVOT_AREA_DATA] = STYLE(false, MIXED, TOP, 8,11,1,1),
+ [PIVOT_AREA_LAYERS] = STYLE(false, LEFT, BOTTOM, 8,11,1,3),
+ };
+#undef STYLE
+ for (size_t i = 0; i < PIVOT_N_AREAS; i++)
+ table->areas[i] = default_area_styles[i];
+
+ /* Set default border styles. */
+ static const enum table_stroke default_strokes[PIVOT_N_BORDERS] = {
+ [PIVOT_BORDER_TITLE] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_OUTER_LEFT] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_OUTER_TOP] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_OUTER_RIGHT] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_OUTER_BOTTOM] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_INNER_LEFT] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_INNER_TOP] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_INNER_RIGHT] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_INNER_BOTTOM] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_DATA_LEFT] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_DATA_TOP] = TABLE_STROKE_THICK,
+ [PIVOT_BORDER_DIM_ROW_HORZ] = TABLE_STROKE_SOLID,
+ [PIVOT_BORDER_DIM_ROW_VERT] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_DIM_COL_HORZ] = TABLE_STROKE_SOLID,
+ [PIVOT_BORDER_DIM_COL_VERT] = TABLE_STROKE_SOLID,
+ [PIVOT_BORDER_CAT_ROW_HORZ] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_CAT_ROW_VERT] = TABLE_STROKE_NONE,
+ [PIVOT_BORDER_CAT_COL_HORZ] = TABLE_STROKE_SOLID,
+ [PIVOT_BORDER_CAT_COL_VERT] = TABLE_STROKE_SOLID,
+ };
+ for (size_t i = 0; i < PIVOT_N_BORDERS; i++)
+ table->borders[i] = (struct table_border_style) {
+ .stroke = default_strokes[i],
+ .color = CELL_COLOR_BLACK,
+ };
+
+ table->row_labels_in_corner = true;
+ hmap_init (&table->cells);
+
+ return table;
+}
+
+/* Creates and returns a new pivot table with the given TITLE and a single cell
+ with the given CONTENT.
+
+ This is really just for error handling. */
+struct pivot_table *
+pivot_table_create_for_text (struct pivot_value *title,
+ struct pivot_value *content)
+{
+ struct pivot_table *table = pivot_table_create__ (title);
+
+ struct pivot_dimension *d = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Error"));
+ d->hide_all_labels = true;
+ pivot_category_create_leaf (d->root, pivot_value_new_text ("null"));
+
+ pivot_table_put1 (table, 0, content);
+
+ return table;
+}
+
+/* Destroys TABLE and frees everything it points to. */
+void
+pivot_table_destroy (struct pivot_table *table)
+{
+ if (!table)
+ return;
+
+ free (table->current_layer);
+ free (table->table_look);
+
+ for (int i = 0; i < TABLE_N_AXES; i++)
+ pivot_table_sizing_uninit (&table->sizing[i]);
+
+ free (table->continuation);
+
+ for (int i = 0; i < sizeof table->ccs / sizeof *table->ccs; i++)
+ free (table->ccs[i]);
+
+ free (table->command_local);
+ free (table->command_c);
+ free (table->language);
+ free (table->locale);
+
+ free (table->dataset);
+ free (table->datafile);
+
+ for (size_t i = 0; i < table->n_footnotes; i++)
+ pivot_footnote_destroy (table->footnotes[i]);
+ free (table->footnotes);
+
+ pivot_value_destroy (table->title);
+ pivot_value_destroy (table->subtype);
+ pivot_value_destroy (table->corner_text);
+ pivot_value_destroy (table->caption);
+
+ for (size_t i = 0; i < PIVOT_N_AREAS; i++)
+ area_style_uninit (&table->areas[i]);
+
+ for (size_t i = 0; i < table->n_dimensions; i++)
+ pivot_dimension_destroy (table->dimensions[i]);
+ free (table->dimensions);
+
+ for (size_t i = 0; i < PIVOT_N_AXES; i++)
+ free (table->axes[i].dimensions);
+
+ struct pivot_cell *cell, *next_cell;
+ HMAP_FOR_EACH_SAFE (cell, next_cell, struct pivot_cell, hmap_node,
+ &table->cells)
+ {
+ hmap_delete (&table->cells, &cell->hmap_node);
+ pivot_value_destroy (cell->value);
+ free (cell);
+ }
+ hmap_destroy (&table->cells);
+
+ free (table);
+}
+
+/* Sets the format used for PIVOT_RC_COUNT cells to the one used for variable
+ WV, which should be the weight variable for the dictionary whose data or
+ statistics are being put into TABLE.
+
+ This has no effect if WV is NULL. */
+void
+pivot_table_set_weight_var (struct pivot_table *table,
+ const struct variable *wv)
+{
+ if (wv)
+ pivot_table_set_weight_format (table, var_get_print_format (wv));
+}
+
+/* Sets the format used for PIVOT_RC_COUNT cells to WFMT, which should be the
+ format for the dictionary whose data or statistics are being put into TABLE.
+
+ This has no effect if WFMT is NULL. */
+void
+pivot_table_set_weight_format (struct pivot_table *table,
+ const struct fmt_spec *wfmt)
+{
+ if (wfmt)
+ table->weight_format = *wfmt;
+}
+
+/* Returns true if TABLE has no cells, false otherwise. */
+bool
+pivot_table_is_empty (const struct pivot_table *table)
+{
+ return hmap_is_empty (&table->cells);
+}
+
+static unsigned int
+pivot_cell_hash_indexes (const size_t *indexes, size_t n_idx)
+{
+ return hash_bytes (indexes, n_idx * sizeof *indexes, 0);
+}
+
+static bool
+equal_indexes (const size_t *a, const size_t *b, size_t n)
+{
+ for (size_t i = 0; i < n; i++)
+ if (a[i] != b[i])
+ return false;
+
+ return true;
+}
+
+static struct pivot_cell *
+pivot_table_lookup_cell__ (const struct pivot_table *table,
+ const size_t *dindexes, unsigned int hash)
+{
+ struct pivot_cell *cell;
+ HMAP_FOR_EACH_WITH_HASH (cell, struct pivot_cell, hmap_node, hash,
+ &table->cells)
+ if (equal_indexes (dindexes, cell->idx, table->n_dimensions))
+ return cell;
+ return false;
+}
+
+static struct pivot_cell *
+pivot_cell_allocate (size_t n_idx)
+{
+ struct pivot_cell *cell UNUSED;
+ return xmalloc (sizeof *cell + n_idx * sizeof *cell->idx);
+}
+
+static struct pivot_cell *
+pivot_table_insert_cell (struct pivot_table *table, const size_t *dindexes)
+{
+ unsigned int hash = pivot_cell_hash_indexes (dindexes, table->n_dimensions);
+ struct pivot_cell *cell = pivot_table_lookup_cell__ (table, dindexes, hash);
+ if (!cell)
+ {
+ cell = pivot_cell_allocate (table->n_dimensions);
+ for (size_t i = 0; i < table->n_dimensions; i++)
+ cell->idx[i] = dindexes[i];
+ cell->value = NULL;
+ hmap_insert (&table->cells, &cell->hmap_node, hash);
+ }
+ return cell;
+}
+
+/* Puts VALUE in the cell in TABLE whose indexes are given by the N indexes in
+ DINDEXES. N must be the number of dimensions in TABLE. Takes ownership of
+ VALUE.
+
+ If VALUE is a numeric value without a specified format, this function checks
+ each of the categories designated by DINDEXES[] and takes the format from
+ the first category with a result class. If none has a result class, uses
+ the overall default numeric format. */
+void
+pivot_table_put (struct pivot_table *table, const size_t *dindexes, size_t n,
+ struct pivot_value *value)
+{
+ assert (n == table->n_dimensions);
+
+ if (value->type == PIVOT_VALUE_NUMERIC && !value->numeric.format.w)
+ {
+ for (size_t i = 0; i < table->n_dimensions; i++)
+ {
+ const struct pivot_dimension *d = table->dimensions[i];
+ if (dindexes[i] < d->n_leaves)
+ {
+ const struct pivot_category *c = d->data_leaves[dindexes[i]];
+ if (c->format.w)
+ {
+ value->numeric.format = c->format;
+ goto done;
+ }
+ }
+ }
+ value->numeric.format = *settings_get_format ();
+
+ done:;
+ }
+
+ struct pivot_cell *cell = pivot_table_insert_cell (table, dindexes);
+ pivot_value_destroy (cell->value);
+ cell->value = value;
+}
+
+/* Puts VALUE in the cell in TABLE with index IDX1. TABLE must have 1
+ dimension. Takes ownership of VALUE. */
+void
+pivot_table_put1 (struct pivot_table *table, size_t idx1,
+ struct pivot_value *value)
+{
+ size_t dindexes[] = { idx1 };
+ pivot_table_put (table, dindexes, sizeof dindexes / sizeof *dindexes, value);
+}
+
+/* Puts VALUE in the cell in TABLE with index (IDX1, IDX2). TABLE must have 2
+ dimensions. Takes ownership of VALUE. */
+void
+pivot_table_put2 (struct pivot_table *table, size_t idx1, size_t idx2,
+ struct pivot_value *value)
+{
+ size_t dindexes[] = { idx1, idx2 };
+ pivot_table_put (table, dindexes, sizeof dindexes / sizeof *dindexes, value);
+}
+
+/* Puts VALUE in the cell in TABLE with index (IDX1, IDX2, IDX3). TABLE must
+ have 3 dimensions. Takes ownership of VALUE. */
+void
+pivot_table_put3 (struct pivot_table *table, size_t idx1, size_t idx2,
+ size_t idx3, struct pivot_value *value)
+{
+ size_t dindexes[] = { idx1, idx2, idx3 };
+ pivot_table_put (table, dindexes, sizeof dindexes / sizeof *dindexes, value);
+}
+
+/* Puts VALUE in the cell in TABLE with index (IDX1, IDX2, IDX3, IDX4). TABLE
+ must have 4 dimensions. Takes ownership of VALUE. */
+void
+pivot_table_put4 (struct pivot_table *table, size_t idx1, size_t idx2,
+ size_t idx3, size_t idx4, struct pivot_value *value)
+{
+ size_t dindexes[] = { idx1, idx2, idx3, idx4 };
+ pivot_table_put (table, dindexes, sizeof dindexes / sizeof *dindexes, value);
+}
+
+/* Creates and returns a new footnote in TABLE with the given CONTENT and an
+ automatically assigned marker.
+
+ The footnote will only appear in output if it is referenced. Use
+ pivot_value_add_footnote() to add a reference to the footnote. */
+struct pivot_footnote *
+pivot_table_create_footnote (struct pivot_table *table,
+ struct pivot_value *content)
+{
+ return pivot_table_create_footnote__ (table, table->n_footnotes,
+ NULL, content);
+}
+
+static struct pivot_value *
+pivot_make_default_footnote_marker (int idx, bool show_numeric_markers)
+{
+ char text[INT_BUFSIZE_BOUND (size_t)];
+ if (show_numeric_markers)
+ snprintf (text, sizeof text, "%d", idx + 1);
+ else
+ str_format_26adic (idx + 1, false, text, sizeof text);
+ return pivot_value_new_user_text (text, -1);
+}
+
+/* Creates or modifies a footnote in TABLE with 0-based number IDX. If MARKER
+ is nonnull, sets the footnote's marker; if CONTENT is nonnull, sets the
+ footnote's content. */
+struct pivot_footnote *
+pivot_table_create_footnote__ (struct pivot_table *table, size_t idx,
+ struct pivot_value *marker,
+ struct pivot_value *content)
+{
+ if (idx >= table->n_footnotes)
+ {
+ while (idx >= table->allocated_footnotes)
+ table->footnotes = x2nrealloc (table->footnotes,
+ &table->allocated_footnotes,
+ sizeof *table->footnotes);
+ while (idx >= table->n_footnotes)
+ {
+ struct pivot_footnote *f = xmalloc (sizeof *f);
+ f->idx = table->n_footnotes;
+ f->marker = pivot_make_default_footnote_marker (
+ f->idx, table->show_numeric_markers);
+ f->content = NULL;
+
+ table->footnotes[table->n_footnotes++] = f;
+ }
+ }
+
+ struct pivot_footnote *f = table->footnotes[idx];
+ if (marker)
+ {
+ pivot_value_destroy (f->marker);
+ f->marker = marker;
+ }
+ if (content)
+ {
+ pivot_value_destroy (f->content);
+ f->content = content;
+ }
+ return f;
+}
+
+/* Frees the data owned by F. */
+void
+pivot_footnote_destroy (struct pivot_footnote *f)
+{
+ if (f)
+ {
+ pivot_value_destroy (f->content);
+ pivot_value_destroy (f->marker);
+ free (f);
+ }
+}
+
+/* Converts per-axis presentation-order indexes, given in PINDEXES, into data
+ indexes for each dimension in TABLE in DINDEXES[]. */
+void
+pivot_table_convert_indexes_ptod (const struct pivot_table *table,
+ const size_t *pindexes[PIVOT_N_AXES],
+ size_t dindexes[/* table->n_dimensions */])
+{
+ for (size_t i = 0; i < PIVOT_N_AXES; i++)
+ {
+ const struct pivot_axis *axis = &table->axes[i];
+
+ for (size_t j = 0; j < axis->n_dimensions; j++)
+ {
+ const struct pivot_dimension *d = axis->dimensions[j];
+ dindexes[d->top_index]
+ = d->presentation_leaves[pindexes[i][j]]->data_index;
+ }
+ }
+}
+
+size_t *
+pivot_table_enumerate_axis (const struct pivot_table *table,
+ enum pivot_axis_type axis_type,
+ const size_t *layer_indexes, bool omit_empty,
+ size_t *n)
+{
+ const struct pivot_axis *axis = &table->axes[axis_type];
+ if (!axis->n_dimensions)
+ {
+ size_t *enumeration = xnmalloc (2, sizeof *enumeration);
+ enumeration[0] = 0;
+ enumeration[1] = SIZE_MAX;
+ if (n)
+ *n = 1;
+ return enumeration;
+ }
+ else if (!axis->extent)
+ {
+ size_t *enumeration = xmalloc (sizeof *enumeration);
+ *enumeration = SIZE_MAX;
+ if (n)
+ *n = 0;
+ return enumeration;
+ }
+
+ size_t *enumeration = xnmalloc (xsum (xtimes (axis->extent,
+ axis->n_dimensions), 1),
+ sizeof *enumeration);
+ size_t *p = enumeration;
+ size_t *dindexes = xcalloc (table->n_dimensions, sizeof *dindexes);
+
+ size_t *axis_indexes;
+ PIVOT_AXIS_FOR_EACH (axis_indexes, axis)
+ {
+ if (omit_empty)
+ {
+ enum pivot_axis_type axis2_type
+ = pivot_axis_type_transpose (axis_type);
+
+ size_t *axis2_indexes;
+ PIVOT_AXIS_FOR_EACH (axis2_indexes, &table->axes[axis2_type])
+ {
+ const size_t *pindexes[PIVOT_N_AXES];
+ pindexes[PIVOT_AXIS_LAYER] = layer_indexes;
+ pindexes[axis_type] = axis_indexes;
+ pindexes[axis2_type] = axis2_indexes;
+ pivot_table_convert_indexes_ptod (table, pindexes, dindexes);
+ if (pivot_table_get (table, dindexes))
+ goto found;
+ }
+ continue;
+
+ found:
+ free (axis2_indexes);
+ }
+
+ memcpy (p, axis_indexes, axis->n_dimensions * sizeof *p);
+ p += axis->n_dimensions;
+ }
+ *p = SIZE_MAX;
+ if (n)
+ *n = (p - enumeration) / axis->n_dimensions;
+
+ free (dindexes);
+ return enumeration;
+}
+
+static const struct pivot_cell *
+pivot_table_lookup_cell (const struct pivot_table *table,
+ const size_t *dindexes)
+{
+ unsigned int hash = pivot_cell_hash_indexes (dindexes, table->n_dimensions);
+ return pivot_table_lookup_cell__ (table, dindexes, hash);
+}
+
+const struct pivot_value *
+pivot_table_get (const struct pivot_table *table, const size_t *dindexes)
+{
+ const struct pivot_cell *cell = pivot_table_lookup_cell (table, dindexes);
+ return cell ? cell->value : NULL;
+}
+
+struct pivot_value *
+pivot_table_get_rw (struct pivot_table *table, const size_t *dindexes)
+{
+ struct pivot_cell *cell = pivot_table_insert_cell (table, dindexes);
+ if (!cell->value)
+ cell->value = pivot_value_new_user_text ("", -1);
+ return cell->value;
+}
+
+static void
+distribute_extra_depth (struct pivot_category *category, size_t extra_depth)
+{
+ if (pivot_category_is_group (category) && category->n_subs)
+ for (size_t i = 0; i < category->n_subs; i++)
+ distribute_extra_depth (category->subs[i], extra_depth);
+ else
+ category->extra_depth += extra_depth;
+}
+
+static void
+pivot_category_assign_label_depth (struct pivot_category *category,
+ bool dimension_labels_in_corner)
+{
+ category->extra_depth = 0;
+
+ if (pivot_category_is_group (category))
+ {
+ size_t depth = 0;
+ for (size_t i = 0; i < category->n_subs; i++)
+ {
+ pivot_category_assign_label_depth (category->subs[i], false);
+ depth = MAX (depth, category->subs[i]->label_depth);
+ }
+
+ for (size_t i = 0; i < category->n_subs; i++)
+ {
+ struct pivot_category *sub = category->subs[i];
+
+ size_t extra_depth = depth - sub->label_depth;
+ if (extra_depth)
+ distribute_extra_depth (sub, extra_depth);
+
+ sub->label_depth = depth;
+ }
+
+ category->show_label_in_corner = (category->show_label
+ && dimension_labels_in_corner);
+ category->label_depth
+ = (category->show_label && !category->show_label_in_corner
+ ? depth + 1 : depth);
+ }
+ else
+ category->label_depth = 1;
+}
+
+static bool
+pivot_axis_assign_label_depth (struct pivot_table *table,
+ enum pivot_axis_type axis_type,
+ bool dimension_labels_in_corner)
+{
+ struct pivot_axis *axis = &table->axes[axis_type];
+ bool any_label_shown_in_corner = false;
+ axis->label_depth = 0;
+ axis->extent = 1;
+ for (size_t i = 0; i < axis->n_dimensions; i++)
+ {
+ struct pivot_dimension *d = axis->dimensions[i];
+ pivot_category_assign_label_depth (d->root, dimension_labels_in_corner);
+ d->label_depth = d->hide_all_labels ? 0 : d->root->label_depth;
+ axis->label_depth += d->label_depth;
+ axis->extent *= d->n_leaves;
+
+ if (d->root->show_label_in_corner)
+ any_label_shown_in_corner = true;
+ }
+ return any_label_shown_in_corner;
+}
+
+void
+pivot_table_assign_label_depth (struct pivot_table *table)
+{
+ pivot_axis_assign_label_depth (table, PIVOT_AXIS_COLUMN, false);
+ if (pivot_axis_assign_label_depth (
+ table, PIVOT_AXIS_ROW, (table->row_labels_in_corner
+ && !table->corner_text))
+ && table->axes[PIVOT_AXIS_COLUMN].label_depth == 0)
+ table->axes[PIVOT_AXIS_COLUMN].label_depth = 1;
+ pivot_axis_assign_label_depth (table, PIVOT_AXIS_LAYER, false);
+}
+\f
+/* Footnotes. */
+
+\f
+\f
+static void
+indent (int indentation)
+{
+ for (int i = 0; i < indentation * 2; i++)
+ putchar (' ');
+}
+
+static void
+pivot_value_dump (const struct pivot_value *value)
+{
+ char *s = pivot_value_to_string (value, SETTINGS_VALUE_SHOW_DEFAULT,
+ SETTINGS_VALUE_SHOW_DEFAULT);
+ fputs (s, stdout);
+ free (s);
+}
+
+static void
+pivot_table_dump_value (const struct pivot_value *value, const char *name,
+ int indentation)
+{
+ if (value)
+ {
+ indent (indentation);
+ printf ("%s: ", name);
+ pivot_value_dump (value);
+ putchar ('\n');
+ }
+}
+
+static void
+pivot_table_dump_string (const char *string, const char *name, int indentation)
+{
+ if (string)
+ {
+ indent (indentation);
+ printf ("%s: %s\n", name, string);
+ }
+}
+
+static void
+pivot_category_dump (const struct pivot_category *c, int indentation)
+{
+ indent (indentation);
+ printf ("%s \"", pivot_category_is_leaf (c) ? "leaf" : "group");
+ pivot_value_dump (c->name);
+ printf ("\" ");
+
+ if (pivot_category_is_leaf (c))
+ printf ("data_index=%zu\n", c->data_index);
+ else
+ {
+ printf (" (label %s)", c->show_label ? "shown" : "hidden");
+ printf ("\n");
+
+ for (size_t i = 0; i < c->n_subs; i++)
+ pivot_category_dump (c->subs[i], indentation + 1);
+ }
+}
+
+void
+pivot_dimension_dump (const struct pivot_dimension *d, int indentation)
+{
+ indent (indentation);
+ printf ("%s dimension %zu (where 0=innermost), label_depth=%zu:\n",
+ pivot_axis_type_to_string (d->axis_type), d->level, d->label_depth);
+
+ pivot_category_dump (d->root, indentation + 1);
+}
+
+static void
+area_style_dump (enum pivot_area area, const struct area_style *a,
+ int indentation)
+{
+ indent (indentation);
+ printf ("%s: ", pivot_area_to_string (area));
+ font_style_dump (&a->font_style);
+ putchar (' ');
+ cell_style_dump (&a->cell_style);
+ putchar ('\n');
+}
+
+static void
+table_border_style_dump (enum pivot_border border,
+ const struct table_border_style *b, int indentation)
+{
+ indent (indentation);
+ printf ("%s: %s ", pivot_border_to_string (border),
+ table_stroke_to_string (b->stroke));
+ cell_color_dump (&b->color);
+ putchar ('\n');
+}
+
+static char ***
+compose_headings (const struct pivot_axis *axis,
+ const size_t *column_enumeration,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables)
+{
+ if (!axis->n_dimensions || !axis->extent || !axis->label_depth)
+ return NULL;
+
+ char ***headings = xnmalloc (axis->label_depth, sizeof *headings);
+ for (size_t i = 0; i < axis->label_depth; i++)
+ headings[i] = xcalloc (axis->extent, sizeof **headings);
+
+ const size_t *indexes;
+ size_t column = 0;
+ PIVOT_ENUMERATION_FOR_EACH (indexes, column_enumeration, axis)
+ {
+ int row = axis->label_depth - 1;
+ for (int dim_index = 0; dim_index < axis->n_dimensions; dim_index++)
+ {
+ const struct pivot_dimension *d = axis->dimensions[dim_index];
+ if (d->hide_all_labels)
+ continue;
+ for (const struct pivot_category *c
+ = d->presentation_leaves[indexes[dim_index]];
+ c;
+ c = c->parent)
+ {
+ if (pivot_category_is_leaf (c) || (c->show_label
+ && !c->show_label_in_corner))
+ {
+ headings[row][column] = pivot_value_to_string (
+ c->name, show_values, show_variables);
+ if (!*headings[row][column])
+ headings[row][column] = xstrdup ("<blank>");
+ row--;
+ }
+ }
+ }
+ column++;
+ }
+
+ return headings;
+}
+
+void
+pivot_table_dump (const struct pivot_table *table, int indentation)
+{
+ if (!table)
+ return;
+
+ int old_decimal = settings_get_decimal_char (FMT_COMMA);
+ if (table->decimal == '.' || table->decimal == ',')
+ settings_set_decimal_char (table->decimal);
+
+ pivot_table_dump_value (table->title, "title", indentation);
+ pivot_table_dump_string (table->command_c, "command", indentation);
+ pivot_table_dump_string (table->dataset, "dataset", indentation);
+ pivot_table_dump_string (table->datafile, "datafile", indentation);
+ pivot_table_dump_string (table->notes, "notes", indentation);
+ pivot_table_dump_string (table->table_look, "table-look", indentation);
+ if (table->date)
+ {
+ indent (indentation);
+ printf ("date: %s", ctime (&table->date)); /* XXX thread unsafe */
+ }
+
+ indent (indentation);
+ printf ("areas:\n");
+ for (enum pivot_area area = 0; area < PIVOT_N_AREAS; area++)
+ area_style_dump (area, &table->areas[area], indentation + 1);
+
+ indent (indentation);
+ printf ("borders:\n");
+ for (enum pivot_border border = 0; border < PIVOT_N_BORDERS; border++)
+ table_border_style_dump (border, &table->borders[border], indentation + 1);
+
+ for (size_t i = 0; i < table->n_dimensions; i++)
+ pivot_dimension_dump (table->dimensions[i], indentation);
+
+ /* Presentation and data indexes. */
+ size_t *dindexes = xcalloc (table->n_dimensions, sizeof *dindexes);
+
+ const struct pivot_axis *layer_axis = &table->axes[PIVOT_AXIS_LAYER];
+ if (layer_axis->n_dimensions)
+ {
+ indent (indentation);
+ printf ("current layer:");
+
+ for (size_t i = 0; i < layer_axis->n_dimensions; i++)
+ {
+ const struct pivot_dimension *d = layer_axis->dimensions[i];
+ char *name = pivot_value_to_string (d->root->name,
+ table->show_values,
+ table->show_variables);
+ char *value = pivot_value_to_string (
+ d->data_leaves[table->current_layer[i]]->name,
+ table->show_values, table->show_variables);
+ printf (" %s=%s", name, value);
+ free (value);
+ free (name);
+ }
+
+ putchar ('\n');
+ }
+
+ size_t *layer_indexes;
+ size_t layer_iteration = 0;
+ PIVOT_AXIS_FOR_EACH (layer_indexes, &table->axes[PIVOT_AXIS_LAYER])
+ {
+ indent (indentation);
+ printf ("layer %zu:", layer_iteration++);
+
+ const struct pivot_axis *layer_axis = &table->axes[PIVOT_AXIS_LAYER];
+ for (size_t i = 0; i < layer_axis->n_dimensions; i++)
+ {
+ const struct pivot_dimension *d = layer_axis->dimensions[i];
+
+ fputs (i == 0 ? " " : ", ", stdout);
+ pivot_value_dump (d->root->name);
+ fputs (" =", stdout);
+
+ struct pivot_value **names = xnmalloc (layer_axis->label_depth,
+ sizeof *names);
+ size_t n_names = 0;
+ for (const struct pivot_category *c
+ = d->presentation_leaves[layer_indexes[i]];
+ c;
+ c = c->parent)
+ {
+ if (pivot_category_is_leaf (c) || c->show_label)
+ names[n_names++] = c->name;
+ }
+
+ for (size_t i = n_names; i-- > 0; )
+ {
+ putchar (' ');
+ pivot_value_dump (names[i]);
+ }
+ free (names);
+ }
+ putchar ('\n');
+
+ size_t *column_enumeration = pivot_table_enumerate_axis (
+ table, PIVOT_AXIS_COLUMN, layer_indexes, table->omit_empty, NULL);
+ size_t *row_enumeration = pivot_table_enumerate_axis (
+ table, PIVOT_AXIS_ROW, layer_indexes, table->omit_empty, NULL);
+
+ char ***column_headings = compose_headings (
+ &table->axes[PIVOT_AXIS_COLUMN], column_enumeration,
+ table->show_values, table->show_variables);
+ for (size_t y = 0; y < table->axes[PIVOT_AXIS_COLUMN].label_depth; y++)
+ {
+ indent (indentation + 1);
+ for (size_t x = 0; x < table->axes[PIVOT_AXIS_COLUMN].extent; x++)
+ {
+ if (x)
+ fputs ("; ", stdout);
+ if (column_headings[y][x])
+ fputs (column_headings[y][x], stdout);
+ }
+ putchar ('\n');
+ }
+
+ indent (indentation + 1);
+ printf ("-----------------------------------------------\n");
+
+ char ***row_headings = compose_headings (
+ &table->axes[PIVOT_AXIS_ROW], row_enumeration,
+ table->show_values, table->show_variables);
+
+ size_t x = 0;
+ const size_t *pindexes[PIVOT_N_AXES]
+ = { [PIVOT_AXIS_LAYER] = layer_indexes };
+ PIVOT_ENUMERATION_FOR_EACH (pindexes[PIVOT_AXIS_ROW], row_enumeration,
+ &table->axes[PIVOT_AXIS_ROW])
+ {
+ indent (indentation + 1);
+
+ size_t i = 0;
+ for (size_t y = 0; y < table->axes[PIVOT_AXIS_ROW].label_depth; y++)
+ {
+ if (i++)
+ fputs ("; ", stdout);
+ if (row_headings[y][x])
+ fputs (row_headings[y][x], stdout);
+ }
+
+ printf (" | ");
+
+ i = 0;
+ PIVOT_ENUMERATION_FOR_EACH (pindexes[PIVOT_AXIS_COLUMN],
+ column_enumeration,
+ &table->axes[PIVOT_AXIS_COLUMN])
+ {
+ if (i++)
+ printf ("; ");
+
+ pivot_table_convert_indexes_ptod (table, pindexes, dindexes);
+ const struct pivot_value *value = pivot_table_get (
+ table, dindexes);
+ if (value)
+ pivot_value_dump (value);
+ }
+ printf ("\n");
+
+ x++;
+ }
+
+ free (column_enumeration);
+ free (row_enumeration);
+ }
+
+ pivot_table_dump_value (table->caption, "caption", indentation);
+
+ for (size_t i = 0; i < table->n_footnotes; i++)
+ {
+ const struct pivot_footnote *f = table->footnotes[i];
+ indent (indentation);
+ putchar ('[');
+ if (f->marker)
+ pivot_value_dump (f->marker);
+ else
+ printf ("%d", f->idx);
+ putchar (']');
+ pivot_value_dump (f->content);
+ putchar ('\n');
+ }
+
+ settings_set_decimal_char (old_decimal);
+}
+\f
+static const char *
+consume_int (const char *p, size_t *n)
+{
+ *n = 0;
+ while (c_isdigit (*p))
+ *n = *n * 10 + (*p++ - '0');
+ return p;
+}
+
+static size_t
+pivot_format_inner_template (struct string *out, const char *template,
+ char escape,
+ struct pivot_value **values, size_t n_values,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables)
+{
+ size_t args_consumed = 0;
+ while (*template && *template != ':')
+ {
+ if (*template == '\\' && template[1])
+ {
+ ds_put_byte (out, template[1] == 'n' ? '\n' : template[1]);
+ template += 2;
+ }
+ else if (*template == escape)
+ {
+ size_t index;
+ template = consume_int (template + 1, &index);
+ if (index >= 1 && index <= n_values)
+ {
+ pivot_value_format (values[index - 1], show_values,
+ show_variables, out);
+ args_consumed = MAX (args_consumed, index);
+ }
+ }
+ else
+ ds_put_byte (out, *template++);
+ }
+ return args_consumed;
+}
+
+static const char *
+pivot_extract_inner_template (const char *template, const char **p)
+{
+ *p = template;
+
+ for (;;)
+ {
+ if (*template == '\\' && template[1] != '\0')
+ template += 2;
+ else if (*template == ':')
+ return template + 1;
+ else if (*template == '\0')
+ return template;
+ else
+ template++;
+ }
+}
+
+static void
+pivot_format_template (struct string *out, const char *template,
+ const struct pivot_argument *args, size_t n_args,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables)
+{
+ while (*template)
+ {
+ if (*template == '\\' && template[1] != '\0')
+ {
+ ds_put_byte (out, template[1] == 'n' ? '\n' : template[1]);
+ template += 2;
+ }
+ else if (*template == '^')
+ {
+ size_t index;
+ template = consume_int (template + 1, &index);
+ if (index >= 1 && index <= n_args && args[index - 1].n > 0)
+ pivot_value_format (args[index - 1].values[0],
+ show_values, show_variables, out);
+ }
+ else if (*template == '[')
+ {
+ const char *tmpl[2];
+ template = pivot_extract_inner_template (template + 1, &tmpl[0]);
+ template = pivot_extract_inner_template (template, &tmpl[1]);
+ template += *template == ']';
+
+ size_t index;
+ template = consume_int (template, &index);
+ if (index < 1 || index > n_args)
+ continue;
+
+ const struct pivot_argument *arg = &args[index - 1];
+ size_t left = arg->n;
+ while (left)
+ {
+ struct pivot_value **values = arg->values + (arg->n - left);
+ int tmpl_idx = left == arg->n && *tmpl[0] != ':' ? 0 : 1;
+ char escape = "%^"[tmpl_idx];
+ size_t used = pivot_format_inner_template (
+ out, tmpl[tmpl_idx], escape, values, left,
+ show_values, show_variables);
+ if (!used || used > left)
+ break;
+ left -= used;
+ }
+ }
+ else
+ ds_put_byte (out, *template++);
+ }
+}
+
+static enum settings_value_show
+interpret_show (enum settings_value_show global_show,
+ enum settings_value_show table_show,
+ enum settings_value_show value_show,
+ bool has_label)
+{
+ return (!has_label ? SETTINGS_VALUE_SHOW_VALUE
+ : value_show != SETTINGS_VALUE_SHOW_DEFAULT ? value_show
+ : table_show != SETTINGS_VALUE_SHOW_DEFAULT ? table_show
+ : global_show);
+}
+
+/* Appends a text representation of the body of VALUE to OUT. SHOW_VALUES and
+ SHOW_VARIABLES control whether variable and value labels are included.
+
+ The "body" omits subscripts and superscripts and footnotes. */
+bool
+pivot_value_format_body (const struct pivot_value *value,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ struct string *out)
+{
+ enum settings_value_show show;
+ bool numeric = false;
+
+ switch (value->type)
+ {
+ case PIVOT_VALUE_NUMERIC:
+ show = interpret_show (settings_get_show_values (),
+ show_values,
+ value->numeric.show,
+ value->numeric.value_label != NULL);
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ {
+ char *s = data_out (&(union value) { .f = value->numeric.x },
+ "UTF-8", &value->numeric.format);
+ ds_put_cstr (out, s + strspn (s, " "));
+ free (s);
+ }
+ if (show & SETTINGS_VALUE_SHOW_LABEL)
+ {
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ ds_put_byte (out, ' ');
+ ds_put_cstr (out, value->numeric.value_label);
+ }
+ numeric = !(show & SETTINGS_VALUE_SHOW_LABEL);
+ break;
+
+ case PIVOT_VALUE_STRING:
+ show = interpret_show (settings_get_show_values (),
+ show_values,
+ value->string.show,
+ value->string.value_label != NULL);
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ {
+ if (value->string.hex)
+ {
+ for (const uint8_t *p = CHAR_CAST (uint8_t *, value->string.s);
+ *p; p++)
+ ds_put_format (out, "%02X", *p);
+ }
+ else
+ ds_put_cstr (out, value->string.s);
+ }
+ if (show & SETTINGS_VALUE_SHOW_LABEL)
+ {
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ ds_put_byte (out, ' ');
+ ds_put_cstr (out, value->string.value_label);
+ }
+ break;
+
+ case PIVOT_VALUE_VARIABLE:
+ show = interpret_show (settings_get_show_variables (),
+ show_variables,
+ value->variable.show,
+ value->variable.var_label != NULL);
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ ds_put_cstr (out, value->variable.var_name);
+ if (show & SETTINGS_VALUE_SHOW_LABEL)
+ {
+ if (show & SETTINGS_VALUE_SHOW_VALUE)
+ ds_put_byte (out, ' ');
+ ds_put_cstr (out, value->variable.var_label);
+ }
+ break;
+
+ case PIVOT_VALUE_TEXT:
+ ds_put_cstr (out, value->text.local);
+ break;
+
+ case PIVOT_VALUE_TEMPLATE:
+ pivot_format_template (out, value->template.s, value->template.args,
+ value->template.n_args, show_values,
+ show_variables);
+ break;
+ }
+
+ return numeric;
+}
+
+/* Appends a text representation of VALUE to OUT. SHOW_VALUES and
+ SHOW_VARIABLES control whether variable and value labels are included.
+
+ Subscripts and superscripts and footnotes are included. */
+void
+pivot_value_format (const struct pivot_value *value,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ struct string *out)
+{
+ pivot_value_format_body ( value, show_values, show_variables, out);
+
+ if (value->subscript)
+ ds_put_format (out, "_%s", value->subscript);
+
+ if (value->superscript)
+ ds_put_format (out, "^%s", value->superscript);
+
+ for (size_t i = 0; i < value->n_footnotes; i++)
+ {
+ ds_put_byte (out, '^');
+ pivot_value_format (value->footnotes[i]->marker,
+ show_values, show_variables, out);
+ }
+}
+
+/* Returns a text representation of VALUE. The caller must free the string,
+ with free(). */
+char *
+pivot_value_to_string (const struct pivot_value *value,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables)
+{
+ struct string s = DS_EMPTY_INITIALIZER;
+ pivot_value_format (value, show_values, show_variables, &s);
+ return ds_steal_cstr (&s);
+}
+
+/* Frees the data owned by V. */
+void
+pivot_value_destroy (struct pivot_value *value)
+{
+ if (value)
+ {
+ font_style_uninit (value->font_style);
+ free (value->font_style);
+ free (value->cell_style);
+ for (size_t i = 0; i < value->n_footnotes; i++)
+ pivot_footnote_destroy (value->footnotes[i]);
+ free (value->footnotes);
+
+ switch (value->type)
+ {
+ case PIVOT_VALUE_NUMERIC:
+ free (value->numeric.var_name);
+ free (value->numeric.value_label);
+ break;
+
+ case SETTINGS_VALUE_SHOW_VALUE:
+ free (value->string.var_name);
+ free (value->string.value_label);
+ break;
+
+ case PIVOT_VALUE_VARIABLE:
+ free (value->variable.var_name);
+ free (value->variable.var_label);
+ break;
+
+ case PIVOT_VALUE_TEXT:
+ free (value->text.local);
+ if (value->text.c != value->text.local)
+ free (value->text.c);
+ if (value->text.id != value->text.local
+ && value->text.id != value->text.c)
+ free (value->text.id);
+ break;
+
+ case PIVOT_VALUE_TEMPLATE:
+ free (value->template.s);
+ for (size_t i = 0; i < value->template.n_args; i++)
+ pivot_argument_uninit (&value->template.args[i]);
+ free (value->template.args);
+ break;
+ }
+ free (value);
+ }
+}
+
+/* Sets AREA to the style to use for VALUE, with defaults coming from
+ DEFAULT_STYLE for the parts of the style that VALUE doesn't override. */
+void
+pivot_value_get_style (struct pivot_value *value,
+ const struct area_style *default_style,
+ struct area_style *area)
+{
+ font_style_copy (&area->font_style, (value->font_style
+ ? value->font_style
+ : &default_style->font_style));
+ area->cell_style = (value->cell_style
+ ? *value->cell_style
+ : default_style->cell_style);
+}
+
+/* Copies AREA into VALUE's style. */
+void
+pivot_value_set_style (struct pivot_value *value,
+ const struct area_style *area)
+{
+ if (value->font_style)
+ font_style_uninit (value->font_style);
+ else
+ value->font_style = xmalloc (sizeof *value->font_style);
+ font_style_copy (value->font_style, &area->font_style);
+
+ if (!value->cell_style)
+ value->cell_style = xmalloc (sizeof *value->cell_style);
+ *value->cell_style = area->cell_style;
+}
+
+/* Frees the data owned by ARG (but not ARG itself). */
+void
+pivot_argument_uninit (struct pivot_argument *arg)
+{
+ if (arg)
+ {
+ for (size_t i = 0; i < arg->n; i++)
+ pivot_value_destroy (arg->values[i]);
+ free (arg->values);
+ }
+}
+
+struct pivot_value *
+pivot_value_new_user_text_nocopy (char *text)
+{
+ struct pivot_value *value = xmalloc (sizeof *value);
+ *value = (struct pivot_value) {
+ .type = PIVOT_VALUE_TEXT,
+ .text = {
+ .local = text,
+ .c = text,
+ .id = text,
+ .user_provided = true,
+ }
+ };
+ return value;
+}
+
+struct pivot_value *
+pivot_value_new_user_text (const char *text, size_t length)
+{
+ return pivot_value_new_user_text_nocopy (
+ xmemdup0 (text, length != SIZE_MAX ? length : strlen (text)));
+}
+
+/* TEXT should be a translatable string, but not actually translated yet,
+ e.g. enclosed in N_(). */
+struct pivot_value *
+pivot_value_new_text (const char *text)
+{
+ char *c = xstrdup (text);
+ char *local = xstrdup (gettext (c));
+
+ struct pivot_value *value = xmalloc (sizeof *value);
+ *value = (struct pivot_value) {
+ .type = PIVOT_VALUE_TEXT,
+ .text = {
+ .local = local,
+ .c = c,
+ .id = c,
+ .user_provided = false,
+ }
+ };
+ return value;
+}
+
+/* FORMAT should be a translatable string, but not actually translated yet,
+ e.g. enclosed in N_(). */
+struct pivot_value * PRINTF_FORMAT (1, 2)
+pivot_value_new_text_format (const char *format, ...)
+{
+ va_list args;
+ va_start (args, format);
+ char *c = xvasprintf (format, args);
+ va_end (args);
+
+ va_start (args, format);
+ char *local = xvasprintf (gettext (format), args);
+ va_end (args);
+
+ struct pivot_value *value = xmalloc (sizeof *value);
+ *value = (struct pivot_value) {
+ .type = PIVOT_VALUE_TEXT,
+ .text = {
+ .local = local,
+ .c = c,
+ .id = xstrdup (c),
+ .user_provided = false,
+ }
+ };
+ return value;
+}
+
+static char *
+xstrdup_if_nonempty (const char *s)
+{
+ return s && s[0] ? xstrdup (s) : NULL;
+}
+
+/* Returns a new pivot_value that represents X.
