+++ /dev/null
-/* PSPP - a program for statistical analysis.
- Copyright (C) 2010, 2011, 2012 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_combination.h>
-#include <math.h>
-
-#include "data/case.h"
-#include "data/casegrouper.h"
-#include "data/casereader.h"
-#include "data/dataset.h"
-#include "data/dictionary.h"
-#include "data/format.h"
-#include "data/value.h"
-#include "language/command.h"
-#include "language/dictionary/split-file.h"
-#include "language/lexer/lexer.h"
-#include "language/lexer/value-parser.h"
-#include "language/lexer/variable-parser.h"
-#include "libpspp/assertion.h"
-#include "libpspp/ll.h"
-#include "libpspp/message.h"
-#include "libpspp/misc.h"
-#include "libpspp/taint.h"
-#include "linreg/sweep.h"
-#include "math/categoricals.h"
-#include "math/covariance.h"
-#include "math/interaction.h"
-#include "math/moments.h"
-#include "output/pivot-table.h"
-
-#include "gettext.h"
-#define N_(msgid) msgid
-#define _(msgid) gettext (msgid)
-
-struct glm_spec
- {
- const struct variable **dep_vars;
- size_t n_dep_vars;
-
- const struct variable **factor_vars;
- size_t n_factor_vars;
-
- struct interaction **interactions;
- size_t n_interactions;
-
- enum mv_class exclude;
-
- const struct variable *wv; /* The weight variable */
-
- const struct dictionary *dict;
-
- int ss_type;
- bool intercept;
-
- double alpha;
-
- bool dump_coding;
- };
-
-struct glm_workspace
- {
- double total_ssq;
- struct moments *totals;
-
- struct categoricals *cats;
-
- /*
- Sums of squares due to different variables. Element 0 is the SSE
- for the entire model. For i > 0, element i is the SS due to
- variable i.
- */
- gsl_vector *ssq;
- };
-
-/* Default design: all possible interactions */
-static void
-design_full (struct glm_spec *glm)
-{
- size_t n = (1 << glm->n_factor_vars) - 1;
- glm->interactions = xnmalloc (n, sizeof *glm->interactions);
-
- /* All subsets, with exception of the empty set, of [0, glm->n_factor_vars) */
- for (size_t sz = 1; sz <= glm->n_factor_vars; ++sz)
- {
- gsl_combination *c = gsl_combination_calloc (glm->n_factor_vars, sz);
-
- do
- {
- struct interaction *iact = interaction_create (NULL);
- for (int e = 0; e < gsl_combination_k (c); ++e)
- interaction_add_variable (
- iact, glm->factor_vars [gsl_combination_get (c, e)]);
-
- glm->interactions[glm->n_interactions++] = iact;
- }
- while (gsl_combination_next (c) == GSL_SUCCESS);
-
- gsl_combination_free (c);
- }
- assert (glm->n_interactions == n);
-}
-
-static void output_glm (const struct glm_spec *,
- const struct glm_workspace *ws);
-static void run_glm (struct glm_spec *cmd, struct casereader *input,
- const struct dataset *ds);
-
-static struct interaction *parse_design_term (struct lexer *,
- const struct dictionary *);
-
-int
-cmd_glm (struct lexer *lexer, struct dataset *ds)
-{
- struct const_var_set *factors = NULL;
- bool design = false;
- struct dictionary *dict = dataset_dict (ds);
- struct glm_spec glm = {
- .dict = dict,
- .exclude = MV_ANY,
- .intercept = true,
- .wv = dict_get_weight (dict),
- .alpha = 0.05,
- .ss_type = 3,
- };
-
- int dep_vars_start = lex_ofs (lexer);
- if (!parse_variables_const (lexer, glm.dict,
- &glm.dep_vars, &glm.n_dep_vars,
- PV_NO_DUPLICATE | PV_NUMERIC))
- goto error;
- int dep_vars_end = lex_ofs (lexer) - 1;
-
- if (!lex_force_match (lexer, T_BY))
- goto error;
-
- if (!parse_variables_const (lexer, glm.dict,
- &glm.factor_vars, &glm.n_factor_vars,
- PV_NO_DUPLICATE | PV_NUMERIC))
- goto error;
-
- if (glm.n_dep_vars > 1)
- {
