X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fregression.q;h=595e7e750c54d4d996b85b71eb141f87b4ba8d52;hb=06c817b718b0d677912acfa55d8191a38d56b739;hp=1d31d1845e02e20064610bf3886cd8d11c71f5a0;hpb=73f67789df91a09ee91976434fb15c2ee1fb5e78;p=pspp diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q index 1d31d1845e..595e7e750c 100644 --- a/src/language/stats/regression.q +++ b/src/language/stats/regression.q @@ -1,5 +1,5 @@ /* PSPP - a program for statistical analysis. - Copyright (C) 2005 Free Software Foundation, Inc. + Copyright (C) 2005, 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 @@ -542,7 +542,7 @@ regression_trns_free (void *t_) Gets the predicted values. */ static int -regression_trns_pred_proc (void *t_, struct ccase *c, +regression_trns_pred_proc (void *t_, struct ccase **c, casenumber case_idx UNUSED) { size_t i; @@ -563,12 +563,12 @@ regression_trns_pred_proc (void *t_, struct ccase *c, n_vals = (*model->get_vars) (model, vars); vals = xnmalloc (n_vals, sizeof (*vals)); - output = case_data_rw (c, model->pred); - assert (output != NULL); + *c = case_unshare (*c); + output = case_data_rw (*c, model->pred); for (i = 0; i < n_vals; i++) { - vals[i] = case_data (c, vars[i]); + vals[i] = case_data (*c, vars[i]); } output->f = (*model->predict) ((const struct variable **) vars, vals, model, n_vals); @@ -581,7 +581,7 @@ regression_trns_pred_proc (void *t_, struct ccase *c, Gets the residuals. */ static int -regression_trns_resid_proc (void *t_, struct ccase *c, +regression_trns_resid_proc (void *t_, struct ccase **c, casenumber case_idx UNUSED) { size_t i; @@ -603,14 +603,15 @@ regression_trns_resid_proc (void *t_, struct ccase *c, n_vals = (*model->get_vars) (model, vars); vals = xnmalloc (n_vals, sizeof (*vals)); - output = case_data_rw (c, model->resid); + *c = case_unshare (*c); + output = case_data_rw (*c, model->resid); assert (output != NULL); for (i = 0; i < n_vals; i++) { - vals[i] = case_data (c, vars[i]); + vals[i] = case_data (*c, vars[i]); } - obs = case_data (c, model->depvar); + obs = case_data (*c, model->depvar); output->f = (*model->residual) ((const struct variable **) vars, vals, obs, model, n_vals); free (vals); @@ -821,7 +822,7 @@ prepare_categories (struct casereader *input, struct moments_var *mom) { int n_data; - struct ccase c; + struct ccase *c; size_t i; assert (vars != NULL); @@ -832,7 +833,7 @@ prepare_categories (struct casereader *input, cat_stored_values_create (vars[i]); n_data = 0; - for (; casereader_read (input, &c); case_destroy (&c)) + for (; (c = casereader_read (input)) != NULL; case_unref (c)) { /* The second condition ensures the program will run even if @@ -841,7 +842,7 @@ prepare_categories (struct casereader *input, */ for (i = 0; i < n_vars; i++) { - const union value *val = case_data (&c, vars[i]); + const union value *val = case_data (c, vars[i]); if (var_is_alpha (vars[i])) cat_value_update (vars[i], val); else @@ -861,39 +862,6 @@ coeff_init (pspp_linreg_cache * c, struct design_matrix *dm) pspp_coeff_init (c->coeff, 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) -{ - 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); - pspp_linreg_set_indep_variable_mean (c, (mom + j)->v, mean); - pspp_linreg_set_indep_variable_sd (c, (mom + j)->v, sqrt (variance)); - } - } - } -} - static bool run_regression (struct casereader *input, struct cmd_regression *cmd, struct dataset *ds, pspp_linreg_cache **models) @@ -901,7 +869,7 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, size_t i; int n_indep = 0; int k; - struct ccase c; + struct ccase *c; const struct variable **indep_vars; struct design_matrix *X; struct moments_var *mom; @@ -911,13 +879,14 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, assert (models != 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_variables) { @@ -949,16 +918,16 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, const struct variable *dep_var; struct casereader *reader; casenumber row; - struct ccase c; + struct ccase *c; size_t n_data; /* Number of valid cases. */ dep_var = cmd->v_dependent[k]; n_indep = identify_indep_vars (indep_vars, dep_var); reader = casereader_clone (input); reader = casereader_create_filter_missing (reader, indep_vars, n_indep, - MV_ANY, NULL); + MV_ANY, NULL, NULL); reader = casereader_create_filter_missing (reader, &dep_var, 1, - MV_ANY, NULL); + MV_ANY, NULL, NULL); n_data = prepare_categories (casereader_clone (reader), indep_vars, n_indep, mom); @@ -973,7 +942,8 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, { lopts.get_indep_mean_std[i] = 1; } - models[k] = pspp_linreg_cache_alloc (X->m->size1, X->m->size2); + models[k] = pspp_linreg_cache_alloc (dep_var, (const struct variable **) indep_vars, + X->m->size1, X->m->size2); models[k]->depvar = dep_var; /* For large data sets, use QR decomposition. @@ -987,18 +957,18 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, The second pass fills the design matrix. */ reader = casereader_create_counter (reader, &row, -1); - for (; casereader_read (reader, &c); case_destroy (&c)) + for (; (c = casereader_read (reader)) != NULL; case_unref (c)) { for (i = 0; i < n_indep; ++i) { const struct variable *v = indep_vars[i]; - const union value *val = case_data (&c, v); + 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, dep_var)); + gsl_vector_set (Y, row, case_num (c, dep_var)); } /* Now that we know the number of coefficients, allocate space