#include "math/correlation.h"
#include "math/covariance.h"
#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"
typedef void (*rotation_coefficients) (double *x, double *y,
double a, double b, double c, double d,
- const gsl_matrix *loadings );
+ const gsl_matrix *loadings);
static void
varimax_coefficients (double *x, double *y,
double a, double b, double c, double d,
- const gsl_matrix *loadings )
+ const gsl_matrix *loadings)
{
*x = d - 2 * a * b / loadings->size1;
*y = c - (a * a - b * b) / loadings->size1;
static void
equamax_coefficients (double *x, double *y,
double a, double b, double c, double d,
- const gsl_matrix *loadings )
+ const gsl_matrix *loadings)
{
*x = d - loadings->size2 * a * b / loadings->size1;
*y = c - loadings->size2 * (a * a - b * b) / (2 * loadings->size1);
double detR; /* The determinant of the correlation matrix */
+ gsl_matrix *ai_cov; /* The anti-image covariance matrix */
+ gsl_matrix *ai_cor; /* The anti-image correlation matrix */
struct covariance *cvm;
};
static struct idata *
idata_alloc (size_t n_vars)
{
- struct idata *id = xzalloc (sizeof (*id));
+ struct idata *id = XZALLOC (struct idata);
id->n_extractions = 0;
id->msr = gsl_vector_alloc (n_vars);
gsl_vector_free (id->msr);
gsl_vector_free (id->eval);
gsl_matrix_free (id->evec);
+ gsl_matrix_free (id->ai_cov);
+ gsl_matrix_free (id->ai_cor);
free (id);
}
-
-static gsl_matrix *
-anti_image (const gsl_matrix *m)
+/* Return the sum of squares of all the elements in row J excluding column J */
+static double
+ssq_row_od_n (const gsl_matrix *m, int j)
{
- int i, j;
- gsl_matrix *a;
+ int i;
+ double ss = 0;
assert (m->size1 == m->size2);
- a = gsl_matrix_alloc (m->size1, m->size2);
+ assert (j < m->size1);
for (i = 0; i < m->size1; ++i)
{
- for (j = 0; j < m->size2; ++j)
- {
- double *p = gsl_matrix_ptr (a, i, j);
- *p = gsl_matrix_get (m, i, j);
- *p /= gsl_matrix_get (m, i, i);
- *p /= gsl_matrix_get (m, j, j);
- }
+ if (i == j) continue;
+ ss += pow2 (gsl_matrix_get (m, i, j));
}
- return a;
+ return ss;
}
-
-/* Return the sum of all the elements excluding row N */
+/* Return the sum of squares of all the elements excluding row N */
static double
ssq_od_n (const gsl_matrix *m, int n)
{
for (i = 0; i < m->size1; ++i)
{
- if (i == n ) continue;
for (j = 0; j < m->size2; ++j)
{
+ if (i == j) continue;
ss += pow2 (gsl_matrix_get (m, i, j));
}
}
}
+static gsl_matrix *
+anti_image_corr (const gsl_matrix *m, const struct idata *idata)
+{
+ int i, j;
+ gsl_matrix *a;
+ assert (m->size1 == m->size2);
+
+ a = gsl_matrix_alloc (m->size1, m->size2);
+
+ for (i = 0; i < m->size1; ++i)
+ {
+ for (j = 0; j < m->size2; ++j)
+ {
+ double *p = gsl_matrix_ptr (a, i, j);
+ *p = gsl_matrix_get (m, i, j);
+ *p /= sqrt (gsl_matrix_get (m, i, i) *
+ gsl_matrix_get (m, j, j));
+ }
+ }
+
+ for (i = 0; i < m->size1; ++i)
+ {
+ double r = ssq_row_od_n (idata->mm.corr, i);
+ double u = ssq_row_od_n (a, i);
+ gsl_matrix_set (a, i, i, r / (r + u));
+ }
+
+ return a;
+}
+
+static gsl_matrix *
+anti_image_cov (const gsl_matrix *m)
+{
+ int i, j;
+ gsl_matrix *a;
+ assert (m->size1 == m->size2);
+
+ a = gsl_matrix_alloc (m->size1, m->size2);
+
+ for (i = 0; i < m->size1; ++i)
+ {
+ for (j = 0; j < m->size2; ++j)
+ {
+ double *p = gsl_matrix_ptr (a, i, j);
+ *p = gsl_matrix_get (m, i, j);
+ *p /= gsl_matrix_get (m, i, i);
+ *p /= gsl_matrix_get (m, j, j);
+ }
+ }
+
+ return a;
+}
#if 0
static void
int i;
/* If there is a cached value, then return that. */
- if ( idata->n_extractions != 0)
+ if (idata->n_extractions != 0)
return idata->n_extractions;
/* Otherwise, if the number of factors has been explicitly requested,
gsl_vector_view row = gsl_matrix_row (mat, p->data[n - 1 - i]);
size_t maxindex = gsl_vector_max_index (&row.vector);
- if ( maxindex > column_n )
+ if (maxindex > column_n)
break;
/* All subsequent elements of this row, are of no interest.