- lex_ofs_error (lexer, dep_vars_start, dep_vars_end,
- _("Multivariate analysis is not yet implemented."));
- goto error;
- }
-
- factors = const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
-
- size_t allocated_interactions = 0;
- 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, "INCLUDE"))
- glm.exclude = MV_SYSTEM;
- else if (lex_match_id (lexer, "EXCLUDE"))
- glm.exclude = MV_ANY;
- else
- {
- lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
- goto error;
- }
- }
- }
- else if (lex_match_id (lexer, "INTERCEPT"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD
- && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "INCLUDE"))
- glm.intercept = true;
- else if (lex_match_id (lexer, "EXCLUDE"))
- glm.intercept = false;
- else
- {
- lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
- goto error;
- }
- }
- }
- else if (lex_match_id (lexer, "CRITERIA"))
- {
- lex_match (lexer, T_EQUALS);
- if (!lex_force_match_phrase (lexer, "ALPHA(")
- || !lex_force_num (lexer))
- goto error;
- glm.alpha = lex_number (lexer);
- lex_get (lexer);
- if (!lex_force_match (lexer, T_RPAREN))
- goto error;
- }
- else if (lex_match_id (lexer, "METHOD"))
- {
- lex_match (lexer, T_EQUALS);
- if (!lex_force_match_phrase (lexer, "SSTYPE(")
- || !lex_force_int_range (lexer, "SSTYPE", 1, 3))
- goto error;
-
- glm.ss_type = lex_integer (lexer);
- lex_get (lexer);
-
- if (!lex_force_match (lexer, T_RPAREN))
- goto error;
- }
- else if (lex_match_id (lexer, "DESIGN"))
- {
- lex_match (lexer, T_EQUALS);
-
- do
- {
- struct interaction *iact = parse_design_term (lexer, glm.dict);
- if (!iact)
- goto error;
-
- if (glm.n_interactions >= allocated_interactions)
- glm.interactions = x2nrealloc (glm.interactions,
- &allocated_interactions,
- sizeof *glm.interactions);
- glm.interactions[glm.n_interactions++] = iact;
-
- lex_match (lexer, T_COMMA);
- }
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH);
-
- if (glm.n_interactions > 0)
- design = true;
- }
- else if (lex_match_id (lexer, "SHOWCODES"))
- {
- /* Undocumented debug option */
- glm.dump_coding = true;
- }
- else
- {
- lex_error_expecting (lexer, "MISSING", "INTERCEPT", "CRITERIA",
- "METHOD", "DESIGN");
- goto error;
- }
- }
-
- if (!design)
- design_full (&glm);
-
- struct casegrouper *grouper = casegrouper_create_splits (proc_open (ds), glm.dict);
- struct casereader *group;
- while (casegrouper_get_next_group (grouper, &group))
- run_glm (&glm, group, ds);
- bool ok = casegrouper_destroy (grouper);
- ok = proc_commit (ds) && ok;
-
- const_var_set_destroy (factors);
- free (glm.factor_vars);
- for (size_t i = 0; i < glm.n_interactions; ++i)
- interaction_destroy (glm.interactions[i]);
-
- free (glm.interactions);
- free (glm.dep_vars);
-
- return CMD_SUCCESS;
-
-error:
- const_var_set_destroy (factors);
- free (glm.factor_vars);
- for (size_t i = 0; i < glm.n_interactions; ++i)
- interaction_destroy (glm.interactions[i]);
-
- free (glm.interactions);
- free (glm.dep_vars);
-
- return CMD_FAILURE;
-}
-
-static inline bool
-not_dropped (size_t j, const bool *ff)
-{
- return !ff[j];
-}
-
-static void
-fill_submatrix (const gsl_matrix * cov, gsl_matrix * submatrix, bool *dropped_f)
-{
- size_t i;
- size_t j;
- size_t n = 0;
- size_t m = 0;
-
- for (i = 0; i < cov->size1; i++)
- {
- if (not_dropped (i, dropped_f))
- {
- m = 0;
- for (j = 0; j < cov->size2; j++)
- {
- if (not_dropped (j, dropped_f))
- {
- gsl_matrix_set (submatrix, n, m,
- gsl_matrix_get (cov, i, j));
- m++;
- }
- }
- n++;
- }
- }
-}
-
-
-/*
- Type 1 sums of squares.