+
+ The format to use for X is unspecified. Usually the easiest way to specify
+ a format is through assigning a result class to one of the categories that
+ the pivot_value will end up in. If that is not suitable, then the caller
+ can use pivot_value_set_rc() or assign directly to value->numeric.format. */
+struct pivot_value *
+pivot_value_new_number (double x)
+{
+ struct pivot_value *value = xmalloc (sizeof *value);
+ *value = (struct pivot_value) {
+ .type = PIVOT_VALUE_NUMERIC,
+ .numeric = { .x = x, },
+ };
+ return value;
+}
+
+/* Returns a new pivot_value that represents X, formatted as an integer. */
+struct pivot_value *
+pivot_value_new_integer (double x)
+{
+ struct pivot_value *value = pivot_value_new_number (x);
+ value->numeric.format = (struct fmt_spec) { FMT_F, 40, 0 };
+ return value;
+}
+
+/* Returns a new pivot_value that represents VALUE, formatted as for
+ VARIABLE. */
+struct pivot_value *
+pivot_value_new_var_value (const struct variable *variable,
+ const union value *value)
+{
+ struct pivot_value *pv = pivot_value_new_value (
+ value, var_get_width (variable), var_get_print_format (variable),
+ var_get_encoding (variable));
+
+ char *var_name = xstrdup (var_get_name (variable));
+ if (var_is_alpha (variable))
+ pv->string.var_name = var_name;
+ else
+ pv->numeric.var_name = var_name;
+
+ const char *label = var_lookup_value_label (variable, value);
+ if (label)
+ {
+ if (var_is_alpha (variable))
+ pv->string.value_label = xstrdup (label);
+ else
+ pv->numeric.value_label = xstrdup (label);
+ }
+
+ return pv;
+}
+
+/* Returns a new pivot_value that represents VALUE, with the given WIDTH,
+ formatted with FORMAT. For a string value, ENCODING must be its character
+ encoding. */
+struct pivot_value *
+pivot_value_new_value (const union value *value, int width,
+ const struct fmt_spec *format, const char *encoding)
+{
+ struct pivot_value *pv = xzalloc (sizeof *pv);
+ if (width > 0)
+ {
+ char *s = recode_string (UTF8, encoding,
+ CHAR_CAST (char *, value_str (value, width)),
+ width);
+ size_t n = strlen (s);
+ while (n > 0 && s[n - 1] == ' ')
+ s[--n] = '\0';
+
+ pv->type = PIVOT_VALUE_STRING;
+ pv->string.s = s;
+ pv->string.hex = format->type == FMT_AHEX;
+ }
+ else
+ {
+ pv->type = PIVOT_VALUE_NUMERIC;
+ pv->numeric.x = value->f;
+ pv->numeric.format = *format;
+ }
+
+ return pv;
+}
+
+/* Returns a new pivot_value for VARIABLE. */
+struct pivot_value *
+pivot_value_new_variable (const struct variable *variable)
+{
+ struct pivot_value *value = xmalloc (sizeof *value);
+ *value = (struct pivot_value) {
+ .type = PIVOT_VALUE_VARIABLE,
+ .variable = {
+ .var_name = xstrdup (var_get_name (variable)),
+ .var_label = xstrdup_if_nonempty (var_get_label (variable)),
+ },
+ };
+ return value;
+}
+
+/* Attaches a reference to FOOTNOTE to V. */
+void
+pivot_value_add_footnote (struct pivot_value *v,
+ struct pivot_footnote *footnote)
+{
+ v->footnotes = xrealloc (v->footnotes,
+ (v->n_footnotes + 1) * sizeof *v->footnotes);
+ v->footnotes[v->n_footnotes++] = footnote;
+}
+
+/* If VALUE is a numeric value, and RC is a result class such as
+ PIVOT_RC_COUNT, changes VALUE's format to the result class's. */
+void
+pivot_value_set_rc (struct pivot_table *table, struct pivot_value *value,
+ const char *rc)
+{
+ if (value->type == PIVOT_VALUE_NUMERIC)
+ {
+ const struct fmt_spec *f = pivot_table_get_format (table, rc);
+ if (f)
+ value->numeric.format = *f;
+ }
+}
+
--- /dev/null
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2017-2018 Free Software Foundation, Inc.
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see <http://www.gnu.org/licenses/>. */
+
+#ifndef OUTPUT_PIVOT_TABLE_H
+#define OUTPUT_PIVOT_TABLE_H 1
+
+#include <stdint.h>
+#include <time.h>
+#include "data/format.h"
+#include "data/settings.h"
+#include "libpspp/compiler.h"
+#include "libpspp/hmap.h"
+#include "output/table.h"
+
+struct pivot_value;
+struct variable;
+union value;
+
+/* Pivot tables.
+
+ Pivot tables are PSPP's primary form of output. They are analogous to the
+ pivot tables you might be familiar with from spreadsheets and databases.
+ See https://en.wikipedia.org/wiki/Pivot_table for a brief introduction to
+ the overall concept of a pivot table.
+
+ In PSPP, the most important internal pieces of a pivot table are:
+
+ - Title. Every pivot table has a title that is displayed above it. It also
+ has an optional caption (displayed below it) and corner text (displayed in
+ the upper left corner).
+
+ - Dimensions. A dimension consists of zero or more categories. A category
+ has a label, such as "df" or "Asymp. Sig." or 123 or a variable name. The
+ categories are the leaves of a tree whose non-leaf nodes form groups of
+ categories. The tree always has a root group whose label is the name of
+ the dimension.
+
+ - Axes. A table has three axes: column, row, and layer. Each dimension is
+ assigned to an axis, and each axis has zero or more dimensions. When an
+ axis has more than one dimension, they are ordered from innermost to
+ outermost.
+
+ - Data. A table's data consists of zero or more cells. Each cell maps from
+ a category for each dimension to a value, which is commonly a number but
+ could also be a variable name or an arbitrary text string.
+
+ Creating a pivot table usually consists of the following steps:
+
+ 1. Create the table with pivot_table_create(), passing in the title.
+
+ 2. Create each dimension with pivot_dimension_create() and populate it with
+ categories and, possibly, with groups that contain the categories. This
+ call also assigns the dimension to an axis.
+
+ In simple cases, only a call to pivot_dimension_create() is needed.
+ Other functions such as pivot__create_group() can be used for
+ hierarchies of categories.
+
+ Sometimes it's easier to create categories in tandem with inserting data,
+ for example by adding a category for a variable just before inserting the
+ first cell for that variable. In that case, creating categories and
+ inserting data can be interleaved.
+
+ 3. Insert data. For each cell, supply the category indexes, which are
+ assigned starting from 0 in the order in which the categories were
+ created in step 2, and the value to go in the cell. If the table has a
+ small, fixed number of dimensions, functions like, e.g.
+ pivot_table_put3() for 3 dimensions, can be used. The general function
+ pivot_table_put() works for other cases.
+
+ 4. Output the table for user consumption. Use pivot_table_submit(). */
+\f
+/* Pivot table display styling. */
+
+/* Areas of a pivot table for styling purposes. */
+enum pivot_area
+ {
+ PIVOT_AREA_TITLE,
+ PIVOT_AREA_CAPTION,
+ PIVOT_AREA_FOOTER, /* Footnotes. */
+ PIVOT_AREA_CORNER, /* Top-left corner. */
+ PIVOT_AREA_COLUMN_LABELS,
+ PIVOT_AREA_ROW_LABELS,
+ PIVOT_AREA_DATA,
+ PIVOT_AREA_LAYERS, /* Layer indication. */
+ PIVOT_N_AREAS
+ };
+
+const char *pivot_area_to_string (enum pivot_area);
+
+/* Table borders for styling purposes. */
+enum pivot_border
+ {
+ PIVOT_BORDER_TITLE,
+
+ /* Outer frame. */
+ PIVOT_BORDER_OUTER_LEFT,
+ PIVOT_BORDER_OUTER_TOP,
+ PIVOT_BORDER_OUTER_RIGHT,
+ PIVOT_BORDER_OUTER_BOTTOM,
+
+ /* Inner frame. */
+ PIVOT_BORDER_INNER_LEFT,
+ PIVOT_BORDER_INNER_TOP,
+ PIVOT_BORDER_INNER_RIGHT,
+ PIVOT_BORDER_INNER_BOTTOM,
+
+ /* Data area. */
+ PIVOT_BORDER_DATA_LEFT,
+ PIVOT_BORDER_DATA_TOP,
+
+ /* Dimensions. */
+ PIVOT_BORDER_DIM_ROW_HORZ,
+ PIVOT_BORDER_DIM_ROW_VERT,
+ PIVOT_BORDER_DIM_COL_HORZ,
+ PIVOT_BORDER_DIM_COL_VERT,
+
+ /* Categories. */
+ PIVOT_BORDER_CAT_ROW_HORZ,
+ PIVOT_BORDER_CAT_ROW_VERT,
+ PIVOT_BORDER_CAT_COL_HORZ,
+ PIVOT_BORDER_CAT_COL_VERT,
+
+ PIVOT_N_BORDERS
+ };
+
+const char *pivot_border_to_string (enum pivot_border);
+
+/* Sizing for rows or columns of a rendered table. The comments below talk
+ about columns and their widths but they apply equally to rows and their
+ heights. */
+struct pivot_table_sizing
+ {
+ /* Minimum and maximum column width, in 1/96" units. */
+ int range[2];
+
+ /* Specific column widths, in 1/96" units. */
+ int *widths;
+ size_t n_widths;
+
+ /* Specific page breaks: 0-based columns after which a page break must
+ occur, e.g. a value of 1 requests a break after the second column. */
+ size_t *breaks;
+ size_t n_breaks;
+
+ /* Keeps: columns to keep together on a page if possible. */
+ struct pivot_keep *keeps;
+ size_t n_keeps;
+ };
+
+void pivot_table_sizing_uninit (struct pivot_table_sizing *);
+
+/* A set of columns to keep together on a page if possible, e.g. ofs=1, n=10
+ requests keeping together the 2nd through 11th columns. */
+struct pivot_keep
+ {
+ size_t ofs; /* 0-based first column. */
+ size_t n; /* Number of columns. */
+ };
+\f
+/* Axes. */
+
+enum pivot_axis_type
+ {
+ PIVOT_AXIS_LAYER,
+ PIVOT_AXIS_ROW,
+ PIVOT_AXIS_COLUMN,
+
+ PIVOT_N_AXES
+ };
+
+const char *pivot_axis_type_to_string (enum pivot_axis_type);
+
+/* An axis within a pivot table. */
+struct pivot_axis
+ {
+ /* dimensions[0] is the innermost dimension,
+ dimensions[1] is the next outer dimension,
+ ...
+ dimensions[n_dimensions - 1] is the outermost dimension. */
+ struct pivot_dimension **dimensions;
+ size_t n_dimensions;
+
+ /* The number of rows or columns along the axis,
+ that is, the product of dimension[*]->n_leaves.
+ It is 0 if any dimension has 0 leaves. */
+ size_t extent;
+
+ /* Sum of dimensions[*]->label_depth. */
+ size_t label_depth;
+ };
+
+/* Successively assigns to INDEXES (which should be a "size_t *") each of the
+ combinations of the categories in AXIS's dimensions, in lexicographic order
+ with the innermost dimension iterating most quickly.
+
+ The value assigned to INDEXES is dynamically allocated. If the client
+ breaks out of the loop prematurely, it needs to free it with free(). */
+#define PIVOT_AXIS_FOR_EACH(INDEXES, AXIS) \
+ for ((INDEXES) = NULL; \
+ ((INDEXES) = pivot_axis_iterator_next (INDEXES, AXIS)) != NULL; )
+size_t *pivot_axis_iterator_next (size_t *indexes, const struct pivot_axis *);
+\f
+/* Dimensions.
+
+ A pivot_dimension identifies the categories associated with a single
+ dimension within a multidimensional pivot table.
+
+ A dimension contains a collection of categories, which are the leaves in a
+ tree of groups.
+
+ (A dimension or a group can contain zero categories, but this is unusual.
+ If a dimension contains no categories, then its table cannot contain any
+ data.)
+*/
+struct pivot_dimension
+ {
+ /* table->axes[axis_type]->dimensions[level] == dimension. */
+ struct pivot_table *table;
+ enum pivot_axis_type axis_type;
+ size_t level; /* 0 for innermost dimension within axis. */
+
+ /* table->dimensions[top_index] == dimension. */
+ size_t top_index;
+
+ /* Hierarchy of categories within the dimension. The groups and categories
+ are sorted in the order that should be used for display. This might be
+ different from the original order produced for output if the user
+ adjusted it.
+
+ The root must always be a group, although it is allowed to have no
+ subcategories. */
+ struct pivot_category *root;
+
+ /* All of the leaves reachable via the root.
+
+ The indexing for presentation_leaves is presentation order, thus
+ presentation_leaves[i]->presentation_index == i. This order is the same
+ as would be produced by an in-order traversal of the groups. It is the
+ order into which the user reordered or sorted the categories.
+
+ The indexing for data_leaves is that used for idx[] in struct
+ pivot_cell, thus data_leaves[i]->data_index == i. This might differ
+ from what an in-order traversal of 'root' would yield, if the user
+ reordered categories. */
+ struct pivot_category **data_leaves;
+ struct pivot_category **presentation_leaves;
+ size_t n_leaves, allocated_leaves;
+
+ /* Display. */
+ bool hide_all_labels;
+
+ /* Number of rows or columns needed to express the labels. */
+ int label_depth;
+ };
+
+struct pivot_dimension *pivot_dimension_create (
+ struct pivot_table *, enum pivot_axis_type, const char *name, ...)
+ SENTINEL (0);
+#define pivot_dimension_create(...) \
+ pivot_dimension_create(__VA_ARGS__, NULL_SENTINEL)
+struct pivot_dimension *pivot_dimension_create__ (struct pivot_table *,
+ enum pivot_axis_type,
+ struct pivot_value *name);
+
+void pivot_dimension_destroy (struct pivot_dimension *);
+
+void pivot_dimension_dump (const struct pivot_dimension *, int indentation);
+\f
+/* A pivot_category is a leaf (a category) or a group:
+
+ - For a leaf, neither index is SIZE_MAX.
+
+ - For a group, both indexes are SIZE_MAX.
+
+ Do not use 'subs' or 'n_subs' to determine whether a category is a group,
+ because a group may (pathologically) have no leaves. */
+struct pivot_category
+ {
+ struct pivot_value *name;
+ struct pivot_category *parent;
+ struct pivot_dimension *dimension;
+ size_t label_depth, extra_depth;
+
+ /* Groups only.
+
+ If show_label is true, then the group itself has a row (or a column)
+ giving the group's name. Otherwise, the group's own name is not
+ displayed. */
+ struct pivot_category **subs; /* Child categories or groups. */
+ size_t n_subs, allocated_subs;
+ bool show_label; /* Display a label for the group itself? */
+ bool show_label_in_corner;
+
+ /* Leaf only. */
+ struct fmt_spec format;
+ size_t group_index; /* In ->parent->subs[]. */
+ size_t data_index; /* In ->dimension->data_leaves[]. */
+ size_t presentation_index; /* In ->dimension->presentation_leaves[]. */
+ };
+
+static inline bool
+pivot_category_is_group (const struct pivot_category *category)
+{
+ return category->data_index == SIZE_MAX;
+}
+
+static inline bool
+pivot_category_is_leaf (const struct pivot_category *category)
+{
+ return !pivot_category_is_group (category);
+}
+
+/* Creating leaf categories. */
+int pivot_category_create_leaves (struct pivot_category *parent, ...)
+ SENTINEL (0);
+#define pivot_category_create_leaves(...) \
+ pivot_category_create_leaves(__VA_ARGS__, NULL_SENTINEL)
+
+int pivot_category_create_leaf (
+ struct pivot_category *parent, struct pivot_value *name);
+int pivot_category_create_leaf_rc (
+ struct pivot_category *parent, struct pivot_value *name, const char *rc);
+
+/* Creating category groups. */
+struct pivot_category *pivot_category_create_group (
+ struct pivot_category *parent, const char *name, ...) SENTINEL (0);
+#define pivot_category_create_group(...) \
+ pivot_category_create_group(__VA_ARGS__, NULL_SENTINEL)
+struct pivot_category *pivot_category_create_group__ (
+ struct pivot_category *parent, struct pivot_value *name);
+
+void pivot_category_destroy (struct pivot_category *);
+
+/* Pivot result classes.
+
+ These are used to mark leaf categories as having particular types of data,
+ to set their numeric formats. The formats that actually get used for these
+ classes are in the result_classes[] global array in pivot-table.c, except
+ that PIVOT_RC_OTHER comes from settings_get_format() and PIVOT_RC_COUNT
+ should come from the weight variable in the dataset's dictionary. */
+#define PIVOT_RC_OTHER ("RC_OTHER")
+#define PIVOT_RC_INTEGER ("RC_INTEGER")
+#define PIVOT_RC_CORRELATION ("RC_CORRELATIONS")
+#define PIVOT_RC_SIGNIFICANCE ("RC_SIGNIFICANCE")
+#define PIVOT_RC_PERCENT ("RC_PERCENT")
+#define PIVOT_RC_RESIDUAL ("RC_RESIDUAL")
+#define PIVOT_RC_COUNT ("RC_COUNT")
+
+bool pivot_result_class_change (const char *, const struct fmt_spec *);
+\f
+/* A pivot table. See the top of this file for more information. */
+struct pivot_table
+ {
+ /* Display settings. */
+ bool rotate_inner_column_labels;
+ bool rotate_outer_row_labels;
+ bool row_labels_in_corner;
+ bool show_grid_lines;
+ bool omit_empty;
+ size_t *current_layer; /* axis[PIVOT_AXIS_LAYER]->n_dimensions elements. */
+ char *table_look;
+ enum settings_value_show show_values;
+ enum settings_value_show show_variables;
+ struct fmt_spec weight_format;
+
+ /* Footnote display settings. */
+ bool show_numeric_markers;
+ bool footnote_marker_superscripts;
+
+ /* Column and row sizing and page breaks.
+ sizing[TABLE_HORZ] is for columns, sizing[TABLE_VERT] is for rows. */
+ struct pivot_table_sizing sizing[TABLE_N_AXES];
+
+ /* Print settings. */
+ bool print_all_layers;
+ bool paginate_layers;
+ bool shrink_to_fit[TABLE_N_AXES];
+ bool top_continuation, bottom_continuation;
+ char *continuation;
+ size_t n_orphan_lines;
+
+ /* Format settings. */
+ int epoch;
+ char decimal; /* Usually ',' or '.'. */
+ char grouping; /* Usually '.' or ','. */
+ char *ccs[5]; /* Custom currency. */
+ double small;
+
+ /* Command information. */
+ char *command_local; /* May be NULL. */
+ char *command_c; /* May be NULL. */
+ char *language; /* May be NULL. */
+ char *locale; /* May be NULL. */
+
+ /* Source information. */
+ char *dataset; /* May be NULL. */
+ char *datafile; /* May be NULL. */
+ time_t date; /* May be 0 if unknown. */
+
+ /* Footnotes. */
+ struct pivot_footnote **footnotes;
+ size_t n_footnotes, allocated_footnotes;
+
+ /* Titles. */
+ struct pivot_value *title;
+ struct pivot_value *subtype; /* Same as pivot_item's subtype. */
+ struct pivot_value *corner_text;
+ struct pivot_value *caption;
+ char *notes;
+
+ /* Styles. */
+ struct area_style areas[PIVOT_N_AREAS];
+ struct table_border_style borders[PIVOT_N_BORDERS];
+
+ /* Dimensions. */
+ struct pivot_dimension **dimensions;
+ size_t n_dimensions;
+
+ /* Allocation of dimensions to rows, columns, and layers. */
+ struct pivot_axis axes[PIVOT_N_AXES];
+
+ struct hmap cells; /* Contains "struct pivot_cell"s. */
+ };
+
+/* Creating and destroy pivot tables. */
+struct pivot_table *pivot_table_create (const char *title);
+struct pivot_table *pivot_table_create__ (struct pivot_value *title);
+struct pivot_table *pivot_table_create_for_text (struct pivot_value *title,
+ struct pivot_value *content);
+void pivot_table_destroy (struct pivot_table *);
+
+/* Format of PIVOT_RC_COUNT cells. */
+void pivot_table_set_weight_var (struct pivot_table *,
+ const struct variable *);
+void pivot_table_set_weight_format (struct pivot_table *,
+ const struct fmt_spec *);
+
+/* Query. */
+bool pivot_table_is_empty (const struct pivot_table *);
+
+/* Output. */
+void pivot_table_submit (const struct pivot_table *);
+
+/* Data cells. */
+void pivot_table_put (struct pivot_table *, const size_t *dindexes, size_t n,
+ struct pivot_value *);
+void pivot_table_put1 (struct pivot_table *, size_t idx1,
+ struct pivot_value *);
+void pivot_table_put2 (struct pivot_table *, size_t idx1, size_t idx2,
+ struct pivot_value *);
+void pivot_table_put3 (struct pivot_table *, size_t idx1, size_t idx2,
+ size_t idx3, struct pivot_value *);
+void pivot_table_put4 (struct pivot_table *, size_t idx1, size_t idx2,
+ size_t idx3, size_t idx4, struct pivot_value *);
+
+const struct pivot_value *pivot_table_get (const struct pivot_table *,
+ const size_t *dindexes);
+
+struct pivot_value *pivot_table_get_rw (struct pivot_table *,
+ const size_t *dindexes);
+
+/* Footnotes.
+
+ Use pivot_table_create_footnote() to create a footnote.
+ Use pivot_value_add_footnote() to add a reference to a footnote. */
+struct pivot_footnote
+ {
+ size_t idx;
+ struct pivot_value *content;
+ struct pivot_value *marker;
+ };
+
+struct pivot_footnote *pivot_table_create_footnote (
+ struct pivot_table *, struct pivot_value *content);
+struct pivot_footnote *pivot_table_create_footnote__ (
+ struct pivot_table *, size_t idx,
+ struct pivot_value *marker, struct pivot_value *content);
+
+void pivot_footnote_destroy (struct pivot_footnote *);
+
+/* Internals. */
+void pivot_table_convert_indexes_ptod (const struct pivot_table *,
+ const size_t *pindexes[PIVOT_N_AXES],
+ size_t *dindexes);
+size_t *pivot_table_enumerate_axis (const struct pivot_table *,
+ enum pivot_axis_type,
+ const size_t *layer_indexes,
+ bool omit_empty, size_t *n);
+#define PIVOT_ENUMERATION_FOR_EACH(INDEXES, ENUMERATION, AXIS) \
+ for ((INDEXES) = (ENUMERATION); *(INDEXES) != SIZE_MAX; \
+ (INDEXES) += MAX (1, (AXIS)->n_dimensions))
+
+void pivot_table_assign_label_depth (struct pivot_table *);
+
+void pivot_table_dump (const struct pivot_table *, int indentation);
+\f
+/* pivot_value. */
+
+enum pivot_value_type
+ {
+ PIVOT_VALUE_NUMERIC, /* A value of a numeric variable. */
+ PIVOT_VALUE_STRING, /* A value of a string variable. */
+ PIVOT_VALUE_VARIABLE, /* Name of a variable. */
+ PIVOT_VALUE_TEXT, /* Text. */
+ PIVOT_VALUE_TEMPLATE, /* Templated text. */
+ };
+
+/* A pivot_value is the content of a single pivot table cell. A pivot_value is
+ also a pivot table's title, caption, footnote marker and contents, and so
+ on.
+
+ A given pivot_value is one of:
+
+ 1. A number resulting from a calculation (PIVOT_VALUE_NUMERIC). Use
+ pivot_value_new_number() to create such a pivot_value.
+
+ A numeric pivot_value has an associated display format (usually an F or
+ PCT format). This format can be set directly on the pivot_value, but
+ that is not usually the easiest way. Instead, it is usually true that
+ all of the values in a single category should have the same format
+ (e.g. all "Significance" values might use format F40.3), so PSPP makes
+ it easy to set the default format for a category while creating the
+ category. See pivot_dimension_create() for more details.
+
+ For numbers that should be displayed as integers,
+ pivot_value_new_integer() can occasionally be a useful special case.
+
+ 2. A numeric or string value obtained from data (PIVOT_VALUE_NUMERIC or
+ PIVOT_VALUE_STRING). If such a value corresponds to a variable, then the
+ variable's name can be attached to the pivot_value. If the value has a
+ value label, then that can also be attached. When a label is present,
+ the user can control whether to show the value or the label or both.
+
+ Use pivot_value_new_var_value() to create pivot_values of these kinds.
+
+ 3. A variable name (PIVOT_VALUE_VARIABLE). The variable label, if any, can
+ be attached too, and again the user can control whether to show the value
+ or the label or both.
+
+ 4. A text string (PIVOT_VALUE_TEXT). The value stores the string in English
+ and translated into the output language (localized). Use
+ pivot_value_new_text() or pivot_value_new_text_format() for those cases.
+ In some cases, only an English or a localized version is available for
+ one reason or another, although this is regrettable; in those cases, use
+ pivot_value_new_user_text() or pivot_value_new_user_text_nocopy().
+
+ (There is also a PIVOT_VALUE_TEMPLATE but PSPP does not yet create these
+ itself.)
+
+
+ Footnotes
+ =========
+
+ A pivot_value may reference any number of footnotes. Use
+ pivot_value_add_footnote() to add a footnote reference. The footnotes being
+ referenced must first be created with pivot_table_create_footnote().
+
+
+ Styling
+ =======
+
+ A pivot_value can have specific font and cell styles. Only the user should
+ add these.
+*/
+struct pivot_value
+ {
+ struct font_style *font_style;
+ struct cell_style *cell_style;
+ char *subscript;
+ char *superscript;
+
+ struct pivot_footnote **footnotes;
+ size_t n_footnotes;
+
+ enum pivot_value_type type;
+ union
+ {
+ /* PIVOT_VALUE_NUMERIC. */
+ struct
+ {
+ double x; /* The numeric value. */
+ struct fmt_spec format; /* Format to display 'x'. */
+ char *var_name; /* May be NULL. */
+ char *value_label; /* May be NULL. */
+ enum settings_value_show show; /* Show value or label or both? */
+ }
+ numeric;
+
+ /* PIVOT_VALUE_STRING. */
+ struct
+ {
+ char *s; /* The string value. */
+ bool hex; /* Display in hex? */
+ char *var_name; /* May be NULL. */
+ char *value_label; /* May be NULL. */
+ enum settings_value_show show; /* Show value or label or both? */
+ }
+ string;
+
+ /* PIVOT_VALUE_VARIABLE. */
+ struct
+ {
+ char *var_name;
+ char *var_label; /* May be NULL. */
+ enum settings_value_show show; /* Show name or label or both? */
+ }
+ variable;
+
+ /* PIVOT_VALUE_TEXT. */
+ struct
+ {
+ char *local; /* Localized. */
+ char *c; /* English. */
+ char *id; /* Identifier. */
+ bool user_provided;
+ }
+ text;
+
+ /* PIVOT_VALUE_TEMPLATE. */
+ struct
+ {
+ char *s;
+ struct pivot_argument *args;
+ size_t n_args;
+ }
+ template;
+ };
+ };
+
+/* Numbers resulting from calculations. */
+struct pivot_value *pivot_value_new_number (double);
+struct pivot_value *pivot_value_new_integer (double);
+
+/* Values from data. */
+struct pivot_value *pivot_value_new_var_value (
+ const struct variable *, const union value *);
+struct pivot_value *pivot_value_new_value (const union value *, int width,
+ const struct fmt_spec *,
+ const char *encoding);
+
+/* Values from variable names. */
+struct pivot_value *pivot_value_new_variable (const struct variable *);
+
+/* Values from text strings. */
+struct pivot_value *pivot_value_new_text (const char *);
+struct pivot_value *pivot_value_new_text_format (const char *, ...)
+ PRINTF_FORMAT (1, 2);
+
+struct pivot_value *pivot_value_new_user_text (const char *, size_t length);
+struct pivot_value *pivot_value_new_user_text_nocopy (char *);
+
+/* Footnotes. */
+void pivot_value_add_footnote (struct pivot_value *, struct pivot_footnote *);
+
+/* Numeric formats. */
+void pivot_value_set_rc (struct pivot_table *, struct pivot_value *,
+ const char *rc);
+
+/* Converting a pivot_value to a string for display. */
+char *pivot_value_to_string (const struct pivot_value *,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables);
+void pivot_value_format (const struct pivot_value *,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ struct string *);
+bool pivot_value_format_body (const struct pivot_value *,
+ enum settings_value_show show_values,
+ enum settings_value_show show_variables,
+ struct string *);
+
+void pivot_value_destroy (struct pivot_value *);
+
+/* Styling. */
+void pivot_value_get_style (struct pivot_value *,
+ const struct area_style *default_style,
+ struct area_style *);
+void pivot_value_set_style (struct pivot_value *, const struct area_style *);
+
+/* Template arguments. */
+struct pivot_argument
+ {
+ size_t n;
+ struct pivot_value **values;
+ };
+
+void pivot_argument_uninit (struct pivot_argument *);
+
+#endif /* output/pivot-table.h */
struct tab_joined_cell
{
int d[TABLE_N_AXES][2]; /* Table region, same as struct table_cell. */
- union
- {
- char *text;
- struct table_item *subtable;
- }
- u;
+ char *text;
size_t n_footnotes;
const struct footnote **footnotes;
static const struct table_class tab_table_class;
-struct fmt_spec ugly[n_RC] = {
- {FMT_F, 8, 0}, /* INTEGER */
- {FMT_F, 8, 3}, /* WEIGHT (ignored) */
- {FMT_F, 8, 3}, /* PVALUE */
- {FMT_F, 8, 3} /* OTHER (ignored) */
-};
-
-
/* Creates and returns a new table with NC columns and NR rows and initially no
header rows or columns. The table's cells are initially empty. */
struct tab_table *
table_set_nc (&t->table, nc);
table_set_nr (&t->table, nr);
- t->title = NULL;
- t->caption = NULL;
t->cf = nc;
t->cc = pool_calloc (t->container, nr * nc, sizeof *t->cc);
t->ct = pool_calloc (t->container, nr * nc, sizeof *t->ct);
t->rv = pool_nmalloc (t->container, nr, nc + 1);
memset (t->rv, TAL_0, nr * (nc + 1));
- memset (t->fmtmap, 0, sizeof (*t->fmtmap) * n_RC);
- t->fmtmap[RC_PVALUE] = ugly[RC_PVALUE];
- t->fmtmap[RC_INTEGER] = ugly[RC_INTEGER];
- t->fmtmap[RC_OTHER] = *settings_get_format ();
-
memset (t->styles, 0, sizeof t->styles);
memset (t->rule_colors, 0, sizeof t->rule_colors);
- t->col_ofs = t->row_ofs = 0;
-
return t;
}
-void
-tab_set_format (struct tab_table *t, enum result_class rc,
- const struct fmt_spec *fmt)
-{
- t->fmtmap[rc] = *fmt;
-}
-
-
-/* Sets the width and height of a table, in columns and rows,
- respectively. Use only to reduce the size of a table, since it
- does not change the amount of allocated memory.
-
- This function is obsolete. Please do not add new uses of it. (Instead, use
- table_select() or one of its helper functions.) */
-void
-tab_resize (struct tab_table *t, int nc, int nr)
-{
- if (nc != -1)
- {
- assert (nc + t->col_ofs <= t->cf);
- table_set_nc (&t->table, nc + t->col_ofs);
- }
- if (nr != -1)
- {
- assert (nr + t->row_ofs <= tab_nr (t));
- table_set_nr (&t->table, nr + t->row_ofs);
- }
-}
-
-/* Changes either or both dimensions of a table and reallocates memory as
- necessary.
-
- This function is obsolete. Please do not add new uses of it. (Instead, use
- table_paste() or one of its helper functions to paste multiple tables
- together into a larger one.) */
-void
-tab_realloc (struct tab_table *t, int nc, int nr)
-{
- int ro, co;
-
- ro = t->row_ofs;
- co = t->col_ofs;
- if (ro || co)
- tab_offset (t, 0, 0);
-
- if (nc == -1)
- nc = tab_nc (t);
- if (nr == -1)
- nr = tab_nr (t);
-
- assert (nc == tab_nc (t));
-
- if (nc > t->cf)
- {
- int mr1 = MIN (nr, tab_nr (t));
- int mc1 = MIN (nc, tab_nc (t));
-
- void **new_cc;
- unsigned short *new_ct;
- int r;
-
- new_cc = pool_calloc (t->container, nr * nc, sizeof *new_cc);
- new_ct = pool_malloc (t->container, nr * nc);
- for (r = 0; r < mr1; r++)
- {
- memcpy (&new_cc[r * nc], &t->cc[r * tab_nc (t)],
- mc1 * sizeof *t->cc);
- memcpy (&new_ct[r * nc], &t->ct[r * tab_nc (t)],
- mc1 * sizeof *t->ct);
- memset (&new_ct[r * nc + tab_nc (t)], 0, nc - tab_nc (t));
- }
- pool_free (t->container, t->cc);
- pool_free (t->container, t->ct);
- t->cc = new_cc;
- t->ct = new_ct;
- t->cf = nc;
- }
- else if (nr != tab_nr (t))
- {
- t->cc = pool_nrealloc (t->container, t->cc, nr * nc, sizeof *t->cc);
- t->ct = pool_nrealloc (t->container, t->ct, nr * nc, sizeof *t->ct);
-
- t->rh = pool_nrealloc (t->container, t->rh, nc, nr + 1);
- t->rv = pool_nrealloc (t->container, t->rv, nr, nc + 1);
-
- if (nr > tab_nr (t))
- {
- memset (&t->rh[nc * (tab_nr (t) + 1)], TAL_0,
- (nr - tab_nr (t)) * nc);
- memset (&t->rv[(nc + 1) * tab_nr (t)], TAL_0,
- (nr - tab_nr (t)) * (nc + 1));
- }
- }
-
- memset (&t->ct[nc * tab_nr (t)], 0, nc * (nr - tab_nr (t)) * sizeof *t->ct);
- memset (&t->cc[nc * tab_nr (t)], 0, nc * (nr - tab_nr (t)) * sizeof *t->cc);
-
- table_set_nr (&t->table, nr);
- table_set_nc (&t->table, nc);
-
- if (ro || co)
- tab_offset (t, co, ro);
-}
-
/* Sets the number of header rows on each side of TABLE to L on the
left, R on the right, T on the top, B on the bottom. Header rows
are repeated when a table is broken across multiple columns or
{
if (debugging)
{
- if (x + t->col_ofs < 0 || x + t->col_ofs > tab_nc (t)
- || y1 + t->row_ofs < 0 || y1 + t->row_ofs >= tab_nr (t)
- || y2 + t->row_ofs < 0 || y2 + t->row_ofs >= tab_nr (t))
+ if (x < 0 || x > tab_nc (t)
+ || y1 < 0 || y1 >= tab_nr (t)
+ || y2 < 0 || y2 >= tab_nr (t))
{
- printf (_("bad vline: x=%d+%d=%d y=(%d+%d=%d,%d+%d=%d) in "
- "table size (%d,%d)\n"),
- x, t->col_ofs, x + t->col_ofs,
- y1, t->row_ofs, y1 + t->row_ofs,
- y2, t->row_ofs, y2 + t->row_ofs, tab_nc (t), tab_nr (t));
+ printf (_("bad vline: x=%d y=(%d,%d) in table size (%d,%d)\n"),
+ x, y1, y2, tab_nc (t), tab_nr (t));
return;
}
}
- x += t->col_ofs;
- y1 += t->row_ofs;
- y2 += t->row_ofs;
-
assert (x >= 0);
assert (x <= tab_nc (t));
assert (y1 >= 0);
{
if (debugging)
{
- if (y + t->row_ofs < 0 || y + t->row_ofs > tab_nr (t)
- || x1 + t->col_ofs < 0 || x1 + t->col_ofs >= tab_nc (t)
- || x2 + t->col_ofs < 0 || x2 + t->col_ofs >= tab_nc (t))
+ if (y < 0 || y > tab_nr (t)
+ || x1 < 0 || x1 >= tab_nc (t)
+ || x2 < 0 || x2 >= tab_nc (t))
{
- printf (_("bad hline: x=(%d+%d=%d,%d+%d=%d) y=%d+%d=%d in "
- "table size (%d,%d)\n"),
- x1, t->col_ofs, x1 + t->col_ofs,
- x2, t->col_ofs, x2 + t->col_ofs,
- y, t->row_ofs, y + t->row_ofs, tab_nc (t), tab_nr (t));
+ printf (_("bad hline: x=(%d,%d) y=%d in table size (%d,%d)\n"),
+ x1, x2, y, tab_nc (t), tab_nr (t));
return;
}
}
- x1 += t->col_ofs;
- x2 += t->col_ofs;
- y += t->row_ofs;
-
assert (y >= 0);
assert (y <= tab_nr (t));
assert (x2 >= x1);
{
if (debugging)
{
- if (x1 + t->col_ofs < 0 || x1 + t->col_ofs >= tab_nc (t)
- || x2 + t->col_ofs < 0 || x2 + t->col_ofs >= tab_nc (t)
- || y1 + t->row_ofs < 0 || y1 + t->row_ofs >= tab_nr (t)
- || y2 + t->row_ofs < 0 || y2 + t->row_ofs >= tab_nr (t))
+ if (x1 < 0 || x1 >= tab_nc (t)
+ || x2 < 0 || x2 >= tab_nc (t)
+ || y1 < 0 || y1 >= tab_nr (t)
+ || y2 < 0 || y2 >= tab_nr (t))
{
- printf (_("bad box: (%d+%d=%d,%d+%d=%d)-(%d+%d=%d,%d+%d=%d) "
- "in table size (%d,%d)\n"),
- x1, t->col_ofs, x1 + t->col_ofs,
- y1, t->row_ofs, y1 + t->row_ofs,
- x2, t->col_ofs, x2 + t->col_ofs,
- y2, t->row_ofs, y2 + t->row_ofs, tab_nc (t), tab_nr (t));
+ printf (_("bad box: (%d,%d)-(%d,%d) in table size (%d,%d)\n"),
+ x1, y1, x2, y2, tab_nc (t), tab_nr (t));
NOT_REACHED ();
}
}
- x1 += t->col_ofs;
- x2 += t->col_ofs;
- y1 += t->row_ofs;
- y2 += t->row_ofs;
-
assert (x2 >= x1);
assert (y2 >= y1);
assert (x1 >= 0);
\f
/* Cells. */
-/* Sets cell (C,R) in TABLE, with options OPT, to have a value taken
- from V, displayed with format spec F. */
-void
-tab_value (struct tab_table *table, int c, int r, unsigned short opt,
- const union value *v, const struct variable *var,
- const struct fmt_spec *f)
-{
- char *contents;
-
- if (debugging)
- {
- if (c + table->col_ofs < 0 || r + table->row_ofs < 0
- || c + table->col_ofs >= tab_nc (table)
- || r + table->row_ofs >= tab_nr (table))
- {
- printf ("tab_value(): bad cell (%d+%d=%d,%d+%d=%d) in table size "
- "(%d,%d)\n",
- c, table->col_ofs, c + table->col_ofs,
- r, table->row_ofs, r + table->row_ofs,
- tab_nc (table), tab_nr (table));
- return;
- }
- }
-
- contents = data_out_stretchy (v, var_get_encoding (var),
- f != NULL ? f : var_get_print_format (var),
- table->container);
-
- table->cc[c + r * table->cf] = contents;
- table->ct[c + r * table->cf] = opt;
-}
-
-/* Sets cell (C,R) in TABLE, with options OPT, to have value VAL as
- formatted by FMT.
- If FMT is null, then the default print format will be used.
-*/
-void
-tab_double (struct tab_table *table, int c, int r, unsigned short opt,
- double val, const struct fmt_spec *fmt, enum result_class rc)
-{
- union value double_value;
- char *s;
-
- assert (c >= 0);
- assert (c < tab_nc (table));
- assert (r >= 0);
- assert (r < tab_nr (table));
-
- if (fmt == NULL)
- fmt = &table->fmtmap[rc];
-
- fmt_check_output (fmt);
-
- if (debugging)
- {
- if (c + table->col_ofs < 0 || r + table->row_ofs < 0
- || c + table->col_ofs >= tab_nc (table)
- || r + table->row_ofs >= tab_nr (table))
- {
- printf ("tab_double(): bad cell (%d+%d=%d,%d+%d=%d) in table size "
- "(%d,%d)\n",
- c, table->col_ofs, c + table->col_ofs,
- r, table->row_ofs, r + table->row_ofs,
- tab_nc (table), tab_nr (table));
- return;
- }
- }
-
- double_value.f = val;
- s = data_out_stretchy (&double_value, C_ENCODING, fmt, table->container);
- table->cc[c + r * table->cf] = s + strspn (s, " ");
- table->ct[c + r * table->cf] = opt;
-}
-
-
static void
do_tab_text (struct tab_table *table, int c, int r, unsigned opt, char *text)
{
if (debugging)
{
- if (c + table->col_ofs < 0 || r + table->row_ofs < 0
- || c + table->col_ofs >= tab_nc (table)
- || r + table->row_ofs >= tab_nr (table))
+ if (c < 0 || r < 0 || c >= tab_nc (table) || r >= tab_nr (table))
{
- printf ("tab_text(): bad cell (%d+%d=%d,%d+%d=%d) in table size "
- "(%d,%d)\n",
- c, table->col_ofs, c + table->col_ofs,
- r, table->row_ofs, r + table->row_ofs,
- tab_nc (table), tab_nr (table));
+ printf ("tab_text(): bad cell (%d,%d) in table size (%d,%d)\n",
+ c, r, tab_nc (table), tab_nr (table));
return;
}
}
{
struct tab_joined_cell *j;
- assert (x1 + table->col_ofs >= 0);
- assert (y1 + table->row_ofs >= 0);
+ assert (x1 >= 0);
+ assert (y1 >= 0);
assert (y2 >= y1);
assert (x2 >= x1);
- assert (y2 + table->row_ofs < tab_nr (table));
- assert (x2 + table->col_ofs < tab_nc (table));
+ assert (y2 < tab_nr (table));
+ assert (x2 < tab_nc (table));
if (debugging)
{
- if (x1 + table->col_ofs < 0 || x1 + table->col_ofs >= tab_nc (table)
- || y1 + table->row_ofs < 0 || y1 + table->row_ofs >= tab_nr (table)
- || x2 < x1 || x2 + table->col_ofs >= tab_nc (table)
- || y2 < y1 || y2 + table->row_ofs >= tab_nr (table))
+ if (x1 < 0 || x1 >= tab_nc (table)
+ || y1 < 0 || y1 >= tab_nr (table)
+ || x2 < x1 || x2 >= tab_nc (table)
+ || y2 < y1 || y2 >= tab_nr (table))
{
printf ("tab_joint_text(): bad cell "
- "(%d+%d=%d,%d+%d=%d)-(%d+%d=%d,%d+%d=%d) in table size (%d,%d)\n",
- x1, table->col_ofs, x1 + table->col_ofs,
- y1, table->row_ofs, y1 + table->row_ofs,
- x2, table->col_ofs, x2 + table->col_ofs,
- y2, table->row_ofs, y2 + table->row_ofs,
- tab_nc (table), tab_nr (table));
+ "(%d,%d)-(%d,%d) in table size (%d,%d)\n",
+ x1, y1, x2, y2, tab_nc (table), tab_nr (table));
return NULL;
}
}
tab_box (table, -1, -1, TAL_0, TAL_0, x1, y1, x2, y2);
j = pool_alloc (table->container, sizeof *j);
- j->d[TABLE_HORZ][0] = x1 + table->col_ofs;
- j->d[TABLE_VERT][0] = y1 + table->row_ofs;
- j->d[TABLE_HORZ][1] = ++x2 + table->col_ofs;
- j->d[TABLE_VERT][1] = ++y2 + table->row_ofs;
+ j->d[TABLE_HORZ][0] = x1;
+ j->d[TABLE_VERT][0] = y1;
+ j->d[TABLE_HORZ][1] = ++x2;
+ j->d[TABLE_VERT][1] = ++y2;
j->n_footnotes = 0;
j->footnotes = NULL;
j->style = NULL;
if (x1 == x2 && y1 == y2)
do_tab_text (table, x1, y1, opt, s);
else
- add_joined_cell (table, x1, y1, x2, y2, opt)->u.text = s;
-}
-
-/* Joins cells (X1,X2)-(Y1,Y2) inclusive in TABLE, and sets them
- with options OPT to have text value FORMAT, which is formatted
- as if passed to printf. */
-void
-tab_joint_text_format (struct tab_table *table, int x1, int y1, int x2,
- int y2, unsigned opt, const char *format, ...)
