/* PSPP - a program for statistical analysis.
- Copyright (C) 2009 Free Software Foundation, Inc.
+ Copyright (C) 2009, 2010, 2011 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
#include <config.h>
-
#include <gsl/gsl_vector.h>
#include <gsl/gsl_linalg.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_blas.h>
#include <gsl/gsl_sort_vector.h>
-#include <math/covariance.h>
-
-#include <math/correlation.h>
-#include <math/moments.h>
-#include <data/procedure.h>
-#include <language/lexer/variable-parser.h>
-#include <language/lexer/value-parser.h>
-#include <language/command.h>
-#include <language/lexer/lexer.h>
-
-#include <data/casegrouper.h>
-#include <data/casereader.h>
-#include <data/casewriter.h>
-#include <data/dictionary.h>
-#include <data/format.h>
-#include <data/subcase.h>
-
-#include <libpspp/misc.h>
-#include <libpspp/message.h>
-
-#include <output/table.h>
-
+#include "data/casegrouper.h"
+#include "data/casereader.h"
+#include "data/casewriter.h"
+#include "data/dataset.h"
+#include "data/dictionary.h"
+#include "data/format.h"
+#include "data/subcase.h"
+#include "language/command.h"
+#include "language/lexer/lexer.h"
+#include "language/lexer/value-parser.h"
+#include "language/lexer/variable-parser.h"
+#include "libpspp/message.h"
+#include "libpspp/misc.h"
+#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 "gettext.h"
#define _(msgid) gettext (msgid)
EXTRACTION_PAF,
};
+enum plot_opts
+ {
+ PLOT_SCREE = 0x0001,
+ PLOT_ROTATION = 0x0002
+ };
+
enum print_opts
{
PRINT_UNIVARIATE = 0x0001,
PRINT_FSCORE = 0x1000
};
+enum rotation_type
+ {
+ ROT_VARIMAX = 0,
+ ROT_EQUAMAX,
+ ROT_QUARTIMAX,
+ ROT_NONE
+ };
+
+typedef void (*rotation_coefficients) (double *x, double *y,
+ double a, double b, double c, double d,
+ const gsl_matrix *loadings );
+
+
+static void
+varimax_coefficients (double *x, double *y,
+ double a, double b, double c, double d,
+ 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 )
+{
+ *x = d - loadings->size2 * a * b / loadings->size1;
+ *y = c - loadings->size2 * (a * a - b * b) / (2 * loadings->size1);
+}
+
+static void
+quartimax_coefficients (double *x, double *y,
+ double a UNUSED, double b UNUSED, double c, double d,
+ const gsl_matrix *loadings UNUSED)
+{
+ *x = d ;
+ *y = c ;
+}
+
+static const rotation_coefficients rotation_coeff[3] = {
+ varimax_coefficients,
+ equamax_coefficients,
+ quartimax_coefficients
+};
+
struct cmd_factor
{
enum mv_class exclude;
enum print_opts print;
enum extraction_method extraction;
+ enum plot_opts plot;
+ enum rotation_type rotation;
/* Extraction Criteria */
int n_factors;
double econverge;
int iterations;
+ double rconverge;
+
/* Format */
double blank;
bool sort;
/* Intermediate values used in calculation */
const gsl_matrix *corr ; /* The correlation matrix */
- const gsl_matrix *cov ; /* The covariance matrix */
+ gsl_matrix *cov ; /* The covariance matrix */
const gsl_matrix *n ; /* Matrix of number of samples */
gsl_vector *eval ; /* The eigenvalues */
gsl_vector_free (id->msr);