- Populate SSQ with the Type 1 sums of squares according to COV
- */
-static void
-ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
-{
- const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
- size_t i;
- size_t k;
- bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
- bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
- const struct categoricals *cats = covariance_get_categoricals (cov);
-
- size_t n_dropped_model = 0;
- size_t n_dropped_submodel = 0;
-
- for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
- {
- n_dropped_model++;
- n_dropped_submodel++;
- model_dropped[i] = true;
- submodel_dropped[i] = true;
- }
-
- for (k = 0; k < cmd->n_interactions; k++)
- {
- gsl_matrix *model_cov = NULL;
- gsl_matrix *submodel_cov = NULL;
-
- n_dropped_submodel = n_dropped_model;
- for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
- submodel_dropped[i] = model_dropped[i];
-
- for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
- {
- const struct interaction * x =
- categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
-
- if (x == cmd->interactions [k])
- {
- model_dropped[i] = false;
- n_dropped_model--;
- }
- }
-
- model_cov = gsl_matrix_alloc (cm->size1 - n_dropped_model, cm->size2 - n_dropped_model);
- submodel_cov = gsl_matrix_alloc (cm->size1 - n_dropped_submodel, cm->size2 - n_dropped_submodel);
-
- fill_submatrix (cm, model_cov, model_dropped);
- fill_submatrix (cm, submodel_cov, submodel_dropped);
-
- reg_sweep (model_cov, 0);
- reg_sweep (submodel_cov, 0);
-
- gsl_vector_set (ssq, k + 1,
- gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
- );
-
- gsl_matrix_free (model_cov);
- gsl_matrix_free (submodel_cov);
- }
-
- free (model_dropped);
- free (submodel_dropped);
-}
-
-/*
- Type 2 sums of squares.
- Populate SSQ with the Type 2 sums of squares according to COV
- */
-static void
-ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
-{
- const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
- bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
- bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
- const struct categoricals *cats = covariance_get_categoricals (cov);
-
- for (size_t k = 0; k < cmd->n_interactions; k++)
- {
- gsl_matrix *model_cov = NULL;
- gsl_matrix *submodel_cov = NULL;
- size_t n_dropped_model = 0;
- size_t n_dropped_submodel = 0;
- for (size_t i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
- {
- const struct interaction * x =
- categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
-
- model_dropped[i] = false;
- submodel_dropped[i] = false;
- if (interaction_is_subset (cmd->interactions [k], x))
- {
- assert (n_dropped_submodel < covariance_dim (cov));
- n_dropped_submodel++;
- submodel_dropped[i] = true;
-
- if (cmd->interactions [k]->n_vars < x->n_vars)
- {
- assert (n_dropped_model < covariance_dim (cov));
- n_dropped_model++;
- model_dropped[i] = true;
- }
- }
- }
-
- model_cov = gsl_matrix_alloc (cm->size1 - n_dropped_model, cm->size2 - n_dropped_model);
- submodel_cov = gsl_matrix_alloc (cm->size1 - n_dropped_submodel, cm->size2 - n_dropped_submodel);
-
- fill_submatrix (cm, model_cov, model_dropped);
- fill_submatrix (cm, submodel_cov, submodel_dropped);
-
- reg_sweep (model_cov, 0);
- reg_sweep (submodel_cov, 0);
-
- gsl_vector_set (ssq, k + 1,
- gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
- );
-
- gsl_matrix_free (model_cov);
- gsl_matrix_free (submodel_cov);
- }
-
- free (model_dropped);
- free (submodel_dropped);
-}
-
-/*
- Type 3 sums of squares.