gsl_permutation_free (p);
gsl_matrix_free (mat);
- assert ( 0 == gsl_permutation_valid (perm));
+ assert (0 == gsl_permutation_valid (perm));
/* We want the biggest value to be first */
gsl_permutation_reverse (perm);
l4s += lambda_4;
l2s += lambda_sq;
}
- sv += ( fm->size1 * l4s - (l2s * l2s) ) / (fm->size1 * fm->size1 );
+ sv += (fm->size1 * l4s - (l2s * l2s)) / (fm->size1 * fm->size1);
}
return sv;
}
phi = atan2 (x, y) / 4.0 ;
/* Don't bother rotating if the angle is small */
- if ( fabs (sin (phi) ) <= pow (10.0, -15.0))
+ if (fabs (sin (phi)) <= pow (10.0, -15.0))
continue;
for (p = 0; p < normalised->size1; ++p)
l2s += lambda_sq;
}
}
- sv += ( normalised->size1 * l4s - (l2s * l2s) ) / (normalised->size1 * normalised->size1 );
+ sv += (normalised->size1 * l4s - (l2s * l2s)) / (normalised->size1 * normalised->size1);
}
- if ( fabs (sv - prev_sv) <= cf->rconverge)
+ if (fabs (sv - prev_sv) <= cf->rconverge)
break;
prev_sv = sv;
gsl_vector_set (rotated_loadings, i, ssq);
- if ( sum < 0 )
+ if (sum < 0)
for (j = 0 ; j < result->size1; ++j)
{
double *lambda = gsl_matrix_ptr (result, j, i);
if (! lex_force_match (lexer, T_RPAREN))
goto error;
- mr = create_matrix_reader_from_case_reader (dict, matrix_reader,
- &factor.vars, &factor.n_vars);
+ mr = matrix_reader_create (dict, matrix_reader);
+ factor.vars = xmemdup (mr->cvars, mr->n_cvars * sizeof *mr->cvars);
+ factor.n_vars = mr->n_cvars;
}
else
{
free (factor.vars);
factor.vars = vars;
factor.n_vars = n_vars;
+
+ if (mr)
+ {
+ free (mr->cvars);
+ mr->cvars = xmemdup (vars, n_vars * sizeof *vars);
+ mr->n_cvars = n_vars;
+ }
}
else if (lex_match_id (lexer, "PLOT"))
{
{
if (lex_match_id (lexer, "FACTORS"))
{
- if ( lex_force_match (lexer, T_LPAREN)
+ if (lex_force_match (lexer, T_LPAREN)
&& lex_force_int (lexer))
{
factor.n_factors = lex_integer (lexer);
}
else if (lex_match_id (lexer, "MINEIGEN"))
{
- if ( lex_force_match (lexer, T_LPAREN)
+ if (lex_force_match (lexer, T_LPAREN)
&& lex_force_num (lexer))
{
factor.min_eigen = lex_number (lexer);
}
else if (lex_match_id (lexer, "ECONVERGE"))
{
- if ( lex_force_match (lexer, T_LPAREN)
+ if (lex_force_match (lexer, T_LPAREN)
&& lex_force_num (lexer))
{
factor.econverge = lex_number (lexer);
}
else if (lex_match_id (lexer, "ITERATE"))
{
- if ( lex_force_match (lexer, T_LPAREN)
- && lex_force_int (lexer))
+ if (lex_force_match (lexer, T_LPAREN)
+ && lex_force_int_range (lexer, "ITERATE", 0, INT_MAX))
{
n_iterations = lex_integer (lexer);
lex_get (lexer);
}
else if (lex_match_id (lexer, "BLANK"))
{
- if ( lex_force_match (lexer, T_LPAREN)
+ if (lex_force_match (lexer, T_LPAREN)
&& lex_force_num (lexer))
{
factor.blank = lex_number (lexer);
else if (lex_match_id (lexer, "INV"))
{
}
+#endif
else if (lex_match_id (lexer, "AIC"))
{
+ factor.print |= PRINT_AIC;
}
-#endif
else if (lex_match_id (lexer, "SIG"))
{
factor.print |= PRINT_SIG;
}
}
- if ( factor.rotation == ROT_NONE )
+ if (factor.rotation == ROT_NONE)
factor.print &= ~PRINT_ROTATION;
if (factor.n_vars < 2)
{
struct idata *id = idata_alloc (factor.n_vars);
- while (next_matrix_from_reader (&id->mm, mr,
- factor.vars, factor.n_vars))
+ while (matrix_reader_next (&id->mm, mr, NULL))
{
do_factor_by_matrix (&factor, id);