-{
- va_list args;
- char *s;
-
- va_start (args, format);
- s = pool_vasprintf (table->container, format, args);
- va_end (args);
-
- add_joined_cell (table, x1, y1, x2, y2, opt)->u.text = s;
+ add_joined_cell (table, x1, y1, x2, y2, opt)->text = s;
}
struct footnote *
char *text = table->cc[index];
j = add_joined_cell (table, x, y, x, y, table->ct[index]);
- j->u.text = text ? text : xstrdup ("");
+ j->text = text ? text : xstrdup ("");
}
j->footnotes = pool_realloc (table->container, j->footnotes,
char *text = table->cc[index];
j = add_joined_cell (table, x, y, x, y, table->ct[index]);
- j->u.text = text ? text : xstrdup ("");
+ j->text = text ? text : xstrdup ("");
}
j->style = style;
return table->cc[c + r * table->cf] == NULL;
}
\f
-/* Miscellaneous. */
-
-/* Set the title of table T to TITLE, which is formatted as if
- passed to printf(). */
-void
-tab_title (struct tab_table *t, const char *title, ...)
-{
- va_list args;
-
- free (t->title);
- va_start (args, title);
- t->title = xvasprintf (title, args);
- va_end (args);
-}
-
-/* Set the caption of table T to CAPTION, which is formatted as if
- passed to printf(). */
-void
-tab_caption (struct tab_table *t, const char *caption, ...)
-{
- va_list args;
-
- free (t->caption);
- va_start (args, caption);
- t->caption = xvasprintf (caption, args);
- va_end (args);
-}
-
-/* Easy, type-safe way to submit a tab table to som. */
-void
-tab_submit (struct tab_table *t)
-{
- table_item_submit (table_item_create (&t->table, t->title, t->caption));
-}
-\f
/* Editing. */
-/* Set table row and column offsets for all functions that affect
- cells or rules. */
-void
-tab_offset (struct tab_table *t, int col, int row)
-{
- int diff = 0;
-
- if (debugging)
- {
- if (row < -1 || row > tab_nr (t))
- {
- printf ("tab_offset(): row=%d in %d-row table\n", row, tab_nr (t));
- NOT_REACHED ();
- }
- if (col < -1 || col > tab_nc (t))
- {
- printf ("tab_offset(): col=%d in %d-column table\n", col,
- tab_nc (t));
- NOT_REACHED ();
- }
- }
-
- if (row != -1)
- diff += (row - t->row_ofs) * t->cf, t->row_ofs = row;
- if (col != -1)
- diff += (col - t->col_ofs), t->col_ofs = col;
-
- t->cc += diff;
- t->ct += diff;
-}
-
-/* Increment the row offset by one. If the table is too small,
- increase its size. */
-void
-tab_next_row (struct tab_table *t)
-{
- t->cc += t->cf;
- t->ct += t->cf;
- if (++t->row_ofs >= tab_nr (t))
- tab_realloc (t, -1, tab_nr (t) * 4 / 3);
-}
-\f
/* Writes STRING to the output. OPTIONS may be any valid combination of TAB_*
bits.
void
tab_output_text (int options, const char *string)
{
- enum text_item_type type = (options & TAB_EMPH ? TEXT_ITEM_TITLE
- : options & TAB_FIX ? TEXT_ITEM_LOG
+ enum text_item_type type = (options & TAB_FIX ? TEXT_ITEM_LOG
: TEXT_ITEM_PARAGRAPH);
text_item_submit (text_item_create (type, string));
}
tab_destroy (struct table *table)
{
struct tab_table *t = tab_cast (table);
- free (t->title);
- t->title = NULL;
- free (t->caption);
- t->caption = NULL;
pool_destroy (t->container);
}
if (opt & TAB_JOIN)
{
const struct tab_joined_cell *jc = cc;
- cell->text = jc->u.text;
+ cell->text = jc->text;
cell->footnotes = jc->footnotes;
cell->n_footnotes = jc->n_footnotes;
This is a type of table (see output/table.h) whose content is composed
manually by the code that generates it, by filling in cells one by one.
-
- Some of the features of this type of table are obsolete but have not yet
- been removed, because some code still uses them. These features are:
-
- - The title and caption. These are properties of the table_item (see
- output/table-item.h) in which a table is embedded, not properties of
- the table itself.
-
- - Row and columns offsets (via tab_offset(), tab_next_row()). This
- feature simply isn't used enough to justify keeping it.
-
- - Table resizing. The code that does use this feature is just as well
- served by creating multiple tables and pasting them together with
- table_paste(). Eliminating this feature would also slightly simplify
- the table code here.
*/
#include "libpspp/compiler.h"
#include "output/table.h"
#include "data/format.h"
-enum result_class
- {
- RC_INTEGER,
- RC_WEIGHT,
- RC_PVALUE,
- RC_OTHER,
- n_RC
- };
-
#define TAB_STYLE_MASK (7u << (TAB_FIRST_AVAILABLE + 1))
#define TAB_STYLE_SHIFT (TAB_FIRST_AVAILABLE + 1)
struct pool *container;
/* Table title and caption, or null. */
- char *title, *caption;
int cf; /* Column factor for indexing purposes. */
/* Table contents.
unsigned char *rh; /* Horiz rules; unsigned char[nr+1][nc]. */
unsigned char *rv; /* Vert rules; unsigned char[nr][nc+1]. */
struct cell_color *rule_colors[32];
-
- /* X and Y offsets. */
- int col_ofs, row_ofs;
-
- struct fmt_spec fmtmap [n_RC];
};
struct tab_table *tab_cast (const struct table *);
/* Tables. */
struct tab_table *tab_create (int nc, int nr);
-void tab_resize (struct tab_table *, int nc, int nr);
-void tab_realloc (struct tab_table *, int nc, int nr);
void tab_headers (struct tab_table *, int l, int r, int t, int b);
-void tab_title (struct tab_table *, const char *, ...)
- PRINTF_FORMAT (2, 3);
-void tab_caption (struct tab_table *, const char *, ...)
- PRINTF_FORMAT (2, 3);
-void tab_submit (struct tab_table *);
/* Rules. */
void tab_hline (struct tab_table *, int style, int x1, int x2, int y);
void tab_box (struct tab_table *, int f_h, int f_v, int i_h, int i_v,
int x1, int y1, int x2, int y2);
-/* Obsolete cell options. */
-#define TAT_TITLE TAB_EMPH /* Title attributes. */
-
-void tab_set_format (struct tab_table *, enum result_class, const struct fmt_spec *);
-
-
/* Cells. */
-struct fmt_spec;
-struct dictionary;
-union value;
-void tab_value (struct tab_table *, int c, int r, unsigned short opt,
- const union value *, const struct variable *,
- const struct fmt_spec *);
-
-void tab_double (struct tab_table *, int c, int r, unsigned short opt,
- double v, const struct fmt_spec *, enum result_class );
-
void tab_text (struct tab_table *, int c, int r, unsigned opt, const char *);
void tab_text_format (struct tab_table *, int c, int r, unsigned opt,
const char *, ...)
void tab_joint_text (struct tab_table *, int x1, int y1, int x2, int y2,
unsigned opt, const char *);
-void tab_joint_text_format (struct tab_table *, int x1, int y1, int x2, int y2,
- unsigned opt, const char *, ...)
- PRINTF_FORMAT (7, 8);
struct footnote *tab_create_footnote (struct tab_table *, size_t idx,
const char *content, const char *marker,
bool tab_cell_is_empty (const struct tab_table *, int c, int r);
-/* Editing. */
-void tab_offset (struct tab_table *, int col, int row);
-void tab_next_row (struct tab_table *);
-
-/* Current row/column offset. */
-#define tab_row(TABLE) ((TABLE)->row_ofs)
-#define tab_col(TABLE) ((TABLE)->col_ofs)
-
/* Simple output. */
void tab_output_text (int options, const char *string);
void tab_output_text_format (int options, const char *, ...)
+++ /dev/null
-/* PSPP - a program for statistical analysis.
- Copyright (C) 2009, 2011, 2013, 2014 Free Software Foundation, Inc.
-
- This program is free software: you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program. If not, see <http://www.gnu.org/licenses/>. */
-
-#include <config.h>
-
-#include "output/table-provider.h"
-
-#include "data/casereader.h"
-#include "data/data-out.h"
-#include "data/format.h"
-#include "libpspp/i18n.h"
-
-#include "gl/xalloc.h"
-
-struct table_casereader
- {
- struct table table;
- struct casereader *reader;
- char *heading;
- struct fmt_spec format;
- };
-
-static const struct table_class table_casereader_class;
-
-static struct table_casereader *
-table_casereader_cast (const struct table *table)
-{
- assert (table->klass == &table_casereader_class);
- return UP_CAST (table, struct table_casereader, table);
-}
-
-/* Returns a new table that has one column and the same number of rows as
- READER. Each row in the table is derived from column COLUMN in the same row
- of READER by formatting with data_out() using the specified FORMAT (which
- must be a valid format for the column's width).
-
- If HEADING is nonnull, adds an additional row above the first row of data
- that contains HEADING, and sets that row as a header row.
-
- The returned table has no rules, except that if HEADING is nonnull, a single
- line (TAL_1) separates HEADING from the first row if data. */
-struct table *
-table_from_casereader (const struct casereader *reader, size_t column,
- const char *heading, const struct fmt_spec *format)
-{
- struct table_casereader *tc;
- struct table *t;
-
- assert (fmt_check_width_compat (format,
- caseproto_get_width (
- casereader_get_proto (reader), column)));
-
- tc = xmalloc (sizeof *tc);
- t = &tc->table;
- table_init (t, &table_casereader_class);
- table_set_nc (t, 1);
- table_set_nr (t, casereader_count_cases (reader));
- tc->reader = casereader_project_1 (casereader_clone (reader), column);
- tc->heading = NULL;
- tc->format = *format;
-
- if (heading != NULL)
- {
- tc->heading = xstrdup (heading);
- table_set_nr (t, table_nr (t) + 1);
- table_set_ht (t, 1);
- }
-
- return t;
-}
-
-static void
-table_casereader_destroy (struct table *t)
-{
- struct table_casereader *tc = table_casereader_cast (t);
- casereader_destroy (tc->reader);
- free (tc->heading);
- free (t);
-}
-
-static void
-free_string (void *s_)
-{
- char *s = s_;
- free (s);
-}
-
-static void
-table_casereader_get_cell (const struct table *t, int x, int y,
- struct table_cell *cell)
-{
- struct table_casereader *tc = table_casereader_cast (t);
- struct ccase *c;
- char *s;
-
- static const struct area_style style = {
- AREA_STYLE_INITIALIZER__,
- .cell_style.halign = TABLE_HALIGN_RIGHT
- };
-
- cell->d[TABLE_HORZ][0] = x;
- cell->d[TABLE_HORZ][1] = x + 1;
- cell->d[TABLE_VERT][0] = y;
- cell->d[TABLE_VERT][1] = y + 1;
- cell->style = &style;
- cell->options = 0;
- cell->n_footnotes = 0;
- if (tc->heading != NULL)
- {
- if (y == 0)
- {
- s = xstrdup (tc->heading);
- cell->text = s;
- cell->destructor = free_string;
- cell->destructor_aux = s;
- return;
- }
- y--;
- }
-
- c = casereader_peek (tc->reader, y);
- if (c == NULL)
- s = xstrdup ("I/O Error");
- else
- {
- s = data_out (case_data_idx (c, 0), UTF8, &tc->format);
- case_unref (c);
- }
- cell->text = s;
- cell->destructor = free_string;
- cell->destructor_aux = s;
-}
-
-static int
-table_casereader_get_rule (const struct table *t, enum table_axis axis,
- int x UNUSED, int y,
- struct cell_color *color UNUSED)
-{
- struct table_casereader *tc = table_casereader_cast (t);
- if (axis == TABLE_VERT)
- return tc->heading != NULL && y == 1 ? TAL_1 : TAL_0;
- else
- return TAL_0;
-}
-
-static const struct table_class table_casereader_class =
- {
- table_casereader_destroy,
- table_casereader_get_cell,
- table_casereader_get_rule,
- NULL, /* paste */
- NULL, /* select (XXX) */
- };
#include <inttypes.h>
#include <stdlib.h>
+#include "data/format.h"
#include "libpspp/assertion.h"
#include "libpspp/cast.h"
#include "libpspp/compiler.h"
enum
{
TAB_NONE = 0,
- TAB_EMPH = 1 << 0, /* Emphasize cell contents. */
TAB_FIX = 1 << 1, /* Use fixed font. */
TAB_MARKUP = 1 << 2, /* Text contains Pango markup. */
TAB_NUMERIC = 1 << 3, /* Cell contents are numeric. */
/* Simple kinds of tables. */
struct table *table_from_string (enum table_halign, const char *);
-struct table *table_from_variables (unsigned int options,
- struct variable **, size_t);
-struct table *table_from_casereader (const struct casereader *,
- size_t column,
- const char *heading,
- const struct fmt_spec *);
/* Combining tables. */
struct table *table_paste (struct table *, struct table *,
#include "output/driver-provider.h"
#include "output/message-item.h"
#include "output/output-item.h"
-#include "output/tab.h"
#include "output/table-item.h"
#include "output/text-item.h"
#include "ui/gui/help-menu.h"
src/libpspp-core.la \
$(CAIRO_LIBS)
-
check_PROGRAMS += tests/ui/syntax-gen-test
tests_ui_syntax_gen_test_SOURCES = tests/ui/syntax-gen-test.c
tests_ui_syntax_gen_test_LDADD = \
])
AT_CHECK([pspp -o pspp.csv pc+-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-File label: PSPP synthetic test file
+Table: File Label
+Label,PSPP synthetic test file
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
Table: Data List
NUM1,NUM2,NUM3,NUM4,STR1,STR2,STR3,STR4,STR5,STR6
-0,1,2,.,abcdefgh,ijkl,mnopq,r,stuvwxyzAB ,CDEFGHIJKLM
+0,1,2,.,abcdefgh,ijkl,mnopq,r,stuvwxyzAB,CDEFGHIJKLM
])
AT_CLEANUP
])
AT_CHECK([pspp -o pspp.csv pc+-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-File label: PSPP synthetic test file
+Table: File Label
+Label,PSPP synthetic test file
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
STR8,13,,Nominal,Input,8,Left,A8,A8,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
NUM1,1,one
NUM2,2,two
,3,three
])
AT_CHECK([pspp -o pspp.csv pc+-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-File label: PSPP synthetic test file
+Table: File Label
+Label,PSPP synthetic test file
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
Table: Data List
NUM1,NUM2,STR4,STR8,STR15
--5,150,abcd,efghj ,efghijklABCDEFG
+-5,150,abcd,efghj,efghijklABCDEFG
1000,.,PQRS,TUVWXYZa,bcdefghijklmnop
])
AT_CLEANUP
SYSFILE INFO FILE='pc+-file.sav' ENCODING='us-ascii'.
])
AT_CHECK([pspp -O format=csv pc+-file.sps], [0], [dnl
-File:,pc+-file.sav
-Label:,PSPP synthetic test file
-Created:,11/28/14 15:11:00 by PCSPSS PSPP synthetic test product
-Integer Format:,Little Endian
-Real Format:,IEEE 754 LE.
-Variables:,4
-Cases:,1
-Type:,SPSS/PC+ System File
-Weight:,NUM3
-Compression:,None
-Encoding:,us-ascii
+Table: File Information
+File,pc+-file.sav
+Label,PSPP synthetic test file
+Created,11/28/14 15:11:00 by PCSPSS PSPP synthetic test product
+Integer Format,Little Endian
+Real Format,IEEE 754 LE.
+Variables,4
+Cases,1
+Type,SPSS/PC+ System File
+Weight,NUM3
+Compression,None
+Encoding,us-ascii
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
AT_CHECK([sed 's/default encoding.*For/default encoding. For/' stdout], [0], [dnl
"warning: `pc+-file.sav': Using default encoding. For best results, specify an encoding explicitly. Use SYSFILE INFO with ENCODING=""DETECT"" to analyze the possible encodings."
-File label: PSPP synthetic test file
+Table: File Label
+Label,PSPP synthetic test file
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
NUM1,NUM2,NUM3,NUM4
2,3,4,5
-File:,pc+-file.sav
-Label:,PSPP synthetic test file
-Created:,11/28/14 15:11:00 by PCSPSS PSPP synthetic test product
-Integer Format:,Little Endian
-Real Format:,IEEE 754 LE.
-Variables:,4
-Cases:,1
-Type:,SPSS/PC+ System File
-Weight:,Not weighted.
-Compression:,None
-Encoding:,us-ascii
+Table: File Information
+File,pc+-file.sav
+Label,PSPP synthetic test file
+Created,11/28/14 15:11:00 by PCSPSS PSPP synthetic test product
+Integer Format,Little Endian
+Real Format,IEEE 754 LE.
+Variables,4
+Cases,1
+Type,SPSS/PC+ System File
+Weight,Not weighted
+Compression,None
+Encoding,us-ascii
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
LIST.
])
AT_CHECK([pspp -O format=csv pc+-file.sps], [0], [dnl
-File label: PSPP synthetic test file
+Table: File Label
+Label,PSPP synthetic test file
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
Table: Data List
NUM1,NUM2,STR4,STR8,STR15
--5,150,abcd,efghj ,efghijklABCDEFG
+-5,150,abcd,efghj,efghijklABCDEFG
1000,.,PQRS,TUVWXYZa,bcdefghijklmnop
])
AT_CLEANUP
VAR5,5,,Scale,Input,8,Right,F1.0,F1.0,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
VAR1,1,one
VAR2,2,two
VAR3,3,three
/Created/d
/Product/d
'], [0], [dnl
-File:,data.por
-Label:,No label.
-Variables:,5
-Cases:,Unknown
-Type:,SPSS Portable File
-Weight:,Not weighted.
-Compression:,None
+Table: File Information
+File,data.por
+Label,
+Variables,5
+Cases,Unknown
+Type,SPSS Portable File
+Weight,Not weighted
+Compression,None
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
VAR5,5,,Scale,Input,8,Right,F1.0,F1.0,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
VAR1,1,one
VAR2,2,two
VAR3,3,three
])
AT_CHECK([pspp -o pspp.csv sys-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-File label: PSPP synthetic test file: ôõöø
+Table: File Label
+Label,PSPP synthetic test file: ôõöø
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
str17,17,,Nominal,Input,17,Left,A17,A17,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
num1,1,один (in Russian)
num2,1,one
,2,two
])
AT_CHECK([pspp -o pspp.csv sys-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Documents in the active dataset:
-
-First line of documents
-
+Table: Documents
+"First line of documents
Second line of documents
-
abbé appliqué attaché blasé café canapé cliché consommé
-
-
-Last line of documents
+Last line of documents"
Table: Data List
num1
AT_CHECK([pspp -o pspp.csv sys-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Multiple Response Sets
-Name,Variables,Details
-$a,"あ
+Name,Label,Encoding,Counted Value,Member Variables
+$a,my mcgroup,Categories,,"あ
b
-c
-","Multiple category set
-Label: my mcgroup
-"
-$b,"g
+c"
+$b,,Dichotomies,55,"g
e
f
-d
-","Multiple dichotomy set
-Counted value: 55
-Category label source: Variable labels
-"
-$c,"h
+d"
+$c,mdgroup #2,Dichotomies,はい,"h
i
-j
-","Multiple dichotomy set
-Label: mdgroup #2
-Label source: Provided by user
-Counted value: `はい'
-Category label source: Variable labels
-"
-$d,"k
+j"
+$d,third mdgroup,Dichotomies,34,"k
l
-m
-","Multiple dichotomy set
-Label: third mdgroup
-Label source: Provided by user
-Counted value: 34
-Category label source: Value labels of counted value
-"
-$e,"n
+m"
+$e,,Dichotomies,choice,"n
o
-p
-","Multiple dichotomy set
-Label source: First variable label among variables
-Counted value: `choice'
-Category label source: Value labels of counted value
-"
+p"
])
done
AT_CLEANUP
SYSFILE INFO FILE='sys-file.sav'.
])
AT_CHECK([pspp -o pspp.csv sys-file.sps])
- AT_CHECK([sed 7q pspp.csv], [0], [dnl
-File:,sys-file.sav
-Label:,"PSPP synthetic
+ AT_CHECK([sed 8q pspp.csv], [0], [dnl
+Table: File Information
+File,sys-file.sav
+Label,"PSPP synthetic
test file"
-Created:,01 Jan 11 20:53:52 by $(@%:@) SPSS DATA FILE PSPP synthetic test file
-Product:,"Extra product info
+Created,01 Jan 11 20:53:52 by $(@%:@) SPSS DATA FILE PSPP synthetic test file
+Product,"Extra product info
another line
blah"
])
AT_CHECK([pspp -o pspp.csv sys-file.sps])
AT_CHECK([cat pspp.csv], [0],
[[Table: Variable and Dataset Attributes
-Variable,Name,Value
+Variable and Name,,Value
(dataset),Attr1[1],Value1
,Attr1[2],'déclaration'
,SécondAttr[1],123
Table: Data List
num1,num2,str4,str8,str15
--99,0,,abcdefgh,0123 @&t@
-.,151,jklm,nopqrstu,vwxyzABC @&t@
+-99,0,,abcdefgh,0123
+.,151,jklm,nopqrstu,vwxyzABC
1,2,DEFG,HIJKLMNO,PQRSTUV
])
done
Table: Data List
num1,num2,str4,str8,str15
-1,100,,abcdefgh,0123 @&t@
-.,251,jklm,nopqrstu,vwxyzABC @&t@
+1,100,,abcdefgh,0123
+.,251,jklm,nopqrstu,vwxyzABC
101,102,DEFG,HIJKLMNO,PQRSTUV
])
done
Table: Data List
num1,num2,str4,str8,str15
--49,50,,abcdefgh,0123 @&t@
-.,201,jklm,nopqrstu,vwxyzABC @&t@
+-49,50,,abcdefgh,0123
+.,201,jklm,nopqrstu,vwxyzABC
51,52,DEFG,HIJKLMNO,PQRSTUV
])
done
Table: Data List
num1,num2,str4,str8,str15
--99,0,,abcdefgh,0123 @&t@
-.,151,jklm,nopqrstu,vwxyzABC @&t@
+-99,0,,abcdefgh,0123
+.,151,jklm,nopqrstu,vwxyzABC
1,2,DEFG,HIJKLMNO,PQRSTUV
])
done
warning: `sys-file.sav': Invalid multiple response set name `e'.
Table: Multiple Response Sets
-Name,Variables,Details
-$a,"あ
+Name,Label,Encoding,Counted Value,Member Variables
+$a,my mcgroup,Categories,,"あ
b
-c
-","Multiple category set
-Label: my mcgroup
-"
-$c,"h
+c"
+$c,mdgroup #2,Dichotomies,はい,"h
i
-j
-","Multiple dichotomy set
-Label: mdgroup #2
-Label source: Provided by user
-Counted value: `はい'
-Category label source: Variable labels
-"
-$d,"k
+j"
+$d,third mdgroup,Dichotomies,34,"k
l
-m
-","Multiple dichotomy set
-Label: third mdgroup
-Label source: Provided by user
-Counted value: 34
-Category label source: Value labels of counted value
-"
+m"
])
done
AT_CLEANUP
Table: Data List
str14
-one data item @&t@
+one data item
])
done
AT_CLEANUP
Table: Data List
num1,num2,str4,str8,str15
--99,0,,abcdefgh,0123 @&t@
+-99,0,,abcdefgh,0123
])
done
AT_CLEANUP
s3,3,,Nominal,Input,9,Left,A9,A9,"""1234 ""; ""12345 ""; ""12345678"""
Table: Value Labels
-Variable,Value,Label
-s1,abc ,First value label
-,abcdefgh ,Second value label
+Variable Value,,Label
+s1,abc,First value label
+,abcdefgh,Second value label
,abcdefghi,Third value label
-s2,0 ,Fourth value label
-,01234567 ,Fifth value label
+s2,0,Fourth value label
+,01234567,Fifth value label
,012345678,Sixth value label
])
AT_CHECK_UNQUOTED([dd if=foo.sav bs=1 count=4; echo], [0], [$magic
Table: Data List
cont,size,pop,count
-Asia ,44579000,3.7E+009,44.00
-Africa ,30065000,7.8E+008,53.00
-North America ,24256000,4.8E+008,23.00
-South America ,17819000,3.4E+008,12.00
-Antarctica ,13209000,.00,.00
-Europe ,9938000,7.3E+008,46.00
-Australia/Oceania ,7687000,31000000,14.00
+Asia,44579000,3.7E+009,44.00
+Africa,30065000,7.8E+008,53.00
+North America,24256000,4.8E+008,23.00
+South America,17819000,3.4E+008,12.00
+Antarctica,13209000,.00,.00
+Europe,9938000,7.3E+008,46.00
+Australia/Oceania,7687000,31000000,14.00
])
AT_CLEANUP
])
AT_CHECK([pspp -o pspp.csv get.sps])
AT_CHECK([[sed 's/(Entered [^)]*)/(Entered <date>)/' pspp.csv]], [0], [dnl
-File label: clientèle confrère cortège crèche
-
-Documents in the active dataset:
-
-DOCUMENT coördinate smörgåsbord
+Table: File Label
+Label,clientèle confrère cortège crèche
+Table: Documents
+"DOCUMENT coördinate smörgåsbord
épée séance soufflé soirée
-
jalapeño vicuña.
-
-(Entered <date>)
+ (Entered <date>)"
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
croûton,3,,Nominal,Input,32,Left,A1000,A1000,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
àéîöçxyzabc,1.00,éclair élan
-roué,abcdefghi,sauté précis
+Provençal soupçon,abcdefghi,sauté précis
Table: Variable and Dataset Attributes
-Variable,Name,Value
+Variable and Name,,Value
(dataset),Furtwängler,kindergärtner
àéîöçxyzabc,Atatürk,Düsseldorf Gewürztraminer
])
Table: Data List
s
-y @&t@
-z @&t@
+y
+z
])
AT_CLEANUP
7
8
-Table: Open datasets.
-Dataset
+Table: Datasets
clone
initial (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
clone (active dataset)
initial
5
6
-Table: Open datasets.
-Dataset
+Table: Datasets
clone
initial (active dataset)
7,7.00
8,8.00
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
initial
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
])
AT_CLEANUP
LIST.
])
AT_CHECK([pspp -O format=csv dataset.pspp], [1], [dnl
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
second
x
1
-Table: Open datasets.
-Dataset
+Table: Datasets
second (active dataset)
dataset.pspp:10: error: LIST: LIST is allowed only after the active dataset has been defined.
DATASET DISPLAY.
])
AT_CHECK([pspp -O format=csv dataset.pspp], [0], [dnl
-Table: Open datasets.
-Dataset
+Table: Datasets
a (active dataset)
b
c
-Table: Open datasets.
-Dataset
+Table: Datasets
c (active dataset)
])
AT_CLEANUP
DATASET DISPLAY.
])
AT_CHECK([pspp -O format=csv dataset.pspp], [0], [dnl
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
x
-Table: Open datasets.
-Dataset
+Table: Datasets
x (active dataset)
])
AT_CLEANUP
LIST.
])
AT_CHECK([pspp -O format=csv dataset.pspp], [1], [dnl
-Table: Open datasets.
-Dataset
+Table: Datasets
another
one (active dataset)
DATASET DISPLAY.
])
AT_CHECK([pspp -O format=csv dataset.pspp], [0], [dnl
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
this (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
this (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
that
theother
yetanother
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
-Table: Open datasets.
-Dataset
+Table: Datasets
that
theother
this (active dataset)
yetanother
-Table: Open datasets.
-Dataset
+Table: Datasets
unnamed dataset (active dataset)
])
AT_CLEANUP
Table: Data List
bool,bytea,char,int8,int2,int4,numeric,text,oid,float4,float8,money,pbchar,varchar,date,time,timestamp,timestamptz,interval,interval_months,timetz,timetz_zone
-.00,30,a ,.00,.00,.00,-2.560980E+002,this-long-text ,.00,.00,.00,$.01,a ,A ,01-JAN-2000,0:00:00,08-JAN-1999 04:05:06,08-JAN-1999 12:05:06,0 00:01:00,0,10:09:00,4.00
-. ,20,,. ,. ,. ,. ,,. ,. ,. ,. ,,,.,.,.,.,.,.,.,. @&t@
-1.00,31,b ,1.00,1.00,1.00,6.553500E+004,that-long-text ,.00,1.00,1.00,$1.23,b ,B ,10-JAN-1963,1:05:02,10-JAN-1963 23:58:00,10-JAN-1963 22:58:00,12 01:03:04,25,1:05:02,-7.00
+.00,30,a,.00,.00,.00,-2.560980E+002,this-long-text,.00,.00,.00,$.01,a,A,01-JAN-2000,0:00:00,08-JAN-1999 04:05:06,08-JAN-1999 12:05:06,0 00:01:00,0,10:09:00,4.00
+. ,,,. ,. ,. ,. ,,. ,. ,. ,. ,,,.,.,.,.,.,.,.,. @&t@
+1.00,31,b,1.00,1.00,1.00,6.553500E+004,that-long-text,.00,1.00,1.00,$1.23,b,B,10-JAN-1963,1:05:02,10-JAN-1963 23:58:00,10-JAN-1963 22:58:00,12 01:03:04,25,1:05:02,-7.00
])
dnl Test query with empty result set.
Table: Data List
VAR001,VAR002,VAR003
-.00,fred ,20.00
-1.00,11 ,21.00
-2.00,twelve ,22.00
-3.00,13 ,23.00
-4.00,14 ,24.00
+.00,fred,20.00
+1.00,11,21.00
+2.00,twelve,22.00
+3.00,13,23.00
+4.00,14,24.00
])
AT_CLEANUP
Table: Data List
V1,V2,VAR001
-.00,fred ,20.00
-1.00,11 ,21.00
-2.00,twelve ,22.00
-3.00,13 ,23.00
-4.00,14 ,24.00
+.00,fred,20.00
+1.00,11,21.00
+2.00,twelve,22.00
+3.00,13,23.00
+4.00,14,24.00
])
AT_CLEANUP
Table: Data List
name,id,height
-fred ,.00,23.40
-bert ,1.00,.56
-charlie ,2.00,. @&t@
-dick ,3.00,-34.09
+fred,.00,23.40
+bert,1.00,.56
+charlie,2.00,. @&t@
+dick,3.00,-34.09
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv gnum.sps], [0], [dnl
Table: Data List
VAR001,VAR002,VAR003
-3 ,4.00,5.00
-6 ,7.00,8.00
-9 ,10.00,11.00
+3,4.00,5.00
+6,7.00,8.00
+9,10.00,11.00
])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Data List
username,password,uid,gid,gecos,home,shell
-root ,$1$nyeSP5gD$pDq/ ,0,0,",,, ",/root ,/bin/bash @&t@
-blp ,$1$BrP/pFg4$g7OG ,1000,1000,"Ben Pfaff,,, ",/home/blp ,/bin/bash @&t@
-john ,$1$JBuq/Fioq$g4A ,1001,1001,"John Darrington,,, ",/home/john ,/bin/bash @&t@
-jhs ,$1$D3li4hPL$88X1 ,1002,1002,"Jason Stover,,, ",/home/jhs ,/bin/csh @&t@
+root,$1$nyeSP5gD$pDq/,0,0,",,,",/root,/bin/bash
+blp,$1$BrP/pFg4$g7OG,1000,1000,"Ben Pfaff,,,",/home/blp,/bin/bash
+john,$1$JBuq/Fioq$g4A,1001,1001,"John Darrington,,,",/home/john,/bin/bash
+jhs,$1$D3li4hPL$88X1,1002,1002,"Jason Stover,,,",/home/jhs,/bin/csh
])
AT_CLEANUP
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Data List
model,year,mileage,price,type,age
-Civic ,2002,29883,15900,Si ,2
-Civic ,2003,13415,15900,EX ,1
-Civic ,1992,107000,3800,n/a ,12
-Accord ,2002,26613,17900,EX ,1
+Civic,2002,29883,15900,Si,2
+Civic,2003,13415,15900,EX,1
+Civic,1992,107000,3800,n/a,12
+Accord,2002,26613,17900,EX,1
Table: Data List
model,year,mileage,price,type,age
-Civic ,2002,29883,15900,Si ,2
-Civic ,2003,13415,15900,EX ,1
-Civic ,1992,107000,3800,n/a ,12
-Accord ,2002,26613,17900,EX ,1
+Civic,2002,29883,15900,Si,2
+Civic,2003,13415,15900,EX,1
+Civic,1992,107000,3800,n/a,12
+Accord,2002,26613,17900,EX,1
])
AT_CLEANUP
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Data List
name,age,color,received,price,height,type
-Rover ,4.5,Brown,12.02.2004,80.00,"1'4"" ",Dog @&t@
-Charlie ,. ,Gold ,05.04.2007,12.30,"3"" ",Fish @&t@
-Molly ,2.0,Black,12.12.2006,25.00,"5"" ",Cat @&t@
-Gilly ,. ,White,10.04.2007,10.00,"3"" ",Guinea Pig
+Rover,4.5,Brown,12.02.2004,80.00,"1'4""",Dog
+Charlie,. ,Gold,05.04.2007,12.30,"3""",Fish
+Molly,2.0,Black,12.12.2006,25.00,"5""",Cat
+Gilly,. ,White,10.04.2007,10.00,"3""",Guinea Pig
])
AT_CLEANUP
dnl " (fixes Emacs highlighting)
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Data List
s
-é @&t@
+é
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv x.sps], [0], [dnl
Table: Data List
foo,title,last
-1,this ,1
-2,that ,2
-3,other ,3
+1,this,1
+2,that,2
+3,other,3
])
AT_CLEANUP
])
AT_CHECK([pspp -o pspp.csv list.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variable,Value,Label
-s,a,
+Table: Split Values
+Variable,Value
+s,a
Table: Data List
n
2.00
3.00
-Variable,Value,Label
-s,b,
+Table: Split Values
+Variable,Value
+s,b
Table: Data List
n
1.00
-Variable,Value,Label
-s,c,
+Table: Split Values
+Variable,Value
+s,c
Table: Data List
n
AT_CHECK([pspp -o pspp.csv list.sps], [1], [ignore])
AT_CLEANUP
+
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([LIST tutorial example])
+AT_DATA([list.sps], [dnl
+data list list /forename (A12) height.
+begin data.
+Ahmed 188
+Bertram 167
+Catherine 134.231
+David 109.1
+end data
+
+list /format=numbered.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt list.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Reading free-form data from INLINE.
+Variable,Format
+forename,A12
+height,F8.0
+
+Table: Data List
+Case Number,forename,height
+1,Ahmed,188.00
+2,Bertram,167.00
+3,Catherine,134.23
+4,David,109.10
+])
+AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04,var05,var06,var07,var08
-mean ,,24.3000,5.4000,69.7000,20.1000,13.4000,2.7000,27.9000,3.7000
-STDDEV ,,5.7000,1.5000,23.5000,5.8000,2.8000,4.5000,5.4000,1.5000
-n ,,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000
-corr ,var01,1.0000,.1800,-.2200,.3600,.2700,.3300,.5000,.1700
-corr ,var02,.1800,1.0000,-.1700,.3100,.1600,.1500,.2900,.2900
-corr ,var03,-.2200,-.1700,1.0000,-.1400,-.1200,-.1700,-.2000,-.0500
-corr ,var04,.3600,.3100,-.1400,1.0000,.2200,.2400,.3200,.2000
-corr ,var05,.2700,.1600,-.1200,.2200,1.0000,.2100,.1200,.2700
-corr ,var06,.3300,.1500,-.1700,.2400,.2100,1.0000,.3800,.2000
-corr ,var07,.5000,.2900,-.2000,.3200,.1200,.3800,1.0000,.0400
-corr ,var08,.1700,.2900,-.0500,.2000,.2700,.2000,.0400,1.0000
+mean,,24.3000,5.4000,69.7000,20.1000,13.4000,2.7000,27.9000,3.7000
+STDDEV,,5.7000,1.5000,23.5000,5.8000,2.8000,4.5000,5.4000,1.5000
+n,,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000,92.0000
+corr,var01,1.0000,.1800,-.2200,.3600,.2700,.3300,.5000,.1700
+corr,var02,.1800,1.0000,-.1700,.3100,.1600,.1500,.2900,.2900
+corr,var03,-.2200,-.1700,1.0000,-.1400,-.1200,-.1700,-.2000,-.0500
+corr,var04,.3600,.3100,-.1400,1.0000,.2200,.2400,.3200,.2000
+corr,var05,.2700,.1600,-.1200,.2200,1.0000,.2100,.1200,.2700
+corr,var06,.3300,.1500,-.1700,.2400,.2100,1.0000,.3800,.2000
+corr,var07,.5000,.2900,-.2000,.3200,.1200,.3800,1.0000,.0400
+corr,var08,.1700,.2900,-.0500,.2000,.2700,.2000,.0400,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04
-mean ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-N ,,100.0000,101.0000,102.0000,103.0000
-corr ,var01,1.0000,9.0000,8.0000,7.0000
-corr ,var02,9.0000,1.0000,6.0000,5.0000
-corr ,var03,8.0000,6.0000,1.0000,4.0000
-corr ,var04,7.0000,5.0000,4.0000,1.0000
+mean,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+N,,100.0000,101.0000,102.0000,103.0000
+corr,var01,1.0000,9.0000,8.0000,7.0000
+corr,var02,9.0000,1.0000,6.0000,5.0000
+corr,var03,8.0000,6.0000,1.0000,4.0000
+corr,var04,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04
-MEAN ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-N ,,100.0000,101.0000,102.0000,103.0000
-CORR ,var01,1.0000,9.0000,8.0000,7.0000
-CORR ,var02,9.0000,1.0000,6.0000,5.0000
-CORR ,var03,8.0000,6.0000,1.0000,4.0000
-CORR ,var04,7.0000,5.0000,4.0000,1.0000
+MEAN,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+N,,100.0000,101.0000,102.0000,103.0000
+CORR,var01,1.0000,9.0000,8.0000,7.0000
+CORR,var02,9.0000,1.0000,6.0000,5.0000
+CORR,var03,8.0000,6.0000,1.0000,4.0000
+CORR,var04,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04
-mean ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-n ,,100.0000,101.0000,102.0000,103.0000
-corr ,var01,1.0000,9.0000,8.0000,7.0000
-corr ,var02,9.0000,1.0000,6.0000,5.0000
-corr ,var03,8.0000,6.0000,1.0000,4.0000
-corr ,var04,7.0000,5.0000,4.0000,1.0000
+mean,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+n,,100.0000,101.0000,102.0000,103.0000
+corr,var01,1.0000,9.0000,8.0000,7.0000
+corr,var02,9.0000,1.0000,6.0000,5.0000
+corr,var03,8.0000,6.0000,1.0000,4.0000
+corr,var04,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04
-mean ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-n ,,100.0000,101.0000,102.0000,103.0000
-corr ,var01,1.0000,9.0000,8.0000,7.0000
-corr ,var02,9.0000,1.0000,6.0000,5.0000
-corr ,var03,8.0000,6.0000,1.0000,4.0000
-corr ,var04,7.0000,5.0000,4.0000,1.0000
+mean,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+n,,100.0000,101.0000,102.0000,103.0000
+corr,var01,1.0000,9.0000,8.0000,7.0000
+corr,var02,9.0000,1.0000,6.0000,5.0000
+corr,var03,8.0000,6.0000,1.0000,4.0000
+corr,var04,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
Table: Data List
s1,s2,ROWTYPE_,VARNAME_,var01,var02,var03
-8,0,mean ,,21.4000,5.0000,72.9000
-8,0,STDDEV ,,6.5000,1.6000,22.8000
-8,0,n ,,106.0000,106.0000,106.0000
-8,0,corr ,var01,1.0000,.4100,-.1600
-8,0,corr ,var02,.4100,1.0000,-.2200
-8,0,corr ,var03,-.1600,-.2200,1.0000
-8,1,mean ,,11.4000,1.0000,52.9000
-8,1,STDDEV ,,9.5000,8.6000,12.8000
-8,1,n ,,10.0000,11.0000,12.0000
-8,1,corr ,var01,1.0000,.5100,.3600
-8,1,corr ,var02,.5100,1.0000,-.4100
-8,1,corr ,var03,.3600,-.4100,1.0000
+8,0,mean,,21.4000,5.0000,72.9000
+8,0,STDDEV,,6.5000,1.6000,22.8000
+8,0,n,,106.0000,106.0000,106.0000
+8,0,corr,var01,1.0000,.4100,-.1600
+8,0,corr,var02,.4100,1.0000,-.2200
+8,0,corr,var03,-.1600,-.2200,1.0000
+8,1,mean,,11.4000,1.0000,52.9000
+8,1,STDDEV,,9.5000,8.6000,12.8000
+8,1,n,,10.0000,11.0000,12.0000
+8,1,corr,var01,1.0000,.5100,.3600
+8,1,corr,var02,.5100,1.0000,-.4100
+8,1,corr,var03,.3600,-.4100,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-data.pspp], [0], [dnl
Table: Data List
ROWTYPE_,VARNAME_,var01,var_two,variable_number_three,variableFour
-mean ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-N ,,100.0000,101.0000,102.0000,103.0000
-corr ,var01,1.0000,9.0000,8.0000,7.0000
-corr ,var_two,9.0000,1.0000,6.0000,5.0000
-corr ,variable_number_three,8.0000,6.0000,1.0000,4.0000
-corr ,variableFour,7.0000,5.0000,4.0000,1.0000
+mean,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+N,,100.0000,101.0000,102.0000,103.0000
+corr,var01,1.0000,9.0000,8.0000,7.0000
+corr,var_two,9.0000,1.0000,6.0000,5.0000
+corr,variable_number_three,8.0000,6.0000,1.0000,4.0000
+corr,variableFour,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv matrix-reader.pspp], [0], [dnl
Table: Correlation Matrix
,,var02,var04,var06
-Correlations,var02,22.00,24.00,26.00
-,var04,42.00,44.00,46.00
-,var06,62.00,64.00,66.00
+Correlation,var02,22.000,24.000,26.000
+,var04,42.000,44.000,46.000
+,var06,62.000,64.000,66.000
Table: Component Matrix
,Component,
Table: Data List
ROWTYPE_,VARNAME_,var01,var02,var03,var04
-N ,,99.0000,99.0000,99.0000,99.0000
-mean ,,34.0000,35.0000,36.0000,37.0000
-STDDEV ,,22.0000,11.0000,55.0000,66.0000
-corr ,var01,1.0000,9.0000,8.0000,7.0000
-corr ,var02,9.0000,1.0000,6.0000,5.0000
-corr ,var03,8.0000,6.0000,1.0000,4.0000
-corr ,var04,7.0000,5.0000,4.0000,1.0000
+N,,99.0000,99.0000,99.0000,99.0000
+mean,,34.0000,35.0000,36.0000,37.0000
+STDDEV,,22.0000,11.0000,55.0000,66.0000
+corr,var01,1.0000,9.0000,8.0000,7.0000
+corr,var02,9.0000,1.0000,6.0000,5.0000
+corr,var03,8.0000,6.0000,1.0000,4.0000
+corr,var04,7.0000,5.0000,4.0000,1.0000
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv get.pspp], [0], [dnl
Table: Data List
number,time,date,datetime,string,filter
-. ,-0 05:17,10/31/2010,09-APR-2008 09:29:00,xxx ,1
-1.625,0 12:00:00,.,.,xyzzy ,1
+. ,-0 05:17,10/31/2010,09-APR-2008 09:29:00,xxx,1
+1.625,0 12:00:00,.,.,xyzzy,1
])
AT_CLEANUP
]])
AT_CHECK([pspp -O format=csv save-attrs.pspp], [0],
[[Table: Variable and Dataset Attributes
-Variable,Name,Value
+Variable and Name,,Value
(dataset),array[1],array element 1
,array[2],array element 2
,key,value
]])
AT_CHECK([pspp -O format=csv get-attrs.pspp], [0], [dnl
Table: Variable and Dataset Attributes
-Variable,Name,Value
+Variable and Name,,Value
(dataset),array,array element 2
,key,value
b,ValidationRule,a * b > 3
"mrsets.sps:42: warning: MRSETS: Variables specified on MCGROUP should have the same categories, but a and c (and possibly others) in multiple category group $f have different value labels for value b."
