X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fglm.q;h=0d792df898bd36efdbbd5e1b872f1245012401f4;hb=c360fff4fd3e4a98cfe02441f43c27725cead44b;hp=f16eff76117c4e52da57f75baff887271fd32fc0;hpb=b5b474193e450bba97610065df0518c08074a7fb;p=pspp diff --git a/src/language/stats/glm.q b/src/language/stats/glm.q index f16eff7611..0d792df898 100644 --- a/src/language/stats/glm.q +++ b/src/language/stats/glm.q @@ -1,5 +1,5 @@ /* PSPP - a program for statistical analysis. - Copyright (C) 2007 Free Software Foundation, Inc. + 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 @@ -23,7 +23,6 @@ #include #include -#include #include #include #include @@ -38,22 +37,21 @@ #include #include #include -#include -#include +#include +#include #include #include -#include +#include #include "xalloc.h" #include "gettext.h" -#define GLM_LARGE_DATA 1000 - /* (headers) */ /* (specification) "GLM" (glm_): *dependent=custom; + design=custom; by=varlist; with=varlist. */ @@ -61,12 +59,16 @@ /* (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; }; @@ -81,182 +83,211 @@ static const struct variable **v_dependent; */ static size_t n_dependent; -#if 0 -/* - Return value for the procedure. - */ -static int pspp_glm_rc = CMD_SUCCESS; -#else +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); -#endif -static bool run_glm (struct casereader*, +static bool run_glm (struct casereader *, struct cmd_glm *, - const struct dataset *, - pspp_linreg_cache *); - + 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; - pspp_linreg_cache *model = NULL; bool ok; - model = xmalloc (sizeof *model); - if (!parse_glm (lexer, ds, &cmd, NULL)) return CMD_FAILURE; - /* Data pass. */ + 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, model); + run_glm (group, &cmd, ds); } ok = casegrouper_destroy (grouper); ok = proc_commit (ds) && ok; - free (model); 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) + 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)) + 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. */ + n_dependent = 1; /* Drop this line after adding support for multivariate GLM. */ return 1; } -static void -coeff_init (pspp_linreg_cache * c, struct design_matrix *dm) -{ - c->coeff = xnmalloc (dm->m->size2 + 1, sizeof (*c->coeff)); - c->coeff[0] = xmalloc (sizeof (*(c->coeff[0]))); /* The first coefficient is the intercept. */ - c->coeff[0]->v_info = NULL; /* Intercept has no associated variable. */ - pspp_coeff_init (c->coeff + 1, dm); -} - -/* - Put the moments in the linreg cache. - */ -static void -compute_moments (pspp_linreg_cache * c, struct moments_var *mom, - struct design_matrix *dm, size_t n) +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) { - size_t i; - size_t j; - double weight; - double mean; - double variance; - double skewness; - double kurtosis; - /* - Scan the variable names in the columns of the design matrix. - When we find the variable we need, insert its mean in the cache. - */ - for (i = 0; i < dm->m->size2; i++) - { - for (j = 0; j < n; j++) - { - if (design_matrix_col_to_var (dm, i) == (mom + j)->v) - { - moments1_calculate ((mom + j)->m, &weight, &mean, &variance, - &skewness, &kurtosis); - gsl_vector_set (c->indep_means, i, mean); - gsl_vector_set (c->indep_std, i, sqrt (variance)); - } - } - } -} -/* Encode categorical variables. - Returns number of valid cases. */ -static int -prepare_categories (struct casereader *input, - const struct variable **vars, size_t n_vars, - struct moments_var *mom) -{ - int n_data; - struct ccase c; - size_t i; - - for (i = 0; i < n_vars; i++) - if (var_is_alpha (vars[i])) - cat_stored_values_create (vars[i]); - - n_data = 0; - for (; casereader_read (input, &c); case_destroy (&c)) - { - /* - The second condition ensures the program will run even if - there is only one variable to act as both explanatory and - response. - */ - for (i = 0; i < n_vars; i++) - { - const union value *val = case_data (&c, vars[i]); - if (var_is_alpha (vars[i])) - cat_value_update (vars[i], val); - else - moments1_add (mom[i].m, val->f, 1.0); - } - n_data++; - } - casereader_destroy (input); - - return n_data; + linreg *result = NULL; + + return result; } static bool run_glm (struct casereader *input, struct cmd_glm *cmd, - const struct dataset *ds, - pspp_linreg_cache *model) + const struct dataset *ds) { - size_t i; - int n_indep = 0; - struct ccase c; - const struct variable **indep_vars; - struct design_matrix *X; - struct moments_var *mom; - gsl_vector *Y; - struct casereader *reader; casenumber row; - size_t n_data; /* Number of valid cases. */ - + 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; - assert (model != NULL); - - if (!casereader_peek (input, 0, &c)) + c = casereader_peek (input, 0); + if (c == NULL) { casereader_destroy (input); return true; } - output_split_file_values (ds, &c); - case_destroy (&c); + output_split_file_values (ds, c); + case_unref (c); if (!v_dependent) { @@ -264,88 +295,103 @@ run_glm (struct casereader *input, 1u << DC_SYSTEM); } - for (i = 0; i < n_dependent; i++) - { - if (!var_is_numeric (v_dependent[i])) - { - msg (SE, _("Dependent variable must be numeric.")); - return false; - } - } - - mom = xnmalloc (n_dependent, sizeof (*mom)); - mom->m = moments1_create (MOMENT_VARIANCE); - mom->v = v_dependent[0]; lopts.get_depvar_mean_std = 1; lopts.get_indep_mean_std = xnmalloc (n_dependent, sizeof (int)); - indep_vars = xnmalloc (cmd->n_by, sizeof *indep_vars); + + 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++) { - indep_vars[i] = cmd->v_by[i]; + if (var_is_alpha (cmd->v_by[i])) + { + n_categoricals++; + } + else + { + n_numerics++; + } } - n_indep = cmd->n_by; - - reader = casereader_clone (input); - reader = casereader_create_filter_missing (reader, indep_vars, n_indep, - MV_ANY, NULL); - reader = casereader_create_filter_missing (reader, v_dependent, 1, - MV_ANY, NULL); - n_data = prepare_categories (casereader_clone (reader), - indep_vars, n_indep, mom); - - if ((n_data > 0) && (n_indep > 0)) + 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++) { - Y = gsl_vector_alloc (n_data); - X = - design_matrix_create (n_indep, - (const struct variable **) indep_vars, - n_data); - for (i = 0; i < X->m->size2; i++) + if (var_is_alpha (cmd->v_by[i])) { - lopts.get_indep_mean_std[i] = 1; + categoricals[j] = cmd->v_by[i]; + j++; } - model = pspp_linreg_cache_alloc (X->m->size1, X->m->size2); - model->indep_means = gsl_vector_alloc (X->m->size2); - model->indep_std = gsl_vector_alloc (X->m->size2); - model->depvar = v_dependent[0]; - reader = casereader_create_counter (reader, &row, -1); - for (; casereader_read (reader, &c); case_destroy (&c)) + else { - for (i = 0; i < n_indep; ++i) - { - const struct variable *v = indep_vars[i]; - const union value *val = case_data (&c, v); - if (var_is_alpha (v)) - design_matrix_set_categorical (X, row, v, val); - else - design_matrix_set_numeric (X, row, v, val); - } - gsl_vector_set (Y, row, case_num (&c, model->depvar)); + numerics[k] = cmd->v_by[i]; + k++; } - casereader_destroy (reader); - /* - Now that we know the number of coefficients, allocate space - and store pointers to the variables that correspond to the - coefficients. - */ - coeff_init (model, X); - - /* - Find the least-squares estimates and other statistics. - */ - pspp_linreg ((const gsl_vector *) Y, X->m, &lopts, model); - compute_moments (model, mom, X, n_dependent); - - gsl_vector_free (Y); - design_matrix_destroy (X); } - else + for (i = 0; i < cmd->n_with; i++) { - msg (SE, gettext ("No valid data found. This command was skipped.")); + if (var_is_alpha (cmd->v_with[i])) + { + categoricals[j] = cmd->v_with[i]; + j++; + } + else + { + numerics[k] = cmd->v_with[i]; + k++; + } } - free (indep_vars); + 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); + + 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);