- gsl_matrix_free (id->mm.corr);
- id->mm.corr = NULL;
- gsl_matrix_free (id->mm.cov);
- id->mm.cov = NULL;
+ gsl_matrix_free (id->ai_cov);
+ id->ai_cov = NULL;
+ gsl_matrix_free (id->ai_cor);
+ id->ai_cor = NULL;
+
+ matrix_material_uninit (&id->mm);
}
idata_free (id);
}
else
- if ( ! run_factor (ds, &factor))
+ if (! run_factor (ds, &factor))
goto error;
-
- destroy_matrix_reader (mr);
+ matrix_reader_destroy (mr);
free (factor.vars);
return CMD_SUCCESS;
error:
- destroy_matrix_reader (mr);
+ matrix_reader_destroy (mr);
free (factor.vars);
return CMD_FAILURE;
}
while (casegrouper_get_next_group (grouper, &group))
{
- if ( factor->missing_type == MISS_LISTWISE )
+ if (factor->missing_type == MISS_LISTWISE)
group = casereader_create_filter_missing (group, factor->vars, factor->n_vars,
factor->exclude,
NULL, NULL);
struct scree *s;
const char *label ;
- if ( !(f->plot & PLOT_SCREE) )
+ if (!(f->plot & PLOT_SCREE))
return;
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);
+ struct pivot_table *table = pivot_table_create (N_("Communalities"));
- tab_title (t, _("Communalities"));
-
- tab_headers (t, heading_columns, 0, heading_rows, 0);
-
- 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)
+ 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)
+ 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);
+ struct pivot_table *table = pivot_table_create (
+ N_("Total Variance Explained"));
- tab_title (t, _("Total Variance Explained"));
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Total"), PIVOT_RC_OTHER,
+ /* xgettext:no-c-format */
+ N_("% of Variance"), PIVOT_RC_PERCENT,
+ /* xgettext:no-c-format */
+ N_("Cumulative %"), PIVOT_RC_PERCENT);
- 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);
-
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-
- 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;
+ int row = pivot_category_create_leaf (
+ components->root, pivot_value_new_integer (i + 1));
- tab_text_format (t, c++, i + heading_rows, TAB_LEFT | TAT_TITLE, _("%zu"), 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"));
+ struct pivot_table *table = pivot_table_create (
+ N_("Factor Correlation Matrix"));
- tab_headers (t, heading_columns, 0, heading_rows, 0);
+ create_numeric_dimension (
+ table, PIVOT_AXIS_ROW,
+ factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"),
+ fcm->size2, true);
- /* Outline the box */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- nc - 1, nr - 1);
+ create_numeric_dimension (table, PIVOT_AXIS_COLUMN, N_("Factor 2"),
+ fcm->size1, false);
- /* Vertical lines */
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_columns, 0,
- nc - 1, nr - 1);
+ 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)));
- tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
- tab_hline (t, TAL_1, 1, nc - 1, 1);
-
- tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-
- 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"));
+ pivot_table_submit (table);
+}
- for (i = 0 ; i < fcm->size1; ++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, heading_columns + i, 0, 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->size2; ++i)
- {
- tab_text_format (t, 0, heading_rows + i, TAB_CENTER | TAT_TITLE, _("%zu"), i + 1);
