+++ /dev/null
-/* PSPP - a program for statistical analysis.
- 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
- 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 <gsl/gsl_cdf.h>
-#include <gsl/gsl_matrix.h>
-#include <math.h>
-
-#include "data/casegrouper.h"
-#include "data/casereader.h"
-#include "data/dataset.h"
-#include "data/dictionary.h"
-#include "data/format.h"
-#include "data/variable.h"
-#include "language/command.h"
-#include "language/dictionary/split-file.h"
-#include "language/lexer/lexer.h"
-#include "language/lexer/variable-parser.h"
-#include "libpspp/assertion.h"
-#include "libpspp/message.h"
-#include "libpspp/misc.h"
-#include "math/correlation.h"
-#include "math/covariance.h"
-#include "math/moments.h"
-#include "output/pivot-table.h"
-
-#include "gl/xalloc.h"
-#include "gl/minmax.h"
-
-#include "gettext.h"
-#define _(msgid) gettext (msgid)
-#define N_(msgid) msgid
-
-
-struct corr
- {
- size_t n_vars_total;
- size_t n_vars1;
-
- const struct variable **vars;
- };
-
-
-/* Handling of missing values. */
-enum corr_missing_type
- {
- CORR_PAIRWISE, /* Handle missing values on a per-variable-pair basis. */
- CORR_LISTWISE /* Discard entire case if any variable is missing. */
- };
-
-struct corr_opts
-{
- enum corr_missing_type missing_type;
- enum mv_class exclude; /* Classes of missing values to exclude. */
-
- bool sig; /* Flag significant values or not */
- int tails; /* Report significance with how many tails ? */
- bool descriptive_stats;
- bool xprod_stats;
-
- const struct variable *wv; /* The weight variable (if any) */
-};
-
-
-static void
-output_descriptives (const struct corr *corr, const struct corr_opts *opts,
- const gsl_matrix *means,
- const gsl_matrix *vars, const gsl_matrix *ns)
-{
- struct pivot_table *table = pivot_table_create (
- N_("Descriptive Statistics"));
- pivot_table_set_weight_var (table, opts->wv);
-
- 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 pivot_dimension *variables = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Variable"));
-
- for (size_t r = 0; r < corr->n_vars_total; ++r)
- {
- const struct variable *v = corr->vars[r];
-
- int row = pivot_category_create_leaf (variables->root,
- pivot_value_new_variable (v));
-
- 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]));
- }
-
- pivot_table_submit (table);
-}
-
-static void
-output_correlation (const struct corr *corr, const struct corr_opts *opts,
- const gsl_matrix *cm, const gsl_matrix *samples,
- const gsl_matrix *cv)
-{
- struct pivot_table *table = pivot_table_create (N_("Correlations"));
- pivot_table_set_weight_var (table, opts->wv);
-
- /* Column variable dimension. */
- struct pivot_dimension *columns = pivot_dimension_create (
- table, PIVOT_AXIS_COLUMN, N_("Variables"));
-
- size_t matrix_cols = (corr->n_vars_total > corr->n_vars1
- ? corr->n_vars_total - corr->n_vars1
- : corr->n_vars1);
- for (size_t 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];
- pivot_category_create_leaf (columns->root, pivot_value_new_variable (v));
- }
-
- /* 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 (opts->xprod_stats)
- pivot_category_create_leaves (statistics->root, N_("Cross-products"),
- N_("Covariance"));
-
- if (opts->missing_type != CORR_LISTWISE)
- pivot_category_create_leaves (statistics->root, N_("N"), PIVOT_RC_COUNT);
-
- /* 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]));
-
- struct pivot_footnote *sig_footnote = pivot_table_create_footnote (
- table, pivot_value_new_text (N_("Significant at .05 level")));
-
- for (size_t r = 0; r < corr->n_vars1; r++)
- for (size_t 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->xprod_stats)
- {
- 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);
- }
- }
-
- pivot_table_submit (table);
-}
-
-
-static void
-run_corr (struct casereader *r, const struct corr_opts *opts, const struct corr *corr)
-{
- struct covariance *cov = covariance_2pass_create (
- corr->n_vars_total, corr->vars, NULL,opts->wv, opts->exclude, true);
-
- struct casereader *rc = casereader_clone (r);
- struct ccase *c;
- for (; (c = casereader_read (r)); case_unref (c))
- covariance_accumulate_pass1 (cov, c);
- for (; (c = casereader_read (rc)); case_unref (c))
- covariance_accumulate_pass2 (cov, c);
- casereader_destroy (rc);
-
- gsl_matrix *cov_matrix = covariance_calculate (cov);
- if (!cov_matrix)
- {
- msg (SE, _("The data for the chosen variables are all missing or empty."));
- covariance_destroy (cov);
- return;
- }
-