])
-m4_define([MRSETS_DISPLAY_OUTPUT],
- [Table: Multiple Response Sets
-Name,Variables,Details
-$a,"w
+m4_define([MRSETS_DISPLAY_OUTPUT], [dnl
+Table: Multiple Response Sets
+Name,Label,Encoding,Counted Value,Member Variables
+$a,First multiple dichotomy group,Dichotomies,5,"w
x
y
-z
-","Multiple dichotomy set
-Label: First multiple dichotomy group
-Label source: Provided by user
-Counted value: 5
-Category label source: Variable labels
-"
-$b,"z
-y
-","Multiple dichotomy set
-Counted value: 123
-Category label source: Value labels of counted value
-"
-$c,"w
+z"
+$b,,Dichotomies,123,"z
+y"
+$c,duplicate variable label,Dichotomies,1,"w
x
y
-z
-","Multiple dichotomy set
-Label: duplicate variable label
-Label source: First variable label among variables
-Counted value: 1
-Category label source: Value labels of counted value
-"
-$d,"a
+z"
+$d,,Dichotomies,c,"a
b
c
-d
-","Multiple dichotomy set
-Counted value: `c'
-Category label source: Variable labels
-"
-$e,"w
+d"
+$e,First multiple category group,Categories,,"w
x
y
-z
-","Multiple category set
-Label: First multiple category group
-"
-$f,"a
+z"
+$f,,Categories,,"a
b
c
-d
-","Multiple category set
-"
+d"
])
AT_SETUP([MRSETS add, display, delete])
/DELETE NAME=ALL
/DISPLAY NAME=ALL.
]])
-AT_CHECK([pspp -O format=csv mrsets.sps], [0],
+AT_CHECK([pspp -o - -O format=csv -o mrsets.csv -o mrsets.txt -o mrsets.pdf mrsets.sps], [0],
[DEFINE_MRSETS_OUTPUT
Table: Multiple Response Sets
-Name,Variables,Details
-$a,"w
+Name,Label,Encoding,Counted Value,Member Variables
+$a,First multiple dichotomy group,Dichotomies,5,"w
x
y
-z
-","Multiple dichotomy set
-Label: First multiple dichotomy group
-Label source: Provided by user
-Counted value: 5
-Category label source: Variable labels
-"
+z"
-MRSETS_DISPLAY_OUTPUT
Table: Multiple Response Sets
-Name,Variables,Details
-$a,"w
+Name,Label,Encoding,Counted Value,Member Variables
+$a,First multiple dichotomy group,Dichotomies,5,"w
+x
+y
+z"
+$b,,Dichotomies,123,"z
+y"
+$c,duplicate variable label,Dichotomies,1,"w
+x
+y
+z"
+$d,,Dichotomies,c,"a
+b
+c
+d"
+$e,First multiple category group,Categories,,"w
x
y
-z
-","Multiple dichotomy set
-Label: First multiple dichotomy group
-Label source: Provided by user
-Counted value: 5
-Category label source: Variable labels
-"
-$b,"z
+z"
+$f,,Categories,,"a
+b
+c
+d"
+
+Table: Multiple Response Sets
+Name,Label,Encoding,Counted Value,Member Variables
+$a,First multiple dichotomy group,Dichotomies,5,"w
+x
y
-","Multiple dichotomy set
-Counted value: 123
-Category label source: Value labels of counted value
-"
-$d,"a
+z"
+$b,,Dichotomies,123,"z
+y"
+$d,,Dichotomies,c,"a
b
c
-d
-","Multiple dichotomy set
-Counted value: `c'
-Category label source: Variable labels
-"
-$e,"w
+d"
+$e,First multiple category group,Categories,,"w
x
y
-z
-","Multiple category set
-Label: First multiple category group
-"
-$f,"a
+z"
+$f,,Categories,,"a
b
c
-d
-","Multiple category set
-"
+d"
mrsets.sps:50: note: MRSETS: The active dataset dictionary does not contain any multiple response sets.
])
])
AT_CHECK([pspp -o pspp.csv split-file.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variable,Value,Label
-X,1,
+Table: Split Values
+Variable,Value
+X,1
Table: Data List
X,Y
1,5
1,4
-Variable,Value,Label
-X,2,
+Table: Split Values
+Variable,Value
+X,2
Table: Data List
X,Y
])
AT_CHECK([pspp -o pspp.csv sysfile-info.sps])
AT_CHECK(
- [sed -e '/^Created:,/d' \
- -e '/^Endian:,/d' \
- -e '/^Integer Format:,/d' \
- -e '/^Real Format:,/d' \
- -e '/^Encoding:,/d' pspp.csv],
+ [sed -e '/^Created,/d' \
+ -e '/^Endian,/d' \
+ -e '/^Integer Format,/d' \
+ -e '/^Real Format,/d' \
+ -e '/^Encoding,/d' pspp.csv],
[0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
name,A10
-File:,pro.sav
-Label:,No label.
-Variables:,2
-Cases:,3
-Type:,SPSS System File
-Weight:,Not weighted.
-Compression:,SAV
+Table: File Information
+File,pro.sav
+Label,
+Variables,2
+Cases,3
+Type,SPSS System File
+Weight,Not weighted
+Compression,SAV
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
DISPLAY FILE LABEL.
])
AT_CHECK([pspp -O format=csv display.sps], [0], [dnl
-The active dataset does not have a file label.
+Table: File Label
+Label,(none)
-File label: foo bar baz quux
+Table: File Label
+Label,foo bar baz quux
])
AT_CLEANUP
dt,2,,Scale,Input,8,Right,DATETIME20.0,DATETIME20.0,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
ad,07/10/1982,label 1
,01/02/1993,label 2
,05/04/2003,label 3
DISPLAY DICTIONARY.
FREQUENCIES x/STAT=NONE.
])
-AT_CHECK([pspp -O format=csv value-labels.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt value-labels.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
x,1,,Scale,Input,8,Right,F8.2,F8.2,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
x,1.00,one
,2.00,first line\nsecond line
,3.00,three
Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-one,1.00,1,33.33,33.33,33.33
-"first line
-second line",2.00,1,33.33,33.33,66.67
-three,3.00,1,33.33,33.33,100.00
-Total,,3,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,one,1,33.3%,33.3%,33.3%
+,"first line
+second line",1,33.3%,33.3%,66.7%
+,three,1,33.3%,33.3%,100.0%
+Total,,3,100.0%,,
])
AT_CLEANUP
DISPLAY DICTIONARY.
FREQUENCIES x/STAT=NONE.
])
-AT_CHECK([pspp -O format=csv get.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt get.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
x,1,,Scale,Input,8,Right,F8.2,F8.2,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
x,1.00,one
,2.00,first line\nsecond line
,3.00,three
Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-one,1.00,1,33.33,33.33,33.33
-"first line
-second line",2.00,1,33.33,33.33,66.67
-three,3.00,1,33.33,33.33,100.00
-Total,,3,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,one,1,33.3%,33.3%,33.3%
+,"first line
+second line",1,33.3%,33.3%,66.7%
+,three,1,33.3%,33.3%,100.0%
+Total,,3,100.0%,,
])
AT_CLEANUP
DESCRIPTIVES ALL.
])
-AT_CHECK([pspp -O format=csv var-labels.sps], [0],[dnl
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+AT_CHECK([pspp -o pspp.csv -o pspp.txt var-labels.sps])
+AT_CHECK([cat pspp.csv], [0],[dnl
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
x,4,2.50,1.29,1.00,4.00
y,4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
x,4,2.50,1.29,1.00,4.00
y,4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
x,4,2.50,1.29,1.00,4.00
y,4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
x,4,2.50,1.29,1.00,4.00
y,4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
foo,4,2.50,1.29,1.00,4.00
bar,4,250.00,129.10,100.00,400.00
-
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
-foo (x),4,2.50,1.29,1.00,4.00
-bar (y),4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
+
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
+x foo,4,2.50,1.29,1.00,4.00
+y bar,4,250.00,129.10,100.00,400.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
])
AT_CLEANUP
])
AT_CHECK([pspp -o pspp.csv vector.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Vector,Position,Variable,Print Format
+Table: Vectors
+Vector and Position,,Variable,Print Format
v,1,v1,F8.2
,2,v2,F8.2
,3,v3,F8.2
])
AT_CHECK([pspp -o pspp.csv vector.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Vector,Position,Variable,Print Format
+Table: Vectors
+Vector and Position,,Variable,Print Format
#vec,1,#vec1,COMMA10.2
,2,#vec2,COMMA10.2
,3,#vec3,COMMA10.2
])
AT_CHECK([pspp -o pspp.csv vector.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Vector,Position,Variable,Print Format
+Table: Vectors
+Vector and Position,,Variable,Print Format
x,1,x1,F8.2
,2,x2,F8.2
,3,x3,F8.2
])
AT_CHECK([pspp -o pspp.csv vector.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Vector,Position,Variable,Print Format
+Table: Vectors
+Vector and Position,,Variable,Print Format
a,1,u,F1.0
,2,w,F1.0
,3,x,F1.0
descriptives AVAR /statistics all /format serial.
frequencies AVAR /statistics all.
])
-AT_CHECK([pspp -o pspp.csv weight.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt weight.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading 1 record from `weight.txt'.
Variable,Record,Columns,Format
AVAR,1,1- 5,F5.0
BVAR,1,6- 10,F5.0
-Table: Valid cases = 730; cases with missing value(s) = 0.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-AVAR,730,0,31.515,.405,10.937,119.608,2.411,.181,1.345,.090,76.000,18.000,94.000,23006.000
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+AVAR,730,31.515,.405,10.937,119.608,2.411,.181,1.345,.090,76.000,18,94,23006.00
+Valid N (listwise),730,,,,,,,,,,,,
+Missing N (listwise),0,,,,,,,,,,,,
-Table: AVAR
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,18,1,.137,.137,.137
-,19,7,.959,.959,1.096
-,20,26,3.562,3.562,4.658
-,21,76,10.411,10.411,15.068
-,22,57,7.808,7.808,22.877
-,23,58,7.945,7.945,30.822
-,24,38,5.205,5.205,36.027
-,25,38,5.205,5.205,41.233
-,26,30,4.110,4.110,45.342
-,27,21,2.877,2.877,48.219
-,28,23,3.151,3.151,51.370
-,29,24,3.288,3.288,54.658
-,30,23,3.151,3.151,57.808
-,31,14,1.918,1.918,59.726
-,32,21,2.877,2.877,62.603
-,33,21,2.877,2.877,65.479
-,34,14,1.918,1.918,67.397
-,35,14,1.918,1.918,69.315
-,36,17,2.329,2.329,71.644
-,37,11,1.507,1.507,73.151
-,38,16,2.192,2.192,75.342
-,39,14,1.918,1.918,77.260
-,40,15,2.055,2.055,79.315
-,41,14,1.918,1.918,81.233
-,42,14,1.918,1.918,83.151
-,43,8,1.096,1.096,84.247
-,44,15,2.055,2.055,86.301
-,45,10,1.370,1.370,87.671
-,46,12,1.644,1.644,89.315
-,47,13,1.781,1.781,91.096
-,48,13,1.781,1.781,92.877
-,49,5,.685,.685,93.562
-,50,5,.685,.685,94.247
-,51,3,.411,.411,94.658
-,52,7,.959,.959,95.616
-,53,6,.822,.822,96.438
-,54,2,.274,.274,96.712
-,55,2,.274,.274,96.986
-,56,2,.274,.274,97.260
-,57,3,.411,.411,97.671
-,58,1,.137,.137,97.808
-,59,3,.411,.411,98.219
-,61,1,.137,.137,98.356
-,62,3,.411,.411,98.767
-,63,1,.137,.137,98.904
-,64,1,.137,.137,99.041
-,65,2,.274,.274,99.315
-,70,1,.137,.137,99.452
-,78,1,.137,.137,99.589
-,79,1,.137,.137,99.726
-,80,1,.137,.137,99.863
-,94,1,.137,.137,100.000
-Total,,730,100.0,100.0,
-
-Table: AVAR
+Table: Statistics
+,,AVAR
N,Valid,730
,Missing,0
Mean,,31.515
S.E. Mean,,.405
-Mode,,21.000
+Median,,28.000
+Mode,,21
Std Dev,,10.937
Variance,,119.608
Kurtosis,,2.411
Skewness,,1.345
S.E. Skew,,.090
Range,,76.000
-Minimum,,18.000
-Maximum,,94.000
-Sum,,23006.000
-Percentiles,50 (Median),28
+Minimum,,18
+Maximum,,94
+Sum,,23006.00
+
+Table: AVAR
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,18,1,.1%,.1%,.1%
+,19,7,1.0%,1.0%,1.1%
+,20,26,3.6%,3.6%,4.7%
+,21,76,10.4%,10.4%,15.1%
+,22,57,7.8%,7.8%,22.9%
+,23,58,7.9%,7.9%,30.8%
+,24,38,5.2%,5.2%,36.0%
+,25,38,5.2%,5.2%,41.2%
+,26,30,4.1%,4.1%,45.3%
+,27,21,2.9%,2.9%,48.2%
+,28,23,3.2%,3.2%,51.4%
+,29,24,3.3%,3.3%,54.7%
+,30,23,3.2%,3.2%,57.8%
+,31,14,1.9%,1.9%,59.7%
+,32,21,2.9%,2.9%,62.6%
+,33,21,2.9%,2.9%,65.5%
+,34,14,1.9%,1.9%,67.4%
+,35,14,1.9%,1.9%,69.3%
+,36,17,2.3%,2.3%,71.6%
+,37,11,1.5%,1.5%,73.2%
+,38,16,2.2%,2.2%,75.3%
+,39,14,1.9%,1.9%,77.3%
+,40,15,2.1%,2.1%,79.3%
+,41,14,1.9%,1.9%,81.2%
+,42,14,1.9%,1.9%,83.2%
+,43,8,1.1%,1.1%,84.2%
+,44,15,2.1%,2.1%,86.3%
+,45,10,1.4%,1.4%,87.7%
+,46,12,1.6%,1.6%,89.3%
+,47,13,1.8%,1.8%,91.1%
+,48,13,1.8%,1.8%,92.9%
+,49,5,.7%,.7%,93.6%
+,50,5,.7%,.7%,94.2%
+,51,3,.4%,.4%,94.7%
+,52,7,1.0%,1.0%,95.6%
+,53,6,.8%,.8%,96.4%
+,54,2,.3%,.3%,96.7%
+,55,2,.3%,.3%,97.0%
+,56,2,.3%,.3%,97.3%
+,57,3,.4%,.4%,97.7%
+,58,1,.1%,.1%,97.8%
+,59,3,.4%,.4%,98.2%
+,61,1,.1%,.1%,98.4%
+,62,3,.4%,.4%,98.8%
+,63,1,.1%,.1%,98.9%
+,64,1,.1%,.1%,99.0%
+,65,2,.3%,.3%,99.3%
+,70,1,.1%,.1%,99.5%
+,78,1,.1%,.1%,99.6%
+,79,1,.1%,.1%,99.7%
+,80,1,.1%,.1%,99.9%
+,94,1,.1%,.1%,100.0%
+Total,,730,100.0%,,
])
AT_CLEANUP
n,s,nlabel,slabel
.,,,
0,a,Very dissa,Wouldn't b
-1,b,Dissatisfi,Unhappy @&t@
-2,c,Neutral ,Bored @&t@
-3,d,Satisfied ,Satiated @&t@
-4,e,Very satis,Elated @&t@
+1,b,Dissatisfi,Unhappy
+2,c,Neutral,Bored
+3,d,Satisfied,Satiated
+4,e,Very satis,Elated
5,f,,
6,g,,
])
AlphaBetaGamma,B,X,Yabbadabbadoo
2.00,3.00,4.00,5.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X * Yabbadabbadoo,1,100.0%,0,0.0%,1,100.0%
+X × Yabbadabbadoo,1,100.0%,0,.0%,1,100.0%
-Table: X * Yabbadabbadoo [[count]].
-,Yabbadabbadoo,,,,,,,
-X,1.00,2.00,3.00,4.00,5.00,6.00,7.00,Total
-1.00,.00,.00,.00,.00,.00,.00,.00,.00
-2.00,.00,.00,.00,.00,.00,.00,.00,.00
-3.00,.00,.00,.00,.00,.00,.00,.00,.00
-4.00,.00,.00,.00,.00,1.00,.00,.00,1.00
-5.00,.00,.00,.00,.00,.00,.00,.00,.00
-6.00,.00,.00,.00,.00,.00,.00,.00,.00
-7.00,.00,.00,.00,.00,.00,.00,.00,.00
-Total,.00,.00,.00,.00,1.00,.00,.00,1.00
+Table: X × Yabbadabbadoo
+,,,Yabbadabbadoo,,,,,,,Total
+,,,1.00,2.00,3.00,4.00,5.00,6.00,7.00,
+X,1.00,Count,0,0,0,0,0,0,0,0
+,2.00,,0,0,0,0,0,0,0,0
+,3.00,,0,0,0,0,0,0,0,0
+,4.00,,0,0,0,0,1,0,0,1
+,5.00,,0,0,0,0,0,0,0,0
+,6.00,,0,0,0,0,0,0,0,0
+,7.00,,0,0,0,0,0,0,0,0
+Total,,,0,0,0,0,1,0,0,1
])
AT_CLEANUP
Table: Data List
X,Y
-87.34,bar @&t@
-87.50,foo @&t@
+87.34,bar
+87.50,foo
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv ar.sps], [0],
[Table: Data List
s,x,new
-widgets ,1.00,4.00
-thingummies ,2.00,3.00
-oojars ,3.00,1.00
-widgets ,4.00,4.00
-oojars ,5.00,1.00
-thingummies ,6.00,3.00
-oojimiflips ,7.00,2.00
+widgets,1.00,4.00
+thingummies,2.00,3.00
+oojars,3.00,1.00
+widgets,4.00,4.00
+oojars,5.00,1.00
+thingummies,6.00,3.00
+oojimiflips,7.00,2.00
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
new,3,,Scale,Input,8,Right,F8.2,F8.2,
Table: Value Labels
-Variable,Value,Label
+Variable Value,,Label
new,1.00,oojars
,2.00,oojimiflips
,3.00,thingummies
[dnl
Table: Data List
a,b,x,y
-one ,nine ,5.00,3.00
-two ,ten ,8.00,6.00
-three ,eleven,7.00,1.00
-four ,nought,2.00,4.00
+one,nine,5.00,3.00
+two,ten,8.00,6.00
+three,eleven,7.00,1.00
+four,nought,2.00,4.00
])
AT_CLEANUP
/missing = pairwise
.
])
-AT_CHECK([pspp -o pspp.csv correlations.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
-Table: Correlations
+AT_CHECK([pspp -o pspp.csv -o pspp.txt correlations.sps])
+AT_CHECK([cat pspp.csv], [0],
+[[Table: Correlations
,,foo,bar,wiz,bang
-foo,Pearson Correlation,1.000,.802,.890,-.308
+foo,Pearson Correlation,1.000,.802,.890[a],-.308
,Sig. (2-tailed),,.055,.017,.553
bar,Pearson Correlation,.802,1.000,.519,.118
,Sig. (2-tailed),.055,,.291,.824
-wiz,Pearson Correlation,.890,.519,1.000,-.344
+wiz,Pearson Correlation,.890[a],.519,1.000,-.344
,Sig. (2-tailed),.017,.291,,.505
bang,Pearson Correlation,-.308,.118,-.344,1.000
,Sig. (2-tailed),.553,.824,.505,
+Footnotes:
+a,Significant at .05 level
+
Table: Correlations
,,bar,wiz
bar,Pearson Correlation,1.000,.497
Table: Correlations
,,foo,bar,wiz,bang
-foo,Pearson Correlation,1.000,.805,.883,-.308
+foo,Pearson Correlation,1.000,.805[a],.883[a],-.308
,Sig. (2-tailed),,.029,.008,.553
,N,7,7,7,6
-bar,Pearson Correlation,.805,1.000,.497,.164
+bar,Pearson Correlation,.805[a],1.000,.497,.164
,Sig. (2-tailed),.029,,.210,.725
,N,7,8,8,7
-wiz,Pearson Correlation,.883,.497,1.000,-.337
+wiz,Pearson Correlation,.883[a],.497,1.000,-.337
,Sig. (2-tailed),.008,.210,,.460
,N,7,8,8,7
bang,Pearson Correlation,-.308,.164,-.337,1.000
,Sig. (2-tailed),.553,.725,.460,
,N,6,7,7,7
-])
+
+Footnotes:
+a,Significant at .05 level
+]])
AT_CLEANUP
AT_SETUP([CORRELATIONS -- weighted])
AT_CHECK([sed '/a,Pearson/,$s/,\([[^,]]*\),.*/,\1,.../' pspp.csv], [0], [dnl
Table: Descriptive Statistics
,Mean,Std. Deviation,N
-a,24.00,8.93,14.00
-f,4.73,.85,12.00
-b,14.50,6.41,14.00
-c,21.71,4.98,14.00
-g,24.86,6.09,14.00
-h,23.57,6.30,14.00
-i,27.79,6.73,14.00
-e,27.21,4.95,14.00
-d,27.93,5.23,14.00
+a,24.00,8.93,14
+f,4.73,.85,12
+b,14.50,6.41,14
+c,21.71,4.98,14
+g,24.86,6.09,14
+h,23.57,6.30,14
+i,27.79,6.73,14
+e,27.21,4.95,14
+d,27.93,5.23,14
Table: Correlations
,,c,g,h,i,e,d
AT_SETUP([CORRELATIONS -- incorrect subtable selection])
AT_DATA([correlations.sps], [dnl
set format = F12.4.
+OUTPUT MODIFY /SELECT TABLES /TABLECELLS SELECT = [[CORRELATIONS]] FORMAT=F12.4.
set decimal = dot.
data list notable list /var1 var2 var3 var4 var5 *.
begin data.
])
-AT_CHECK([pspp -O format=csv correlations.sps], [0],
-[Table: Correlations
+AT_CHECK([pspp -o pspp.csv -o pspp.txt correlations.sps])
+AT_CHECK([cat pspp.csv], [0],
+[[Table: Correlations
,,var4,var5
-var1,Pearson Correlation,.5693,-.0519
+var1,Pearson Correlation,.5693[a],-.0519
,Sig. (2-tailed),.000,.623
,N,93,92
-var2,Pearson Correlation,.3792,-.0407
+var2,Pearson Correlation,.3792[a],-.0407
,Sig. (2-tailed),.000,.698
,N,95,93
-var3,Pearson Correlation,.3699,-.0543
+var3,Pearson Correlation,.3699[a],-.0543
,Sig. (2-tailed),.000,.603
,N,95,94
+Footnotes:
+a,Significant at .05 level
+
Table: Correlations
,,var1,var2
-var3,Pearson Correlation,.6964,.5615
+var3,Pearson Correlation,.6964[a],.5615[a]
,Sig. (2-tailed),.000,.000
,N,96,97
-var4,Pearson Correlation,.5693,.3792
+var4,Pearson Correlation,.5693[a],.3792[a]
,Sig. (2-tailed),.000,.000
,N,93,95
var5,Pearson Correlation,-.0519,-.0407
,Sig. (2-tailed),.623,.698
,N,92,93
-])
+
+Footnotes:
+a,Significant at .05 level
+]])
AT_CLEANUP
CROSSTABS VARIABLES X (1,7) Y (1,7) /TABLES X BY Y.
])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0],
+AT_CHECK([pspp -o pspp.csv -o pspp.txt crosstabs.sps])
+AT_CHECK([cat pspp.csv], [0],
[[Table: Reading free-form data from INLINE.
Variable,Format
A,F8.0
X,F8.0
Y,F8.0
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X * Y,1,100.0%,0,0.0%,1,100.0%
-
-Table: X * Y [count].
-,Y,,,,,,,
-X,1.00,2.00,3.00,4.00,5.00,6.00,7.00,Total
-1.00,.00,.00,.00,.00,.00,.00,.00,.00
-2.00,.00,.00,.00,.00,.00,.00,.00,.00
-3.00,.00,.00,.00,.00,.00,.00,.00,.00
-4.00,.00,.00,.00,.00,1.00,.00,.00,1.00
-5.00,.00,.00,.00,.00,.00,.00,.00,.00
-6.00,.00,.00,.00,.00,.00,.00,.00,.00
-7.00,.00,.00,.00,.00,.00,.00,.00,.00
-Total,.00,.00,.00,.00,1.00,.00,.00,1.00
+X × Y,1,100.0%,0,.0%,1,100.0%
+
+Table: X × Y
+,,,Y,,,,,,,Total
+,,,1.00,2.00,3.00,4.00,5.00,6.00,7.00,
+X,1.00,Count,0,0,0,0,0,0,0,0
+,2.00,,0,0,0,0,0,0,0,0
+,3.00,,0,0,0,0,0,0,0,0
+,4.00,,0,0,0,0,1,0,0,1
+,5.00,,0,0,0,0,0,0,0,0
+,6.00,,0,0,0,0,0,0,0,0
+,7.00,,0,0,0,0,0,0,0,0
+Total,,,0,0,0,0,1,0,0,1
]])
AT_CLEANUP
x,F8.0
y,F8.0
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,0,0.0%,1,100.0%,1,100.0%
+x × y,0,.0%,1,100.0%,1,100.0%
+
+Table: x × y
+,,
+,,
]])
AT_CLEANUP
CROSSTABS /TABLES = x BY y.
])
-AT_CHECK([pspp -o - -O format=csv crosstabs.sps], [0],
+AT_CHECK([pspp -o - -O format=csv -o pspp.txt crosstabs.sps], [0],
[[Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
"crosstabs.sps:6: warning: Missing value(s) for all variables from x onward. These will be filled with the system-missing value or blanks, as appropriate."
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,4,66.7%,2,33.3%,6,100.0%
-
-Table: x * y [count].
-,y,,,,
-x,one unity ,three lots ,two duality ,zero none ,Total
-1.00,1.00,.00,.00,1.00,2.00
-2.00,.00,.00,1.00,.00,1.00
-3.00,.00,1.00,.00,.00,1.00
-Total,1.00,1.00,1.00,1.00,4.00
+x × y,4,66.7%,2,33.3%,6,100.0%
+
+Table: x × y
+,,,y,,,,Total
+,,,one unity,three lots,two duality,zero none,
+x,1.00,Count,1,0,0,1,2
+,2.00,,0,0,1,0,1
+,3.00,,0,1,0,0,1
+Total,,,1,1,1,1,4
]])
AT_CLEANUP
CROSSTABS TABLES y by z.
]])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0],
- [[Table: Reading 1 record from INLINE.
+AT_CHECK([pspp -o - -O format=csv -o pspp.txt crosstabs.sps], [0],
+ [Table: Reading 1 record from INLINE.
Variable,Record,Columns,Format
x,1,1- 2,F2.0
y,1,3- 3,F1.0
8,1,1
9,1,2
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-y * z,9,100.0%,0,0.0%,9,100.0%
-
-Table: y * z [count].
-,z,,
-y,1,2,Total
-1,4.00,3.00,7.00
-2,1.00,1.00,2.00
-Total,5.00,4.00,9.00
-]])
+y × z,9,100.0%,0,.0%,9,100.0%
+
+Table: y × z
+,,,z,,Total
+,,,1,2,
+y,1,Count,4,3,7
+,2,,1,1,2
+Total,,,5,4,9
+])
AT_CLEANUP
# Bug #26739, which caused CROSSTABS to crash or to fail to output
x,F8.0
y,F8.0
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,4,100.0%,0,0.0%,4,100.0%
-
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-2.00,.00,1.00,1.00
-3.00,1.00,.00,1.00
-4.00,1.00,1.00,2.00
-Total,2.00,2.00,4.00
-
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed)
+x × y,4,100.0%,0,.0%,4,100.0%
+
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,2.00,Count,0,1,1
+,3.00,,1,0,1
+,4.00,,1,1,2
+Total,,,2,2,4
+
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed)
Pearson Chi-Square,2.00,2,.368
Likelihood Ratio,2.77,2,.250
Linear-by-Linear Association,.27,1,.602
/CELLS=COUNT ROW COLUMN TOTAL.
])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0],
- [[Variable,Value,Label
-v0,a ,
+AT_CHECK([pspp -o pspp.csv -o pspp.txt crosstabs.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Split Values
+Variable,Value
+v0,a
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-v1 * v2,6,100.0%,0,0.0%,6,100.0%
-
-"Table: v1 * v2 [count, row %, column %, total %]."
-,v2,,
-v1,e ,f ,Total
-c ,3.00,1.00,4.00
-,75.00%,25.00%,100.00%
-,75.00%,50.00%,66.67%
-,50.00%,16.67%,66.67%
-d ,1.00,1.00,2.00
-,50.00%,50.00%,100.00%
-,25.00%,50.00%,33.33%
-,16.67%,16.67%,33.33%
-Total,4.00,2.00,6.00
-,66.67%,33.33%,100.00%
-,100.00%,100.00%,100.00%
-,66.67%,33.33%,100.00%
-
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
+v1 × v2,6,100.0%,0,.0%,6,100.0%
+
+Table: v1 × v2
+,,,v2,,Total
+,,,e,f,
+v1,c,Count,3,1,4
+,,Row %,75.0%,25.0%,100.0%
+,,Column %,75.0%,50.0%,66.7%
+,,Total %,50.0%,16.7%,66.7%
+,d,Count,1,1,2
+,,Row %,50.0%,50.0%,100.0%
+,,Column %,25.0%,50.0%,33.3%
+,,Total %,16.7%,16.7%,33.3%
+Total,,Count,4,2,6
+,,Row %,66.7%,33.3%,100.0%
+,,Column %,100.0%,100.0%,100.0%
+,,Total %,66.7%,33.3%,100.0%
+
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
Pearson Chi-Square,.38,1,.540,,
Likelihood Ratio,.37,1,.545,,
Fisher's Exact Test,,,,1.000,.600
Continuity Correction,.00,1,1.000,,
N of Valid Cases,6,,,,
-Variable,Value,Label
-v0,b ,
+Table: Split Values
+Variable,Value
+v0,b
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-v1 * v2,4,100.0%,0,0.0%,4,100.0%
-
-"Table: v1 * v2 [count, row %, column %, total %]."
-,v2,,
-v1,e ,f ,Total
-c ,.00,1.00,1.00
-,.00%,100.00%,100.00%
-,.00%,33.33%,25.00%
-,.00%,25.00%,25.00%
-d ,1.00,2.00,3.00
-,33.33%,66.67%,100.00%
-,100.00%,66.67%,75.00%
-,25.00%,50.00%,75.00%
-Total,1.00,3.00,4.00
-,25.00%,75.00%,100.00%
-,100.00%,100.00%,100.00%
-,25.00%,75.00%,100.00%
-
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
+v1 × v2,4,100.0%,0,.0%,4,100.0%
+
+Table: v1 × v2
+,,,v2,,Total
+,,,e,f,
+v1,c,Count,0,1,1
+,,Row %,.0%,100.0%,100.0%
+,,Column %,.0%,33.3%,25.0%
+,,Total %,.0%,25.0%,25.0%
+,d,Count,1,2,3
+,,Row %,33.3%,66.7%,100.0%
+,,Column %,100.0%,66.7%,75.0%
+,,Total %,25.0%,50.0%,75.0%
+Total,,Count,1,3,4
+,,Row %,25.0%,75.0%,100.0%
+,,Column %,100.0%,100.0%,100.0%
+,,Total %,25.0%,75.0%,100.0%
+
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
Pearson Chi-Square,.44,1,.505,,
Likelihood Ratio,.68,1,.410,,
Fisher's Exact Test,,,,1.000,.750
Continuity Correction,.00,1,1.000,,
N of Valid Cases,4,,,,
-]])
+])
AT_CLEANUP
# Bug #24752.
CROSSTABS TABLES x BY y BY z/STATISTICS=ALL.
]])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0],
- [[Table: Reading 1 record from INLINE.
+AT_CHECK([pspp -o - -O format=csv -o pspp.csv -o pspp.txt crosstabs.sps], [0],
+ [Table: Reading 1 record from INLINE.
Variable,Record,Columns,Format
x,1,1- 2,F2.0
y,1,3- 3,F1.0
8,1,1
9,1,2
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y * z,9,100.0%,0,0.0%,9,100.0%
-
-Table: x * y * z [count].
-z,,y,,
-,x,1,2,Total
-1,1,1.00,.00,1.00
-,3,1.00,.00,1.00
-,5,.00,1.00,1.00
-,7,1.00,.00,1.00
-,8,1.00,.00,1.00
-Total,,4.00,1.00,5.00
-2,2,.00,1.00,1.00
-,4,1.00,.00,1.00
-,6,1.00,.00,1.00
-,9,1.00,.00,1.00
-Total,,3.00,1.00,4.00
-
-Table: Chi-square tests.
-z,Statistic,Value,df,Asymp. Sig. (2-tailed)
-1,Pearson Chi-Square,5.00,4,.287
-,Likelihood Ratio,5.00,4,.287
-,Linear-by-Linear Association,.01,1,.938
-,N of Valid Cases,5,,
-2,Pearson Chi-Square,4.00,3,.261
-,Likelihood Ratio,4.50,3,.212
-,Linear-by-Linear Association,1.58,1,.209
-,N of Valid Cases,4,,
-
-Table: Symmetric measures.
-z,Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-1,Nominal by Nominal,Phi,1.00,,,
-,,Cramer's V,1.00,,,
-,,Contingency Coefficient,.71,,,
-,Ordinal by Ordinal,Kendall's tau-b,.00,.32,.00,
-,,Kendall's tau-c,.00,.32,.00,
-,,Gamma,.00,.50,.00,
-,,Spearman Correlation,.00,.22,.00,
-,Interval by Interval,Pearson's R,.04,.22,.07,
-,N of Valid Cases,,5,,,
-2,Nominal by Nominal,Phi,1.00,,,
-,,Cramer's V,1.00,,,
-,,Contingency Coefficient,.71,,,
-,Ordinal by Ordinal,Kendall's tau-b,-.71,.20,-1.73,
-,,Kendall's tau-c,-.75,.43,-1.73,
-,,Gamma,-1.00,.00,-1.73,
-,,Spearman Correlation,-.77,.17,-1.73,
-,Interval by Interval,Pearson's R,-.73,.18,-1.49,
-,N of Valid Cases,,4,,,
-
-Table: Directional measures.
-z,Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-1,Nominal by Nominal,Lambda,Symmetric,.40,.28,1.12,.264
-,,,x Dependent,.25,.22,1.12,.264
-,,,y Dependent,1.00,.00,1.12,.264
-,,Goodman and Kruskal tau,x Dependent,.25,,,. @&t@
-,,,y Dependent,1.00,,,. @&t@
-,,Uncertainty Coefficient,Symmetric,.47,.18,,. @&t@
-,,,x Dependent,.31,.15,2.02,. @&t@
-,,,y Dependent,1.00,.00,2.02,. @&t@
-,Ordinal by Ordinal,Somers' d,Symmetric,.00,,.00,1.000
-,,,x Dependent,.00,.50,.00,1.000
-,,,y Dependent,.00,.20,.00,1.000
-,Nominal by Interval,Eta,x Dependent,.04,,,. @&t@
-,,,y Dependent,1.00,,,. @&t@
-2,Nominal by Nominal,Lambda,Symmetric,.50,.25,2.00,.046
-,,,x Dependent,.33,.27,1.15,.248
-,,,y Dependent,1.00,.00,1.15,.248
-,,Goodman and Kruskal tau,x Dependent,.33,,,. @&t@
-,,,y Dependent,1.00,,,. @&t@
-,,Uncertainty Coefficient,Symmetric,.58,.17,,. @&t@
-,,,x Dependent,.41,.17,2.36,. @&t@
-,,,y Dependent,1.00,.00,2.36,. @&t@
-,Ordinal by Ordinal,Somers' d,Symmetric,-.67,,-1.73,.083
-,,,x Dependent,-1.00,.00,-1.73,.083
-,,,y Dependent,-.50,.29,-1.73,.083
-,Nominal by Interval,Eta,x Dependent,.73,,,. @&t@
-,,,y Dependent,1.00,,,. @&t@
-]])
+x × y × z,9,100.0%,0,.0%,9,100.0%
+
+Table: x × y × z
+,,,,,y,,Total
+,,,,,1,2,
+z,1,x,1,Count,1,0,1
+,,,3,,0,0,1
+,,,5,,1,0,1
+,,,7,,0,0,1
+,,,8,,0,1,1
+,,Total,,,4,1,5
+,2,x,2,,0,0,1
+,,,4,,0,1,1
+,,,6,,0,0,1
+,,,9,,1,0,1
+,,Total,,,3,1,4
+
+Table: Chi-Square Tests
+,,,Value,df,Asymptotic Sig. (2-tailed)
+z,1,Pearson Chi-Square,5.00,4,.287
+,,Likelihood Ratio,5.00,4,.287
+,,Linear-by-Linear Association,.01,1,.938
+,,N of Valid Cases,5,,
+,2,Pearson Chi-Square,4.00,3,.261
+,,Likelihood Ratio,4.50,3,.212
+,,Linear-by-Linear Association,1.58,1,.209
+,,N of Valid Cases,4,,
+
+Table: Symmetric Measures
+,,,,Value,Asymp. Std. Error,Approx. T
+z,1,Nominal by Nominal,Phi,1.00,,
+,,,Cramer's V,1.00,,
+,,,Contingency Coefficient,.71,,
+,,Ordinal by Ordinal,Kendall's tau-b,.00,.32,.00
+,,,Kendall's tau-c,.00,.32,.00
+,,,Gamma,.00,.50,.00
+,,,Spearman Correlation,.00,.22,.00
+,,Interval by Interval,Pearson's R,.04,.22,.07
+,,N of Valid Cases,,5,,
+,2,Nominal by Nominal,Phi,1.00,,
+,,,Cramer's V,1.00,,
+,,,Contingency Coefficient,.71,,
+,,Ordinal by Ordinal,Kendall's tau-b,-.71,.20,-1.73
+,,,Kendall's tau-c,-.75,.43,-1.73
+,,,Gamma,-1.00,.00,-1.73
+,,,Spearman Correlation,-.77,.17,-1.73
+,,Interval by Interval,Pearson's R,-.73,.18,-1.49
+,,N of Valid Cases,,4,,
+
+Table: Directional Measures
+,,,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
+z,1,Nominal by Nominal,Lambda,Symmetric,.40,.28,1.12,.264
+,,,,x Dependent,.25,.22,1.12,.264
+,,,,y Dependent,1.00,.00,1.12,.264
+,,,Goodman and Kruskal tau,x Dependent,.25,,,
+,,,,y Dependent,1.00,,,
+,,,Uncertainty Coefficient,Symmetric,.47,.18,,
+,,,,x Dependent,.31,.15,2.02,
+,,,,y Dependent,1.00,.00,2.02,
+,,Ordinal by Ordinal,Somers' d,Symmetric,.00,,.00,1.000
+,,,,x Dependent,.00,.50,.00,1.000
+,,,,y Dependent,.00,.20,.00,1.000
+,,Nominal by Interval,Eta,x Dependent,.04,,,
+,,,,y Dependent,1.00,,,
+,2,Nominal by Nominal,Lambda,Symmetric,.50,.25,2.00,.046
+,,,,x Dependent,.33,.27,1.15,.248
+,,,,y Dependent,1.00,.00,1.15,.248
+,,,Goodman and Kruskal tau,x Dependent,.33,,,
+,,,,y Dependent,1.00,,,
+,,,Uncertainty Coefficient,Symmetric,.58,.17,,
+,,,,x Dependent,.41,.17,2.36,
+,,,,y Dependent,1.00,.00,2.36,
+,,Ordinal by Ordinal,Somers' d,Symmetric,-.67,,-1.73,.083
+,,,,x Dependent,-1.00,.00,-1.73,.083
+,,,,y Dependent,-.50,.29,-1.73,.083
+,,Nominal by Interval,Eta,x Dependent,.73,,,
+,,,,y Dependent,1.00,,,
+])
AT_CLEANUP
AT_SETUP([CROSSTABS rounding weights with COUNT])
CROSSTABS /TABLES x BY y /COUNT TRUNCATE.
