--- /dev/null
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2010 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 <data/case.h>
+#include <data/casegrouper.h>
+#include <data/casereader.h>
+
+#include <math/covariance.h>
+#include <math/categoricals.h>
+#include <math/moments.h>
+#include <gsl/gsl_matrix.h>
+#include <linreg/sweep.h>
+
+#include <libpspp/ll.h>
+
+#include <language/lexer/lexer.h>
+#include <language/lexer/variable-parser.h>
+#include <language/lexer/value-parser.h>
+#include <language/command.h>
+
+#include <data/procedure.h>
+#include <data/value.h>
+#include <data/dictionary.h>
+
+#include <language/dictionary/split-file.h>
+#include <libpspp/taint.h>
+#include <libpspp/misc.h>
+
+#include <gsl/gsl_cdf.h>
+#include <math.h>
+#include <data/format.h>
+
+#include <libpspp/message.h>
+
+#include <output/tab.h>
+
+#include "gettext.h"
+#define _(msgid) gettext (msgid)
+
+struct glm_spec
+{
+ size_t n_dep_vars;
+ const struct variable **dep_vars;
+
+ size_t n_factor_vars;
+ const struct variable **factor_vars;
+
+ enum mv_class exclude;
+
+ /* The weight variable */
+ const struct variable *wv;
+
+ bool intercept;
+};
+
+struct glm_workspace
+{
+ double total_ssq;
+ struct moments *totals;
+};
+
+static void output_glm (const struct glm_spec *, const struct glm_workspace *ws);
+static void run_glm (const struct glm_spec *cmd, struct casereader *input, const struct dataset *ds);
+
+int
+cmd_glm (struct lexer *lexer, struct dataset *ds)
+{
+ const struct dictionary *dict = dataset_dict (ds);
+ struct glm_spec glm ;
+ glm.n_dep_vars = 0;
+ glm.n_factor_vars = 0;
+ glm.dep_vars = NULL;
+ glm.factor_vars = NULL;
+ glm.exclude = MV_ANY;
+ glm.intercept = true;
+ glm.wv = dict_get_weight (dict);
+
+
+ if (!parse_variables_const (lexer, dict,
+ &glm.dep_vars, &glm.n_dep_vars,
+ PV_NO_DUPLICATE | PV_NUMERIC))
+ goto error;
+
+ lex_force_match (lexer, T_BY);
+
+ if (!parse_variables_const (lexer, dict,
+ &glm.factor_vars, &glm.n_factor_vars,
+ PV_NO_DUPLICATE | PV_NUMERIC))
+ goto error;
+
+ if ( glm.n_dep_vars > 1)
+ {
+ msg (ME, _("Multivariate analysis is not yet implemented"));
+ return CMD_FAILURE;
+ }
+
+ struct const_var_set *factors = const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
+
+
+ while (lex_token (lexer) != '.')