gsl_vector_free (id->eval);
gsl_matrix_free (id->evec);
+ if (id->cov != NULL)
+ gsl_matrix_free (id->cov);
free (id);
}
+#if 0
static void
dump_matrix (const gsl_matrix *m)
{
}
printf ("\n");
}
+#endif
static int
}
+static void
+drot_go (double phi, double *l0, double *l1)
+{
+ double r0 = cos (phi) * *l0 + sin (phi) * *l1;
+ double r1 = - sin (phi) * *l0 + cos (phi) * *l1;
+
+ *l0 = r0;
+ *l1 = r1;
+}
+
+
+static gsl_matrix *
+clone_matrix (const gsl_matrix *m)
+{
+ int j, k;
+ gsl_matrix *c = gsl_matrix_calloc (m->size1, m->size2);
+
+ for (j = 0 ; j < c->size1; ++j)
+ {
+ for (k = 0 ; k < c->size2; ++k)
+ {
+ const double *v = gsl_matrix_const_ptr (m, j, k);
+ gsl_matrix_set (c, j, k, *v);
+ }
+ }
+
+ return c;
+}
+
+
+static double
+initial_sv (const gsl_matrix *fm)
+{
+ int j, k;
+
+ double sv = 0.0;
+ for (j = 0 ; j < fm->size2; ++j)
+ {
+ double l4s = 0;
+ double l2s = 0;
+
+ for (k = j + 1 ; k < fm->size2; ++k)
+ {
+ double lambda = gsl_matrix_get (fm, k, j);
+ double lambda_sq = lambda * lambda;
+ double lambda_4 = lambda_sq * lambda_sq;
+
+ l4s += lambda_4;
+ l2s += lambda_sq;
+ }
+ sv += ( fm->size1 * l4s - (l2s * l2s) ) / (fm->size1 * fm->size1 );
+ }
+ return sv;
+}
+
+static void
+rotate (const struct cmd_factor *cf, const gsl_matrix *unrot,
+ const gsl_vector *communalities,
+ gsl_matrix *result,
+ gsl_vector *rotated_loadings
+ )
+{
+ int j, k;
+ int i;
+ double prev_sv;
+
+ /* First get a normalised version of UNROT */
+ gsl_matrix *normalised = gsl_matrix_calloc (unrot->size1, unrot->size2);
+ gsl_matrix *h_sqrt = gsl_matrix_calloc (communalities->size, communalities->size);
+ gsl_matrix *h_sqrt_inv ;
+
+ /* H is the diagonal matrix containing the absolute values of the communalities */
+ for (i = 0 ; i < communalities->size ; ++i)
+ {
+ double *ptr = gsl_matrix_ptr (h_sqrt, i, i);
+ *ptr = fabs (gsl_vector_get (communalities, i));
+ }
+
+ /* Take the square root of the communalities */
+ gsl_linalg_cholesky_decomp (h_sqrt);
+
+
+ /* Save a copy of h_sqrt and invert it */
+ h_sqrt_inv = clone_matrix (h_sqrt);
+ gsl_linalg_cholesky_decomp (h_sqrt_inv);
+ gsl_linalg_cholesky_invert (h_sqrt_inv);
+
+ /* normalised vertion is H^{1/2} x UNROT */
+ gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, h_sqrt_inv, unrot, 0.0, normalised);
+
+ gsl_matrix_free (h_sqrt_inv);
+
+
+ /* Now perform the rotation iterations */
+
+ prev_sv = initial_sv (normalised);
+ for (i = 0 ; i < cf->iterations ; ++i)
+ {
+ double sv = 0.0;
+ for (j = 0 ; j < normalised->size2; ++j)
+ {
+ /* These variables relate to the convergence criterium */
+ double l4s = 0;
+ double l2s = 0;
+
+ for (k = j + 1 ; k < normalised->size2; ++k)
+ {
+ int p;
+ double a = 0.0;
+ double b = 0.0;
+ double c = 0.0;
+ double d = 0.0;
+ double x, y;
+ double phi;
+
+ for (p = 0; p < normalised->size1; ++p)
+ {
+ double jv = gsl_matrix_get (normalised, p, j);
+ double kv = gsl_matrix_get (normalised, p, k);
+
+ double u = jv * jv - kv * kv;
+ double v = 2 * jv * kv;
+ a += u;
+ b += v;
+ c += u * u - v * v;