]])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0],
- [[Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt crosstabs.sps])
+AT_CHECK([cat pspp.csv], [0],
+ [Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,9.00,100.0%,.00,0.0%,9.00,100.0%
+x × y,9.00,100.0%,.00,.0%,9.00,100.0%
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,2.80,3.20,6.00
-2.00,1.00,2.00,3.00
-Total,3.80,5.20,9.00
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,2.80,3.20,6.00
+,2.00,,1.00,2.00,3.00
+Total,,,3.80,5.20,9.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,9.00,100.0%,.00,0.0%,9.00,100.0%
+x × y,9.00,100.0%,.00,.0%,9.00,100.0%
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,2.80,3.20,6.00
-2.00,1.00,2.00,3.00
-Total,3.80,5.20,9.00
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,2.80,3.20,6.00
+,2.00,,1.00,2.00,3.00
+Total,,,3.80,5.20,9.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,9.00,100.0%,.00,0.0%,9.00,100.0%
+x × y,9.00,100.0%,.00,.0%,9.00,100.0%
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,2.00,4.00,6.00
-2.00,1.00,2.00,3.00
-Total,3.00,6.00,9.00
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,2.00,4.00,6.00
+,2.00,,1.00,2.00,3.00
+Total,,,3.00,6.00,9.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,7.00,100.0%,.00,0.0%,7.00,100.0%
+x × y,7.00,100.0%,.00,.0%,7.00,100.0%
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,2.00,2.00,4.00
-2.00,1.00,2.00,3.00
-Total,3.00,4.00,7.00
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,2.00,2.00,4.00
+,2.00,,1.00,2.00,3.00
+Total,,,3.00,4.00,7.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,9.00,100.0%,.00,0.0%,9.00,100.0%
+x × y,9.00,100.0%,.00,.0%,9.00,100.0%
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,3.00,3.00,6.00
-2.00,1.00,2.00,3.00
-Total,4.00,5.00,9.00
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,3.00,3.00,6.00
+,2.00,,1.00,2.00,3.00
+Total,,,4.00,5.00,9.00
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,8.00,100.0%,.00,0.0%,8.00,100.0%
-
-Table: x * y [count].
-,y,,
-x,1.00,2.00,Total
-1.00,2.00,3.00,5.00
-2.00,1.00,2.00,3.00
-Total,3.00,5.00,8.00
-]])
+x × y,8.00,100.0%,.00,.0%,8.00,100.0%
+
+Table: x × y
+,,,y,,Total
+,,,1.00,2.00,
+x,1.00,Count,2.00,3.00,5.00
+,2.00,,1.00,2.00,3.00
+Total,,,3.00,5.00,8.00
+])
AT_CLEANUP
AT_SETUP([CROSSTABS descending sort order])
/FORMAT = DVALUE.
]])
-AT_CHECK([pspp -O format=csv crosstabs-descending.sps], [0],
- [[Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt crosstabs-descending.sps])
+AT_CHECK([cat pspp.csv], [0],
+ [Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,6,100.0%,0,0.0%,6,100.0%
-
-Table: x * y [count].
-,y,,
-x,2.00,1.00,Total
-4.00,.00,1.00,1.00
-3.00,2.00,1.00,3.00
-2.00,2.00,.00,2.00
-Total,4.00,2.00,6.00
-]])
+x × y,6,100.0%,0,.0%,6,100.0%
+
+Table: x × y
+,,,y,,Total
+,,,2.00,1.00,
+x,4.00,Count,0,1,1
+,3.00,,2,1,3
+,2.00,,2,0,2
+Total,,,4,2,6
+])
AT_CLEANUP
# Bug #31260.
CROSSTABS /TABLES= X1 by X2.
])
AT_CHECK([pspp -O format=csv crosstabs.sps], [0], [dnl
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X1 * X2,0,0.0%,1,100.0%,1,100.0%
+X1 × X2,0,.0%,1,100.0%,1,100.0%
-crosstabs.sps:8: warning: CROSSTABS: Crosstabulation X1 * X2 contained no non-missing cases.
+crosstabs.sps:8: warning: CROSSTABS: Crosstabulation X1 × X2 contained no non-missing cases.
])
AT_CLEANUP
crosstabs /tables = female by ses /statistic = chisq.
])
-AT_CHECK([pspp -O format=csv fisher-exact.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt fisher-exact.sps])
+AT_CHECK([cat pspp.csv], [0], [Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-type of school * female,200,100.0%,0,0.0%,200,100.0%
+type of school × female,200,100.0%,0,.0%,200,100.0%
-Table: type of school * female [[count]].
-,female,,
-type of school,male,female,Total
-public,77.000,91.000,168.000
-private,14.000,18.000,32.000
-Total,91.000,109.000,200.000
+Table: type of school × female
+,,,female,,Total
+,,,male,female,
+type of school,public,Count,77,91,168
+,private,,14,18,32
+Total,,,91,109,200
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
Pearson Chi-Square,.047,1,.828,,
Likelihood Ratio,.047,1,.828,,
Fisher's Exact Test,,,,.849,.492
Linear-by-Linear Association,.047,1,.829,,
N of Valid Cases,200,,,,
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-female * ses,200,100.0%,0,0.0%,200,100.0%
+female × ses,200,100.0%,0,.0%,200,100.0%
-Table: female * ses [[count]].
-,ses,,,
-female,low,middle,high,Total
-male,15.000,47.000,29.000,91.000
-female,32.000,48.000,29.000,109.000
-Total,47.000,95.000,58.000,200.000
+Table: female × ses
+,,,ses,,,Total
+,,,low,middle,high,
+female,male,Count,15,47,29,91
+,female,,32,48,29,109
+Total,,,47,95,58,200
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed)
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed)
Pearson Chi-Square,4.577,2,.101
Likelihood Ratio,4.679,2,.096
Linear-by-Linear Association,3.110,1,.078
AT_CLEANUP
-AT_SETUP([CROSSTABS Pearson's R])
-# Test 1.
+AT_SETUP([CROSSTABS Pearson's R - 1])
AT_DATA([pearson.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=CORR.
])
-AT_CHECK([pspp -O format=csv pearson.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt pearson.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,5,100.0%,0,0.0%,5,100.0%
-
-Table: x * y [[count]].
-,y,,,,,
-x,4.000,6.000,10.000,12.000,13.000,Total
-1.000,1.000,.000,.000,.000,.000,1.000
-3.000,.000,1.000,.000,.000,.000,1.000
-5.000,.000,.000,1.000,1.000,.000,2.000
-6.000,.000,.000,.000,.000,1.000,1.000
-Total,1.000,1.000,1.000,1.000,1.000,5.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Spearman Correlation,.975,.022,7.550,
-Interval by Interval,Pearson's R,.968,.017,6.708,
-N of Valid Cases,,5,,,
+x × y,5,100.0%,0,.0%,5,100.0%
+
+Table: x × y
+,,,y,,,,,Total
+,,,4.000,6.000,10.000,12.000,13.000,
+x,1.000,Count,1,0,0,0,0,1
+,3.000,,0,1,0,0,0,1
+,5.000,,0,0,1,1,0,2
+,6.000,,0,0,0,0,1,1
+Total,,,1,1,1,1,1,5
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Spearman Correlation,.975,.022,7.550
+Interval by Interval,Pearson's R,.968,.017,6.708
+N of Valid Cases,,5,,
])
+AT_CLEANUP
-# Test 2.
+AT_SETUP([CROSSTABS Pearson's R - 2])
AT_DATA([pearson2.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=CORR.
])
-AT_CHECK([pspp -O format=csv pearson2.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt pearson2.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,10,100.0%,0,0.0%,10,100.0%
-
-Table: x * y [[count]].
-,y,,,,,,,,,
-x,1.500,4.000,5.000,6.000,6.500,7.000,9.000,10.500,11.000,Total
-1.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-2.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-3.000,.000,1.000,.000,.000,.000,.000,.000,.000,.000,1.000
-4.000,.000,.000,.000,1.000,.000,.000,.000,.000,.000,1.000
-5.000,.000,.000,1.000,.000,.000,.000,.000,.000,.000,1.000
-6.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,1.000
-7.000,.000,.000,.000,.000,1.000,.000,.000,.000,.000,1.000
-8.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,1.000
-9.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,1.000
-10.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,1.000
-Total,2.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,10.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Spearman Correlation,.973,.015,11.844,
-Interval by Interval,Pearson's R,.971,.017,11.580,
-N of Valid Cases,,10,,,
+x × y,10,100.0%,0,.0%,10,100.0%
+
+Table: x × y
+,,,y,,,,,,,,,Total
+,,,1.500,4.000,5.000,6.000,6.500,7.000,9.000,10.500,11.000,
+x,1.000,Count,1,0,0,0,0,0,0,0,0,1
+,2.000,,1,0,0,0,0,0,0,0,0,1
+,3.000,,0,1,0,0,0,0,0,0,0,1
+,4.000,,0,0,0,1,0,0,0,0,0,1
+,5.000,,0,0,1,0,0,0,0,0,0,1
+,6.000,,0,0,0,0,0,1,0,0,0,1
+,7.000,,0,0,0,0,1,0,0,0,0,1
+,8.000,,0,0,0,0,0,0,1,0,0,1
+,9.000,,0,0,0,0,0,0,0,1,0,1
+,10.000,,0,0,0,0,0,0,0,0,1,1
+Total,,,2,1,1,1,1,1,1,1,1,10
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Spearman Correlation,.973,.015,11.844
+Interval by Interval,Pearson's R,.971,.017,11.580
+N of Valid Cases,,10,,
])
+AT_CLEANUP
-# Test 3.
+AT_SETUP([CROSSTABS Pearson's R - 3])
AT_DATA([pearson3.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=CORR.
])
-AT_CHECK([pspp -O format=csv pearson3.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt pearson3.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,9,100.0%,0,0.0%,9,100.0%
-
-Table: x * y [[count]].
-,y,,,,,,,,
-x,28.000,58.000,66.000,75.000,85.000,87.000,91.000,122.000,Total
-25.000,1.000,.000,.000,.000,.000,.000,.000,.000,1.000
-35.000,.000,1.000,.000,.000,.000,.000,.000,.000,1.000
-44.000,.000,.000,1.000,.000,.000,.000,.000,.000,1.000
-50.000,.000,.000,.000,1.000,.000,.000,.000,.000,1.000
-56.000,.000,.000,.000,.000,.000,1.000,1.000,.000,2.000
-65.000,.000,.000,.000,.000,1.000,.000,1.000,.000,2.000
-87.000,.000,.000,.000,.000,.000,.000,.000,1.000,1.000
-Total,1.000,1.000,1.000,1.000,1.000,1.000,2.000,1.000,9.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Spearman Correlation,.911,.068,5.860,
-Interval by Interval,Pearson's R,.966,.017,9.915,
-N of Valid Cases,,9,,,
+x × y,9,100.0%,0,.0%,9,100.0%
+
+Table: x × y
+,,,y,,,,,,,,Total
+,,,28.000,58.000,66.000,75.000,85.000,87.000,91.000,122.000,
+x,25.000,Count,1,0,0,0,0,0,0,0,1
+,35.000,,0,1,0,0,0,0,0,0,1
+,44.000,,0,0,1,0,0,0,0,0,1
+,50.000,,0,0,0,1,0,0,0,0,1
+,56.000,,0,0,0,0,0,1,1,0,2
+,65.000,,0,0,0,0,1,0,1,0,2
+,87.000,,0,0,0,0,0,0,0,1,1
+Total,,,1,1,1,1,1,1,2,1,9
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Spearman Correlation,.911,.068,5.860
+Interval by Interval,Pearson's R,.966,.017,9.915
+N of Valid Cases,,9,,
])
+AT_CLEANUP
-# Test 4.
+AT_SETUP([CROSSTABS Pearson's R - 4])
AT_DATA([pearson4.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=CORR.
])
-AT_CHECK([pspp -O format=csv pearson4.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt pearson4.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,12,100.0%,0,0.0%,12,100.0%
-
-Table: x * y [[count]].
-,y,,,,,,,,,,,,
-x,2.000,4.000,5.000,7.000,9.000,11.000,12.000,14.000,15.000,17.000,18.000,20.000,Total
-2.000,.000,.000,.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-3.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,.000,.000,1.000
-4.000,.000,.000,.000,.000,1.000,1.000,.000,.000,.000,.000,.000,.000,2.000
-5.000,.000,.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-6.000,1.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,2.000
-7.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,.000,1.000
-8.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,1.000
-9.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,1.000
-10.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,1.000,2.000
-Total,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,12.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Spearman Correlation,.657,.140,2.758,
-Interval by Interval,Pearson's R,.667,.132,2.830,
-N of Valid Cases,,12,,,
+x × y,12,100.0%,0,.0%,12,100.0%
+
+Table: x × y
+,,,y,,,,,,,,,,,,Total
+,,,2.000,4.000,5.000,7.000,9.000,11.000,12.000,14.000,15.000,17.000,18.000,20.000,
+x,2.000,Count,0,0,0,1,0,0,0,0,0,0,0,0,1
+,3.000,,0,0,0,0,0,0,1,0,0,0,0,0,1
+,4.000,,0,0,0,0,1,1,0,0,0,0,0,0,2
+,5.000,,0,0,1,0,0,0,0,0,0,0,0,0,1
+,6.000,,1,1,0,0,0,0,0,0,0,0,0,0,2
+,7.000,,0,0,0,0,0,0,0,1,0,0,0,0,1
+,8.000,,0,0,0,0,0,0,0,0,1,0,0,0,1
+,9.000,,0,0,0,0,0,0,0,0,0,1,0,0,1
+,10.000,,0,0,0,0,0,0,0,0,0,0,1,1,2
+Total,,,1,1,1,1,1,1,1,1,1,1,1,1,12
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Spearman Correlation,.657,.140,2.758
+Interval by Interval,Pearson's R,.667,.132,2.830
+N of Valid Cases,,12,,
])
+AT_CLEANUP
-# Test 5.
+AT_SETUP([CROSSTABS Pearson's R - 5])
AT_DATA([pearson5.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=CORR.
])
-AT_CHECK([pspp -O format=csv pearson5.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt pearson5.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,10,100.0%,0,0.0%,10,100.0%
-
-Table: x * y [[count]].
-,y,,,,,,,,,,
-x,15000.000,26000.000,29000.000,32000.000,33000.000,41000.000,45000.000,52000.000,68000.000,80000.000,Total
-18.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-24.000,.000,1.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000
-25.000,.000,.000,1.000,.000,.000,.000,.000,.000,.000,.000,1.000
-26.000,.000,.000,.000,1.000,.000,.000,.000,.000,.000,.000,1.000
-33.000,.000,.000,.000,.000,1.000,.000,.000,.000,.000,.000,1.000
-37.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,.000,1.000
-40.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,.000,1.000
-45.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,.000,1.000
-57.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,.000,1.000
-64.000,.000,.000,.000,.000,.000,.000,.000,.000,.000,1.000,1.000
-Total,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,1.000,10.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Spearman Correlation,1.000,.000,+Infinity,
-Interval by Interval,Pearson's R,.992,.004,22.638,
-N of Valid Cases,,10,,,
+x × y,10,100.0%,0,.0%,10,100.0%
+
+Table: x × y
+,,,y,,,,,,,,,,Total
+,,,15000.00,26000.00,29000.00,32000.00,33000.00,41000.00,45000.00,52000.00,68000.00,80000.00,
+x,18.000,Count,1,0,0,0,0,0,0,0,0,0,1
+,24.000,,0,1,0,0,0,0,0,0,0,0,1
+,25.000,,0,0,1,0,0,0,0,0,0,0,1
+,26.000,,0,0,0,1,0,0,0,0,0,0,1
+,33.000,,0,0,0,0,1,0,0,0,0,0,1
+,37.000,,0,0,0,0,0,1,0,0,0,0,1
+,40.000,,0,0,0,0,0,0,1,0,0,0,1
+,45.000,,0,0,0,0,0,0,0,1,0,0,1
+,57.000,,0,0,0,0,0,0,0,0,1,0,1
+,64.000,,0,0,0,0,0,0,0,0,0,1,1
+Total,,,1,1,1,1,1,1,1,1,1,1,10
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Spearman Correlation,1.000,.000,+Infinit
+Interval by Interval,Pearson's R,.992,.004,22.638
+N of Valid Cases,,10,,
])
AT_CLEANUP
-AT_SETUP([CROSSTABS Goodman and Kruskal's lambda])
+AT_SETUP([CROSSTABS Goodman and Kruskal's lambda - 1])
AT_DATA([lambda.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/CELLS=NONE/STATISTICS=LAMBDA.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lambda.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+x × y,1296.000,100.0%,.000,.0%,1296.000,100.0%
+
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
+Nominal by Nominal,Lambda,Symmetric,.423,.021,16.875,.000
+,,x Dependent,.497,.024,15.986,.000
+,,y Dependent,.370,.020,16.339,.000
+,Goodman and Kruskal tau,x Dependent,.382,,,
+,,y Dependent,.198,,,
+])
+AT_CLEANUP
+
+AT_SETUP([CROSSTABS Goodman and Kruskal's lambda - 2])
+AT_DATA([lambda.sps], [dnl
+SET FORMAT F8.3.
* From http://vassarstats.net.
DATA LIST LIST NOTABLE/x y w.
END DATA.
CROSSTABS x BY y/CELLS=NONE/STATISTICS=LAMBDA.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lambda.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+x × y,137.000,100.0%,.000,.0%,137.000,100.0%
+
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
+Nominal by Nominal,Lambda,Symmetric,.259,.081,2.902,.004
+,,x Dependent,.250,.089,2.479,.013
+,,y Dependent,.267,.085,2.766,.006
+,Goodman and Kruskal tau,x Dependent,.129,,,
+,,y Dependent,.123,,,
+])
+AT_CLEANUP
+
+AT_SETUP([CROSSTABS Goodman and Kruskal's lambda - 3])
+AT_DATA([lambda.sps], [dnl
+SET FORMAT F8.3.
* From Goodman, L.A., Kruskal, W.H. (1954) "Measures of association for
cross classifications". Part I. Journal of the American Statistical
END DATA.
CROSSTABS x BY y/CELLS=NONE/STATISTICS=LAMBDA.
])
-AT_CHECK([pspp -O format=csv lambda.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lambda.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,1296.000,100.0%,.000,0.0%,1296.000,100.0%
+x × y,6800.000,100.0%,.000,.0%,6800.000,100.0%
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Nominal by Nominal,Lambda,Symmetric,.423,.021,16.875,.000
-,,x Dependent,.497,.024,15.986,.000
-,,y Dependent,.370,.020,16.339,.000
-,Goodman and Kruskal tau,x Dependent,.382,,,. @&t@
-,,y Dependent,.198,,,. @&t@
-
-Table: Summary.
-,Cases,,,,,
-,Valid,,Missing,,Total,
-,N,Percent,N,Percent,N,Percent
-x * y,137.000,100.0%,.000,0.0%,137.000,100.0%
-
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Nominal by Nominal,Lambda,Symmetric,.259,.081,2.902,.004
-,,x Dependent,.250,.089,2.479,.013
-,,y Dependent,.267,.085,2.766,.006
-,Goodman and Kruskal tau,x Dependent,.129,,,. @&t@
-,,y Dependent,.123,,,. @&t@
-
-Table: Summary.
-,Cases,,,,,
-,Valid,,Missing,,Total,
-,N,Percent,N,Percent,N,Percent
-x * y,6800.000,100.0%,.000,0.0%,6800.000,100.0%
-
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.208,.010,18.793,.000
,,x Dependent,.224,.013,16.076,.000
,,y Dependent,.192,.012,14.438,.000
-,Goodman and Kruskal tau,x Dependent,.089,,,. @&t@
-,,y Dependent,.081,,,. @&t@
+,Goodman and Kruskal tau,x Dependent,.089,,,
+,,y Dependent,.081,,,
])
AT_CLEANUP
CROSSTABS x BY y/CELLS=NONE/STATISTICS=LAMBDA.
])
-AT_CHECK([pspp -O format=csv lambda.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lambda.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,500.000,100.0%,.000,0.0%,500.000,100.0%
+x × y,500.000,100.0%,.000,.0%,500.000,100.0%
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.031,.013,2.336,.019
,,x Dependent,.000,.000,NaN,NaN
,,y Dependent,.033,.014,2.336,.019
-,Goodman and Kruskal tau,x Dependent,.012,,,. @&t@
-,,y Dependent,.009,,,. @&t@
+,Goodman and Kruskal tau,x Dependent,.012,,,
+,,y Dependent,.009,,,
])
AT_CLEANUP
-AT_SETUP([CROSSTABS Somers' D, Tau-B, Tau-C, Gamma])
+AT_SETUP([CROSSTABS Somers' D, Tau-B, Tau-C, Gamma - 1])
AT_DATA([somersd.sps], [dnl
SET FORMAT F8.3.
2 7 0.0375
END DATA.
CROSSTABS x BY y/STATISTICS=D/CELLS=NONE.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt somersd.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+x × y,1.000000,100.0%,.000000,.0%,1.000000,100.0%
+
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
+Ordinal by Ordinal,Somers' d,Symmetric,-.084,,-.149,.882
+,,x Dependent,-.045,.300,-.149,.882
+,,y Dependent,-.684,2.378,-.149,.882
+])
+AT_CLEANUP
+
+AT_SETUP([CROSSTABS Somers' D, Tau-B, Tau-C, Gamma - 2])
+AT_DATA([somersd.sps], [dnl
+SET FORMAT F8.3.
* From http://uregina.ca/~gingrich/gamma.pdf.
DATA LIST LIST NOTABLE/x y w.
END DATA.
CROSSTABS x BY y/STATISTICS=BTAU CTAU GAMMA D/CELLS=NONE.
])
-AT_CHECK([pspp -O format=csv somersd.sps], [0], [dnl
-Table: Summary.
-,Cases,,,,,
-,Valid,,Missing,,Total,
-,N,Percent,N,Percent,N,Percent
-x * y,1.000000,100.0%,.000000,0.0%,1.000000,100.0%
-
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Somers' d,Symmetric,-.084,,-.149,.882
-,,x Dependent,-.045,.300,-.149,.882
-,,y Dependent,-.684,2.378,-.149,.882
-
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt somersd.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,687.000,100.0%,.000,0.0%,687.000,100.0%
+x × y,687.000,100.0%,.000,.0%,687.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,.372,.033,10.669,
-,Kendall's tau-c,.310,.029,10.669,
-,Gamma,.591,.043,10.669,
-N of Valid Cases,,687.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,.372,.033,10.669
+,Kendall's tau-c,.310,.029,10.669
+,Gamma,.591,.043,10.669
+N of Valid Cases,,687.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,.371,,10.669,.000
,,x Dependent,.351,.032,10.669,.000
,,y Dependent,.394,.035,10.669,.000
])
+AT_CLEANUP
+AT_SETUP([CROSSTABS Somers' D, Tau-B, Tau-C, Gamma - 3])
AT_DATA([ordinal.sps], [dnl
SET FORMAT F8.3.
END DATA.
CROSSTABS x BY y/STATISTICS=LAMBDA D PHI BTAU/CELLS=NONE.
])
-AT_CHECK([pspp -O format=csv ordinal.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt ordinal.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,150.000,100.0%,.000,0.0%,150.000,100.0%
+x × y,150.000,100.0%,.000,.0%,150.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,1.000,.000,24.841,
-,Gamma,1.000,.000,24.841,
-N of Valid Cases,,150.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,1.000,.000,24.841
+,Gamma,1.000,.000,24.841
+N of Valid Cases,,150.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,1.000,,24.841,.000
,,x Dependent,1.000,.000,24.841,.000
,,y Dependent,1.000,.000,24.841,.000
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,150.000,100.0%,.000,0.0%,150.000,100.0%
+x × y,150.000,100.0%,.000,.0%,150.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,1.000,.000,24.841,
-,Gamma,1.000,.000,24.841,
-N of Valid Cases,,150.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,1.000,.000,24.841
+,Gamma,1.000,.000,24.841
+N of Valid Cases,,150.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,1.000,,24.841,.000
,,x Dependent,1.000,.000,24.841,.000
,,y Dependent,1.000,.000,24.841,.000
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,150.000,100.0%,.000,0.0%,150.000,100.0%
+x × y,150.000,100.0%,.000,.0%,150.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,-1.000,.000,-24.841,
-,Gamma,-1.000,.000,-24.841,
-N of Valid Cases,,150.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,-1.000,.000,-24.841
+,Gamma,-1.000,.000,-24.841
+N of Valid Cases,,150.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,-1.000,,-24.841,.000
,,x Dependent,-1.000,.000,-24.841,.000
,,y Dependent,-1.000,.000,-24.841,.000
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,150.000,100.0%,.000,0.0%,150.000,100.0%
+x × y,150.000,100.0%,.000,.0%,150.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,.972,.007,24.841,
-,Gamma,1.000,.000,24.841,
-N of Valid Cases,,150.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,.972,.007,24.841
+,Gamma,1.000,.000,24.841
+N of Valid Cases,,150.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,.971,,24.841,.000
,,x Dependent,.944,.013,24.841,.000
,,y Dependent,1.000,.000,24.841,.000
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,150.000,100.0%,.000,0.0%,150.000,100.0%
+x × y,150.000,100.0%,.000,.0%,150.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,.119,.059,1.009,
-,Gamma,1.000,.000,1.009,
-N of Valid Cases,,150.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,.119,.059,1.009
+,Gamma,1.000,.000,1.009
+N of Valid Cases,,150.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,.035,,1.009,.313
,,x Dependent,.805,.032,1.009,.313
,,y Dependent,.018,.017,1.009,.313
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,148.000,100.0%,.000,0.0%,148.000,100.0%
+x × y,148.000,100.0%,.000,.0%,148.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Ordinal by Ordinal,Kendall's tau-b,-.208,.078,-2.641,
-,Gamma,-.381,.130,-2.641,
-N of Valid Cases,,148.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Ordinal by Ordinal,Kendall's tau-b,-.208,.078,-2.641
+,Gamma,-.381,.130,-2.641
+N of Valid Cases,,148.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Ordinal by Ordinal,Somers' d,Symmetric,-.206,,-2.641,.008
,,x Dependent,-.182,.069,-2.641,.008
,,y Dependent,-.237,.089,-2.641,.008
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,148.000,100.0%,.000,0.0%,148.000,100.0%
+x × y,148.000,100.0%,.000,.0%,148.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Nominal by Nominal,Phi,.731,,,
-,Cramer's V,.731,,,
-Ordinal by Ordinal,Gamma,-.110,.107,-1.022,
-N of Valid Cases,,148.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Nominal by Nominal,Phi,.731,,
+,Cramer's V,.731,,
+Ordinal by Ordinal,Gamma,-.110,.107,-1.022
+N of Valid Cases,,148.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.338,.059,4.743,.000
,,x Dependent,.640,.085,4.875,.000
,,y Dependent,.174,.050,3.248,.001
-,Goodman and Kruskal tau,x Dependent,.534,,,. @&t@
-,,y Dependent,.167,,,. @&t@
+,Goodman and Kruskal tau,x Dependent,.534,,,
+,,y Dependent,.167,,,
Ordinal by Ordinal,Somers' d,Symmetric,-.074,,-1.022,.307
,,x Dependent,-.060,.059,-1.022,.307
,,y Dependent,-.096,.094,-1.022,.307
-Table: Summary.
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,212.000,100.0%,.000,0.0%,212.000,100.0%
+x × y,212.000,100.0%,.000,.0%,212.000,100.0%
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Nominal by Nominal,Phi,.432,,,
-,Cramer's V,.249,,,
-Ordinal by Ordinal,Kendall's tau-b,.209,.062,3.338,
-N of Valid Cases,,212.000,,,
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Nominal by Nominal,Phi,.432,,
+,Cramer's V,.249,,
+Ordinal by Ordinal,Kendall's tau-b,.209,.062,3.338
+N of Valid Cases,,212.000,,
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.102,.067,1.473,.141
,,x Dependent,.027,.087,.302,.763
,,y Dependent,.165,.065,2.349,.019
-,Goodman and Kruskal tau,x Dependent,.051,,,. @&t@
-,,y Dependent,.068,,,. @&t@
+,Goodman and Kruskal tau,x Dependent,.051,,,
+,,y Dependent,.068,,,
Ordinal by Ordinal,Somers' d,Symmetric,.209,,3.338,.001
,,x Dependent,.202,.060,3.338,.001
,,y Dependent,.217,.064,3.338,.001
.
])
-AT_CHECK([pspp -O format=csv kappa.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt kappa.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-p1 * p2,20.000,100.0%,.000,0.0%,20.000,100.0%
-
-Table: p1 * p2 [[count]].
-,p2,,
-p1,.000,1.000,Total
-.000,18.000,1.000,19.000
-1.000,1.000,.000,1.000
-Total,19.000,1.000,20.000
-
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Measure of Agreement,Kappa,-.053,.037,-.235,
-N of Valid Cases,,20.000,,,
+p1 × p2,20.000,100.0%,.000,.0%,20.000,100.0%
+
+Table: p1 × p2
+,,,p2,,Total
+,,,.000,1.000,
+p1,.000,Count,18.000,1.000,19.000
+,1.000,,1.000,.000,1.000
+Total,,,19.000,1.000,20.000
+
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Measure of Agreement,Kappa,-.053,.037,-.235
+N of Valid Cases,,20.000,,
])
AT_CLEANUP
END DATA.
CROSSTABS x BY y/STATISTICS=CHISQ PHI CC LAMBDA UC BTAU CTAU GAMMA D CORR/CELLS=NONE.
])
-AT_CHECK([pspp -O format=csv crosstabs.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt crosstabs.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,66.0000,100.0%,.0000,0.0%,66.0000,100.0%
+x × y,66.0000,100.0%,.0000,.0%,66.0000,100.0%
-Table: Chi-square tests.
-Statistic,Value,df,Asymp. Sig. (2-tailed)
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed)
Pearson Chi-Square,6.9562,2.0000,.031
Likelihood Ratio,6.6901,2.0000,.035
Linear-by-Linear Association,5.8450,1.0000,.016
N of Valid Cases,66.0000,,
-Table: Symmetric measures.
-Category,Statistic,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
-Nominal by Nominal,Phi,.3246,,,
-,Cramer's V,.3246,,,
-,Contingency Coefficient,.3088,,,
-Ordinal by Ordinal,Kendall's tau-b,.2752,.0856,1.9920,
-,Kendall's tau-c,.1497,.0751,1.9920,
-,Gamma,.8717,.1250,1.9920,
-,Spearman Correlation,.2908,.0906,2.4311,
-Interval by Interval,Pearson's R,.2999,.0973,2.5147,
-N of Valid Cases,,66.0000,,,
-
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Symmetric Measures
+,,Value,Asymp. Std. Error,Approx. T
+Nominal by Nominal,Phi,.3246,,
+,Cramer's V,.3246,,
+,Contingency Coefficient,.3088,,
+Ordinal by Ordinal,Kendall's tau-b,.2752,.0856,1.9920
+,Kendall's tau-c,.1497,.0751,1.9920
+,Gamma,.8717,.1250,1.9920
+,Spearman Correlation,.2908,.0906,2.4311
+Interval by Interval,Pearson's R,.2999,.0973,2.5147
+N of Valid Cases,,66.0000,,
+
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.0455,.1629,.2723,.785
,,x Dependent,.0000,.0000,NaN,NaN
,,y Dependent,.0500,.1791,.2723,.785
-,Goodman and Kruskal tau,x Dependent,.1054,,,. @&t@
-,,y Dependent,.0434,,,. @&t@
-,Uncertainty Coefficient,Symmetric,.0780,.0474,,. @&t@
-,,x Dependent,.2217,.1062,1.5373,. @&t@
-,,y Dependent,.0473,.0306,1.5373,. @&t@
+,Goodman and Kruskal tau,x Dependent,.1054,,,
+,,y Dependent,.0434,,,
+,Uncertainty Coefficient,Symmetric,.0780,.0474,,
+,,x Dependent,.2217,.1062,1.5373,
+,,y Dependent,.0473,.0306,1.5373,
Ordinal by Ordinal,Somers' d,Symmetric,.1960,,1.9920,.046
,,x Dependent,.1152,.0572,1.9920,.046
,,y Dependent,.6573,.1417,1.9920,.046
END DATA.
CROSSTABS x BY y/STATISTICS=LAMBDA UC/CELLS=NONE.
])
-AT_CHECK([pspp -O format=csv uc.sps], [0], [dnl
-Table: Summary.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt uc.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x * y,987.000,100.0%,.000,0.0%,987.000,100.0%
+x × y,987.000,100.0%,.000,.0%,987.000,100.0%
-Table: Directional measures.
-Category,Statistic,Type,Value,Asymp. Std. Error,Approx. T,Approx. Sig.
+Table: Directional Measures
+,,,Value,Asymp. Std. Error,Approx. T,Approx Sig.
Nominal by Nominal,Lambda,Symmetric,.000,.000,NaN,NaN
,,x Dependent,.000,.000,NaN,NaN
,,y Dependent,.000,.000,NaN,NaN
-,Goodman and Kruskal tau,x Dependent,.076,,,. @&t@
-,,y Dependent,.108,,,. @&t@
-,Uncertainty Coefficient,Symmetric,.105,.012,,. @&t@
-,,x Dependent,.073,.009,7.890,. @&t@
-,,y Dependent,.184,.019,7.890,. @&t@
+,Goodman and Kruskal tau,x Dependent,.076,,,
+,,y Dependent,.108,,,
+,Uncertainty Coefficient,Symmetric,.105,.012,,
+,,x Dependent,.073,.009,7.890,
+,,y Dependent,.184,.019,7.890,
])
AT_CLEANUP
+AT_SETUP([CROSSTABS estimated risk])
+dnl Example data and expected output from
+dnl http://www.psychology.nottingham.ac.uk/staff/ddc/c8cxpa/further/Project_resources/SPSSCrosstabW.pdf
+AT_DATA([risk.sps], [dnl
+DATA LIST LIST /factor disease count (F8.0).
+WEIGHT BY count.
+VALUE LABELS /factor 0 'Placebo' 1 'Aspirin'
+ /disease 1 'No' 0 'Yes'.
+BEGIN DATA.
+0 1 80
+0 0 20
+1 1 135
+1 0 15
+END DATA.
+CROSSTABS factor BY disease/STATISTICS=RISK CHISQ.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt risk.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Reading free-form data from INLINE.
+Variable,Format
+factor,F8.0
+disease,F8.0
+count,F8.0
+Table: Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+factor × disease,250,100.0%,0,.0%,250,100.0%
+
+Table: factor × disease
+,,,disease,,Total
+,,,Yes,No,
+factor,Placebo,Count,20,80,100
+,Aspirin,,15,135,150
+Total,,,35,215,250
+
+Table: Chi-Square Tests
+,Value,df,Asymptotic Sig. (2-tailed),Exact Sig. (2-tailed),Exact Sig. (1-tailed)
+Pearson Chi-Square,4.98,1,.026,,
+Likelihood Ratio,4.88,1,.027,,
+Fisher's Exact Test,,,,.039,.021
+Continuity Correction,4.19,1,.041,,
+Linear-by-Linear Association,4.96,1,.026,,
+N of Valid Cases,250,,,,
+
+Table: Risk Estimate
+,Value,95% Confidence Interval,
+,,Lower,Upper
+Odds Ratio for factor (Placebo / Aspirin),2.25,2.25,2.25
+For cohort disease = Yes,1.08,1.08,1.08
+For cohort disease = No,.99,.99,.99
+N of Valid Cases,250.00,,
+])
+AT_CLEANUP
AT_SETUP([CROSSTABS barchart])
AT_DATA([bc.sps], [dnl
V15,1,16- 16,F1.0
V16,1,17- 17,F1.0
-Table: Valid cases = 10; cases with missing value(s) = 0.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-V0,10,0,3.80,.84,2.66,7.07,-.03,1.33,.89,.69,8.00,1.00,9.00,38.00
-V1,10,0,4.60,.96,3.03,9.16,-1.39,1.33,-.03,.69,9.00,.00,9.00,46.00
-V2,10,0,4.10,1.16,3.67,13.43,-2.02,1.33,.48,.69,8.00,1.00,9.00,41.00
-V3,10,0,4.10,.87,2.77,7.66,-2.05,1.33,.42,.69,7.00,1.00,8.00,41.00
-V4,10,0,7.00,.47,1.49,2.22,7.15,1.33,-2.52,.69,5.00,3.00,8.00,70.00
-V5,10,0,4.90,1.03,3.25,10.54,-1.40,1.33,-.20,.69,9.00,.00,9.00,49.00
-V6,10,0,5.90,.80,2.51,6.32,-.29,1.33,-.96,.69,7.00,1.00,8.00,59.00
-V7,10,0,4.70,1.10,3.47,12.01,-1.99,1.33,-.16,.69,9.00,.00,9.00,47.00
-V8,10,0,4.10,1.10,3.48,12.10,-1.93,1.33,.37,.69,9.00,.00,9.00,41.00
-V9,10,0,4.30,.87,2.75,7.57,-.87,1.33,.73,.69,8.00,1.00,9.00,43.00
-V10,10,0,5.50,.85,2.68,7.17,-1.84,1.33,-.33,.69,7.00,2.00,9.00,55.00
-V11,10,0,6.50,.78,2.46,6.06,-1.28,1.33,-.89,.69,6.00,3.00,9.00,65.00
-V12,10,0,7.90,.60,1.91,3.66,5.24,1.33,-2.21,.69,6.00,3.00,9.00,79.00
-V13,10,0,4.30,.99,3.13,9.79,-1.25,1.33,.33,.69,9.00,.00,9.00,43.00
-V14,10,0,3.60,1.01,3.20,10.27,-.96,1.33,.81,.69,9.00,.00,9.00,36.00
-V15,10,0,3.70,.92,2.91,8.46,-1.35,1.33,.71,.69,7.00,1.00,8.00,37.00
-V16,10,0,6.40,.91,2.88,8.27,-1.14,1.33,-.92,.69,7.00,2.00,9.00,64.00
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+V0,10,3.80,.84,2.66,7.07,-.03,1.33,.89,.69,8.00,1,9,38.00
+V1,10,4.60,.96,3.03,9.16,-1.39,1.33,-.03,.69,9.00,0,9,46.00
+V2,10,4.10,1.16,3.67,13.43,-2.02,1.33,.48,.69,8.00,1,9,41.00
+V3,10,4.10,.87,2.77,7.66,-2.05,1.33,.42,.69,7.00,1,8,41.00
+V4,10,7.00,.47,1.49,2.22,7.15,1.33,-2.52,.69,5.00,3,8,70.00
+V5,10,4.90,1.03,3.25,10.54,-1.40,1.33,-.20,.69,9.00,0,9,49.00
+V6,10,5.90,.80,2.51,6.32,-.29,1.33,-.96,.69,7.00,1,8,59.00
+V7,10,4.70,1.10,3.47,12.01,-1.99,1.33,-.16,.69,9.00,0,9,47.00
+V8,10,4.10,1.10,3.48,12.10,-1.93,1.33,.37,.69,9.00,0,9,41.00
+V9,10,4.30,.87,2.75,7.57,-.87,1.33,.73,.69,8.00,1,9,43.00
+V10,10,5.50,.85,2.68,7.17,-1.84,1.33,-.33,.69,7.00,2,9,55.00
+V11,10,6.50,.78,2.46,6.06,-1.28,1.33,-.89,.69,6.00,3,9,65.00
+V12,10,7.90,.60,1.91,3.66,5.24,1.33,-2.21,.69,6.00,3,9,79.00
+V13,10,4.30,.99,3.13,9.79,-1.25,1.33,.33,.69,9.00,0,9,43.00
+V14,10,3.60,1.01,3.20,10.27,-.96,1.33,.81,.69,9.00,0,9,36.00
+V15,10,3.70,.92,2.91,8.46,-1.35,1.33,.71,.69,7.00,1,8,37.00
+V16,10,6.40,.91,2.88,8.27,-1.14,1.33,-.92,.69,7.00,2,9,64.00
+Valid N (listwise),10,,,,,,,,,,,,
+Missing N (listwise),0,,,,,,,,,,,,
])
AT_CLEANUP
[DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0],
- [Table: Valid cases = 7; cases with missing value(s) = 6.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-V1,1,6,2.00,. ,. ,. ,. ,. ,. ,. ,.00,2.00,2.00,2.00
-V2,2,5,2.50,.50,.71,.50,. ,. ,. ,. ,1.00,2.00,3.00,5.00
-V3,3,4,3.00,.58,1.00,1.00,. ,. ,.00,1.22,2.00,2.00,4.00,9.00
+AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+V1,1,2.00,. ,. ,. ,. ,. ,. ,. ,.00,2,2,2.00
+V2,2,2.50,.50,.71,.50,. ,. ,. ,. ,1.00,2,3,5.00
+V3,3,3.00,.58,1.00,1.00,. ,. ,.00,1.22,2.00,2,4,9.00
+Valid N (listwise),7,,,,,,,,,,,,
+Missing N (listwise),6,,,,,,,,,,,,
])
AT_CLEANUP
[DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=include.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0],
- [Table: Valid cases = 7; cases with missing value(s) = 3.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-V1,5,2,1.20,.20,.45,.20,5.00,2.00,2.24,.91,1.00,1.00,2.00,6.00
-V2,5,2,1.60,.40,.89,.80,.31,2.00,1.26,.91,2.00,1.00,3.00,8.00
-V3,5,2,2.20,.58,1.30,1.70,-1.49,2.00,.54,.91,3.00,1.00,4.00,11.00
+AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+V1,5,1.20,.20,.45,.20,5.00,2.00,2.24,.91,1.00,1,2,6.00
+V2,5,1.60,.40,.89,.80,.31,2.00,1.26,.91,2.00,1,3,8.00
+V3,5,2.20,.58,1.30,1.70,-1.49,2.00,.54,.91,3.00,1,4,11.00
+Valid N (listwise),7,,,,,,,,,,,,
+Missing N (listwise),3,,,,,,,,,,,,
])
AT_CLEANUP
[DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=listwise.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0],
- [Table: Valid cases = 1; cases with missing value(s) = 6.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-V1,1,0,2.00,. ,. ,. ,. ,. ,. ,. ,.00,2.00,2.00,2.00
-V2,1,0,3.00,. ,. ,. ,. ,. ,. ,. ,.00,3.00,3.00,3.00
-V3,1,0,4.00,. ,. ,. ,. ,. ,. ,. ,.00,4.00,4.00,4.00
+AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+V1,1,2.00,. ,. ,. ,. ,. ,. ,. ,.00,2,2,2.00
+V2,1,3.00,. ,. ,. ,. ,. ,. ,. ,.00,3,3,3.00
+V3,1,4.00,. ,. ,. ,. ,. ,. ,. ,.00,4,4,4.00
+Valid N (listwise),1,,,,,,,,,,,,
+Missing N (listwise),6,,,,,,,,,,,,
])
AT_CLEANUP
[DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=listwise include.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0],
- [Table: Valid cases = 4; cases with missing value(s) = 3.
-Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
-V1,4,0,1.25,.25,.50,.25,4.00,2.62,2.00,1.01,1.00,1.00,2.00,5.00
-V2,4,0,1.75,.48,.96,.92,-1.29,2.62,.85,1.01,2.00,1.00,3.00,7.00
-V3,4,0,2.50,.65,1.29,1.67,-1.20,2.62,.00,1.01,3.00,1.00,4.00,10.00
+AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
+V1,4,1.25,.25,.50,.25,4.00,2.62,2.00,1.01,1.00,1,2,5.00
+V2,4,1.75,.48,.96,.92,-1.29,2.62,.85,1.01,2.00,1,3,7.00
+V3,4,2.50,.65,1.29,1.67,-1.20,2.62,.00,1.01,3.00,1,4,10.00
+Valid N (listwise),4,,,,,,,,,,,,
+Missing N (listwise),3,,,,,,,,,,,,
])
AT_CLEANUP
descript all/stat=mean.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0],
- [Table: Valid cases = 6; cases with missing value(s) = 0.
-Variable,N,Mean
+AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean
X,6,2.500
+Valid N (listwise),6,
+Missing N (listwise),0,
])
AT_CLEANUP
DESCRIPTIVES /VAR=abc.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
-Table: Valid cases = 6; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
abc,6,3.00,.84,2.00,4.00
+Valid N (listwise),6,,,,
+Missing N (listwise),0,,,,
])
AT_CLEANUP
LIST.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
-Table: Mapping of variables to corresponding Z-scores.
+Table: Mapping of Variables to Z-scores
Source,Target
a,Za
b,Zb
-Table: Valid cases = 3; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
a,3,2.00,1.00,1.00,3.00
b,3,60.00,10.00,50.00,70.00
+Valid N (listwise),3,,,,
+Missing N (listwise),0,,,,
Table: Data List
a,b,Za,Zb
DESCRIPTIVES /VAR=a b /SAVE.
LIST.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
-Table: Mapping of variables to corresponding Z-scores.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt descriptives.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Mapping of Variables to Z-scores
Source,Target
a,Za
b,Zb
-Variable,Value,Label
-group,1.00,
+Table: Split Values
+Variable,Value
+group,1.00
-Table: Valid cases = 3; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
a,3,2.00,1.00,1.00,3.00
b,3,60.00,10.00,50.00,70.00
+Valid N (listwise),3,,,,
+Missing N (listwise),0,,,,
-Variable,Value,Label
-group,2.00,
+Table: Split Values
+Variable,Value
+group,2.00
-Table: Valid cases = 4; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
a,4,300.00,182.57,100.00,500.00
b,4,8000.00,1825.74,6000.00,10000.00
+Valid N (listwise),4,,,,
+Missing N (listwise),0,,,,
-Variable,Value,Label
-group,1.00,
+Table: Split Values
+Variable,Value
+group,1.00
Table: Data List
group,a,b,Za,Zb
1.00,2.00,60.00,.00,.00
1.00,3.00,70.00,1.00,1.00
-Variable,Value,Label
-group,2.00,
+Table: Split Values
+Variable,Value
+group,2.00
Table: Data List
group,a,b,Za,Zb
DESCRIPTIVES /VAR=abc/SAVE.
LIST.
])
-AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt descriptives.sps], [0], [dnl
+descriptives.sps:15: warning: DESCRIPTIVES: DESCRIPTIVES with Z scores ignores TEMPORARY. Temporary transformations will be made permanent.
+])
+AT_CHECK([cat pspp.csv], [0], [dnl
descriptives.sps:15: warning: DESCRIPTIVES: DESCRIPTIVES with Z scores ignores TEMPORARY. Temporary transformations will be made permanent.
-Table: Mapping of variables to corresponding Z-scores.
+Table: Mapping of Variables to Z-scores
Source,Target
abc,Zabc
-Table: Valid cases = 6; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
abc,6,3.00,.84,2.00,4.00
+Valid N (listwise),6,,,,
+Missing N (listwise),0,,,,
Table: Data List
id,abc,Zabc
1.00,1.00,1.00,-.66,-1.26,-1.26,-1.00,-1.00
])
AT_CLEANUP
+
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([DESCRIPTIVES tutorial example])
+cp $top_srcdir/examples/physiology.sav .
+AT_DATA([descriptives.sps], [dnl
+GET FILE='physiology.sav'.
+DESCRIPTIVES sex, weight, height.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt descriptives.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
+Sex of subject ,40,.45,.50,Male,Female
+Weight in kilograms ,40,72.12,26.70,-55.6,92.1
+Height in millimeters ,40,1677.12,262.87,179,1903
+Valid N (listwise),40,,,,
+Missing N (listwise),0,,,,
+])
+AT_CLEANUP
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-Breaking Strain,24.00,100%,.00,0%,24.00,100%
+Breaking Strain,24.00,100.0%,.00,.0%,24.00,100.0%
Table: Extreme Values
,,,Case Number,Value
,,Cases,,,,,
,,Valid,,Missing,,Total,
,Manufacturer,N,Percent,N,Percent,N,Percent
-Breaking Strain,Aspeger,8.00,100%,.00,0%,8.00,100%
-,Bloggs,8.00,100%,.00,0%,8.00,100%
-,Charlies,8.00,100%,.00,0%,8.00,100%
+Breaking Strain,Aspeger,8.00,100.0%,.00,.0%,8.00,100.0%
+,Bloggs,8.00,100.0%,.00,.0%,8.00,100.0%
+,Charlies,8.00,100.0%,.00,.0%,8.00,100.0%
Table: Extreme Values
,Manufacturer,,,Case Number,Value
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-V1,23.00,100%,.00,0%,23.00,100%
+V1,23.00,100.0%,.00,.0%,23.00,100.0%
Table: Extreme Values
,,,Case Number,Value
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x,19.430,100%,.000,0%,19.430,100%
+x,19.430,100.0%,.000,.0%,19.430,100.0%
Table: Extreme Values
,,,Case Number,Value
EXAMINE /x
/PERCENTILES=AEMPIRICAL.
])
-AT_CHECK([pspp -o pspp.csv examine.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt examine.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,3,100%,0,0%,3,100%
+X,3,100.0%,0,.0%,3,100.0%
Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
-X,HAverage,.40,.80,2.00,5.00,8.00,8.00,8.00
+X,Weighted Average,.40,.80,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,3,100%,0,0%,3,100%
+X,3,100.0%,0,.0%,3,100.0%
Table: Percentiles
,,Percentiles,,,,,,
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,3,100%,0,0%,3,100%
+X,3,100.0%,0,.0%,3,100.0%
Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
-X,Rounded,.00,.00,2.00,5.00,5.00,8.00,8.00
+X,Weighted Average,.00,.00,2.00,5.00,5.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,3,100%,0,0%,3,100%
+X,3,100.0%,0,.0%,3,100.0%
Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
-X,Empirical,2.00,2.00,2.00,5.00,8.00,8.00,8.00
+X,Weighted Average,2.00,2.00,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,
Table: Case Processing Summary
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,3,100%,0,0%,3,100%
+X,3,100.0%,0,.0%,3,100.0%
Table: Percentiles
,,Percentiles,,,,,,
,,5,10,25,50,75,90,95
-X,Empirical with averaging,2.00,2.00,2.00,5.00,8.00,8.00,8.00
+X,Weighted Average,2.00,2.00,2.00,5.00,8.00,8.00,8.00
,Tukey's Hinges,,,3.50,5.00,6.50,,
])
AT_CLEANUP
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x,6,85.7143%,1,14.2857%,7,100%
+x,6,85.7%,1,14.3%,7,100.0%
Table: Case Processing Summary
,,Cases,,,,,
,,Valid,,Missing,,Total,
,y,N,Percent,N,Percent,N,Percent
-x,1.00,4,100%,0,0%,4,100%
-,2.00,2,66.6667%,1,33.3333%,3,100%
+x,1.00,4,100.0%,0,.0%,4,100.0%
+,2.00,2,66.7%,1,33.3%,3,100.0%
])
AT_CLEANUP
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x,1,33.3333%,2,66.6667%,3,100%
-y,2,66.6667%,1,33.3333%,3,100%
+x,1,33.3%,2,66.7%,3,100.0%
+y,2,66.7%,1,33.3%,3,100.0%
])
AT_CLEANUP
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,52.00,100%,.00,0%,52.00,100%
+X,52.00,100.0%,.00,.0%,52.00,100.0%
Table: Descriptives
,,,Statistic,Std. Error
dnl Test that big input doesn't crash (bug 11307).
AT_SETUP([EXAMINE -- big input doesn't crash])
-AT_KEYWORDS([categorical categoricals])
+AT_KEYWORDS([categorical categoricals slow])
AT_DATA([examine.sps], [dnl
INPUT PROGRAM.
LOOP #I=1 TO 50000.
dnl Another test that big input doesn't crash.
dnl The actual bug that this checks for has been lost.
AT_SETUP([EXAMINE -- big input doesn't crash 2])
-AT_KEYWORDS([categorical categoricals])
+AT_KEYWORDS([categorical categoricals slow])
AT_DATA([make-big-input.pl],
[for ($i=0; $i<100000; $i++) { print "AB12\n" };
for ($i=0; $i<100000; $i++) { print "AB04\n" };
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-x,14,100%,0,0%,14,100%
+x,14,100.0%,0,.0%,14,100.0%
Table: Extreme Values
,,,y,Value
x,Highest,1,threehundred,300.00
-,,2,thirty ,30.00
-,,3,twelve ,12.00
-,,4,eleven ,11.00
-,,5,ten ,10.00
-,Lowest,1,one ,1.00
-,,2,two ,2.00
-,,3,three ,3.00
-,,4,four ,4.00
-,,5,five ,5.00
+,,2,thirty,30.00
+,,3,twelve,12.00
+,,4,eleven,11.00
+,,5,ten,10.00
+,Lowest,1,one,1.00
+,,2,two,2.00
+,,3,three,3.00
+,,4,four,4.00
+,,5,five,5.00
])
AT_CLEANUP
])
-AT_CHECK([pspp -O format=csv examine-report.sps], [0], [dnl
-Table: Reading free-form data from INLINE.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt examine-report.sps])
+AT_CHECK([cat pspp.csv], [0],
+ [[Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
g,F8.0
,,Cases,,,,,
,,Valid,,Missing,,Total,
,g,N,Percent,N,Percent,N,Percent
-x,. (missing),4,100%,0,0%,4,100%
-,1,9,100%,0,0%,9,100%
-,2,9,100%,0,0%,9,100%
-,9 (missing),4,100%,0,0%,4,100%
-,99 (missing),5,100%,0,0%,5,100%
+x,.,4,100.0%,0,.0%,4,100.0%
+,1,9,100.0%,0,.0%,9,100.0%
+,2,9,100.0%,0,.0%,9,100.0%
+,9[a],4,100.0%,0,.0%,4,100.0%
+,99[a],5,100.0%,0,.0%,5,100.0%
+
+Footnotes:
+a,User-missing value.
Table: Extreme Values
,g,,,Case Number,Value
-x,. (missing),Highest,1,31,4004
+x,.,Highest,1,31,4004
,,,2,30,3003
,,,3,29,2002
,,,4,28,1001
,,,3,12,30
,,,4,13,40
,,,5,14,50
-,9 (missing),Highest,1,22,401
+,9[a],Highest,1,22,401
,,,2,21,301
,,,3,20,201
,,,4,19,101
,,,3,21,301
,,,4,22,401
,,,5,22,401
-,99 (missing),Highest,1,27,901
+,99[a],Highest,1,27,901
,,,2,26,801
,,,3,25,701
,,,4,24,601
,,,3,25,701
,,,4,26,801
,,,5,27,901
-])
+Footnotes:
+a,User-missing value.
+]])
AT_CLEANUP
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-X,100,100%,0,0%,100,100%
+X,100,100.0%,0,.0%,100,100.0%
Table: Descriptives
,,,Statistic,Std. Error
,Cases,,,,,
,Valid,,Missing,,Total,
,N,Percent,N,Percent,N,Percent
-h,3.00,100%,.00,0%,3.00,100%
+h,3.00,100.0%,.00,.0%,3.00,100.0%
Table: Extreme Values
,,,Case Number,Value
AT_CLEANUP
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([EXAMINE tutorial example 1])
+cp $top_srcdir/examples/repairs.sav .
+AT_DATA([repairs.sps], [dnl
+GET FILE='repairs.sav'.
+EXAMINE mtbf /STATISTICS=DESCRIPTIVES.
+COMPUTE mtbf_ln = LN (mtbf).
+EXAMINE mtbf_ln /STATISTICS=DESCRIPTIVES.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt repairs.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Case Processing Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+Mean time between failures (months) ,15,100.0%,0,.0%,15,100.0%
+
+Table: Descriptives
+,,,Statistic,Std. Error
+Mean time between failures (months) ,Mean,,8.32,1.62
+,95% Confidence Interval for Mean,Lower Bound,4.85,
+,,Upper Bound,11.79,
+,5% Trimmed Mean,,7.69,
+,Median,,8.12,
+,Variance,,39.21,
+,Std. Deviation,,6.26,
+,Minimum,,1.63,
+,Maximum,,26.47,
+,Range,,24.84,
+,Interquartile Range,,5.83,
+,Skewness,,1.85,.58
+,Kurtosis,,4.49,1.12
+Table: Case Processing Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+mtbf_ln,15,100.0%,0,.0%,15,100.0%
+
+Table: Descriptives
+,,,Statistic,Std. Error
+mtbf_ln,Mean,,1.88,.19
+,95% Confidence Interval for Mean,Lower Bound,1.47,
+,,Upper Bound,2.29,
+,5% Trimmed Mean,,1.88,
+,Median,,2.09,
+,Variance,,.54,
+,Std. Deviation,,.74,
+,Minimum,,.49,
+,Maximum,,3.28,
+,Range,,2.79,
+,Interquartile Range,,.92,
+,Skewness,,-.16,.58
+,Kurtosis,,-.09,1.12
+])
+AT_CLEANUP
+
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([EXAMINE tutorial example 2])
+cp $top_srcdir/examples/physiology.sav .
+AT_DATA([examine.sps], [dnl
+GET FILE='physiology.sav'.
+EXAMINE height, weight /STATISTICS=EXTREME(3).
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt examine.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Case Processing Summary
+,Cases,,,,,
+,Valid,,Missing,,Total,
+,N,Percent,N,Percent,N,Percent
+Height in millimeters ,40,100.0%,0,.0%,40,100.0%
+Weight in kilograms ,40,100.0%,0,.0%,40,100.0%
+
+Table: Extreme Values
+,,,Case Number,Value
+Height in millimeters ,Highest,1,14,1903
+,,2,15,1884
+,,3,12,1802
+,Lowest,1,30,179
+,,2,31,1598
+,,3,28,1601
+Weight in kilograms ,Highest,1,13,92.1
+,,2,5,92.1
+,,3,17,91.7
+,Lowest,1,38,-55.6
+,,2,39,54.5
+,,3,33,55.4
+])
+AT_CLEANUP
Table: Correlation Matrix
,,question13,question14,question15,question16,question17,question18,question19,question20,question21,question22,question23,question24
-Correlations,question13,1.000,.661,.600,.566,.577,.409,.286,.304,.476,.333,.564,.454
+Correlation,question13,1.000,.661,.600,.566,.577,.409,.286,.304,.476,.333,.564,.454
,question14,.661,1.000,.635,.500,.552,.433,.320,.315,.449,.333,.565,.443
,question15,.600,.635,1.000,.505,.587,.457,.359,.356,.509,.369,.582,.435
,question16,.566,.500,.505,1.000,.586,.405,.335,.317,.452,.363,.459,.430
,question22,.333,.333,.369,.363,.450,.536,.484,.383,.507,1.000,.493,.444
,question23,.564,.565,.582,.459,.613,.569,.444,.410,.598,.493,1.000,.705
,question24,.454,.443,.435,.430,.521,.474,.374,.357,.500,.444,.705,1.000
-Determinant,.002,,,,,,,,,,,,
+Caption: Determinant: 0.00
Table: Factor Matrix
,Factor,,
Table: Total Variance Explained
,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,,Rotation Sums of Squared Loadings,,
-Component,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
-1,3.381,67.616,67.616,3.381,67.616,67.616,2.113,42.267,42.267
-2,.557,11.148,78.764,.557,11.148,78.764,1.825,36.497,78.764
-3,.407,8.136,86.900,,,,,,
-4,.356,7.123,94.023,,,,,,
-5,.299,5.977,100.000,,,,,,
+,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
+1,3.381,67.6%,67.6%,3.381,67.6%,67.6%,2.113,42.3%,42.3%
+2,.557,11.1%,78.8%,.557,11.1%,78.8%,1.825,36.5%,78.8%
+3,.407,8.1%,86.9%,,,,,,
+4,.356,7.1%,94.0%,,,,,,
+5,.299,6.0%,100.0%,,,,,,
Table: Component Matrix
,Component,
Table: Correlation Matrix
,,TRAIT1,TRAIT2,TRAIT3,TRAIT4,TRAIT5
-Correlations,TRAIT1,1.00,.30,.88,1.00,.54
-,TRAIT2,.30,1.00,-.02,.33,.84
-,TRAIT3,.88,-.02,1.00,.87,.13
-,TRAIT4,1.00,.33,.87,1.00,.54
-,TRAIT5,.54,.84,.13,.54,1.00
+Correlation,TRAIT1,1.000,.296,.881,.995,.545
+,TRAIT2,.296,1.000,-.022,.326,.837
+,TRAIT3,.881,-.022,1.000,.867,.130
+,TRAIT4,.995,.326,.867,1.000,.544
+,TRAIT5,.545,.837,.130,.544,1.000
Sig. (1-tailed),TRAIT1,,.260,.004,.000,.103
,TRAIT2,.260,,.482,.238,.009
,TRAIT3,.004,.482,,.006,.390
,TRAIT4,.000,.238,.006,,.103
,TRAIT5,.103,.009,.390,.103,
-Determinant,.00,,,,,
+Caption: Determinant: 0.00
Table: Communalities
,Initial,Extraction
Table: Total Variance Explained
,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,
-Component,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
-1,3.26,65.26,65.26,3.26,65.26,65.26
-2,1.54,30.77,96.03,1.54,30.77,96.03
-3,.17,3.36,99.39,.17,3.36,99.39
-4,.03,.61,100.00,.03,.61,100.00
-5,.00,.00,100.00,,,
+,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
+1,3.26,65.3%,65.3%,3.26,65.3%,65.3%
+2,1.54,30.8%,96.0%,1.54,30.8%,96.0%
+3,.17,3.4%,99.4%,.17,3.4%,99.4%
+4,.03,.6%,100.0%,.03,.6%,100.0%
+5,.00,.0%,100.0%,,,
Table: Component Matrix
,Component,,,
Table: Total Variance Explained
,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,
-Factor,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
-1,2.404,80.124,80.124,2.155,71.847,71.847
-2,.425,14.166,94.290,,,
-3,.171,5.710,100.000,,,
+,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
+1,2.404,80.1%,80.1%,2.155,71.8%,71.8%
+2,.425,14.2%,94.3%,,,
+3,.171,5.7%,100.0%,,,
Table: Factor Matrix
,Factor
ZS,.130,.158
Table: Total Variance Explained
-,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,,Rotation Sums of Squared Loadings
-Factor,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %,Total
-1,2.968,16.491,16.491,2.411,13.393,13.393,2.355
-2,2.026,11.253,27.744,1.271,7.059,20.452,1.209
-3,1.622,9.011,36.756,.948,5.264,25.716,1.231
-4,1.086,6.032,42.788,.283,1.574,27.290,.770
-5,.996,5.533,48.321,,,,
-6,.923,5.130,53.451,,,,
-7,.873,4.852,58.303,,,,
-8,.856,4.756,63.060,,,,
-9,.836,4.644,67.703,,,,
-10,.816,4.534,72.237,,,,
-11,.785,4.359,76.596,,,,
-12,.740,4.110,80.706,,,,
-13,.713,3.964,84.670,,,,
-14,.653,3.626,88.296,,,,
-15,.633,3.519,91.815,,,,
-16,.604,3.356,95.171,,,,
-17,.484,2.687,97.858,,,,
-18,.386,2.142,100.000,,,,
+,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,,Rotation Sums of Squared Loadings,,
+,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
+1,2.968,16.5%,16.5%,2.411,13.4%,13.4%,. ,. ,. @&t@
+2,2.026,11.3%,27.7%,1.271,7.1%,20.5%,. ,. ,-Infinity
+3,1.622,9.0%,36.8%,.948,5.3%,25.7%,. ,. ,-Infinity
+4,1.086,6.0%,42.8%,.283,1.6%,27.3%,. ,. ,-Infinity
+5,.996,5.5%,48.3%,,,,,,
+6,.923,5.1%,53.5%,,,,,,
+7,.873,4.9%,58.3%,,,,,,
+8,.856,4.8%,63.1%,,,,,,
+9,.836,4.6%,67.7%,,,,,,
+10,.816,4.5%,72.2%,,,,,,
+11,.785,4.4%,76.6%,,,,,,
+12,.740,4.1%,80.7%,,,,,,
+13,.713,4.0%,84.7%,,,,,,
+14,.653,3.6%,88.3%,,,,,,
+15,.633,3.5%,91.8%,,,,,,
+16,.604,3.4%,95.2%,,,,,,
+17,.484,2.7%,97.9%,,,,,,
+18,.386,2.1%,100.0%,,,,,,
Table: Factor Matrix
,Factor,,,
Table: Total Variance Explained
,Initial Eigenvalues,,
-Component,Total,% of Variance,Cumulative %
-1,556.895,81.881,81.881
-2,57.963,8.522,90.403
-3,23.576,3.466,93.869
-4,16.446,2.418,96.288
-5,14.603,2.147,98.435
-6,6.831,1.004,99.439
-7,2.375,.349,99.788
-8,1.440,.212,100.000
+,Total,% of Variance,Cumulative %
+1,556.895,81.9%,81.9%
+2,57.963,8.5%,90.4%
+3,23.576,3.5%,93.9%
+4,16.446,2.4%,96.3%
+5,14.603,2.1%,98.4%
+6,6.831,1.0%,99.4%
+7,2.375,.3%,99.8%
+8,1.440,.2%,100.0%
Table: Component Matrix
,Component,,,,,,
Table: Total Variance Explained
,Initial Eigenvalues,,,Extraction Sums of Squared Loadings,,
-Component,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
-1,3.914,55.908,55.908,3.914,55.908,55.908
-2,1.320,18.852,74.760,,,
-3,.716,10.223,84.983,,,
-4,.422,6.030,91.012,,,
-5,.278,3.977,94.989,,,
-6,.216,3.088,98.077,,,
-7,.135,1.923,100.000,,,
+,Total,% of Variance,Cumulative %,Total,% of Variance,Cumulative %
+1,3.914,55.9%,55.9%,3.914,55.9%,55.9%
+2,1.320,18.9%,74.8%,,,
+3,.716,10.2%,85.0%,,,
+4,.422,6.0%,91.0%,,,
+5,.278,4.0%,95.0%,,,
+6,.216,3.1%,98.1%,,,
+7,.135,1.9%,100.0%,,,
Table: Component Matrix
,Component
Table: Data List
CASE_LBL,v,w,x,y,z
-a ,1.00,6.00,11.00,16.00,21.00
-b ,2.00,7.00,12.00,17.00,22.00
-c ,3.00,8.00,13.00,18.00,23.00
-d ,4.00,9.00,14.00,19.00,24.00
-e ,1.00,6.00,11.00,16.00,21.00
+a,1.00,6.00,11.00,16.00,21.00
+b,2.00,7.00,12.00,17.00,22.00
+c,3.00,8.00,13.00,18.00,23.00
+d,4.00,9.00,14.00,19.00,24.00
+e,1.00,6.00,11.00,16.00,21.00
Table: Data List
CASE_LBL,a,b,c,d,e
-v ,1.00,2.00,3.00,4.00,1.00
-w ,6.00,7.00,8.00,9.00,6.00
-x ,11.00,12.00,13.00,14.00,11.00
-y ,16.00,17.00,18.00,19.00,16.00
-z ,21.00,22.00,23.00,24.00,21.00
+v,1.00,2.00,3.00,4.00,1.00
+w,6.00,7.00,8.00,9.00,6.00
+x,11.00,12.00,13.00,14.00,11.00
+y,16.00,17.00,18.00,19.00,16.00
+z,21.00,22.00,23.00,24.00,21.00
])
AT_CLEANUP
Table: Data List
CASE_LBL,VAR000,VAR001
-v1 ,1.00,4.00
-v2 ,2.00,5.00
-v3 ,3.00,6.00
-v4 ,4.00,7.00
-v5 ,5.00,8.00
-v6 ,6.00,9.00
-v7 ,7.00,10.00
-v8 ,8.00,11.00
-v9 ,9.00,12.00
-v10 ,10.00,13.00
+v1,1.00,4.00
+v2,2.00,5.00
+v3,3.00,6.00
+v4,4.00,7.00
+v5,5.00,8.00
+v6,6.00,9.00
+v7,7.00,10.00
+v8,8.00,11.00
+v9,9.00,12.00
+v10,10.00,13.00
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv flip.sps], [0], [dnl
Table: Data List
CASE_LBL,v,BY1
-a ,1.00,1.00
-b ,2.00,2.00
-c ,3.00,3.00
-d ,4.00,4.00
+a,1.00,1.00
+b,2.00,2.00
+c,3.00,3.00
+d,4.00,4.00
])
AT_CLEANUP
])
AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
Table: name
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,bar ,2,20.00,20.00,20.00
-,baz ,4,40.00,40.00,60.00
-,foo ,2,20.00,20.00,80.00
-,quux ,2,20.00,20.00,100.00
-Total,,10,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,bar,2,20.0%,20.0%,20.0%
+,baz,4,40.0%,40.0%,60.0%
+,foo,2,20.0%,20.0%,80.0%
+,quux,2,20.0%,20.0%,100.0%
+Total,,10,100.0%,,
])
AT_CLEANUP
frequencies v1 v2/statistics=none/ORDER=VARIABLE.
frequencies v1 v2/statistics=none.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: v1
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,.00,1,25.00,25.00,25.00
-,2.00,1,25.00,25.00,50.00
-,3.00,1,25.00,25.00,75.00
-,4.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: v1
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,.00,1,25.0%,25.0%,25.0%
+,2.00,1,25.0%,25.0%,50.0%
+,3.00,1,25.0%,25.0%,75.0%
+,4.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
Table: v2
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,25.00,25.00,25.00
-,3.00,1,25.00,25.00,50.00
-,4.00,1,25.00,25.00,75.00
-,5.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,25.0%,25.0%,25.0%
+,3.00,1,25.0%,25.0%,50.0%
+,4.00,1,25.0%,25.0%,75.0%
+,5.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
Table: v1
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,.00,1,25.00,25.00,25.00
-,2.00,1,25.00,25.00,50.00
-,3.00,1,25.00,25.00,75.00
-,4.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,.00,1,25.0%,25.0%,25.0%
+,2.00,1,25.0%,25.0%,50.0%
+,3.00,1,25.0%,25.0%,75.0%
+,4.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
Table: v2
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,25.00,25.00,25.00
-,3.00,1,25.00,25.00,50.00
-,4.00,1,25.00,25.00,75.00
-,5.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,25.0%,25.0%,25.0%
+,3.00,1,25.0%,25.0%,50.0%
+,4.00,1,25.0%,25.0%,75.0%
+,5.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
])
AT_CLEANUP
])
AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
Table: v2
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,25.00,25.00,25.00
-,3.00,1,25.00,25.00,50.00
-,5.00,2,50.00,50.00,100.00
-Total,,4,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,25.0%,25.0%,25.0%
+,3.00,1,25.0%,25.0%,50.0%
+,5.00,2,50.0%,50.0%,100.0%
+Total,,4,100.0%,,
])
AT_CLEANUP
3.00,4.00
Table: v1
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,.00,1,25.00,25.00,25.00
-,2.00,1,25.00,25.00,50.00
-,3.00,1,25.00,25.00,75.00
-,4.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,.00,1,25.0%,25.0%,25.0%
+,2.00,1,25.0%,25.0%,50.0%
+,3.00,1,25.0%,25.0%,75.0%
+,4.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
])
AT_CHECK([test -s pspp.html])
AT_CLEANUP
Reading free-form data from INLINE.
+--------+------+
|Variable|Format|
-#========#======#
++--------+------+
|x |F8.0 |
|w |F8.0 |
+--------+------+
FINISH
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: Reading free-form data from INLINE.
+AT_CHECK([pspp -o pspp.csv -o pspp.txt frequencies.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Reading free-form data from INLINE.
Variable,Format
SEX,A1
X,F8.0
-Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,12.00,1,25.00,25.00,25.00
-,13.00,1,25.00,25.00,50.00
-,21.00,1,25.00,25.00,75.00
-,31.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
-
-Table: X
+Table: Statistics
+,,X
N,Valid,4
,Missing,0
Mean,,19.25
Std Dev,,8.81
Minimum,,12.00
Maximum,,31.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,12.00,1,25.0%,25.0%,25.0%
+,13.00,1,25.0%,25.0%,50.0%
+,21.00,1,25.0%,25.0%,75.0%
+,31.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
])
AT_CLEANUP
-m4_define([FREQUENCIES_NTILES_OUTPUT],
- [Table: x
+m4_define([FREQUENCIES_NTILES_OUTPUT], [dnl
+Table: Statistics
+,,x
N,Valid,5
,Missing,0
Mean,,3.00
Percentiles,0,1.00
,25,2.00
,33,2.33
-,50 (Median),3.00
+,50,3.00
,67,3.67
,75,4.00
,100,5.00
/ALGORITHM=COMPATIBLE
/PERCENTILES = 0 25 50 75 100.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,20.00,20.00,20.00
-,2.00,1,20.00,20.00,40.00
-,3.00,1,20.00,20.00,60.00
-,4.00,1,20.00,20.00,80.00
-,5.00,1,20.00,20.00,100.00
-Total,,5,100.0,100.0,
-
-Table: X
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: Statistics
+,,X
N,Valid,5
,Missing,0
Mean,,3.00
Maximum,,5.00
Percentiles,0,1.00
,25,1.50
-,50 (Median),3.00
+,50,3.00
,75,4.50
,100,5.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,20.0%,20.0%,20.0%
+,2.00,1,20.0%,20.0%,40.0%
+,3.00,1,20.0%,20.0%,60.0%
+,4.00,1,20.0%,20.0%,80.0%
+,5.00,1,20.0%,20.0%,100.0%
+Total,,5,100.0%,,
])
AT_CLEANUP
VAR=x
/PERCENTILES = 0 25 50 75 100.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,20.00,20.00,20.00
-,2.00,1,20.00,20.00,40.00
-,3.00,1,20.00,20.00,60.00
-,4.00,1,20.00,20.00,80.00
-,5.00,1,20.00,20.00,100.00
-Total,,5,100.0,100.0,
-
-Table: X
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: Statistics
+,,X
N,Valid,5
,Missing,0
Mean,,3.00
Maximum,,5.00
Percentiles,0,1.00
,25,2.00
-,50 (Median),3.00
+,50,3.00
,75,4.00
,100,5.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,20.0%,20.0%,20.0%
+,2.00,1,20.0%,20.0%,40.0%
+,3.00,1,20.0%,20.0%,60.0%
+,4.00,1,20.0%,20.0%,80.0%
+,5.00,1,20.0%,20.0%,100.0%
+Total,,5,100.0%,,
])
AT_CLEANUP
VAR=x
/PERCENTILES = 0 25 50 75 100.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,2.00,20.00,20.00,20.00
-,2.00,2.00,20.00,20.00,40.00
-,3.00,2.00,20.00,20.00,60.00
-,4.00,2.00,20.00,20.00,80.00
-,5.00,2.00,20.00,20.00,100.00
-Total,,10.00,100.0,100.0,
-
-Table: X
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: Statistics
+,,X
N,Valid,10.00
,Missing,.00
Mean,,3.00
Maximum,,5.00
Percentiles,0,1.00
,25,2.00
-,50 (Median),3.00
+,50,3.00
,75,4.00
,100,5.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,2.00,20.0%,20.0%,20.0%
+,2.00,2.00,20.0%,20.0%,40.0%
+,3.00,2.00,20.0%,20.0%,60.0%
+,4.00,2.00,20.0%,20.0%,80.0%
+,5.00,2.00,20.0%,20.0%,100.0%
+Total,,10.00,100.0%,,
])
AT_CLEANUP
VAR=x
/PERCENTILES = 0 25 50 75 100.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1.00,16.67,16.67,16.67
-,3.00,2.00,33.33,33.33,50.00
-,4.00,1.00,16.67,16.67,66.67
-,5.00,2.00,33.33,33.33,100.00
-Total,,6.00,100.0,100.0,
-
-Table: X
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: Statistics
+,,X
N,Valid,6.00
,Missing,.00
Mean,,3.50
Maximum,,5.00
Percentiles,0,1.00
,25,3.00
-,50 (Median),3.50
+,50,3.50
,75,4.75
,100,5.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1.00,16.7%,16.7%,16.7%
+,3.00,2.00,33.3%,33.3%,50.0%
+,4.00,1.00,16.7%,16.7%,66.7%
+,5.00,2.00,33.3%,33.3%,100.0%
+Total,,6.00,100.0%,,
])
AT_CLEANUP
/PERCENTILES = 0 25 50 75 100.
])
AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
-Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,7.00,17.50,17.50,17.50
-,2.00,16.00,40.00,40.00,57.50
-,3.00,12.00,30.00,30.00,87.50
-,4.00,5.00,12.50,12.50,100.00
-Total,,40.00,100.0,100.0,
-
-Table: X
+Table: Statistics
+,,X
N,Valid,40.00
,Missing,.00
Mean,,2.38
Maximum,,4.00
Percentiles,0,1.00
,25,2.00
-,50 (Median),2.00
+,50,2.00
,75,3.00
,100,4.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,7.00,17.5%,17.5%,17.5%
+,2.00,16.00,40.0%,40.0%,57.5%
+,3.00,12.00,30.0%,30.0%,87.5%
+,4.00,5.00,12.5%,12.5%,100.0%
+Total,,40.00,100.0%,,
])
AT_CLEANUP
/PERCENTILES = 0 25 50 75 100.
])
-AT_CHECK([pspp -O format=csv frequencies.sps], [0],
- [Table: X
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1.00,10.00,16.67,16.67
-,3.00,2.00,20.00,33.33,50.00
-,4.00,1.00,10.00,16.67,66.67
-,5.00,2.00,20.00,33.33,100.00
-,99.00,4.00,40.00,Missing,
-Total,,10.00,100.0,100.0,
-
-Table: X
+AT_CHECK([pspp -O format=csv frequencies.sps], [0], [dnl
+Table: Statistics
+,,X
N,Valid,6.00
,Missing,4.00
Mean,,3.50
Maximum,,5.00
Percentiles,0,1.00
,25,3.00
-,50 (Median),3.50
+,50,3.50
,75,4.75
,100,5.00
+
+Table: X
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1.00,10.0%,16.7%,16.7%
+,3.00,2.00,20.0%,33.3%,50.0%
+,4.00,1.00,10.0%,16.7%,66.7%
+,5.00,2.00,20.0%,33.3%,100.0%
+Missing,99.00,4.00,40.0%,,
+Total,,10.00,100.0%,,
])
AT_CLEANUP
.
])
-AT_CHECK([pspp median.sps -O format=csv], [0], [dnl
-Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,1.00,1,33.33,33.33,33.33
-,2.00,1,33.33,33.33,66.67
-,3000000.00,1,33.33,33.33,100.00
-Total,,3,100.0,100.0,
-
-Table: x
+AT_CHECK([pspp median.sps -O format=csv], [0], [dnl
+Table: Statistics
+,,x
N,Valid,3
,Missing,0
-Percentiles,50 (Median),2.00
+Median,,2.00
+
+Table: x
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,1.00,1,33.3%,33.3%,33.3%
+,2.00,1,33.3%,33.3%,66.7%
+,3000000,1,33.3%,33.3%,100.0%
+Total,,3,100.0%,,
])
AT_CLEANUP
/STATISTICS = VARIANCE.
])
-AT_CHECK([pspp variance.sps -O format=csv], [0], [dnl
-Table: height
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,109.00,1,25.00,25.00,25.00
-,134.00,1,25.00,25.00,50.00
-,167.00,1,25.00,25.00,75.00
-,188.00,1,25.00,25.00,100.00
-Total,,4,100.0,100.0,
-
-Table: height
+AT_CHECK([pspp variance.sps -O format=csv], [0], [dnl
+Table: Statistics
+,,height
N,Valid,4
,Missing,0
Variance,,1223.00
+
+Table: height
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,109.00,1,25.0%,25.0%,25.0%
+,134.00,1,25.0%,25.0%,50.0%
+,167.00,1,25.0%,25.0%,75.0%
+,188.00,1,25.0%,25.0%,100.0%
+Total,,4,100.0%,,
])
AT_CLEANUP
.
])
-AT_CHECK([pspp median.sps -O format=csv], [0], [dnl
-Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,10.00,1,33.33,33.33,33.33
-,20.00,1,33.33,33.33,66.67
-,3000000.00,1,33.33,33.33,100.00
-Total,,3,100.0,100.0,
-
-Table: x
+AT_CHECK([pspp median.sps -o pspp.csv -o pspp.txt])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Statistics
+,,x
N,Valid,3
,Missing,0
-Mean,,1000010.00
-Std Dev,,1732042.15
+Mean,,1000010
+Std Dev,,1732042
Minimum,,10.00
-Maximum,,3000000.00
-
-Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,10.00,1,33.33,33.33,33.33
-,20.00,1,33.33,33.33,66.67
-,3000000.00,1,33.33,33.33,100.00
-Total,,3,100.0,100.0,
+Maximum,,3000000
Table: x
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,10.00,1,33.3%,33.3%,33.3%
+,20.00,1,33.3%,33.3%,66.7%
+,3000000,1,33.3%,33.3%,100.0%
+Total,,3,100.0%,,
+
+Table: Statistics
+,,x
N,Valid,3
,Missing,0
-Mean,,1000010.00
-Std Dev,,1732042.15
+Mean,,1000010
+Std Dev,,1732042
Minimum,,10.00
-Maximum,,3000000.00
+Maximum,,3000000
+
+Table: x
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Valid,10.00,1,33.3%,33.3%,33.3%
+,20.00,1,33.3%,33.3%,66.7%
+,3000000,1,33.3%,33.3%,100.0%
+Total,,3,100.0%,,
])
AT_CLEANUP
])
AT_CHECK([pspp empty.sps -O format=csv], [0], [dnl
-Table: x
-Value Label,Value,Frequency,Percent,Valid Percent,Cum Percent
-,. ,3,100.00,Missing,
-Total,,3,100.0,100.0,
-
-Table: x
+Table: Statistics
+,,x
N,Valid,0
,Missing,3
-Mean,,.
-S.E. Mean,,.
-Mode,,.
-Std Dev,,.
-Variance,,.
-Kurtosis,,.
-S.E. Kurt,,.
-Skewness,,.
-S.E. Skew,,.
-Range,,.
-Minimum,,.
-Maximum,,.
-Sum,,.
-Percentiles,,.