+ {
+ lex_match (lexer, '/');
+
+ if (lex_match_id (lexer, "MISSING"))
+ {
+ lex_match (lexer, '=');
+ while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ {
+ if (lex_match_id (lexer, "INCLUDE"))
+ {
+ glm.exclude = MV_SYSTEM;
+ }
+ else if (lex_match_id (lexer, "EXCLUDE"))
+ {
+ glm.exclude = MV_ANY;
+ }
+ else
+ {
+ lex_error (lexer, NULL);
+ goto error;
+ }
+ }
+ }
+ else if (lex_match_id (lexer, "INTERCEPT"))
+ {
+ lex_match (lexer, '=');
+ while (lex_token (lexer) != '.' && lex_token (lexer) != '/')
+ {
+ if (lex_match_id (lexer, "INCLUDE"))
+ {
+ glm.intercept = true;
+ }
+ else if (lex_match_id (lexer, "EXCLUDE"))
+ {
+ glm.intercept = false;
+ }
+ else
+ {
+ lex_error (lexer, NULL);
+ goto error;
+ }
+ }
+ }
+ else if (lex_match_id (lexer, "DESIGN"))
+ {
+ size_t n_des;
+ const struct variable **des;
+ lex_match (lexer, '=');
+
+ parse_const_var_set_vars (lexer, factors, &des, &n_des, 0);
+ }
+ else
+ {
+ lex_error (lexer, NULL);
+ goto error;
+ }
+ }
+
+
+ {
+ struct casegrouper *grouper;
+ struct casereader *group;
+ bool ok;
+
+ grouper = casegrouper_create_splits (proc_open (ds), dict);
+ while (casegrouper_get_next_group (grouper, &group))
+ run_glm (&glm, group, ds);
+ ok = casegrouper_destroy (grouper);
+ ok = proc_commit (ds) && ok;
+ }
+
+ return CMD_SUCCESS;
+
+ error:
+ return CMD_FAILURE;
+}
+
+static void dump_matrix (const gsl_matrix *m);
+
+static void
+run_glm (const struct glm_spec *cmd, struct casereader *input, const struct dataset *ds)
+{
+ int v;
+ struct taint *taint;
+ struct dictionary *dict = dataset_dict (ds);
+ struct casereader *reader;
+ struct ccase *c;
+
+ struct glm_workspace ws;
+
+ struct categoricals *cats = categoricals_create (cmd->factor_vars, cmd->n_factor_vars,
+ cmd->wv, cmd->exclude,
+ NULL, NULL,
+ NULL, NULL);
+
+ struct covariance *cov = covariance_2pass_create (cmd->n_dep_vars, cmd->dep_vars,
+ cats,
+ cmd->wv, cmd->exclude);
+
+
+ c = casereader_peek (input, 0);
+ if (c == NULL)
+ {
+ casereader_destroy (input);
+ return;
+ }
+ output_split_file_values (ds, c);
+ case_unref (c);
+
+ taint = taint_clone (casereader_get_taint (input));
+
+ ws.totals = moments_create (MOMENT_VARIANCE);
+
+ bool warn_bad_weight = true;
+ for (reader = casereader_clone (input);
+ (c = casereader_read (reader)) != NULL; case_unref (c))
+ {
+ double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
+
+ for ( v = 0; v < cmd->n_dep_vars; ++v)
+ moments_pass_one (ws.totals, case_data (c, cmd->dep_vars[v])->f, weight);
+
+ covariance_accumulate_pass1 (cov, c);
+ }
+ casereader_destroy (reader);
+
+ categoricals_done (cats);
+
+ for (reader = casereader_clone (input);
+ (c = casereader_read (reader)) != NULL; case_unref (c))
+ {
+ double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
+
+ for ( v = 0; v < cmd->n_dep_vars; ++v)
+ moments_pass_two (ws.totals, case_data (c, cmd->dep_vars[v])->f, weight);
+
+ covariance_accumulate_pass2 (cov, c);
+ }
+ casereader_destroy (reader);
+
+ {
+ gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+
+ dump_matrix (cm);
+
+ ws.total_ssq = gsl_matrix_get (cm, 0, 0);
+
+ reg_sweep (cm, 0);
+
+ dump_matrix (cm);
+ }
+
+ if (!taint_has_tainted_successor (taint))
+ output_glm (cmd, &ws);
+
+ taint_destroy (taint);
+}
+
+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;
+
+ 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 + 4 + cmd->n_factor_vars;
+ if (cmd->intercept)
+ nr++;
+
+ t = tab_create (nc, nr);
+ 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"), "III");
+ 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."));
+
+ r = heading_rows;
+ tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
+
+ double intercept, n_total;
+ if (cmd->intercept)
+ {
+ double mean;
+ moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
+ intercept = pow2 (mean * n_total) / n_total;
+
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Intercept"));
+ tab_double (t, 1, r, 0, intercept, NULL);
+ tab_double (t, 2, r, 0, 1.00, wfmt);
+
+ tab_double (t, 3, r, 0, intercept / 1.0 , NULL);
+ r++;
+ }
+
+ for (f = 0; f < cmd->n_factor_vars; ++f)
+ {
+ tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE,
+ var_to_string (cmd->factor_vars[f]));
+ }
+
+ tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE, _("Error"));
+
+ if (cmd->intercept)
+ {
+ double ssq = intercept + ws->total_ssq;
+ double mse = ssq / n_total;
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Total"));
+ tab_double (t, 1, r, 0, ssq, NULL);
+ tab_double (t, 2, r, 0, n_total, wfmt);
+
+ r++;
+ }
+
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Total"));
+
+ tab_double (t, 1, r, 0, ws->total_ssq, NULL);
+ tab_double (t, 2, r, 0, n_total - 1.0, wfmt);
+
+ tab_submit (t);
+}
+
+static
+void dump_matrix (const gsl_matrix *m)
+{
+ size_t i, j;
+ for (i = 0; i < m->size1; ++i)
+ {
+ for (j = 0; j < m->size2; ++j)
+ {
+ double x = gsl_matrix_get (m, i, j);
+ printf ("%.3f ", x);
+ }
+ printf ("\n");
+ }
+ printf ("\n");
+}
+++ /dev/null
-/* PSPP - a program for statistical analysis.