+ for (size_t j = 0; j < factor->n_vars; j++)
+ pivot_category_create_leaf (
+ d->root, pivot_value_new_variable (factor->vars[j]));
}
-
-
- 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);
- }
-
- tab_submit (t);
}
-
static void
-show_correlation_matrix (const struct cmd_factor *factor, const struct idata *idata)
+show_aic (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;
+ if ((factor->print & PRINT_AIC) == 0)
+ return;
- const int heading_rows = 1;
- const int heading_columns = 2;
+ struct pivot_table *table = pivot_table_create (N_("Anti-Image Matrices"));
- int nc = heading_columns ;
- int nr = heading_rows ;
- int n_data_sets = 0;
+ add_var_dims (table, factor);
- if (factor->print & PRINT_CORRELATION)
- {
- y_pos_corr = n_data_sets;
- n_data_sets++;
- nc = heading_columns + factor->n_vars;
- }
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"),
+ N_("Anti-image Covariance"),
+ N_("Anti-image Correlation"));
- if (factor->print & PRINT_SIG)
- {
- y_pos_sig = n_data_sets;
- n_data_sets++;
- nc = heading_columns + factor->n_vars;
- }
+ 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));
- nr += n_data_sets * factor->n_vars;
+ double corr = gsl_matrix_get (idata->ai_cor, i, j);
+ pivot_table_put3 (table, i, j, 1, pivot_value_new_number (corr));
+ }
- if (factor->print & PRINT_DETERMINANT)
- suffix_rows = 1;
+ pivot_table_submit (table);
+}
- /* If the table would contain only headings, don't bother rendering it */
- if (nr <= heading_rows && suffix_rows == 0)
+static void
+show_correlation_matrix (const struct cmd_factor *factor, const struct idata *idata)
+{
+ if (!(factor->print & (PRINT_CORRELATION | PRINT_SIG | PRINT_DETERMINANT)))
return;
- t = tab_create (nc, nr + suffix_rows);
+ struct pivot_table *table = pivot_table_create (N_("Correlation Matrix"));
- tab_title (t, _("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)"));
+ pivot_category_create_leaves (statistics->root, N_("Sig. (1-tailed)"),
+ PIVOT_RC_SIGNIFICANCE);
- 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);
-
- 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);
+ struct pivot_value *caption = pivot_value_new_user_text_nocopy (
+ xasprintf ("%s: %.2f", _("Determinant"), idata->detR));
+ pivot_table_set_caption (table, caption);
}
- 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);
-
- /* 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);
+ struct pivot_table *table = pivot_table_create (N_("Covariance Matrix"));
+ add_var_dims (table, factor);
+ 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));
+ }
- 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);
- }
- }
- }
-
- tab_submit (t);
+ pivot_table_submit (table);
}
idata->cvm = covariance_1pass_create (factor->n_vars, factor->vars,
factor->wv, factor->exclude, true);
- for ( ; (c = casereader_read (r) ); case_unref (c))
+ for (; (c = casereader_read (r)); case_unref (c))
{
covariance_accumulate (idata->cvm, c);
}
static void
do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata)
{
- if (!idata->mm.cov && !idata->mm.corr)
+ if (!idata->mm.cov && !(idata->mm.corr && idata->mm.var_matrix))
{
- msg (ME, _("The dataset has no complete covariance or correlation matrix."));
+ msg (ME, _("The dataset has no covariance matrix or a "