+ d += 2 * u * v;
+ }
+
+ rotation_coeff [cf->rotation] (&x, &y, a, b, c, d, normalised);
+
+ phi = atan2 (x, y) / 4.0 ;
+
+ /* Don't bother rotating if the angle is small */
+ if ( fabs (sin (phi) ) <= pow (10.0, -15.0))
+ continue;
+
+ for (p = 0; p < normalised->size1; ++p)
+ {
+ double *lambda0 = gsl_matrix_ptr (normalised, p, j);
+ double *lambda1 = gsl_matrix_ptr (normalised, p, k);
+ drot_go (phi, lambda0, lambda1);
+ }
+
+ /* Calculate the convergence criterium */
+ {
+ double lambda = gsl_matrix_get (normalised, k, j);
+ double lambda_sq = lambda * lambda;
+ double lambda_4 = lambda_sq * lambda_sq;
+
+ l4s += lambda_4;
+ l2s += lambda_sq;
+ }
+ }
+ sv += ( normalised->size1 * l4s - (l2s * l2s) ) / (normalised->size1 * normalised->size1 );
+ }
+
+ if ( fabs (sv - prev_sv) <= cf->rconverge)
+ break;
+
+ prev_sv = sv;
+ }
+
+ gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0,
+ h_sqrt, normalised, 0.0, result);
+
+ gsl_matrix_free (h_sqrt);
+
+
+ /* reflect negative sums and populate the rotated loadings vector*/
+ for (i = 0 ; i < result->size2; ++i)
+ {
+ double ssq = 0.0;
+ double sum = 0.0;
+ for (j = 0 ; j < result->size1; ++j)
+ {
+ double s = gsl_matrix_get (result, j, i);
+ ssq += s * s;
+ sum += gsl_matrix_get (result, j, i);
+ }
+
+ gsl_vector_set (rotated_loadings, i, ssq);
+
+ if ( sum < 0 )
+ for (j = 0 ; j < result->size1; ++j)
+ {
+ double *lambda = gsl_matrix_ptr (result, j, i);
+ *lambda = - *lambda;
+ }
+ }
+}
+
+
/*
Get an approximation for the factor matrix into FACTORS, and the communalities into COMMUNALITIES.
R is the matrix to be analysed.
WS is a pointer to a structure which must have been initialised with factor_matrix_workspace_init.
*/
static void
-iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matrix *factors, struct factor_matrix_workspace *ws)
+iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matrix *factors,
+ struct factor_matrix_workspace *ws)
{
size_t i;
gsl_matrix_view mv ;
/* Take the square root of gamma */
gsl_linalg_cholesky_decomp (ws->gamma);
- gsl_blas_dgemm (CblasNoTrans, CblasNoTrans,
- 1.0, &mv.matrix, ws->gamma, 0.0, factors);
+ gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, &mv.matrix, ws->gamma, 0.0, factors);
for (i = 0 ; i < r->size1 ; ++i)
{
const struct dictionary *dict = dataset_dict (ds);
struct cmd_factor factor;
+ factor.n_vars = 0;
+ factor.vars = NULL;
factor.method = METHOD_CORR;
factor.missing_type = MISS_LISTWISE;
factor.exclude = MV_ANY;
factor.min_eigen = SYSMIS;
factor.iterations = 25;
factor.econverge = 0.001;
+
factor.blank = 0;
factor.sort = false;
+ factor.plot = 0;
+ factor.rotation = ROT_VARIMAX;
+
+ factor.rconverge = 0.0001;
factor.wv = dict_get_weight (dict);
- lex_match (lexer, '/');
+ lex_match (lexer, T_SLASH);
if (!lex_force_match_id (lexer, "VARIABLES"))
{
goto error;
}
- lex_match (lexer, '=');
+ lex_match (lexer, T_EQUALS);
if (!parse_variables_const (lexer, dict, &factor.vars, &factor.n_vars,
PV_NO_DUPLICATE | PV_NUMERIC))
goto error;
- while (lex_token (lexer) != '.')