- Copyright (C) 2007, 2009 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 <gsl/gsl_vector.h>
-#include <math.h>
-#include <stdlib.h>
-
-#include <data/case.h>
-#include <data/casegrouper.h>
-#include <data/casereader.h>
-#include <data/dictionary.h>
-#include <data/missing-values.h>
-#include <data/procedure.h>
-#include <data/transformations.h>
-#include <data/value-labels.h>
-#include <data/variable.h>
-#include <language/command.h>
-#include <language/dictionary/split-file.h>
-#include <language/data-io/file-handle.h>
-#include <language/lexer/lexer.h>
-#include <libpspp/compiler.h>
-#include <libpspp/message.h>
-#include <math/covariance.h>
-#include <math/categoricals.h>
-#include <math/linreg.h>
-#include <math/moments.h>
-#include <output/tab.h>
-
-#include "xalloc.h"
-#include "gettext.h"
-
-/* (headers) */
-
-/* (specification)
- "GLM" (glm_):
- *dependent=custom;
- design=custom;
- by=varlist;
- with=varlist.
-*/
-/* (declarations) */
-/* (functions) */
-static struct cmd_glm cmd;
-
-
-/*
- Moments for each of the variables used.
- */
-struct moments_var
-{
- struct moments1 *m;
- double *weight;
- double *mean;
- double *variance;
- const struct variable *v;
-};
-
-
-/*
- Dependent variable used.
- */
-static const struct variable **v_dependent;
-
-/*
- Number of dependent variables.
- */
-static size_t n_dependent;
-
-size_t n_inter; /* Number of interactions. */
-size_t n_members; /* Number of memebr variables in an interaction. */
-
-struct interaction_variable **interactions;
-
-int cmd_glm (struct lexer *lexer, struct dataset *ds);
-
-static bool run_glm (struct casereader *,
- struct cmd_glm *,
- const struct dataset *);
-/*
- If the DESIGN subcommand was not specified, specify all possible
- two-way interactions.
- */
-static void
-check_interactions (struct dataset *ds, struct cmd_glm *cmd)
-{
- size_t i;
- size_t j;
- size_t k = 0;
- struct variable **interaction_vars;
-
- /*
- User did not specify the design matrix, so we
- specify it here.