+ "correlation matrix along with standard devications."));
return;
}
else
idata->analysis_matrix = idata->mm.cov;
+ gsl_matrix *r_inv;
+ r_inv = clone_matrix (idata->mm.corr);
+ gsl_linalg_cholesky_decomp (r_inv);
+ gsl_linalg_cholesky_invert (r_inv);
+
+ idata->ai_cov = anti_image_cov (r_inv);
+ idata->ai_cor = anti_image_corr (r_inv, idata);
+
+ int i;
+ double sum_ssq_r = 0;
+ double sum_ssq_a = 0;
+ for (i = 0; i < r_inv->size1; ++i)
+ {
+ sum_ssq_r += ssq_od_n (idata->mm.corr, i);
+ sum_ssq_a += ssq_od_n (idata->ai_cor, i);
+ }
+
+ gsl_matrix_free (r_inv);
+
if (factor->print & PRINT_DETERMINANT
|| factor->print & PRINT_KMO)
{
gsl_matrix_free (tmp);
}
- if ( factor->print & PRINT_UNIVARIATE)
+ if (factor->print & PRINT_UNIVARIATE
+ && idata->mm.n && idata->mm.mean_matrix && idata->mm.var_matrix)
{
- 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 pivot_table *table = pivot_table_create (
+ N_("Descriptive Statistics"));
+ pivot_table_set_weight_var (table, factor->wv);
- struct tab_table *t = tab_create (nc, nr);
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_title (t, _("Descriptive Statistics"));
+ 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);
- 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_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)
+ if (factor->print & PRINT_KMO && idata->mm.n)
{
- int i;
- double sum_ssq_r = 0;
- double sum_ssq_a = 0;
-
- 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;
-
- gsl_matrix *a, *x;
-
- struct tab_table *t = tab_create (nc, nr);
- tab_title (t, _("KMO and Bartlett's Test"));
-
- x = clone_matrix (idata->mm.corr);
- gsl_linalg_cholesky_decomp (x);
- gsl_linalg_cholesky_invert (x);
-
- a = anti_image (x);
-
- for (i = 0; i < x->size1; ++i)
- {
- sum_ssq_r += ssq_od_n (x, i);
- sum_ssq_a += ssq_od_n (a, i);
- }
-
- gsl_matrix_free (a);
- gsl_matrix_free (x);
-
- 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);
struct factor_matrix_workspace *fmw = factor_matrix_workspace_alloc (idata->msr->size, idata->n_extractions);
gsl_matrix *factor_matrix = gsl_matrix_calloc (factor->n_vars, fmw->n_factors);
- if ( factor->extraction == EXTRACTION_PAF)
+ if (factor->extraction == EXTRACTION_PAF)
{
gsl_vector *diff = gsl_vector_alloc (idata->msr->size);
struct smr_workspace *ws = ws_create (idata->analysis_matrix);
gsl_vector_minmax (diff, &min, &max);
- if ( fabs (min) < factor->econverge && fabs (max) < factor->econverge)
+ if (fabs (min) < factor->econverge && fabs (max) < factor->econverge)
break;
}
gsl_vector_free (diff);
}
+ show_aic (factor, idata);
show_communalities (factor, initial_communalities, extracted_communalities);
-
- if ( factor->rotation != ROT_NONE)
+ if (factor->rotation != ROT_NONE)
{
rotated_factors = gsl_matrix_calloc (factor_matrix->size1, factor_matrix->size2);
rotated_loadings = gsl_vector_calloc (factor_matrix->size2);
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)
+ 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)
+ 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);
}
- if ( factor->rotation == ROT_PROMAX)
+ if (factor->rotation == ROT_PROMAX)
{
show_factor_correlation (factor, fcm);
gsl_matrix_free (fcm);
projects / pspp / blobdiff