#include <output/table.h>
+#include <output/charts/scree.h>
+#include <output/chart.h>
#include "gettext.h"
#define _(msgid) gettext (msgid)
EXTRACTION_PAF,
};
+enum plot_opts
+ {
+ PLOT_SCREE = 0x0001,
+ PLOT_ROTATION = 0x0002
+ };
+
enum print_opts
{
PRINT_UNIVARIATE = 0x0001,
enum mv_class exclude;
enum print_opts print;
enum extraction_method extraction;
+ enum plot_opts plot;
/* Extraction Criteria */
int n_factors;
{
/* Intermediate values used in calculation */
+ const gsl_matrix *corr ; /* The correlation matrix */
+ const gsl_matrix *cov ; /* The covariance matrix */
+ const gsl_matrix *n ; /* Matrix of number of samples */
+
gsl_vector *eval ; /* The eigenvalues */
gsl_matrix *evec ; /* The eigenvectors */
static struct idata *
idata_alloc (size_t n_vars)
{
- struct idata *id = xmalloc (sizeof (*id));
+ struct idata *id = xzalloc (sizeof (*id));
id->n_extractions = 0;
id->msr = gsl_vector_alloc (n_vars);
Return the square of the regression coefficient for VAR regressed against all other variables.
*/
static double
-squared_multiple_correlation (const gsl_matrix *analysis_matrix, int var, struct smr_workspace *ws)
+squared_multiple_correlation (const gsl_matrix *corr, int var, struct smr_workspace *ws)
{
/* For an explanation of what this is doing, see
http://www.visualstatistics.net/Visual%20Statistics%20Multimedia/multiple_regression_analysis.htm
int signum = 0;
gsl_matrix_view rxx;
- gsl_matrix_memcpy (ws->m, analysis_matrix);
+ gsl_matrix_memcpy (ws->m, corr);
gsl_matrix_swap_rows (ws->m, 0, var);
gsl_matrix_swap_columns (ws->m, 0, var);
factor.econverge = 0.001;
factor.blank = 0;
factor.sort = false;
+ factor.plot = 0;
factor.wv = dict_get_weight (dict);
{
lex_match (lexer, '/');
-#if FACTOR_FULLY_IMPLEMENTED
if (lex_match_id (lexer, "PLOT"))
{
lex_match (lexer, '=');
{
if (lex_match_id (lexer, "EIGEN"))
{
+ factor.plot |= PLOT_SCREE;
}
+#if FACTOR_FULLY_IMPLEMENTED
else if (lex_match_id (lexer, "ROTATION"))
{
}
+#endif
else
{
lex_error (lexer, NULL);
}
}
}
- else
-#endif
- if (lex_match_id (lexer, "METHOD"))
+ else if (lex_match_id (lexer, "METHOD"))
{
lex_match (lexer, '=');
while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
else if (lex_match_id (lexer, "AIC"))
{
}
+#endif
else if (lex_match_id (lexer, "SIG"))
{
+ factor.print |= PRINT_SIG;
}
- else if (lex_match_id (lexer, "COVARIANCE"))
+ else if (lex_match_id (lexer, "CORRELATION"))
{
+ factor.print |= PRINT_CORRELATION;
}
- else if (lex_match_id (lexer, "CORRELATION"))
+#if FACTOR_FULLY_IMPLEMENTED
+ else if (lex_match_id (lexer, "COVARIANCE"))
{
}
#endif
}
+static void
+show_scree (const struct cmd_factor *f, struct idata *idata)
+{
+ struct scree *s;
+ const char *label ;
+
+ if ( !(f->plot & PLOT_SCREE) )
+ return;
+
+
+ label = f->extraction == EXTRACTION_PC ? _("Component Number") : _("Factor Number");
+
+ s = scree_create (idata->eval, label);
+
+ chart_submit (scree_get_chart (s));
+}
static void
show_communalities (const struct cmd_factor * factor,
if (nc <= 1)
return;
- t = tab_create (nc, nr, 0);
+ t = tab_create (nc, nr);
tab_title (t, _("Communalities"));
- tab_dim (t, tab_natural_dimensions, NULL);
+ tab_dim (t, tab_natural_dimensions, NULL, NULL);
tab_headers (t, heading_columns, 0, heading_rows, 0);
const int nc = heading_columns + n_factors;
gsl_permutation *perm;
- struct tab_table *t = tab_create (nc, nr, 0);
+ 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_dim (t, tab_natural_dimensions, NULL);
+ tab_dim (t, tab_natural_dimensions, NULL, NULL);
tab_headers (t, heading_columns, 0, heading_rows, 0);
tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
- {
- gsl_vector_const_view r1 = gsl_matrix_const_row (fm, 0);
- gsl_vector_const_view r2 = gsl_matrix_const_row (fm, 1);
- }
-
/* Initialise to the identity permutation */
perm = gsl_permutation_calloc (factor->n_vars);
if ( nc <= heading_columns)
return;
- t = tab_create (nc, nr, 0);
+ t = tab_create (nc, nr);
tab_title (t, _("Total Variance Explained"));
- tab_dim (t, tab_natural_dimensions, NULL);
+ tab_dim (t, tab_natural_dimensions, NULL, NULL);
tab_headers (t, heading_columns, 0, heading_rows, 0);
}
+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)
+ return;