- {
- lex_match (lexer, '/');
+ if (factor.n_vars < 2)
+ msg (MW, _("Factor analysis on a single variable is not useful."));
+ while (lex_token (lexer) != T_ENDCMD)
+ {
+ lex_match (lexer, T_SLASH);
if (lex_match_id (lexer, "PLOT"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "EIGEN"))
{
+ factor.plot |= PLOT_SCREE;
}
#if FACTOR_FULLY_IMPLEMENTED
else if (lex_match_id (lexer, "ROTATION"))
}
else if (lex_match_id (lexer, "METHOD"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "COVARIANCE"))
{
}
}
}
-#if FACTOR_FULLY_IMPLEMENTED
else if (lex_match_id (lexer, "ROTATION"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
- if (lex_match_id (lexer, "VARIMAX"))
+ /* VARIMAX and DEFAULT are defaults */
+ if (lex_match_id (lexer, "VARIMAX") || lex_match_id (lexer, "DEFAULT"))
{
+ factor.rotation = ROT_VARIMAX;
}
- else if (lex_match_id (lexer, "DEFAULT"))
+ else if (lex_match_id (lexer, "EQUAMAX"))
+ {
+ factor.rotation = ROT_EQUAMAX;
+ }
+ else if (lex_match_id (lexer, "QUARTIMAX"))
{
+ factor.rotation = ROT_QUARTIMAX;
+ }
+ else if (lex_match_id (lexer, "NOROTATE"))
+ {
+ factor.rotation = ROT_NONE;
}
else
{
}
}
}
-#endif
else if (lex_match_id (lexer, "CRITERIA"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "FACTORS"))
{
- if ( lex_force_match (lexer, '('))
+ if ( lex_force_match (lexer, T_LPAREN))
{
lex_force_int (lexer);
factor.n_factors = lex_integer (lexer);
lex_get (lexer);
- lex_force_match (lexer, ')');
+ lex_force_match (lexer, T_RPAREN);
}
}
else if (lex_match_id (lexer, "MINEIGEN"))
{
- if ( lex_force_match (lexer, '('))
+ if ( lex_force_match (lexer, T_LPAREN))
{
lex_force_num (lexer);
factor.min_eigen = lex_number (lexer);
lex_get (lexer);
- lex_force_match (lexer, ')');
+ lex_force_match (lexer, T_RPAREN);
}
}
else if (lex_match_id (lexer, "ECONVERGE"))
{
- if ( lex_force_match (lexer, '('))
+ if ( lex_force_match (lexer, T_LPAREN))
{
lex_force_num (lexer);
factor.econverge = lex_number (lexer);
lex_get (lexer);
- lex_force_match (lexer, ')');
+ lex_force_match (lexer, T_RPAREN);
+ }
+ }
+ else if (lex_match_id (lexer, "RCONVERGE"))
+ {
+ if ( lex_force_match (lexer, T_LPAREN))
+ {
+ lex_force_num (lexer);
+ factor.rconverge = lex_number (lexer);
+ lex_get (lexer);
+ lex_force_match (lexer, T_RPAREN);
}
}
else if (lex_match_id (lexer, "ITERATE"))
{
- if ( lex_force_match (lexer, '('))
+ if ( lex_force_match (lexer, T_LPAREN))
{
lex_force_int (lexer);
factor.iterations = lex_integer (lexer);
lex_get (lexer);
- lex_force_match (lexer, ')');
+ lex_force_match (lexer, T_RPAREN);
}
}
else if (lex_match_id (lexer, "DEFAULT"))
else if (lex_match_id (lexer, "EXTRACTION"))
{
extraction_seen = true;
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "PAF"))
{
}
else if (lex_match_id (lexer, "FORMAT"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "SORT"))
{
}
else if (lex_match_id (lexer, "BLANK"))
{
- if ( lex_force_match (lexer, '('))
+ if ( lex_force_match (lexer, T_LPAREN))
{
lex_force_num (lexer);
factor.blank = lex_number (lexer);
lex_get (lexer);
- lex_force_match (lexer, ')');
+ lex_force_match (lexer, T_RPAREN);
}
}
else if (lex_match_id (lexer, "DEFAULT"))
else if (lex_match_id (lexer, "PRINT"))
{
factor.print = 0;
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "UNIVARIATE"))
{
}
else if (lex_match_id (lexer, "MISSING"))
{
- lex_match (lexer, '=');
- while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