- */
- n_inter = (cmd->n_by + cmd->n_with) * (cmd->n_by + cmd->n_with - 1) / 2;
- interactions = xnmalloc (n_inter, sizeof (*interactions));
- interaction_vars = xnmalloc (2, sizeof (*interaction_vars));
- for (i = 0; i < cmd->n_by; i++)
- {
- for (j = i + 1; j < cmd->n_by; j++)
- {
- interaction_vars[0] = cmd->v_by[i];
- interaction_vars[1] = cmd->v_by[j];
- interactions[k] = interaction_variable_create (interaction_vars, 2);
- k++;
- }
- for (j = 0; j < cmd->n_with; j++)
- {
- interaction_vars[0] = cmd->v_by[i];
- interaction_vars[1] = cmd->v_with[j];
- interactions[k] = interaction_variable_create (interaction_vars, 2);
- k++;
- }
- }
- for (i = 0; i < cmd->n_with; i++)
- {
- for (j = i + 1; j < cmd->n_with; j++)
- {
- interaction_vars[0] = cmd->v_with[i];
- interaction_vars[1] = cmd->v_with[j];
- interactions[k] = interaction_variable_create (interaction_vars, 2);
- k++;
- }
- }
-}
-int
-cmd_glm (struct lexer *lexer, struct dataset *ds)
-{
- struct casegrouper *grouper;
- struct casereader *group;
-
- bool ok;
-
- if (!parse_glm (lexer, ds, &cmd, NULL))
- return CMD_FAILURE;
-
- if (!lex_match_id (lexer, "DESIGN"))
- {
- check_interactions (ds, &cmd);
- }
- /* Data pass. */
- grouper = casegrouper_create_splits (proc_open (ds), dataset_dict (ds));
- while (casegrouper_get_next_group (grouper, &group))
- {
- run_glm (group, &cmd, ds);
- }
- ok = casegrouper_destroy (grouper);
- ok = proc_commit (ds) && ok;
-
- free (v_dependent);
- return ok ? CMD_SUCCESS : CMD_FAILURE;
-}
-
-static int
-parse_interactions (struct lexer *lexer, const struct variable **interaction_vars, int n_members,
- int max_members, struct dataset *ds)
-{
- if (lex_match (lexer, '*'))
- {
- if (n_members > max_members)
- {
- max_members *= 2;
- xnrealloc (interaction_vars, max_members, sizeof (*interaction_vars));
- }
- interaction_vars[n_members] = parse_variable (lexer, dataset_dict (ds));
- parse_interactions (lexer, interaction_vars, n_members++, max_members, ds);
- }
- return n_members;
-}
-/* Parser for the design subcommand. */
-static int
-glm_custom_design (struct lexer *lexer, struct dataset *ds,
- struct cmd_glm *cmd UNUSED, void *aux UNUSED)
-{
- size_t n_allocated = 2;
- size_t n_members;
- struct variable **interaction_vars;
- struct variable *this_var;
-
- interactions = xnmalloc (n_allocated, sizeof (*interactions));
- n_inter = 1;
- while (lex_token (lexer) != T_STOP && lex_token (lexer) != '.')
- {
- this_var = parse_variable (lexer, dataset_dict (ds));
- if (lex_match (lexer, '('))
- {
- lex_force_match (lexer, ')');
- }
- else if (lex_match (lexer, '*'))
- {
- interaction_vars = xnmalloc (2 * n_inter, sizeof (*interaction_vars));
- n_members = parse_interactions (lexer, interaction_vars, 1, 2 * n_inter, ds);
- if (n_allocated < n_inter)
- {
- n_allocated *= 2;
- xnrealloc (interactions, n_allocated, sizeof (*interactions));
- }
- interactions [n_inter - 1] =
- interaction_variable_create (interaction_vars, n_members);
- n_inter++;
- free (interaction_vars);
- }
- }
- return 1;
-}
-/* Parser for the dependent sub command */
-static int
-glm_custom_dependent (struct lexer *lexer, struct dataset *ds,
- struct cmd_glm *cmd UNUSED, void *aux UNUSED)
-{
- const struct dictionary *dict = dataset_dict (ds);
- size_t i;
-
- if ((lex_token (lexer) != T_ID
- || dict_lookup_var (dict, lex_tokid (lexer)) == NULL)
- && lex_token (lexer) != T_ALL)
- return 2;
-