+
+ t = tab_create (nc, nr + suffix_rows);
+
+ tab_title (t, _("Correlation Matrix"));
+
+ tab_dim (t, tab_natural_dimensions, NULL, NULL);
+
+ 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, 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);
+ }
+
+ 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 + i, y + j, 0, gsl_matrix_get (idata->corr, i, j), NULL);
+ }
+ }
+
+ 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->corr, i, j);
+ double w = gsl_matrix_get (idata->n, i, j);
+
+ if (i == j)
+ continue;
+
+ tab_double (t, heading_columns + i, y + j, 0, significance_of_correlation (rho, w), NULL);
+ }
+ }
+ }
+ }
+
+ if (factor->print & PRINT_DETERMINANT)
+ {
+ int sign = 0;
+ double det = 0.0;
+
+ const int size = idata->corr->size1;
+ gsl_permutation *p = gsl_permutation_calloc (size);
+ gsl_matrix *tmp = gsl_matrix_calloc (size, size);
+ gsl_matrix_memcpy (tmp, idata->corr);
+
+ gsl_linalg_LU_decomp (tmp, p, &sign);
+ det = gsl_linalg_LU_det (tmp, sign);
+ gsl_permutation_free (p);
+ gsl_matrix_free (tmp);
+
+
+ tab_text (t, 0, nr, TAB_LEFT | TAT_TITLE, _("Determinant"));
+ tab_double (t, 1, nr, 0, det, NULL);
+ }
+
+ tab_submit (t);
+}
+
+
static void
do_factor (const struct cmd_factor *factor, struct casereader *r)
{
struct ccase *c;
- const gsl_matrix *cov_matrix;
const gsl_matrix *var_matrix;
const gsl_matrix *mean_matrix;
- const gsl_matrix *n_matrix;
const gsl_matrix *analysis_matrix;
- struct idata *idata;
+ struct idata *idata = idata_alloc (factor->n_vars);
struct covariance *cov = covariance_create (factor->n_vars, factor->vars,
factor->wv, factor->exclude);
covariance_accumulate (cov, c);
}
- cov_matrix = covariance_calculate (cov);
+ idata->cov = covariance_calculate (cov);
var_matrix = covariance_moments (cov, MOMENT_VARIANCE);
mean_matrix = covariance_moments (cov, MOMENT_MEAN);
- n_matrix = covariance_moments (cov, MOMENT_NONE);
+ idata->n = covariance_moments (cov, MOMENT_NONE);
if ( factor->method == METHOD_CORR)
{
- analysis_matrix = correlation_from_covariance (cov_matrix, var_matrix);
+ idata->corr = correlation_from_covariance (idata->cov, var_matrix);
+ analysis_matrix = idata->corr;
}
else
- analysis_matrix = cov_matrix;
+ analysis_matrix = idata->cov;
if ( factor->print & PRINT_UNIVARIATE)
{
const int nr = heading_rows + factor->n_vars;
- struct tab_table *t = tab_create (nc, nr, 0);
+ struct tab_table *t = tab_create (nc, nr);
tab_title (t, _("Descriptive Statistics"));
- tab_dim (t, tab_natural_dimensions, NULL);
+ tab_dim (t, tab_natural_dimensions, NULL, NULL);
tab_headers (t, heading_columns, 0, heading_rows, 0);
tab_double (t, 1, i + heading_rows, 0, gsl_matrix_get (mean_matrix, i, i), NULL);
tab_double (t, 2, i + heading_rows, 0, sqrt (gsl_matrix_get (var_matrix, i, i)), NULL);
- tab_double (t, 3, i + heading_rows, 0, gsl_matrix_get (n_matrix, i, i), wfmt);
+ tab_double (t, 3, i + heading_rows, 0, gsl_matrix_get (idata->n, i, i), wfmt);
}
tab_submit (t);
}
- if ( factor->print & PRINT_DETERMINANT)
- {
- const int nc = 2;
- const int heading_columns = 0;
- const int heading_rows = 0;
- const int nr = 1;
- struct tab_table *t ;
-
- int sign = 0;
- double det = 0.0;
- const int size = analysis_matrix->size1;
- gsl_permutation *p = gsl_permutation_calloc (size);
- gsl_matrix *tmp = gsl_matrix_calloc (size, size);
-
- gsl_matrix_memcpy (tmp, analysis_matrix);
- gsl_linalg_LU_decomp (tmp, p, &sign);
- det = gsl_linalg_LU_det (tmp, sign);
- gsl_permutation_free (p);
- gsl_matrix_free (tmp);
-
- t = tab_create (nc, nr, 0);
-
- if ( factor->method == METHOD_CORR)
- tab_title (t, _("Correlation Matrix"));
- else
- tab_title (t, _("Covariance Matrix"));
-
- tab_dim (t, tab_natural_dimensions, NULL);
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
-
- tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Determinant"));
- tab_double (t, 1, 0, 0, det, NULL);
-
- tab_submit (t);
- }
-
-
- idata = idata_alloc (factor->n_vars);
-
+ show_correlation_matrix (factor, idata);
#if 1
{
factor_matrix_workspace_free (fmw);
+ show_scree (factor, idata);
+
show_factor_matrix (factor, idata, factor_matrix);
gsl_vector_free (initial_communalities);
projects / pspp-builds.git / blobdiff