if (lex_match_id (lexer, "INCLUDE"))
{
}
}
+ if ( factor.rotation == ROT_NONE )
+ factor.print &= ~PRINT_ROTATION;
+
if ( ! run_factor (ds, &factor))
goto error;
}
+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);
+
+ scree_submit (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_headers (t, heading_columns, 0, heading_rows, 0);
c = 1;
static void
-show_factor_matrix (const struct cmd_factor *factor, struct idata *idata, const gsl_matrix *fm)
+show_factor_matrix (const struct cmd_factor *factor, struct idata *idata, const char *title, const gsl_matrix *fm)
{
int i;
- const int n_factors = n_extracted_factors (factor, idata);
+ const int n_factors = idata->n_extractions;
const int heading_columns = 1;
const int heading_rows = 2;
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_title (t, title);
tab_headers (t, heading_columns, 0, heading_rows, 0);
static void
show_explained_variance (const struct cmd_factor * factor, struct idata *idata,
const gsl_vector *initial_eigenvalues,
- const gsl_vector *extracted_eigenvalues)
+ const gsl_vector *extracted_eigenvalues,
+ const gsl_vector *rotated_loadings)
{
size_t i;
int c = 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)
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_headers (t, heading_columns, 0, heading_rows, 0);
/* Outline the box */
for (i = 0; i < (nc - heading_columns) / 3 ; ++i)
{
tab_text (t, i * 3 + 1, 1, TAB_CENTER | TAT_TITLE, _("Total"));
+ /* 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 %"));
e_total = i_total;
}
-
for (i = 0 ; i < factor->n_vars; ++i)
{
const double i_lambda = gsl_vector_get (initial_eigenvalues, i);
const double e_lambda = gsl_vector_get (extracted_eigenvalues, i);
double e_percent = 100.0 * e_lambda / e_total ;
+ const double r_lambda = gsl_vector_get (rotated_loadings, i);
+ double r_percent = 100.0 * r_lambda / e_total ;
+
c = 0;
tab_text_format (t, c++, i + heading_rows, TAB_LEFT | TAT_TITLE, _("%d"), i + 1);
i_cum += i_percent;
e_cum += e_percent;
+ r_cum += r_percent;
/* Initial Eigenvalues */
if (factor->print & PRINT_INITIAL)
tab_double (t, c++, i + heading_rows, 0, i_cum, NULL);
}
+
if (factor->print & PRINT_EXTRACTION)
{
- if ( i < n_extracted_factors (factor, idata))
+ if (i < idata->n_extractions)
{
/* Sums of squared loadings */
tab_double (t, c++, i + heading_rows, 0, e_lambda, NULL);
tab_double (t, c++, i + heading_rows, 0, e_cum, NULL);
}
}
+
+ if (factor->print & PRINT_ROTATION)
+ {
+ if (i < idata->n_extractions)
+ {
+ tab_double (t, c++, i + heading_rows, 0, r_lambda, NULL);
+ tab_double (t, c++, i + heading_rows, 0, r_percent, NULL);
+ tab_double (t, c++, i + heading_rows, 0, r_cum, NULL);
+ }
+ }
+
}
tab_submit (t);
if (nr <= heading_rows && suffix_rows == 0)
return;
- t = tab_create (nc, nr + suffix_rows, 0);
+ t = tab_create (nc, nr + suffix_rows);
tab_title (t, _("Correlation Matrix"));
- tab_dim (t, tab_natural_dimensions, NULL);
-
tab_hline (t, TAL_1, 0, nc - 1, heading_rows);
if (nr > heading_rows)
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"));
+ tab_text (t, 0, y, TAT_TITLE, _("Sig. (1-tailed)"));
for (i = 0; i < factor->n_vars; ++i)
{
const gsl_matrix *analysis_matrix;
struct idata *idata = idata_alloc (factor->n_vars);
- struct covariance *cov = covariance_create (factor->n_vars, factor->vars,
+ struct covariance *cov = covariance_1pass_create (factor->n_vars, factor->vars,