- if (!parse_variables_const (lexer, dict, &v_dependent, &n_dependent, PV_NONE))
- {
- free (v_dependent);
- return 0;
- }
- for (i = 0; i < n_dependent; i++)
- {
- assert (var_is_numeric (v_dependent[i]));
- }
- assert (n_dependent);
- if (n_dependent > 1)
- msg (SE, _("Multivariate GLM not yet supported"));
- n_dependent = 1; /* Drop this line after adding support for multivariate GLM. */
-
- return 1;
-}
-
-static linreg *
-fit_model (const struct covariance *cov,
- const struct variable *dep_var,
- const struct variable ** indep_vars,
- size_t n_data, size_t n_indep)
-{
- linreg *result = NULL;
-
- return result;
-}
-
-static bool
-run_glm (struct casereader *input,
- struct cmd_glm *cmd,
- const struct dataset *ds)
-{
- casenumber row;
- const struct variable **numerics = NULL;
- const struct variable **categoricals = NULL;
- int n_indep = 0;
- linreg *model = NULL;
- pspp_linreg_opts lopts;
- struct ccase *c;
- size_t i;
- size_t n_data; /* Number of valid cases. */
- size_t n_categoricals = 0;
- size_t n_numerics;
- struct casereader *reader;
- struct covariance *cov;
-
- c = casereader_peek (input, 0);
- if (c == NULL)
- {
- casereader_destroy (input);
- return true;
- }
- output_split_file_values (ds, c);
- case_unref (c);
-
- if (!v_dependent)
- {
- dict_get_vars (dataset_dict (ds), &v_dependent, &n_dependent,
- 1u << DC_SYSTEM);
- }
-
- lopts.get_depvar_mean_std = 1;
-
- lopts.get_indep_mean_std = xnmalloc (n_dependent, sizeof (int));
-
-
- n_numerics = n_dependent;
- for (i = 0; i < cmd->n_with; i++)
- {
- if (var_is_alpha (cmd->v_with[i]))
- {
- n_categoricals++;
- }
- else
- {
- n_numerics++;
- }
- }
- for (i = 0; i < cmd->n_by; i++)
- {
- if (var_is_alpha (cmd->v_by[i]))
- {
- n_categoricals++;
- }
- else
- {
- n_numerics++;
- }
- }
- numerics = xnmalloc (n_numerics, sizeof *numerics);
- categoricals = xnmalloc (n_categoricals, sizeof (*categoricals));
- size_t j = 0;
- size_t k = 0;
- for (i = 0; i < cmd->n_by; i++)
- {
- if (var_is_alpha (cmd->v_by[i]))
- {
- categoricals[j] = cmd->v_by[i];
- j++;
- }
- else
- {
- numerics[k] = cmd->v_by[i];
- k++;
- }
- }
- for (i = 0; i < cmd->n_with; i++)
- {
- if (var_is_alpha (cmd->v_with[i]))
- {
- categoricals[j] = cmd->v_with[i];
- j++;
- }
- else
- {
- numerics[k] = cmd->v_with[i];
- k++;
- }
- }
- for (i = 0; i < n_dependent; i++)
- {
- numerics[k] = v_dependent[i];
- k++;
- }
-
- struct categoricals *cats =
- categoricals_create (categoricals, n_categoricals,
- NULL, MV_NEVER,
- NULL, NULL, NULL, NULL);
-
- cov = covariance_2pass_create (n_numerics, numerics,
- cats,
- NULL, MV_NEVER);
-
- reader = casereader_clone (input);
- reader = casereader_create_filter_missing (reader, numerics, n_numerics,
- MV_ANY, NULL, NULL);
- reader = casereader_create_filter_missing (reader, categoricals, n_categoricals,
- MV_ANY, NULL, NULL);
- struct casereader *r = casereader_clone (reader);
-
- reader = casereader_create_counter (reader, &row, -1);
-
- for (; (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- covariance_accumulate_pass1 (cov, c);
- }
- for (; (c = casereader_read (r)) != NULL; case_unref (c))
- {
- covariance_accumulate_pass2 (cov, c);
- }
-
- covariance_destroy (cov);
- casereader_destroy (reader);
- casereader_destroy (r);
-
- free (numerics);
- free (categoricals);
- free (lopts.get_indep_mean_std);
- casereader_destroy (input);
-
- return true;
-}
-
-/*
- Local Variables:
- mode: c
- End:
-*/
projects / pspp-builds.git / commitdiff