+Mean,,. @&t@
+S.E. Mean,,. @&t@
+Median,,. @&t@
+Mode,,. @&t@
+Std Dev,,. @&t@
+Variance,,. @&t@
+Kurtosis,,. @&t@
+S.E. Kurt,,. @&t@
+Skewness,,. @&t@
+S.E. Skew,,. @&t@
+Range,,. @&t@
+Minimum,,. @&t@
+Maximum,,. @&t@
+Sum,,. @&t@
+
+Table: x
+,,Frequency,Percent,Valid Percent,Cumulative Percent
+Missing,. ,3,100.0%,,
+Total,,3,.0%,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv latin.sps | sed 's/329.62[[678]]/329.62/'], [0],
[dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,263.064,15,17.538,5.269,.000
Intercept,815.103,1,815.103,244.910,.000
Factor A,78.869,5,15.774,4.739,.005
AT_CHECK([pspp -O format=csv 2by2.sps ], [0],
[dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,8667.053,3,2889.018,5.043,.012
Intercept,2256018.640,1,2256018.640,3937.693,.000
Factor0,313.394,1,313.394,.547,.470
Factor1,5157.508,1,5157.508,9.002,.008
-Factor0 * Factor1,3196.150,1,3196.150,5.579,.031
+Factor0 × Factor1,3196.150,1,3196.150,5.579,.031
Error,9166.865,16,572.929,,
Total,2273852.559,20,,,
Corrected Total,17833.918,19,,,
AT_CHECK([pspp -O format=csv type1.sps], [0],
[dnl
Table: Tests of Between-Subjects Effects
-Source,Type I Sum of Squares,df,Mean Square,F,Sig.
+,Type I Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,216.017,7,30.860,5.046,.001
Intercept,,,,,
Agrp,9.579,1,9.579,1.566,.220
Bgrp,186.225,3,62.075,10.151,.000
-Agrp * Bgrp,20.212,3,6.737,1.102,.364
+Agrp × Bgrp,20.212,3,6.737,1.102,.364
Error,183.457,30,6.115,,
Total,3810.000,38,,,
Corrected Total,399.474,37,,,
Table: Tests of Between-Subjects Effects
-Source,Type I Sum of Squares,df,Mean Square,F,Sig.
+,Type I Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,216.017,7,30.860,5.046,.001
Intercept,,,,,
Bgrp,193.251,3,64.417,10.534,.000
Agrp,2.553,1,2.553,.418,.523
-Bgrp * Agrp,20.212,3,6.737,1.102,.364
+Bgrp × Agrp,20.212,3,6.737,1.102,.364
Error,183.457,30,6.115,,
Total,3810.000,38,,,
Corrected Total,399.474,37,,,
AT_CHECK([pspp -O format=csv type2.sps], [0],
[dnl
Table: Tests of Between-Subjects Effects
-Source,Type II Sum of Squares,df,Mean Square,F,Sig.
+,Type II Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,216.017,7,30.860,5.046,.001
Intercept,,,,,
Agrp,2.553,1,2.553,.418,.523
Bgrp,186.225,3,62.075,10.151,.000
-Agrp * Bgrp,20.212,3,6.737,1.102,.364
+Agrp × Bgrp,20.212,3,6.737,1.102,.364
Error,183.457,30,6.115,,
Total,3810.000,38,,,
Corrected Total,399.474,37,,,
AT_CHECK([pspp -O format=csv intercept-exclude.sps], [0],
[dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Model,1636.826,2,818.413,43.556,.000
A,1636.826,2,818.413,43.556,.000
Error,338.216,18,18.790,,
Total,1975.042,20,,,
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,98.568,1,98.568,5.246,.034
Intercept,1538.258,1,1538.258,81.867,.000
A,98.568,1,98.568,5.246,.034
AT_CHECK([pspp -O format=csv glm-miss.sps], [0], [dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,251.621,14,17.973,4.969,.002
Intercept,628.376,1,628.376,173.737,.000
a,72.929,4,18.232,5.041,.009
AT_CHECK([pspp -O format=csv glm-miss2.sps], [0], [dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,251.621,14,17.973,4.969,.002
Intercept,628.376,1,628.376,173.737,.000
a,72.929,4,18.232,5.041,.009
AT_CHECK([pspp -O format=csv glm-miss3.sps], [0], [dnl
Table: Tests of Between-Subjects Effects
-Source,Type III Sum of Squares,df,Mean Square,F,Sig.
+,Type III Sum Of Squares,df,Mean Square,F,Sig.
Corrected Model,251.621,14,17.973,4.969,.002
Intercept,628.376,1,628.376,173.737,.000
a,72.929,4,18.232,5.041,.009
.
])
-AT_CHECK([pspp -O format=csv lr-data.sps], [0],
- [dnl
-Table: Dependent Variable Encoding
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lr-data.sps], [0], [dnl
+note: Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001
+])
+AT_CHECK([cat pspp.csv], [0], [Table: Dependent Variable Encoding
Original Value,Internal Value
-1.000,0
-2.000,1
+1.000,.000
+2.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,66,100.000
-Missing Cases,0,.000
-Total,66,100.000
+Included in Analysis,66,100.0%
+Missing Cases,0,.0%
+Total,66,100.0%
note: Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,37.323,.455,.659
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,37.323,.455,.659
Table: Classification Table
,,,Predicted,,
-,,,outcome,,"Percentage
-Correct"
+,,,outcome,,Percentage Correct
,Observed,,1.000,2.000,
-Step 1,outcome,1.000,43,5,89.583
-,,2.000,4,14,77.778
-,Overall Percentage,,,,86.364
+Step 1,outcome,1.000,43,5,89.6%
+,,2.000,4,14,77.8%
+,Overall Percentage,,,,86.4%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
Step 1,survrate,-.081,.019,17.756,1,.000,.922
,Constant,2.684,.811,10.941,1,.001,14.639
])
-
-
AT_CLEANUP
AT_SETUP([LOGISTIC REGRESSION missing values])
dnl Only the summary information should be different
AT_CHECK([diff run0 run1], [1], [dnl
8,10c8,10
-< Included in Analysis,66,100.000
-< Missing Cases,0,.000
-< Total,66,100.000
+< Included in Analysis,66,100.0%
+< Missing Cases,0,.0%
+< Total,66,100.0%
---
-> Included in Analysis,66,94.286
-> Missing Cases,4,5.714
-> Total,70,100.000
+> Included in Analysis,66,94.3%
+> Missing Cases,4,5.7%
+> Total,70,100.0%
])
AT_CLEANUP
dnl this displays the unweighted totals.
AT_CHECK([diff unweighted-result weighted-result], [1], [dnl
8c8
-< Included in Analysis,66,100.000
+< Included in Analysis,66,100.0%
---
-> Included in Analysis,63,100.000
+> Included in Analysis,63,100.0%
10c10
-< Total,66,100.000
+< Total,66,100.0%
---
-> Total,63,100.000
-23,24c23,24
-< Step 1,outcome,1.000,43,5,89.583
-< ,,2.000,4,14,77.778
+> Total,63,100.0%
+22,23c22,23
+< Step 1,outcome,1.000,43,5,89.6%
+< ,,2.000,4,14,77.8%
---
-> Step 1,outcome,1.000,43.000,5.000,89.583
-> ,,2.000,4.000,14.000,77.778
+> Step 1,outcome,1.000,43.000,5.000,89.6%
+> ,,2.000,4.000,14.000,77.8%
])
logistic regression female with constant /noconst.
])
-AT_CHECK([pspp -O format=csv non-const.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv non-const.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.00,0
-1.00,1
+.00,.000
+1.00,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,200,100.000
-Missing Cases,0,.000
-Total,200,100.000
+Included in Analysis,200,100.0%
+Missing Cases,0,.0%
+Total,200,100.0%
note: Estimation terminated at iteration number 2 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,275.637,.008,.011
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,275.637,.008,.011
Table: Classification Table
,,,Predicted,,
-,,,female,,"Percentage
-Correct"
+,,,female,,Percentage Correct
,Observed,,.00,1.00,
-Step 1,female,.00,0,91,.000
-,,1.00,0,109,100.000
-,Overall Percentage,,,,54.500
+Step 1,female,.00,0,91,.0%
+,,1.00,0,109,100.0%
+,Overall Percentage,,,,54.5%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
.
])
-AT_CHECK([pspp -O format=csv lr-cat.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv lr-cat.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-4.000,0
-9.000,1
+4.000,.000
+9.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,400,100.000
-Missing Cases,0,.000
-Total,400,100.000
+Included in Analysis,400,100.0%
+Missing Cases,0,.0%
+Total,400,100.0%
note: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,458.517,.098,.138
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,458.517,.098,.138
Table: Categorical Variables' Codings
-,,,Parameter coding,,
-,,Frequency,(1),(2),(3)
+,,Frequency,Parameter coding,,
+,,,(1),(2),(3)
bcat,1.000,61,1,0,0
,2.000,151,0,1,0
,3.000,121,0,0,1
Table: Classification Table
,,,Predicted,,
-,,,y,,"Percentage
-Correct"
+,,,y,,Percentage Correct
,Observed,,4.000,9.000,
-Step 1,y,4.000,254,19,93.040
-,,9.000,97,30,23.622
-,Overall Percentage,,,,71.000
+Step 1,y,4.000,254,19,93.0%
+,,9.000,97,30,23.6%
+,Overall Percentage,,,,71.0%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
,bcat(3),.211,.393,.289,1,.591,1.235
,Constant,-5.541,1.138,23.709,1,.000,.004
])
-
AT_CLEANUP
])
-AT_CHECK([pspp -O format=csv stringcat.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv stringcat.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.000,0
-1.000,1
+.000,.000
+1.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,200,100.000
-Missing Cases,0,.000
-Total,200,100.000
+Included in Analysis,200,100.0%
+Missing Cases,0,.0%
+Total,200,100.0%
note: Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,165.701,.280,.408
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,165.701,.280,.408
Table: Categorical Variables' Codings
-,,,Parameter coding,
-,,Frequency,(1),(2)
+,,Frequency,Parameter coding,
+,,,(1),(2)
ses,a,47,1,0
,b,95,0,1
,c,58,0,0
Table: Classification Table
,,,Predicted,,
-,,,honcomp,,"Percentage
-Correct"
+,,,honcomp,,Percentage Correct
,Observed,,.000,1.000,
-Step 1,honcomp,.000,132,15,89.796
-,,1.000,26,27,50.943
-,Overall Percentage,,,,79.500
+Step 1,honcomp,.000,132,15,89.8%
+,,1.000,26,27,50.9%
+,Overall Percentage,,,,79.5%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
AT_CHECK([diff file1 file2], [1], [dnl
8,10c8,10
-< Included in Analysis,100,100.00
-< Missing Cases,0,.00
-< Total,100,100.00
+< Included in Analysis,100,100.0%
+< Missing Cases,0,.0%
+< Total,100,100.0%
---
-> Included in Analysis,100,99.01
-> Missing Cases,1,.99
-> Total,101,100.00
+> Included in Analysis,100,99.0%
+> Missing Cases,1,1.0%
+> Total,101,100.0%
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv ci.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.000,0
-1.000,1
+.000,.000
+1.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,196,100.000
-Missing Cases,0,.000
-Total,196,100.000
+Included in Analysis,196,100.0%
+Missing Cases,0,.0%
+Total,196,100.0%
note: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,211.195,.120,.172
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,211.195,.120,.172
Table: Categorical Variables' Codings
-,,,Parameter coding,
-,,Frequency,(1),(2)
+,,Frequency,Parameter coding,
+,,,(1),(2)
sciostat,1.000,77,1,0
,2.000,49,0,1
,3.000,70,0,0
Table: Classification Table
,,,Predicted,,
-,,,disease,,"Percentage
-Correct"
+,,,disease,,Percentage Correct
,Observed,,.000,1.000,
-Step 1,disease,.000,131,8,94.245
-,,1.000,41,16,28.070
-,Overall Percentage,,,,75.000
+Step 1,disease,.000,131,8,94.2%
+,,1.000,41,16,28.1%
+,Overall Percentage,,,,75.0%
Table: Variables in the Equation
-,,,,,,,,95% CI for Exp(B),
-,,B,S.E.,Wald,df,Sig.,Exp(B),Lower,Upper
+,,B,S.E.,Wald,df,Sig.,Exp(B),95% CI for Exp(B),
+,,,,,,,,Lower,Upper
Step 1,age,.027,.009,8.647,1,.003,1.027,1.009,1.045
,savings,.061,.386,.025,1,.874,1.063,.499,2.264
,sciostat,,,.440,2,.803,,,
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-score: factor,26,100%,0,0%,26,100%
-score: ,26,100%,0,0%,26,100%
+score: factor,26,100.0%,0,.0%,26,100.0%
+score: ,26,100.0%,0,.0%,26,100.0%
Table: Report
,factor,Mean,N,Std. Deviation
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-score: ,4,100%,0,0%,4,100%
+score: ,4,100.0%,0,.0%,4,100.0%
Table: Report
,Mean,N,Std. Deviation
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1 * g2,6,75%,2,25%,8,100%
-a: g2,6,75%,2,25%,8,100%
-a: ,7,87.5%,1,12.5%,8,100%
+a: g1 × g2,6,75.0%,2,25.0%,8,100.0%
+a: g2,6,75.0%,2,25.0%,8,100.0%
+a: ,7,87.5%,1,12.5%,8,100.0%
Table: Report
,g1,g2,Mean,N
a,1.00,11.00,4.00,1.00
-,1.00,21.00,3.00,1.00
-,2.00,21.00,6.00,1.00
-,2.00,31.00,5.67,3.00
+,,21.00,3.00,1.00
+,2.00,,6.00,1.00
+,,31.00,5.67,3.00
Table: Report
,g2,Mean,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-test1: group,10,100%,0,0%,10,100%
-test1: ,10,100%,0,0%,10,100%
+test1: group,10,100.0%,0,.0%,10,100.0%
+test1: ,10,100.0%,0,.0%,10,100.0%
Table: Report
,group,Mean,N,Std. Deviation,Sum,Min,Max,Range,Variance,Kurtosis,Skewness
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-test1: group,10,100%,0,0%,10,100%
-test1: ,10,100%,0,0%,10,100%
+test1: group,10,100.0%,0,.0%,10,100.0%
+test1: ,10,100.0%,0,.0%,10,100.0%
Table: Report
,group,Mean,N,S.E. Mean,S.E. Skew,S.E. Kurt
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-x: ,5,100%,0,0%,5,100%
-y: ,5,100%,0,0%,5,100%
+x: ,5,100.0%,0,.0%,5,100.0%
+y: ,5,100.0%,0,.0%,5,100.0%
Table: Report
,Mean,Harmonic Mean,Geom. Mean
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-score: ,5,100%,0,0%,5,100%
+score: ,5,100.0%,0,.0%,5,100.0%
Table: Report
,Mean,N,Std. Deviation,S.E. Mean,Sum,Min,Max,Range,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,First,Last,Harmonic Mean,Geom. Mean
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-score: ,5,100%,0,0%,5,100%
+score: ,5,100.0%,0,.0%,5,100.0%
Table: Report
,Mean,N,Std. Deviation
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-score: ,5,100%,0,0%,5,100%
+score: ,5,100.0%,0,.0%,5,100.0%
Table: Report
-
-score
])
AT_CLEANUP
])
-AT_CHECK([pspp -O format=csv means-miss-table.sps], [0],
- [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt means-miss-table.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Case Processing Summary
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
-b: g1,6,85.7143%,1,14.2857%,7,100%
-b: ,6,85.7143%,1,14.2857%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
+b: g1,6,85.7%,1,14.3%,7,100.0%
+b: ,6,85.7%,1,14.3%,7,100.0%
Table: Report
,g1,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
Table: Report
,g1,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
-b: g1,6,85.7143%,1,14.2857%,7,100%
-b: ,6,85.7143%,1,14.2857%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
+b: g1,6,85.7%,1,14.3%,7,100.0%
+b: ,6,85.7%,1,14.3%,7,100.0%
Table: Report
,g1,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
Table: Report
,g1,N
,N
a,7.00
])
-
AT_CLEANUP
-
-
-
-
AT_SETUP([MEANS user missing values])
AT_KEYWORDS([categorical categoricals])
])
-AT_CHECK([pspp -O format=csv means-missing.sps], [0],
- [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt means-missing.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Case Processing Summary
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,6,85.7143%,1,14.2857%,7,100%
-a: ,7,100%,0,0%,7,100%
-b: g1,5,71.4286%,2,28.5714%,7,100%
-b: ,6,85.7143%,1,14.2857%,7,100%
+a: g1,6,85.7%,1,14.3%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
+b: g1,5,71.4%,2,28.6%,7,100.0%
+b: ,6,85.7%,1,14.3%,7,100.0%
Table: Report
,g1,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
-b: g1,7,100%,0,0%,7,100%
-b: ,7,100%,0,0%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
+b: g1,7,100.0%,0,.0%,7,100.0%
+b: ,7,100.0%,0,.0%,7,100.0%
Table: Report
,g1,N
,Cases,,,,,
,Included,,Excluded,,Total,
,N,Percent,N,Percent,N,Percent
-a: g1,7,100%,0,0%,7,100%
-a: ,7,100%,0,0%,7,100%
-b: g1,6,85.7143%,1,14.2857%,7,100%
-b: ,6,85.7143%,1,14.2857%,7,100%
+a: g1,7,100.0%,0,.0%,7,100.0%
+a: ,7,100.0%,0,.0%,7,100.0%
+b: g1,6,85.7%,1,14.3%,7,100.0%
+b: ,6,85.7%,1,14.3%,7,100.0%
Table: Report
,g1,N
a,7.00
b,6.00
])
-
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1.000,6.000,.286,.300,.551
-,Group2,2.000,15.000,.714,,
+x,Group 1,1.000,6.000,.286,.300,.551
+,Group 2,2.000,15.000,.714,,
,Total,,21.000,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,7,.538,.400,.229
-,Group2,2,6,.462,,
+x,Group 1,1,7,.538,.400,.229
+,Group 2,2,6,.462,,
,Total,,13,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,8,.500,.400,.284
-,Group2,2,8,.500,,
+x,Group 1,1,8,.500,.400,.284
+,Group 2,2,8,.500,,
,Total,,16,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.478,.600,.164
-,Group2,2,12,.522,,
+x,Group 1,1,11,.478,.600,.164
+,Group 2,2,12,.522,,
,Total,,23,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.550,.600,.404
-,Group2,2,9,.450,,
+x,Group 1,1,11,.550,.600,.404
+,Group 2,2,9,.450,,
,Total,,20,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.500,.600,.228
-,Group2,2,11,.500,,
+x,Group 1,1,11,.500,.600,.228
+,Group 2,2,11,.500,,
,Total,,22,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,8,.348,.500,.210
-,Group2,2,15,.652,,
+x,Group 1,1,8,.348,.500,.210
+,Group 2,2,15,.652,,
,Total,,23,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,12,.667,.500,.238
-,Group2,2,6,.333,,
+x,Group 1,1,12,.667,.500,.238
+,Group 2,2,6,.333,,
,Total,,18,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,10,.500,.500,1.000
-,Group2,2,10,.500,,
+x,Group 1,1,10,.500,.500,1.000
+,Group 2,2,10,.500,,
,Total,,20,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,<= 10,10.000,.385,.500,.327
-,Group2,,16.000,.615,,
+x,Group 1,<= 10,10.000,.385,.500,.327
+,Group 2,,16.000,.615,,
,Total,,26.000,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,10.000,10.000,.435,.500,.678
-,Group2,20.000,13.000,.565,,
+x,Group 1,10.000,10.000,.435,.500,.678
+,Group 2,20.000,13.000,.565,,
,Total,,23.000,1.000,,
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: x
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,3.00,2.33,.67
2.00,3.00,2.33,.67
3.10,4.00,2.33,1.67
Total,14.00,,
Table: y
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,7.00,3.50,3.50
2.00,4.00,3.50,.50
3.00,1.00,3.50,-2.50
Total,14.00,,
Table: Test Statistics
-,x,y
-Chi-Square,3.14,6.00
-df,5,3
-Asymp. Sig.,.678,.112
+,Chi-square,df,Asymp. Sig.
+x,3.14,5,.678
+y,6.00,3,.112
Table: y
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,7.00,2.63,4.38
2.00,4.00,3.50,.50
3.00,1.00,4.38,-3.38
Total,14.00,,
Table: Test Statistics
-,y
-Chi-Square,10.61
-df,3
-Asymp. Sig.,.014
+,Chi-square,df,Asymp. Sig.
+y,10.61,3,.014
Table: Frequencies
,x,,,,y,,,
Total,,10.00,,,,7.00,,
Table: Test Statistics
-,x,y
-Chi-Square,.13,4.13
-df,2,2
-Asymp. Sig.,.936,.127
+,Chi-square,df,Asymp. Sig.
+x,.13,2,.936
+y,4.13,2,.127
])
AT_CLEANUP
])
AT_CHECK([pspp -O format=csv npar.sps], [1], [dnl
-"error: CHISQUARE test specified 6 expected values, but 4 distinct values were encountered in variable y."
+"error: CHISQUARE test specified 6 expected values, but variable y has 4 distinct values."
Table: Test Statistics
-,y
-Chi-Square,.00
-df,0
-Asymp. Sig.,1.000
+,Chi-square,df,Asymp. Sig.
+y,.00,0,1.000
])
AT_CLEANUP
Total,,12.00,,,,15.00,,
Table: Test Statistics
-,x,y
-Chi-Square,17.33,22.87
-df,7,7
-Asymp. Sig.,.015,.002
+,Chi-square,df,Asymp. Sig.
+x,17.33,7,.015
+y,22.87,7,.002
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
-,,,,,
x,12.00,2.47,1.19,1.00,5.00
y,15.00,2.07,1.33,1.00,5.00
])
Total,,14.00,,,,14.00,,
Table: Test Statistics
-,x,y
-Chi-Square,13.43,26.00
-df,7,7
-Asymp. Sig.,.062,.001
+,Chi-square,df,Asymp. Sig.
+x,13.43,7,.062
+y,26.00,7,.001
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
-,,,,,
x,14.00,2.69,1.23,1.00,5.00
y,14.00,1.86,1.10,1.00,4.00
])
.
])
-AT_CHECK([pspp -o pspp.csv kw-simple.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt kw-simple.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Ranks
-,gv,N,Mean Rank
+,,N,Mean Rank
xscore,timed out,5,4.400
,hit wicket,5,7.400
,handled the ball,4,11.500
,Total,14,
Table: Test Statistics
-,,xscore
-Chi-Square,,6.406
-df,,2
-Asymp. Sig.,,.041
+,xscore
+Chi-Square,6.406
+df,2
+Asymp. Sig.,.041
])
AT_CHECK([pspp -o pspp.csv kw-multi.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Ranks
-,gv,N,Mean Rank
+,,N,Mean Rank
xscore,timed out,5,4.400
,hit wicket,5,7.400
,handled the ball,4,11.500
,Total,14,
Table: Test Statistics
-,,xscore,yscore,
-Chi-Square,,6.406,6.406,
-df,,2,2,
-Asymp. Sig.,,.041,.041,
+,xscore,yscore
+Chi-Square,6.406,6.406
+df,2,2
+Asymp. Sig.,.041,.041
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv npar-mann-whitney.sps], [0], [dnl
Table: Ranks
-,N,,,Mean Rank,,Sum of Ranks,
-,0,1,Total,0,1,0,1
-height,15.0000,15.0000,30.0000,14.5333,16.4667,218.0000,247.0000
+,,N,Mean Rank,Sum of Ranks
+height,0,15,14.5333,218.0000
+,1,15,16.4667,247.0000
+,Total,30,,
Table: Test Statistics
,Mann-Whitney U,Wilcoxon W,Z,Asymp. Sig. (2-tailed)
AT_CHECK([pspp -O format=csv npar-mann-whitney.sps], [0], [dnl
Table: Ranks
-,N,,,Mean Rank,,Sum of Ranks,
-,.000,1.000,Total,.000,1.000,.000,1.000
-IOS: Familie,114.000,115.000,229.000,110.018,119.939,12542.000,13793.000
-IOS: Freunde,115.000,115.000,230.000,108.339,122.661,12459.000,14106.000
-IOS: Partner*in,97.000,91.000,188.000,95.351,93.593,9249.000,8517.000
-IOS: Bekannte,115.000,115.000,230.000,111.065,119.935,12772.500,13792.500
+,,N,Mean Rank,Sum of Ranks
+IOS: Familie,.000,114,110.018,12542.000
+,1.000,115,119.939,13793.000
+,Total,229,,
+IOS: Freunde,.000,115,108.339,12459.000
+,1.000,115,122.661,14106.000
+,Total,230,,
+IOS: Partner*in,.000,97,95.351,9249.000
+,1.000,91,93.593,8517.000
+,Total,188,,
+IOS: Bekannte,.000,115,111.065,12772.500
+,1.000,115,119.935,13792.500
+,Total,230,,
Table: Test Statistics
,Mann-Whitney U,Wilcoxon W,Z,Asymp. Sig. (2-tailed)
v7,5,4
Table: Test Statistics
+,Value
N,9
Cochran's Q,12.735
df,6
AT_CHECK([pspp -O format=csv mcnemar.sps], [0], [dnl
Table: v1 & v2
-v1,v2,
-,.000,1.000
+,v2,
+v1,.000,1.000
.000,4,9
1.000,2,5
Table: v1 & junk
-v1,junk,
-,.000,1.000
+,junk,
+v1,.000,1.000
.000,8,5
1.000,2,5
AT_CHECK([pspp -O format=csv npar.sps], [1], [ignore])
AT_CLEANUP
-
\ No newline at end of file
+
.
])
-AT_CHECK([pspp -O format=csv oneway.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt oneway.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,Manufacturer,,,,,Lower Bound,Upper Bound,,
Breaking Strain,Aspeger,5,2.20,1.30,.58,.58,3.82,1.00,4.00
,Bloggs,5,3.20,1.30,.58,1.58,4.82,2.00,5.00
,Charlies,5,5.00,1.58,.71,3.04,6.96,3.00,7.00
,Total,43.73,14,,,
Table: Contrast Coefficients
-,,Manufacturer,,
-,,Aspeger,Bloggs,Charlies
-Contrast,1,-2,1,1
-,2,0,-1,1
+,Manufacturer,,
+Contrast,Aspeger,Bloggs,Charlies
+1,-2,1,1
+2,0,-1,1
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,3.80,1.54,2.47,12,.029
-,,2,1.80,.89,2.03,12,.065
-,Does not assume equal,1,3.80,1.48,2.56,8.74,.031
+Breaking Strain,Assume equal variances,1,3.80,1.54,2.47,12.00,.029
+,,2,1.80,.89,2.03,12.00,.065
+,Does not assume equal variances,1,3.80,1.48,2.56,8.74,.031
,,2,1.80,.92,1.96,7.72,.086
])
AT_CLEANUP
.
])
-AT_CHECK([pspp -O format=csv oneway-splits.sps], [0],
-[Variable,Value,Label
-S,1.00,
+AT_CHECK([pspp -o pspp.csv -o pspp.txt oneway-splits.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Split Values
+Variable,Value
+S,1.00
Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,Manufacturer,,,,,Lower Bound,Upper Bound,,
Breaking Strain,Aspeger,5,2.20,1.30,.58,.58,3.82,1.00,4.00
,Bloggs,2,3.50,2.12,1.50,-15.56,22.56,2.00,5.00
,Total,7,2.57,1.51,.57,1.17,3.97,1.00,5.00
,Total,13.71,6,,,
Table: Contrast Coefficients
-,,Manufacturer,
-,,Aspeger,Bloggs
-Contrast,1,-2,2
-,2,-1,1
+,Manufacturer,
+Contrast,Aspeger,Bloggs
+1,-2,2
+2,-1,1
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,2.60,2.52,1.03,5,.349
-,,2,1.30,1.26,1.03,5,.349
-,Does not assume equal,1,2.60,3.22,.81,1.32,.539
+Breaking Strain,Assume equal variances,1,2.60,2.52,1.03,5.00,.349
+,,2,1.30,1.26,1.03,5.00,.349
+,Does not assume equal variances,1,2.60,3.22,.81,1.32,.539
,,2,1.30,1.61,.81,1.32,.539
-Variable,Value,Label
-S,2.00,
+Table: Split Values
+Variable,Value
+S,2.00
Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,Manufacturer,,,,,Lower Bound,Upper Bound,,
Breaking Strain,Bloggs,3,3.00,1.00,.58,.52,5.48,2.00,4.00
,Charlies,5,5.00,1.58,.71,3.04,6.96,3.00,7.00
,Total,8,4.25,1.67,.59,2.85,5.65,2.00,7.00
,Total,19.50,7,,,
Table: Contrast Coefficients
-,,Manufacturer,
-,,Bloggs,Charlies
-Contrast,1,-2,2
-,2,-1,1
+,Manufacturer,
+Contrast,Bloggs,Charlies
+1,-2,2
+2,-1,1
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,4.00,2.07,1.94,6,.101
-,,2,2.00,1.03,1.94,6,.101
-,Does not assume equal,1,4.00,1.83,2.19,5.88,.072
+Breaking Strain,Assume equal variances,1,4.00,2.07,1.94,6.00,.101
+,,2,2.00,1.03,1.94,6.00,.101
+,Does not assume equal variances,1,4.00,1.83,2.19,5.88,.072
,,2,2.00,.91,2.19,5.88,.072
])
-
AT_CLEANUP
AT_CHECK([pspp -O format=csv oneway-descriptives.sps], [0],
[Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,BRAND,,,,,Lower Bound,Upper Bound,,
QUALITY,11.00,5,12.20,1.30,.58,10.58,13.82,11.00,14.00
,25.00,5,13.20,1.30,.58,11.58,14.82,12.00,15.00
,301.00,5,15.00,1.58,.71,13.04,16.96,13.00,17.00
.
])
-AT_CHECK([pspp -o pspp.csv multivar.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt multivar.sps])
dnl Some machines return 3.88 instead of 3.87 below (see bug #31611).
-AT_CHECK([sed 's/^,Within Groups,3.88/,Within Groups,3.87/' pspp.csv], [0], [dnl
-Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+AT_CHECK([sed 's/^,Within Groups,3.88/,Within Groups,3.87/' pspp.csv], [0],
+ [Table: Descriptives
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,g,,,,,Lower Bound,Upper Bound,,
x,10.00,3,3.67,4.62,2.67,-7.81,15.14,1.00,9.00
,20.00,5,.80,.45,.20,.24,1.36,.00,1.00
,30.00,8,.88,.64,.23,.34,1.41,.00,2.00
,Total,205.33,23,,,
Table: Contrast Coefficients
-,,g,,,
-,,10.00,20.00,30.00,40.00
-Contrast,1,3,2,0,-5
-,2,2,-9,7,0
+,g,,,
+Contrast,10.00,20.00,30.00,40.00
+1,3,2,0,-5
+2,2,-9,7,0
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-x,Assume equal variances,1,-7.40,6.67,1.11,20,.280
-,,2,6.26,12.32,.51,20,.617
-,Does not assume equal,1,-7.40,10.04,-.74,4.53,.497
+x,Assume equal variances,1,-7.40,6.67,1.11,20.00,.280
+,,2,6.26,12.32,.51,20.00,.617
+,Does not assume equal variances,1,-7.40,10.04,-.74,4.53,1.503
,,2,6.26,5.85,1.07,2.87,.366
-y,Assume equal variances,1,-6.88,1.16,5.94,20,.000
-,,2,3.50,2.14,1.63,20,.118
-,Does not assume equal,1,-6.88,.91,-7.51,7.00,.000
+y,Assume equal variances,1,-6.88,1.16,5.94,20.00,.000
+,,2,3.50,2.14,1.63,20.00,.118
+,Does not assume equal variances,1,-6.88,.91,-7.51,7.00,2.000
,,2,3.50,1.32,2.65,7.00,.033
-z,Assume equal variances,1,-9.70,8.07,1.20,20,.243
-,,2,11.73,14.91,.79,20,.440
-,Does not assume equal,1,-9.70,9.57,-1.01,3.64,.373
+z,Assume equal variances,1,-9.70,8.07,1.20,20.00,.243
+,,2,11.73,14.91,.79,20.00,.440
+,Does not assume equal variances,1,-9.70,9.57,-1.01,3.64,1.627
,,2,11.73,14.53,.81,9.88,.438
])
.
])
-AT_CHECK([pspp -O format=csv oneway-pig.sps], [0],
-[Table: Descriptives
-,,,,,,95% Confidence Interval for Mean,,,
-,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
+AT_CHECK([pspp -o pspp.csv -o pspp.txt oneway-pig.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Descriptives
+,,N,Mean,Std. Deviation,Std. Error,95% Confidence Interval for Mean,,Minimum,Maximum
+,family,,,,,Lower Bound,Upper Bound,,
pigmentation,1.000,5,38.600,2.702,1.208,35.245,41.955,36.000,43.000
,2.000,5,46.000,1.732,.775,43.849,48.151,43.000,47.000
,3.000,5,46.400,4.336,1.939,41.016,51.784,40.000,50.000
,Total,676.550,19,,,
Table: Multiple Comparisons (pigmentation)
-,,,Mean Difference,,,95% Confidence Interval,
-,(I) family,(J) family,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
+,,,Mean Difference (I - J),Std. Error,Sig.,95% Confidence Interval,
+,(J) Family,(J) Family,,,,Lower Bound,Upper Bound
LSD,1.000,2.000,-7.400,2.223,.004,-12.112,-2.688
,,3.000,-7.800,2.223,.003,-12.512,-3.088
,,4.000,-13.800,2.223,.000,-18.512,-9.088
,,2.000,6.400,2.223,.065,-.286,13.086
,,3.000,6.000,2.223,.095,-.686,12.686
])
-
AT_CLEANUP
/posthoc tukey gh.
])
-AT_CHECK([pspp -O format=csv oneway-tukey.sps], [0],
-[Table: ANOVA
+AT_CHECK([pspp -o pspp.csv -o pspp.txt oneway-tukey.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
libido,Between Groups,20.133,2,10.067,5.119,.025
,Within Groups,23.600,12,1.967,,
,Total,43.733,14,,,
Table: Multiple Comparisons (libido)
-,,,Mean Difference,,,95% Confidence Interval,
-,(I) Dose of Viagra,(J) Dose of Viagra,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
+,,,Mean Difference (I - J),Std. Error,Sig.,95% Confidence Interval,
+,(J) Family,(J) Family,,,,Lower Bound,Upper Bound
Tukey HSD,Placebo,1 Dose,-1.000,.887,.516,-3.366,1.366
,,2 Doses,-2.800,.887,.021,-5.166,-.434
,1 Dose,Placebo,1.000,.887,.516,-1.366,3.366
,,2 Doses,-1.800,.887,.147,-4.166,.566
,2 Doses,Placebo,2.800,.887,.021,.434,5.166
,,1 Dose,1.800,.887,.147,-.566,4.166
-Games-Howell,Placebo,1 Dose,-1.000,.887,.479,-3.356,1.356
+Games-Howell,Placebo,,-1.000,.887,.479,-3.356,1.356
,,2 Doses,-2.800,.887,.039,-5.439,-.161
,1 Dose,Placebo,1.000,.887,.479,-1.356,3.356
,,2 Doses,-1.800,.887,.185,-4.439,.839
,Total,96.5500,19,,,
Table: Multiple Comparisons (score)
-,,,Mean Difference,,,95% Confidence Interval,
-,(I) program,(J) program,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
+,,,Mean Difference (I - J),Std. Error,Sig.,95% Confidence Interval,
+,(J) Family,(J) Family,,,,Lower Bound,Upper Bound
Šidák,1.0000,2.0000,3.0000,1.0198,.056,-.0575,6.0575
,,3.0000,-.4000,1.0198,.999,-3.4575,2.6575
,,4.0000,3.2000,1.0198,.038,.1425,6.2575
,Total,1555.375,39,,,
Table: Multiple Comparisons (Days of Use)
-,,,Mean Difference,,,95% Confidence Interval,
-,(I) group,(J) group,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
+,,,Mean Difference (I - J),Std. Error,Sig.,95% Confidence Interval,
+,(J) Family,(J) Family,,,,Lower Bound,Upper Bound
Scheffé,one,two,3.800,2.357,.467,-3.112,10.712
,,three,10.300,2.357,.001,3.388,17.212
,,four,6.000,2.357,.110,-.912,12.912
])
-AT_CHECK([pspp -O format=csv oneway-bad-contrast.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt oneway-bad-contrast.sps], [0], [dnl
+oneway-bad-contrast.sps:18: warning: ONEWAY: In contrast list 3, the number of coefficients (3) does not equal the number of groups (2). This contrast list will be ignored.
+])
+AT_CHECK([cat pspp.csv], [0], [dnl
"oneway-bad-contrast.sps:18: warning: ONEWAY: In contrast list 3, the number of coefficients (3) does not equal the number of groups (2). This contrast list will be ignored."
Table: ANOVA
,Total,86.36,7,,,
Table: Contrast Coefficients
-,,sex,
-,,.00,1.00
-Contrast,1,-1,1
-,2,-3,3
-,3,-9,9
+,sex,
+Contrast,.00,1.00
+1,-1,1
+2,-3,3
+3,-9,9
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-height,Assume equal variances,1,-222.27,20.23,10.99,6,.000
-,,2,-666.80,60.68,10.99,6,.000
-,,3,-2000.40,182.03,10.99,6,.000
-,Does not assume equal,1,-222.27,27.67,-8.03,2.00,.015
-,,2,-666.80,83.02,-8.03,2.00,.015
-,,3,-2000.40,249.07,-8.03,2.00,.015
-weight,Assume equal variances,1,-36.16,2.74,13.21,6,.000
-,,2,-108.48,8.21,13.21,6,.000
-,,3,-325.44,24.63,13.21,6,.000
-,Does not assume equal,1,-36.16,2.19,-16.48,5.42,.000
-,,2,-108.48,6.58,-16.48,5.42,.000
-,,3,-325.44,19.75,-16.48,5.42,.000
-temperature,Assume equal variances,1,-.98,2.74,.36,6,.733
-,,2,-2.94,8.22,.36,6,.733
-,,3,-8.83,24.67,.36,6,.733
-,Does not assume equal,1,-.98,2.07,-.47,4.19,.660
-,,2,-2.94,6.22,-.47,4.19,.660
-,,3,-8.83,18.66,-.47,4.19,.660
+height,Assume equal variances,1,-222.27,20.23,10.99,6.00,.000
+,,2,-666.80,60.68,10.99,6.00,.000
+,,3,-2000.40,182.03,10.99,6.00,.000
+,Does not assume equal variances,1,-222.27,27.67,-8.03,2.00,1.985
+,,2,-666.80,83.02,-8.03,2.00,1.985
+,,3,-2000.40,249.07,-8.03,2.00,1.985
+weight,Assume equal variances,1,-36.16,2.74,13.21,6.00,.000
+,,2,-108.48,8.21,13.21,6.00,.000
+,,3,-325.44,24.63,13.21,6.00,.000
+,Does not assume equal variances,1,-36.16,2.19,-16.48,5.42,2.000
+,,2,-108.48,6.58,-16.48,5.42,2.000
+,,3,-325.44,19.75,-16.48,5.42,2.000
+temperature,Assume equal variances,1,-.98,2.74,.36,6.00,.733
+,,2,-2.94,8.22,.36,6.00,.733
+,,3,-8.83,24.67,.36,6.00,.733
+,Does not assume equal variances,1,-.98,2.07,-.47,4.19,1.340
+,,2,-2.94,6.22,-.47,4.19,1.340
+,,3,-8.83,18.66,-.47,4.19,1.340
])
-
AT_CLEANUP
Table: Final Cluster Centers
,Cluster,
-,,
,1,2
-,,
x,6.50,19.20
y,7.50,3250.00
z,6.50,5058.00
Table: Number of Cases in each Cluster
+,,Count
Cluster,1,6
,2,5
Valid,,11
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Final Cluster Centers
,Cluster,,,
-,,,,
,1,2,3,4
-,,,,
x,NaN,NaN,NaN,3.00
Table: Number of Cases in each Cluster
+,,Count
Cluster,1,0
,2,0
,3,0
AT_CHECK([pspp -O format=csv quick-pw.sps > pspp-pw.csv])
-AT_CHECK([head -n 18 pspp-s.csv > top-s.csv])
-AT_CHECK([head -n 18 pspp-pw.csv > top-pw.csv])
+AT_CHECK([head -n 13 pspp-s.csv > top-s.csv])
+AT_CHECK([head -n 13 pspp-pw.csv > top-pw.csv])
AT_CHECK([diff top-s.csv top-pw.csv])
AT_SETUP([QUICK CLUSTER /PRINT subcommand])
AT_DATA([quick-cluster.sps], [dnl
-data list notable list /cluster (A8) x (F) y (F).
+data list notable list /cluster (A8) x y (F8.0).
begin data.
A 10.45 9.38
A 10.67 9.17
AT_CHECK([pspp -O format=csv quick-cluster.sps], [0], [dnl
Table: Initial Cluster Centers
,Cluster,,
-,,,
,1,2,3
-,,,
x,-11,-12,11
y,-12,11,11
Table: Final Cluster Centers
,Cluster,,
-,,,
,1,2,3
-,,,
x,-10,-10,10
y,-10,10,10
Table: Number of Cases in each Cluster
+,,Count
Cluster,1,20
,2,19
,3,18
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-x into Rx(RANK of x)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,Rx,RANK
Table: Data List
x,Rx
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-x into Rx(RANK of x)
-
-y into Ry(RANK of y)
-
-z into Rz(RANK of z)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,Rx,RANK
+y,Ry,RANK
+z,Rz,RANK
Table: Data List
x,y,z,Rx,Ry,Rz
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-a into Ra(RANK of a)
-
-b into Rb(RANK of b)
-
-a into RFR001(RFRACTION of a)
-
-b into RFR002(RFRACTION of b)
-
-a into count(N of a)
-
-b into Nb(N of b)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+a,Ra,RANK
+b,Rb,RANK
+a,RFR001,RFRACTION
+b,RFR002,RFRACTION
+a,count,N
+b,Nb,N
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-a into Sa(SAVAGE of a)
-
-a into Pa(PERCENT of a)
-
-a into PRO001(PROPORTION of a using BLOM)
-
-a into Na(NTILES of a)
-
-a into NOR001(NORMAL of a using BLOM)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function,Fraction
+a,Sa,SAVAGE,
+a,Pa,PERCENT,
+a,PRO001,PROPORTION,BLOM
+a,Na,NTILES,
+a,NOR001,NORMAL,BLOM
Table: Data List
a,b,Sa,Pa,PRO001,Na,NOR001
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-a into Ra(RANK of a BY g2 g1)
-
-a into Na(NORMAL of a using RANKIT BY g2 g1)
-
-Variables Created By RANK
-
-
-
-a into RAN001(RANK of a BY g2)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function,Fraction,Grouping Variables
+a,Ra,RANK,,g2 g1
+a,Na,NORMAL,RANKIT,g2 g1
-a into NOR001(NORMAL of a using RANKIT BY g2)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function,Fraction,Grouping Variables
+a,RAN001,RANK,,g2
+a,NOR001,NORMAL,RANKIT,g2
Table: Data List
a,g1,g2,Ra,Na,RAN001,NOR001
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-a into Pa(PROPORTION of a using TUKEY)
-
-a into Sa(SAVAGE of a)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function,Fraction
+a,Pa,PROPORTION,TUKEY
+a,Sa,SAVAGE,
Table: Data List
a,w,Pa,Sa
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-x into xl(RANK of x)
-
-Variables Created By RANK
-
-
-
-x into xh(RANK of x)
-
-Variables Created By RANK
-
-
-
-x into xc(RANK of x)
-
-Variables Created By RANK
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,xl,RANK
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,xh,RANK
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,xc,RANK
-x into Nx(NORMAL of x using VW)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function,Fraction
+x,Nx,NORMAL,VW
Table: Data List
x,w,xl,xh,xc,Nx
LIST.