- const gsl_matrix *samples_matrix = covariance_moments (cov, MOMENT_NONE);
- const gsl_matrix *var_matrix = covariance_moments (cov, MOMENT_VARIANCE);
- const gsl_matrix *mean_matrix = covariance_moments (cov, MOMENT_MEAN);
-
- gsl_matrix *corr_matrix = correlation_from_covariance (cov_matrix, var_matrix);
-
- if (opts->descriptive_stats)
- output_descriptives (corr, opts, mean_matrix, var_matrix, samples_matrix);
-
- output_correlation (corr, opts, corr_matrix, samples_matrix, cov_matrix);
-
- covariance_destroy (cov);
- gsl_matrix_free (corr_matrix);
- gsl_matrix_free (cov_matrix);
-}
-
-int
-cmd_correlations (struct lexer *lexer, struct dataset *ds)
-{
- size_t n_all_vars = 0; /* Total number of variables involved in this command */
- const struct dictionary *dict = dataset_dict (ds);
-
- struct corr *corrs = NULL;
- size_t n_corrs = 0;
- size_t allocated_corrs = 0;
-
- struct corr_opts opts = {
- .missing_type = CORR_PAIRWISE,
- .wv = dict_get_weight (dict),
- .tails = 2,
- .exclude = MV_ANY,
- };
-
- /* Parse CORRELATIONS. */
- while (lex_token (lexer) != T_ENDCMD)
- {
- lex_match (lexer, T_SLASH);
- if (lex_match_id (lexer, "MISSING"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "PAIRWISE"))
- opts.missing_type = CORR_PAIRWISE;
- else if (lex_match_id (lexer, "LISTWISE"))
- opts.missing_type = CORR_LISTWISE;
- else if (lex_match_id (lexer, "INCLUDE"))
- opts.exclude = MV_SYSTEM;
- else if (lex_match_id (lexer, "EXCLUDE"))
- opts.exclude = MV_ANY;
- else
- {
- lex_error_expecting (lexer, "PAIRWISE", "LISTWISE",
- "INCLUDE", "EXCLUDE");
- goto error;
- }
- lex_match (lexer, T_COMMA);
- }
- }
- else if (lex_match_id (lexer, "PRINT"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "TWOTAIL"))
- opts.tails = 2;
- else if (lex_match_id (lexer, "ONETAIL"))
- opts.tails = 1;
- else if (lex_match_id (lexer, "SIG"))
- opts.sig = false;
- else if (lex_match_id (lexer, "NOSIG"))
- opts.sig = true;
- else
- {
- lex_error_expecting (lexer, "TWOTAIL", "ONETAIL",
- "SIG", "NOSIG");
- goto error;
- }
-
- lex_match (lexer, T_COMMA);
- }
- }
- else if (lex_match_id (lexer, "STATISTICS"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "DESCRIPTIVES"))
- opts.descriptive_stats = true;
- else if (lex_match_id (lexer, "XPROD"))
- opts.xprod_stats = true;
- else if (lex_token (lexer) == T_ALL)
- {
- opts.descriptive_stats = opts.xprod_stats = true;
- lex_get (lexer);
- }
- else
- {
- lex_error_expecting (lexer, "DESCRIPTIVES", "XPROD", "ALL");
- goto error;
- }
-
- lex_match (lexer, T_COMMA);
- }
- }
- else
- {
- if (lex_match_id (lexer, "VARIABLES"))
- lex_match (lexer, T_EQUALS);
-
- const struct variable **vars;
- size_t n_vars1;
- if (!parse_variables_const (lexer, dict, &vars, &n_vars1, PV_NUMERIC))
- goto error;
-
- size_t n_vars_total = n_vars1;
- if (lex_match (lexer, T_WITH)
- && !parse_variables_const (lexer, dict, &vars, &n_vars_total,
- PV_NUMERIC | PV_APPEND))
- goto error;
-
- if (n_corrs >= allocated_corrs)
- corrs = x2nrealloc (corrs, &allocated_corrs, sizeof *corrs);
- corrs[n_corrs++] = (struct corr) {
- .n_vars1 = n_vars1,
- .n_vars_total = n_vars_total,
- .vars = vars,
- };
-
- n_all_vars += n_vars_total;
- }
- }
- if (n_corrs == 0)
- {
- lex_ofs_error (lexer, 0, lex_ofs (lexer) - 1,
- _("No variables specified."));
- goto error;
- }
-
- const struct variable **all_vars = xmalloc (n_all_vars * sizeof *all_vars);
- const struct variable **vv = all_vars;
- for (size_t i = 0; i < n_corrs; ++i)
- {
- const struct corr *c = &corrs[i];
- for (size_t v = 0; v < c->n_vars_total; ++v)
- *vv++ = c->vars[v];
- }
-
- struct casegrouper *grouper = casegrouper_create_splits (proc_open (ds), dict);
- struct casereader *group;
- while (casegrouper_get_next_group (grouper, &group))
- {
- for (size_t i = 0; i < n_corrs; ++i)
- {
- /* FIXME: No need to iterate the data multiple times */
- struct casereader *r = casereader_clone (group);
-
- if (opts.missing_type == CORR_LISTWISE)
- r = casereader_create_filter_missing (r, all_vars, n_all_vars,
- opts.exclude, NULL, NULL);
-
-
- run_corr (r, &opts, &corrs[i]);
- casereader_destroy (r);
- }
- casereader_destroy (group);
- }
- bool ok = casegrouper_destroy (grouper);
- ok = proc_commit (ds) && ok;
-
- free (all_vars);
-
- /* Done. */
- for (size_t i = 0; i < n_corrs; i++)
- free (corrs[i].vars);
- free (corrs);
-
- return ok ? CMD_SUCCESS : CMD_CASCADING_FAILURE;
-
-error:
- for (size_t i = 0; i < n_corrs; i++)
- free (corrs[i].vars);
- free (corrs);
- return CMD_FAILURE;
-}
projects / pspp / blobdiff