factor->wv, factor->exclude);
for ( ; (c = casereader_read (r) ); case_unref (c))
idata->cov = covariance_calculate (cov);
+ if (idata->cov == NULL)
+ {
+ msg (MW, _("The dataset contains no complete observations. No analysis will be performed."));
+ goto finish;
+ }
+
var_matrix = covariance_moments (cov, MOMENT_VARIANCE);
mean_matrix = covariance_moments (cov, MOMENT_MEAN);
idata->n = covariance_moments (cov, MOMENT_NONE);
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_headers (t, heading_columns, 0, heading_rows, 0);
gsl_eigen_symmv_sort (idata->eval, idata->evec, GSL_EIGEN_SORT_ABS_DESC);
#endif
+ idata->n_extractions = n_extracted_factors (factor, idata);
+
+ if (idata->n_extractions == 0)
+ {
+ msg (MW, _("The FACTOR criteria result in zero factors extracted. Therefore no analysis will be performed."));
+ goto finish;
+ }
+
+ if (idata->n_extractions > factor->n_vars)
+ {
+ msg (MW, _("The FACTOR criteria result in more factors than variables, which is not meaningful. No analysis will be performed."));
+ goto finish;
+ }
+
{
+ gsl_matrix *rotated_factors = NULL;
+ gsl_vector *rotated_loadings = NULL;
+
const gsl_vector *extracted_eigenvalues = NULL;
gsl_vector *initial_communalities = gsl_vector_alloc (factor->n_vars);
gsl_vector *extracted_communalities = gsl_vector_alloc (factor->n_vars);
size_t i;
- struct factor_matrix_workspace *fmw = factor_matrix_workspace_alloc (idata->msr->size, n_extracted_factors (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)
}
gsl_vector_free (diff);
+
+
gsl_vector_memcpy (extracted_communalities, idata->msr);
extracted_eigenvalues = fmw->eval;
}
else if (factor->extraction == EXTRACTION_PC)
{
- for (i = 0 ; i < factor->n_vars; ++i)
- {
- gsl_vector_set (initial_communalities, i, communality (idata, i, factor->n_vars));
- }
+ for (i = 0; i < factor->n_vars; ++i)
+ gsl_vector_set (initial_communalities, i, communality (idata, i, factor->n_vars));
+
gsl_vector_memcpy (extracted_communalities, initial_communalities);
iterate_factor_matrix (analysis_matrix, extracted_communalities, factor_matrix, fmw);
+
+
extracted_eigenvalues = idata->eval;
}
+
show_communalities (factor, initial_communalities, extracted_communalities);
- show_explained_variance (factor, idata, idata->eval, extracted_eigenvalues);
+
+ if ( factor->rotation != ROT_NONE)
+ {
+ rotated_factors = gsl_matrix_calloc (factor_matrix->size1, factor_matrix->size2);
+ rotated_loadings = gsl_vector_calloc (factor_matrix->size2);
+
+ rotate (factor, factor_matrix, extracted_communalities, rotated_factors, rotated_loadings);
+ }
+
+ show_explained_variance (factor, idata, idata->eval, extracted_eigenvalues, rotated_loadings);
factor_matrix_workspace_free (fmw);
- show_factor_matrix (factor, idata, factor_matrix);
+ show_scree (factor, idata);
+
+ show_factor_matrix (factor, idata,
+ factor->extraction == EXTRACTION_PC ? _("Component Matrix") : _("Factor Matrix"),
+ factor_matrix);
+
+ if ( factor->rotation != ROT_NONE)
+ {
+ show_factor_matrix (factor, idata,
+ factor->extraction == EXTRACTION_PC ? _("Rotated Component Matrix") : _("Rotated Factor Matrix"),
+ rotated_factors);
+
+ gsl_matrix_free (rotated_factors);
+ }
+
+
gsl_vector_free (initial_communalities);
gsl_vector_free (extracted_communalities);
}
+ finish:
+
idata_free (idata);
casereader_destroy (r);
}
+
+
+
projects / pspp-builds.git / blobdiff