])
AT_CHECK([pspp -O format=csv rank.sps], [0], [dnl
-Variables Created By RANK
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+age,Rm,RANK
-
-
-age into Rm(RANK of age)
-
-Variables Created By RANK
-
-
-
-age into Rf(RANK of age)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+age,Rf,RANK
Table: Data List
age,gender,Rm,Rf
])
AT_CHECK([pspp -o pspp.csv rank.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
-Variables Created By RANK
-
-
-
-foo into RAN001(RANK of foo)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+foo,RAN001,RANK
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
"rank.sps:9: warning: Missing value(s) for all variables from rx onward. These will be filled with the system-missing value or blanks, as appropriate."
-Variables Created By RANK
-
-
-
-x into RNKRA01(RANK of x)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,RNKRA01,RANK
Table: Data List
x,rx,RNKRA01
RANK x.
])
AT_CHECK([pspp -O format=csv --testing-mode rank.sps], [1], [dnl
-Variables Created By RANK
-
-
-
-x into Rx(RANK of x)
+Table: Variables Created by RANK
+Existing Variable,New Variable,Function
+x,Rx,RANK
rank.sps:14: error: RANK: DEBUG XFORM FAIL transformation executed
])
regression.sps:16: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
Table: Model Summary (v2)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.971,.942,.925,1.337
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.971,.942,.925,1.337
Table: ANOVA (v2)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,202.753,2,101.376,56.754,.000
-,Residual,12.504,7,1.786,,
-,Total,215.256,9,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,202.753,2,101.376,56.754,.000
+Residual,12.504,7,1.786,,
+Total,215.256,9,,,
Table: Coefficients (v2)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),2.191,2.357,.000,.930,.380
-,v0,1.813,1.053,.171,1.722,.129
-,v1,-3.427,.332,-1.026,-10.334,.000
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),2.191,2.357,.000,.930,.380
+v0,1.813,1.053,.171,1.722,.129
+v1,-3.427,.332,-1.026,-10.334,.000
Table: Data List
v0,v1,v2,RES1,PRED1
AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
Table: Model Summary (v2)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.971,.942,.925,1.337
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.971,.942,.925,1.337
Table: ANOVA (v2)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,202.753,2,101.376,56.754,.000
-,Residual,12.504,7,1.786,,
-,Total,215.256,9,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,202.753,2,101.376,56.754,.000
+Residual,12.504,7,1.786,,
+Total,215.256,9,,,
Table: Coefficients (v2)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),2.191,2.357,.000,.930,.380
-,v0,1.813,1.053,.171,1.722,.129
-,v1,-3.427,.332,-1.026,-10.334,.000
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),2.191,2.357,.000,.930,.380
+v0,1.813,1.053,.171,1.722,.129
+v1,-3.427,.332,-1.026,-10.334,.000
Table: Model Summary (v2)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.971,.942,.925,1.337
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.971,.942,.925,1.337
Table: ANOVA (v2)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,202.753,2,101.376,56.754,.000
-,Residual,12.504,7,1.786,,
-,Total,215.256,9,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,202.753,2,101.376,56.754,.000
+Residual,12.504,7,1.786,,
+Total,215.256,9,,,
Table: Coefficients (v2)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),2.191,2.357,.000,.930,.380
-,v0,1.813,1.053,.171,1.722,.129
-,v1,-3.427,.332,-1.026,-10.334,.000
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),2.191,2.357,.000,.930,.380
+v0,1.813,1.053,.171,1.722,.129
+v1,-3.427,.332,-1.026,-10.334,.000
Table: Data List
v0,v1,v2,RES1,PRED1
v1,F8.0
Table: Model Summary (v0)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.05,.00,.00,8.11
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.05,.00,.00,8.11
Table: ANOVA (v0)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,235.23,1,235.23,3.58,.059
-,Residual,98438.40,1498,65.71,,
-,Total,98673.63,1499,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,235.23,1,235.23,3.58,.059
+Residual,98438.40,1498,65.71,,
+Total,98673.63,1499,,,
Table: Coefficients (v0)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),1.24,.42,.00,2.95,.003
-,v1,1.37,.72,.05,1.89,.059
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),1.24,.42,.00,2.95,.003
+v1,1.37,.72,.05,1.89,.059
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
Table: Model Summary (science)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.699,.489,.479,7.148
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.699,.489,.479,7.148
Table: ANOVA (science)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,9543.721,4,2385.930,46.695,.000
-,Residual,9963.779,195,51.096,,
-,Total,19507.500,199,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,9543.721,4,2385.930,46.695,.000
+Residual,9963.779,195,51.096,,
+Total,19507.500,199,,,
Table: Coefficients (science)
-,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
-,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
-,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
-,math,.389,.074,.368,5.252,.000,.243,.535
-,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
-,socst,.050,.062,.054,.801,.424,-.073,.173
-,read,.335,.073,.347,4.607,.000,.192,.479
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.,95% Confidence Interval for B,
+,B,Std. Error,Beta,,,Lower Bound,Upper Bound
+(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
+math,.389,.074,.368,5.252,.000,.243,.535
+female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
+socst,.050,.062,.054,.801,.424,-.073,.173
+read,.335,.073,.347,4.607,.000,.192,.479
])
AT_CHECK([pspp -o pspp.csv regression.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Model Summary (X1)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.95,.89,.84,15.08
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.95,.89,.84,15.08
Table: ANOVA (X1)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,3820.45,1,3820.45,16.81,.055
-,Residual,454.55,2,227.27,,
-,Total,4275.00,3,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,3820.45,1,3820.45,16.81,.055
+Residual,454.55,2,227.27,,
+Total,4275.00,3,,,
Table: Coefficients (X1)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),85.45,10.16,.00,8.41,.004
-,Y,-3.73,.91,-.95,-4.10,.055
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),85.45,10.16,.00,8.41,.004
+Y,-3.73,.91,-.95,-4.10,.055
Table: Data List
text,Y,X1,RES1
-V00276601 ,.00,90.00,4.55
-V00292909 ,10.00,30.00,-18.18
-V00291204 ,20.00,20.00,9.09
-V00300070 ,.00,90.00,4.55
+V00276601,.00,90.00,4.55
+V00292909,10.00,30.00,-18.18
+V00291204,20.00,20.00,9.09
+V00300070,.00,90.00,4.55
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
Table: Model Summary (value)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.612,.374,.338,6.176
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.612,.374,.338,6.176
Table: ANOVA (value)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,388.065,1,388.065,10.173,.005
-,Residual,648.498,17,38.147,,
-,Total,1036.563,18,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,388.065,1,388.065,10.173,.005
+Residual,648.498,17,38.147,,
+Total,1036.563,18,,,
Table: Coefficients (value)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,(Constant),.927,2.247,.000,.413,.685
-,number,.611,.192,.612,3.189,.005
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),.927,2.247,.000,.413,.685
+number,.611,.192,.612,3.189,.005
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv regression-origin.sps], [0], [dnl
Table: Model Summary (value)
-,R,R Square,Adjusted R Square,Std. Error of the Estimate
-,.802,.643,.622,6.032
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.802,.643,.622,6.032
Table: ANOVA (value)
-,,Sum of Squares,df,Mean Square,F,Sig.
-,Regression,1181.726,1,1181.726,32.475,.000
-,Residual,654.989,18,36.388,,
-,Total,1836.715,19,,,
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,1181.726,1,1181.726,32.475,.000
+Residual,654.989,18,36.388,,
+Total,1836.715,19,,,
Table: Coefficients (value)
-,,Unstandardized Coefficients,,Standardized Coefficients,,
-,,B,Std. Error,Beta,t,Sig.
-,number,.672,.118,.802,5.699,.000
-,,,,,,
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+number,.672,.118,.802,5.699,.000
])
AT_CLEANUP
+
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([REGRESSION tutorial example])
+cp $top_srcdir/examples/repairs.sav .
+AT_DATA([regression.sps], [dnl
+GET FILE='repairs.sav'.
+REGRESSION /VARIABLES=mtbf duty_cycle /DEPENDENT=mttr.
+REGRESSION /VARIABLES=mtbf /DEPENDENT=mttr.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt regression.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Model Summary (Mean time to repair (hours) )
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.99,.99,.99,2.24
+
+Table: ANOVA (Mean time to repair (hours) )
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,5308.87,2,2654.44,530.75,.000
+Residual,60.02,12,5.00,,
+Total,5368.89,14,,,
+
+Table: Coefficients (Mean time to repair (hours) )
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),9.81,1.50,.00,6.54,.000
+Mean time between failures (months) ,3.10,.10,.99,32.43,.000
+Ratio of working to non-working time,1.09,1.78,.02,.61,.552
+
+Table: Model Summary (Mean time to repair (hours) )
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.99,.99,.99,2.18
+
+Table: ANOVA (Mean time to repair (hours) )
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,5307.00,1,5307.00,1114.73,.000
+Residual,61.89,13,4.76,,
+Total,5368.89,14,,,
+
+Table: Coefficients (Mean time to repair (hours) )
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
+,B,Std. Error,Beta,,
+(Constant),10.50,.96,.00,10.96,.000
+Mean time between failures (months) ,3.11,.09,.99,33.39,.000
+])
+AT_CLEANUP
/VARIABLES=var6 var8 var15 var17
.
])
-AT_CHECK([pspp -o pspp.csv reliability.sps], [0],
+AT_CHECK([pspp -o pspp.csv -o pspp.txt reliability.sps], [0],
[reliability.sps:174: warning: RELIABILITY: The STATISTICS subcommand is not yet implemented. No statistics will be produced.
])
AT_CHECK([cat pspp.csv], [0], [dnl
Scale: Everything
Table: Case Processing Summary
-,,N,%
-Cases,Valid,131,92.91
-,Excluded,10,7.09
-,Total,141,100.00
+Cases,N,Percent
+Valid,131,92.9%
+Excluded,10,7.1%
+Total,141,100.0%
Table: Reliability Statistics
Cronbach's Alpha,N of Items
Scale: Nothing
Table: Case Processing Summary
-,,N,%
-Cases,Valid,131,92.91
-,Excluded,10,7.09
-,Total,141,100.00
+Cases,N,Percent
+Valid,131,92.9%
+Excluded,10,7.1%
+Total,141,100.0%
Table: Reliability Statistics
Cronbach's Alpha,Part 1,Value,.55
Scale: Totals
Table: Case Processing Summary
-,,N,%
-Cases,Valid,131,92.91
-,Excluded,10,7.09
-,Total,141,100.00
+Cases,N,Percent
+Valid,131,92.9%
+Excluded,10,7.1%
+Total,141,100.0%
Table: Reliability Statistics
Cronbach's Alpha,N of Items
Scale: ANY
Table: Case Processing Summary
-,,N,%
-Cases,Valid,131,92.91
-,Excluded,10,7.09
-,Total,141,100.00
+Cases,N,Percent
+Valid,131,92.9%
+Excluded,10,7.1%
+Total,141,100.0%
Table: Reliability Statistics
Cronbach's Alpha,N of Items
])
AT_CHECK([ln -s $top_srcdir/examples/hotel.sav .], [0])
-AT_CHECK([pspp -O format=csv tut-example.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt tut-example.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Scale: ANY
Table: Case Processing Summary
-,,N,%
-Cases,Valid,17,100.00
-,Excluded,0,.00
-,Total,17,100.00
+Cases,N,Percent
+Valid,17,100.0%
+Excluded,0,.0%
+Total,17,100.0%
Table: Reliability Statistics
Cronbach's Alpha,N of Items
.81,3
])
-
AT_CLEANUP
Positive,5,50.000
Negative,5,50.000
-Table: Area Under the Curve (x)
-,,,Asymp. 99% Confidence Interval,
-Area,Std. Error,Asymptotic Sig.,Lower Bound,Upper Bound
-.910,.030,.000,.839,.981
-
-Table: Coordinates of the Curve (x)
-Positive if greater than or equal to,Sensitivity,1 - Specificity
-.000,1.000,1.000
-1.500,.960,.440
-2.500,.880,.160
-3.500,.680,.060
-4.500,.400,.020
-6.000,.000,.000
+Table: Area Under the Curve
+,Area,Std. Error,Asymptotic Sig.,Asymp. 99% Confidence Interval,
+Variable under test,,,,Lower Bound,Upper Bound
+x,.910,.030,.000,.839,.981
+
+Table: Coordinates of the Curve
+Test variable,Positive if greater than or equal to,Sensitivity,1 - Specificity
+x,.000,1.000,1.000
+,1.500,.960,.440
+,2.500,.880,.160
+,3.500,.680,.060
+,4.500,.400,.020
+,6.000,.000,.000
])
AT_CLEANUP
Negative,5,50.000
Table: Area Under the Curve
-,,,,Asymp. 95% Confidence Interval,
-Variable under test,Area,Std. Error,Asymptotic Sig.,Lower Bound,Upper Bound
+,Area,Std. Error,Asymptotic Sig.,Asymp. 95% Confidence Interval,
+Variable under test,,,,Lower Bound,Upper Bound
x,.910,.030,.000,.860,.960
y,.697,.052,.001,.611,.783
print = se
.
])
-AT_CHECK([pspp -o pspp.csv roc.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt roc.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Case Summary
,Valid N (listwise),
Positive,14,14.000
Negative,14,14.000
-Table: Area Under the Curve (x)
-,,,Asymp. 95% Confidence Interval,
-Area,Std. Error,Asymptotic Sig.,Lower Bound,Upper Bound
-.490,.111,.927,.307,.673
+Table: Area Under the Curve
+,Area,Std. Error,Asymptotic Sig.,Asymp. 95% Confidence Interval,
+Variable under test,,,,Lower Bound,Upper Bound
+x,.490,.111,.927,.307,.673
])
AT_CLEANUP
t-test /PAIRS a with b (PAIRED).
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
ID,F8.0
B,F8.0
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,A,2.00,5,.71,.32
-,B,4.00,5,1.54,.69
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,A,5,2.00,.71,.32
+,B,5,4.00,1.54,.69
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,A & B,5,.92,.028
+Pair 1,A & B,5,.918,.028
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,A - B,-2.00,.94,.42,-3.16,-.84,-4.78,4,.009
])
-
AT_CLEANUP
d,F8.0
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,a,2.00,5,.71,.32
-,b,4.00,5,1.54,.69
-Pair 2,c,5.10,5,.69,.31
-,d,3.80,5,.16,.07
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,a,5,2.00,.71,.32
+,b,5,4.00,1.54,.69
+Pair 2,c,5,5.10,.69,.31
+,d,5,3.80,.16,.07
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,a & b,5,.92,.028
-Pair 2,c & d,5,-.92,.028
+Pair 1,a & b,5,.918,.028
+Pair 2,c & d,5,-.918,.028
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,a - b,-2.00,.94,.42,-3.16,-.84,-4.78,4,.009
Pair 2,c - d,1.30,.84,.37,.26,2.34,3.47,4,.025
])
d,F8.0
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,a,2.00,5,.71,.32
-,c,5.10,5,.69,.31
-Pair 2,b,4.00,5,1.54,.69
-,d,3.80,5,.16,.07
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,a,5,2.00,.71,.32
+,c,5,5.10,.69,.31
+Pair 2,b,5,4.00,1.54,.69
+,d,5,3.80,.16,.07
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,a & c,5,.41,.493
-Pair 2,b & d,5,-.87,.054
+Pair 1,a & c,5,.410,.493
+Pair 2,b & d,5,-.872,.054
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,a - c,-3.10,.76,.34,-4.04,-2.16,-9.14,4,.001
Pair 2,b - d,.20,1.68,.75,-1.89,2.29,.27,4,.803
])
/CRITERIA=CI(0.95).
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,y,1.94,530.00,.96,.04
-,x,1.03,530.00,.17,.01
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,y,530.00,1.94,.96,.04
+,x,530.00,1.03,.17,.01
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,y & x,530.00,.11,.008
+Pair 1,y & x,530.00,.114,.008
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,y - x,.91,.95,.04,.83,.99,22.07,529.00,.000
])
-
AT_CLEANUP
B,F8.0
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,A,4.333,3,5.774,3.333
-,B,1.333,3,.577,.333
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,A,3,4.333,5.774,3.333
+,B,3,1.333,.577,.333
Table: Paired Samples Correlations
,,N,Correlation,Sig.
Pair 1,A & B,3,1.000,.000
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,A - B,3.000,5.196,3.000,-9.908,15.908,1.000,2,.423
])
AT_CLEANUP
t-test /GROUPS=indep(1.1,2.1) /var=dep1 dep2.
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
ID,F8.0
DEP2,F8.0
Table: Group Statistics
-,INDEP,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
DEP1,1.10,5,2.00,.71,.32
,2.10,5,4.00,.71,.32
DEP2,1.10,5,4.00,.71,.32
,2.10,5,2.00,.71,.32
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
DEP1,Equal variances assumed,.00,1.000,-4.47,8.00,.002,-2.00,.45,-3.03,-.97
,Equal variances not assumed,,,-4.47,8.00,.002,-2.00,.45,-3.03,-.97
DEP2,Equal variances assumed,.00,1.000,4.47,8.00,.002,2.00,.45,.97,3.03
,Equal variances not assumed,,,4.47,8.00,.002,2.00,.45,.97,3.03
])
-
AT_CLEANUP
AT_SETUP([T-TEST /GROUPS with one value for independent variable])
t-test /groups=indep(1.514) /var=dep.
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
INDEP,F8.0
DEP,F8.0
Table: Group Statistics
-,INDEP,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
DEP,≥ 1.51,11,9.00,3.82,1.15
,< 1.51,11,8.00,2.86,.86
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
DEP,Equal variances assumed,.17,.683,.69,20.00,.495,1.00,1.44,-2.00,4.00
,Equal variances not assumed,,,.69,18.54,.496,1.00,1.44,-2.02,4.02
])
dep2,F8.0
Table: Group Statistics
-,indep,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
dep1,1.00,3,2.50,.87,.50
,2.00,2,3.25,.35,.25
dep2,1.00,3,5.00,1.00,.58
,2.00,2,2.00,1.41,1.00
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
dep1,Equal variances assumed,3.75,.148,-1.12,3.00,.346,-.75,.67,-2.89,1.39
,Equal variances not assumed,,,-1.34,2.78,.279,-.75,.56,-2.61,1.11
dep2,Equal variances assumed,.60,.495,2.85,3.00,.065,3.00,1.05,-.35,6.35
dep2,F8.0
Table: Group Statistics
-,indep,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
dep1,1.00,3,2.50,.87,.50
,2.00,3,3.50,.50,.29
dep2,1.00,3,5.00,1.00,.58
,2.00,3,2.00,1.00,.58
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
dep1,Equal variances assumed,2.00,.230,-1.73,4.00,.158,-1.00,.58,-2.60,.60
,Equal variances not assumed,,,-1.73,3.20,.176,-1.00,.58,-2.77,.77
dep2,Equal variances assumed,.00,1.000,3.67,4.00,.021,3.00,.82,.73,5.27
t-test /testval=2.0 /var=abc.
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
ID,F8.0
ABC,6,3.00,.84,.34
Table: One-Sample Test
-,Test Value = 2.000000,,,,,
-,,,,,95% Confidence Interval of the Difference,
-,t,df,Sig. (2-tailed),Mean Difference,Lower,Upper
+,Test Value = 2,,,,,
+,t,df,Sig. (2-tailed),Mean Difference,95% Confidence Interval of the Difference,
+,,,,,Lower,Upper
ABC,2.93,5,.033,1.00,.12,1.88
])
AT_CLEANUP
x2,6,32.67,33.40,13.64
Table: One-Sample Test
-,Test Value = 3.000000,,,,,
-,,,,,95% Confidence Interval of the Difference,
-,t,df,Sig. (2-tailed),Mean Difference,Lower,Upper
+,Test Value = 3,,,,,
+,t,df,Sig. (2-tailed),Mean Difference,95% Confidence Interval of the Difference,
+,,,,,Lower,Upper
x1,.00,5,1.000,.00,-.88,.88
x2,2.18,5,.082,29.67,-5.39,64.72
])
x2,5,37.60,34.82,15.57
Table: One-Sample Test
-,Test Value = 3.000000,,,,,
-,,,,,95% Confidence Interval of the Difference,
-,t,df,Sig. (2-tailed),Mean Difference,Lower,Upper
+,Test Value = 3,,,,,
+,t,df,Sig. (2-tailed),Mean Difference,95% Confidence Interval of the Difference,
+,,,,,Lower,Upper
x1,-.59,4,.587,-.20,-1.14,.74
x2,2.22,4,.090,34.60,-8.63,77.83
])
x,F8.0
Table: Group Statistics
-,ind,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
x,1.00,3,2.50,.87,.50
,2.00,3,3.50,.50,.29
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
x,Equal variances assumed,2.00,.230,-1.73,4.00,.158,-1.00,.58,-2.60,.60
,Equal variances not assumed,,,-1.73,3.20,.176,-1.00,.58,-2.77,.77
])
AT_CHECK([cat temporary.csv], [0], [expout])
AT_CLEANUP
+dnl This is an example from doc/tutorial.texi
+dnl So if the results of this have to be changed in any way,
+dnl make sure to update that file.
+AT_SETUP([T-TEST tutorial example])
+cp $top_srcdir/examples/physiology.sav .
+AT_DATA([t-test.sps], [dnl
+GET FILE='physiology.sav'.
+RECODE height (179 = SYSMIS).
+T-TEST GROUP=sex(0,1) /VARIABLES=height temperature.
+])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Group Statistics
+,Group,N,Mean,Std. Deviation,S.E. Mean
+Height in millimeters ,Male,22,1796.49,49.71,10.60
+,Female,17,1610.77,25.43,6.17
+Internal body temperature in degrees Celcius,Male,22,36.68,1.95,.42
+,Female,18,37.43,1.61,.38
+
+Table: Independent Samples Test
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
+Height in millimeters ,Equal variances assumed,.97,.331,14.02,37.00,.000,185.72,13.24,158.88,212.55
+,Equal variances not assumed,,,15.15,32.71,.000,185.72,12.26,160.76,210.67
+Internal body temperature in degrees Celcius,Equal variances assumed,.31,.581,-1.31,38.00,.198,-.75,.57,-1.91,.41
+,Equal variances not assumed,,,-1.33,37.99,.190,-.75,.56,-1.89,.39
+])
+AT_CLEANUP
+
dnl Tests for a bug which caused T-TEST to crash when given invalid syntax.
AT_SETUP([T-TEST invalid syntax])
AT_DATA([t-test.sps], [dnl
t-test /GROUPS=indep('a','b') /var=dep1 dep2.
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
ID,F8.0
DEP2,F8.0
Table: Group Statistics
-,INDEP,N,Mean,Std. Deviation,S.E. Mean
+,Group,N,Mean,Std. Deviation,S.E. Mean
DEP1,a,5,2.00,.71,.32
,b,5,4.00,.71,.32
DEP2,a,5,4.00,.71,.32
,b,5,2.00,.71,.32
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
DEP1,Equal variances assumed,.00,1.000,-4.47,8.00,.002,-2.00,.45,-3.03,-.97
,Equal variances not assumed,,,-4.47,8.00,.002,-2.00,.45,-3.03,-.97
DEP2,Equal variances assumed,.00,1.000,4.47,8.00,.002,2.00,.45,.97,3.03
/variables = x.
])
-AT_CHECK([pspp -O format=csv t-test.sps], [0], [dnl
+AT_CHECK([pspp -o pspp.csv -o pspp.txt t-test.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
x,F8.0
gv,A8
Table: Group Statistics
-,gv,N,Mean,Std. Deviation,S.E. Mean
-x,One ,5,2.60,.55,.24
-,Two ,3,3.50,.50,.29
+,Group,N,Mean,Std. Deviation,S.E. Mean
+x,One,5,2.60,.55,.24
+,Two,3,3.50,.50,.29
Table: Independent Samples Test
-,,Levene's Test for Equality of Variances,,t-test for Equality of Means,,,,,,
-,,,,,,,,,95% Confidence Interval of the Difference,
-,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,Lower,Upper
+,,Levene's Test for Equality of Variances,,T-Test for Equality of Means,,,,,,
+,,F,Sig.,t,df,Sig. (2-tailed),Mean Difference,Std. Error Difference,95% Confidence Interval of the Difference,
+,,,,,,,,,Lower,Upper
x,Equal variances assumed,1.13,.329,-2.32,6.00,.060,-.90,.39,-1.85,.05
,Equal variances not assumed,,,-2.38,4.70,.067,-.90,.38,-1.89,.09
])
AT_CHECK([pspp t.sps],[1],[ignore],[ignore])
AT_CLEANUP
-
-
-
-
AT_CHECK([pspp -O format=csv set.pspp], [1], [dnl
"set.pspp:7: error: SET: Output format F41.0 specifies width 41, but F requires a width between 1 and 40."
-Table: Valid cases = 3; cases with missing value(s) = 0.
-Variable,N,Mean,Std Dev,Minimum,Maximum
+Table: Descriptive Statistics
+,N,Mean,Std Dev,Minimum,Maximum
x,3,2.00,1.00,1.00,3.00
+Valid N (listwise),3,,,,
+Missing N (listwise),0,,,,
])
AT_CLEANUP
X,1,1- 1,F1.0
Y,1,2- 2,F1.0
-Documents in the active dataset:
-
-document First line of a document
-
+Table: Documents
+"document First line of a document
Second line of a document
-
The last line should end with a period: .
+ (Entered <date>)"
-(Entered <date>)
-
-File label: This is a test file label
-
-Documents in the active dataset:
-
-document First line of a document
+Table: File Label
+Label,This is a test file label
+Table: Documents
+"document First line of a document
Second line of a document
-
The last line should end with a period: .
-
-(Entered <date>)
-
+ (Entered <date>)
Line one
-
Line two
+ (Entered <date>)"
-(Entered <date>)
-
-File label: This is a test file label
-
-Documents in the active dataset:
-
-document First line of a document
+Table: File Label
+Label,This is a test file label
+Table: Documents
+"document First line of a document
Second line of a document
-
The last line should end with a period: .
-
-(Entered <date>)
-
+ (Entered <date>)
Line one
-
Line two
-
-(Entered <date>)
-
+ (Entered <date>)
document There should be another document now.
+ (Entered <date>)"
-(Entered <date>)
-
-Documents in the active dataset:
-
-document First line of a document
-
+Table: Documents
+"document First line of a document
Second line of a document
-
The last line should end with a period: .
-
-(Entered <date>)
-
+ (Entered <date>)
Line one
-
Line two
-
-(Entered <date>)
-
+ (Entered <date>)
document There should be another document now.
+ (Entered <date>)"
-(Entered <date>)
-
-File label: This is a test file label
+Table: File Label
+Label,This is a test file label
])
AT_CLEANUP
Table: Data List
A,B
-ABC ,def
-GHI ,jkl
+ABC,def
+GHI,jkl
])
AT_CLEANUP
Table: Data List
v1,v2,c
12,34,.00
-32,1 ,1.00
-2 ,13,1.00
+32,1,1.00
+2,13,1.00
41,21,.00
11,04,.00
03,4,1.00
AT_CHECK([pspp -O format=csv recode.sps], [0],
[Table: Data List
s,t,s0,s1,s2,s3,t0,t1,t2,t3
-,,,,xyz ,,,,xyz ,
-a ,a ,b ,,xyz ,,b ,,xyz ,b @&t@
-ab ,ab ,bc ,,xyz ,,bc ,,xyz ,
-abc ,abc ,,,def ,,,,def ,
-abcd,abcd ,,xyzw,xyz ,,,xyzw ,xyz ,
-123 ,123 ,,,xyz ,,,,xyz ,
-123,123 ,,,xyz ,,,,xyz ,
-+1 ,+1 ,,,xyz ,,,,xyz ,
-1x ,1x ,,,xyz ,,,,xyz ,
-abcd,abcdefghi ,,xyzw,xyz ,,,,xyz ,xyz @&t@
-xxx ,abcdefghij,,,xyz ,gone,,,xyz ,jklmnopqr @&t@
+,,,,xyz,,,,xyz,
+a,a,b,,xyz,,b,,xyz,b
+ab,ab,bc,,xyz,,bc,,xyz,
+abc,abc,,,def,,,,def,
+abcd,abcd,,xyzw,xyz,,,xyzw,xyz,
+123,123,,,xyz,,,,xyz,
+123,123,,,xyz,,,,xyz,
++1,+1,,,xyz,,,,xyz,
+1x,1x,,,xyz,,,,xyz,
+abcd,abcdefghi,,xyzw,xyz,,,,xyz,xyz
+xxx,abcdefghij,,,xyz,gone,,,xyz,jklmnopqr
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv recode.sps], [0],
[Table: Data List
s,t,cs0,cs1,cs2,ct0,ct1,ct2,ct3
-,,,,xyz ,,,xyz ,
-a ,a ,b ,a ,xyz ,b ,a ,xyz ,b @&t@
-ab ,ab ,bc ,ab ,xyz ,bc ,ab ,xyz ,ab @&t@
-abc ,abc ,abc ,abc ,def ,abc ,abc ,def ,abc @&t@
-abcd,abcd ,abcd,xyzw,xyz ,abcd ,xyzw ,xyz ,abcd @&t@
-123 ,123 ,123 ,123 ,xyz ,123 ,123 ,xyz ,123 @&t@
-123,123 ,123,123,xyz ,123 ,123 ,xyz ,123 @&t@
-+1 ,+1 ,+1 ,+1 ,xyz ,+1 ,+1 ,xyz ,+1 @&t@
-1x ,1x ,1x ,1x ,xyz ,1x ,1x ,xyz ,1x @&t@
-abcd,abcdefghi ,abcd,xyzw,xyz ,abcdefghi ,abcdefghi ,xyz ,xyz @&t@
-xxx ,abcdefghij,xxx ,xxx ,xyz ,abcdefghij,abcdefghij,xyz ,jklmnopqr @&t@
+,,,,xyz,,,xyz,
+a,a,b,a,xyz,b,a,xyz,b
+ab,ab,bc,ab,xyz,bc,ab,xyz,ab
+abc,abc,abc,abc,def,abc,abc,def,abc
+abcd,abcd,abcd,xyzw,xyz,abcd,xyzw,xyz,abcd
+123,123,123,123,xyz,123,123,xyz,123
+123,123,123,123,xyz,123,123,xyz,123
++1,+1,+1,+1,xyz,+1,+1,xyz,+1
+1x,1x,1x,1x,xyz,1x,1x,xyz,1x
+abcd,abcdefghi,abcd,xyzw,xyz,abcdefghi,abcdefghi,xyz,xyz
+xxx,abcdefghij,xxx,xxx,xyz,abcdefghij,abcdefghij,xyz,jklmnopqr
])
AT_CLEANUP
[Table: Data List
s,t,ns0,ns1,ns2,nt0,nt1,nt2
,,.,0,3,.,0,3
-a ,a ,.,.,3,.,.,3
-ab ,ab ,.,.,3,.,.,3
-abc ,abc ,.,.,3,.,.,3
-abcd,abcd ,1,1,2,1,1,2
-123 ,123 ,123,123,3,123,123,3
-123,123 ,123,123,3,123,123,3
-+1 ,+1 ,1,1,3,1,1,3
-1x ,1x ,.,.,1,.,.,1
-abcd,abcdefghi ,1,1,2,.,.,3
-xxx ,abcdefghij,.,.,3,.,.,3
+a,a,.,.,3,.,.,3
+ab,ab,.,.,3,.,.,3
+abc,abc,.,.,3,.,.,3
+abcd,abcd,1,1,2,1,1,2
+123,123,123,123,3,123,123,3
+123,123,123,123,3,123,123,3
++1,+1,1,1,3,1,1,3
+1x,1x,.,.,1,.,.,1
+abcd,abcdefghi,1,1,2,.,.,3
+xxx,abcdefghij,.,.,3,.,.,3
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv recode.sps], [0],
[Table: Data List
x,sx0,sx1,sx2
-0,,xxx ,foobar @&t@
-1,abcdefghij,xxx ,foobar @&t@
-2,abcdefghij,,xyz @&t@
-3,abcdefghij,xxx ,xyz @&t@
-4,abcdefghij,,xyz @&t@
-5,abcdefghij,xxx ,xyz @&t@
-6,abcdefghij,,xyz @&t@
-7,abcdefghij,xxx ,foobar @&t@
-8,abcdefghij,,foobar @&t@
-9,abcdefghij,xxx ,foobar @&t@
-.,,xxx ,xyz @&t@
+0,,xxx,foobar
+1,abcdefghij,xxx,foobar
+2,abcdefghij,,xyz
+3,abcdefghij,xxx,xyz
+4,abcdefghij,,xyz
+5,abcdefghij,xxx,xyz
+6,abcdefghij,,xyz
+7,abcdefghij,xxx,foobar
+8,abcdefghij,,foobar
+9,abcdefghij,xxx,foobar
+.,,xxx,xyz
])
AT_CLEANUP
Table: Data List
x,y,z
-a,a ,2.00
-a,two ,2.00
-b,three ,2.00
-c,b ,2.00
+a,a,2.00
+a,two,2.00
+b,three,2.00
+c,b,2.00
])
AT_CLEANUP
Reading free-form data from INLINE.
+--------+------+
|Variable|Format|
-#========#======#
++--------+------+
|x |F8.0 |
|y |F8.0 |
|a |A23 |
AT_CHECK([pspp -O box=unicode uc.sps], [0], [dnl
-Valid cases = 3; cases with missing value(s) = 0.
-╭────────╥─┬──────┬───────┬───────┬───────╮
-│Variable║N│ Mean │Std Dev│Minimum│Maximum│
-╞════════╬═╪══════╪═══════╪═══════╪═══════╡
-│x ║3│2.0000│ 1.0000│ 1.0000│ 3.0000│
-╰────────╨─┴──────┴───────┴───────┴───────╯
+ Descriptive Statistics
+╭────────────────────┬─┬──────┬───────┬───────┬───────╮
+│ │N│ Mean │Std Dev│Minimum│Maximum│
+├────────────────────┼─┼──────┼───────┼───────┼───────┤
+│x │3│2.0000│ 1.0000│ 1.0000│ 3.0000│
+│Valid N (listwise) │3│ │ │ │ │
+│Missing N (listwise)│0│ │ │ │ │
+╰────────────────────┴─┴──────┴───────┴───────┴───────╯
])
AT_CLEANUP
])
AT_CHECK([pspp list.sps], [0], [dnl
Data List
-x y z
------
-1 2 3
-4 5 6
-7 8 9
++-+-+-+
+|x|y|z|
++-+-+-+
+|1|2|3|
+|4|5|6|
+|7|8|9|
++-+-+-+
])
AT_CLEANUP
AT_CHECK([pspp -O format=csv prec.sps], [0], [dnl
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,A,2.00,5,.71,.32
-,B,4.00,5,1.54,.69
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,A,5,2.00,.71,.32
+,B,5,4.00,1.54,.69
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,A & B,5,.92,.028
+Pair 1,A & B,5,.918,.028
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,A - B,-2.00,.94,.42,-3.16,-.84,-4.78,4,.009
Table: Paired Sample Statistics
-,,Mean,N,Std. Deviation,S.E. Mean
-Pair 1,A,2.00,5,.71,.32
-,B,4.00,5,1.54,.69
+,,N,Mean,Std. Deviation,S.E. Mean
+Pair 1,A,5,2.00,.71,.32
+,B,5,4.00,1.54,.69
Table: Paired Samples Correlations
,,N,Correlation,Sig.
-Pair 1,A & B,5,.92,.02801
+Pair 1,A & B,5,.918,.02801
Table: Paired Samples Test
-,,Paired Differences,,,,,,,
-,,,,,95% Confidence Interval of the Difference,,,,
-,,Mean,Std. Deviation,Std. Error Mean,Lower,Upper,t,df,Sig. (2-tailed)
+,,Paired Differences,,,,,t,df,Sig. (2-tailed)
+,,Mean,Std. Deviation,S.E. Mean,95% Confidence Interval of the Difference,,,,
+,,,,,Lower,Upper,,,
Pair 1,A - B,-2.00,.94,.42,-3.16,-.84,-4.78,4,.00877
])
AT_CHECK([pspp -O format=csv prec.sps], [1], [ignore])
-AT_CLEANUP
\ No newline at end of file
+AT_CLEANUP
DISPLAY DICTIONARY.
SHOW WEIGHT.
])
-AT_CHECK([pspp -O format=csv dump-dict.sps], [0],
- [File label: My Dictionary
-
-Documents in the active dataset:
+AT_CHECK([pspp -O format=csv dump-dict.sps], [0], [dnl
+Table: File Label
+Label,My Dictionary
+Table: Documents
These Documents
Table: Variables
id,1,,Scale,Input,8,Right,F2.0,F2.0,
name,2,,Nominal,Input,20,Left,A20,A20,
-File label: This is the file label
-
-Documents in the active dataset:
+Table: File Label
+Label,This is the file label
+Table: Documents
This is a document line
Table: Data List
id,name
-34,frederick @&t@
+34,frederick
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
id,1,,Scale,Input,8,Right,F2.0,F2.0,
name,2,,Nominal,Input,20,Left,A20,A20,
-File label: This is the file label
-
-Documents in the active dataset:
+Table: File Label
+Label,This is the file label
+Table: Documents
This is a document line
Table: Data List
id,name
-21,wheelbarrow @&t@
+21,wheelbarrow
])
AT_CLEANUP
longstring,3,My Long String,Nominal,Input,9,Left,A9,A9,
Table: Value Labels
-Variable,Value,Label
-integer,0,Zero
+Variable Value,,Label
+My Integer,0,Zero
,1,Unity
,2,Duality
-string,xx ,foo
-,yy ,bar
-longstring,xxx ,xfoo
+My String,xx,foo
+,yy,bar
+My Long String,xxx,xfoo
])
AT_CLEANUP
datetime,6,A Datetime Variable,Scale,Input,8,Right,DATETIME17.0,DATETIME17.0,
Table: Value Labels
-Variable,Value,Label
-string,1111 ,ones
-,2222 ,twos
-,3333 ,threes
-numeric,1,Unity
+Variable Value,,Label
+A Short String Variable,1111,ones
+,2222,twos
+,3333[a],threes
+A Numeric Variable,1,Unity
,2,Duality
,3,Thripality
+Footnotes:
+a,User-missing value
+
Table: Variable and Dataset Attributes
-Variable,Name,Value
-numeric,colour[1],blue
+Variable and Name,,Value
+A Numeric Variable,colour[1],blue
,colour[2],pink
,colour[3],violet
,nationality,foreign
Table: Data List
string,longstring,numeric,date,dollar,datetime
-1111 ,One ,1,01-JAN-2001,$1.00,01-JAN-2001 01:01
-2222 ,Two ,2,02-FEB-2002,$2.00,02-FEB-2002 02:02
-3333 ,Three ,3,03-MAR-2003,$3.00,03-MAR-2003 03:03
-. ,. ,.,.,. ,.
-5555 ,Five ,5,05-MAY-2005,$5.00,05-MAY-2005 05:05
+1111,One,1,01-JAN-2001,$1.00,01-JAN-2001 01:01
+2222,Two,2,02-FEB-2002,$2.00,02-FEB-2002 02:02
+3333,Three,3,03-MAR-2003,$3.00,03-MAR-2003 03:03
+.,.,.,.,. ,.
+5555,Five,5,05-MAY-2005,$5.00,05-MAY-2005 05:05
Table: Variables
Name,Position,Label,Measurement Level,Role,Width,Alignment,Print Format,Write Format,Missing Values
datetime,6,A Datetime Variable,Scale,Input,8,Right,DATETIME17.0,DATETIME17.0,
Table: Value Labels
-Variable,Value,Label
-string,1111 ,ones
-,2222 ,twos
-,3333 ,threes
-numeric,1,Unity
+Variable Value,,Label
+A Short String Variable,1111,ones
+,2222,twos
+,3333[a],threes
+A Numeric Variable,1,Unity
,2,Duality
,3,Thripality
+Footnotes:
+a,User-missing value
+
Table: Variable and Dataset Attributes
-Variable,Name,Value
-numeric,colour[1],blue
+Variable and Name,,Value
+A Numeric Variable,colour[1],blue
,colour[2],pink
,colour[3],violet
,nationality,foreign
Table: Data List
string,longstring,numeric,date,dollar,datetime
-1111 ,One ,1,01-JAN-2001,$1.00,01-JAN-2001 01:01
-2222 ,Two ,2,02-FEB-2002,$2.00,02-FEB-2002 02:02
-3333 ,Three ,3,03-MAR-2003,$3.00,03-MAR-2003 03:03
-. ,. ,.,.,. ,.
-5555 ,Five ,5,05-MAY-2005,$5.00,05-MAY-2005 05:05
+1111,One,1,01-JAN-2001,$1.00,01-JAN-2001 01:01
+2222,Two,2,02-FEB-2002,$2.00,02-FEB-2002 02:02
+3333,Three,3,03-MAR-2003,$3.00,03-MAR-2003 03:03
+.,.,.,.,. ,.
+5555,Five,5,05-MAY-2005,$5.00,05-MAY-2005 05:05
]])
AT_CLEANUP
projects / pspp / commitdiff