- Populate SSQ with the Type 2 sums of squares according to COV
- */
-static void
-ssq_type3 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
-{
- const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
- bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
- bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
- const struct categoricals *cats = covariance_get_categoricals (cov);
-
- gsl_matrix *submodel_cov = gsl_matrix_alloc (cm->size1, cm->size2);
- fill_submatrix (cm, submodel_cov, submodel_dropped);
- reg_sweep (submodel_cov, 0);
- double ss0 = gsl_matrix_get (submodel_cov, 0, 0);
- gsl_matrix_free (submodel_cov);
- free (submodel_dropped);
-
- for (size_t k = 0; k < cmd->n_interactions; k++)
- {
- size_t n_dropped_model = 0;
- for (size_t i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
- {
- const struct interaction * x =
- categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
-
- model_dropped[i] = false;
-
- if (cmd->interactions [k] == x)
- {
- assert (n_dropped_model < covariance_dim (cov));
- n_dropped_model++;
- model_dropped[i] = true;
- }
- }
-
- gsl_matrix *model_cov = gsl_matrix_alloc (cm->size1 - n_dropped_model,
- cm->size2 - n_dropped_model);
-
- fill_submatrix (cm, model_cov, model_dropped);
-
- reg_sweep (model_cov, 0);
-
- gsl_vector_set (ssq, k + 1, gsl_matrix_get (model_cov, 0, 0) - ss0);
-
- gsl_matrix_free (model_cov);
- }
- free (model_dropped);
-}
-
-static void
-run_glm (struct glm_spec *cmd, struct casereader *input,
- const struct dataset *ds)
-{
- bool warn_bad_weight = true;
- struct dictionary *dict = dataset_dict (ds);
-
-
- input = casereader_create_filter_missing (input,
- cmd->dep_vars, cmd->n_dep_vars,
- cmd->exclude,
- NULL, NULL);
-
- input = casereader_create_filter_missing (input,
- cmd->factor_vars, cmd->n_factor_vars,
- cmd->exclude,
- NULL, NULL);
-
- struct glm_workspace ws = {
- .cats = categoricals_create (cmd->interactions, cmd->n_interactions,
- cmd->wv, MV_ANY)
- };
-
- struct covariance *cov = covariance_2pass_create (
- cmd->n_dep_vars, cmd->dep_vars, ws.cats, cmd->wv, cmd->exclude, true);
-
- output_split_file_values_peek (ds, input);
-
- struct taint *taint = taint_clone (casereader_get_taint (input));
-
- ws.totals = moments_create (MOMENT_VARIANCE);
-
- struct casereader *reader = casereader_clone (input);
- struct ccase *c;
- for (; (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
-
- for (int v = 0; v < cmd->n_dep_vars; ++v)
- moments_pass_one (ws.totals, case_num (c, cmd->dep_vars[v]), weight);
-
- covariance_accumulate_pass1 (cov, c);
- }
- casereader_destroy (reader);
-
- if (cmd->dump_coding)
- reader = casereader_clone (input);
- else
- reader = input;
-
- for (; (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
-
- for (size_t v = 0; v < cmd->n_dep_vars; ++v)
- moments_pass_two (ws.totals, case_num (c, cmd->dep_vars[v]), weight);
-
- covariance_accumulate_pass2 (cov, c);
- }
- casereader_destroy (reader);
-
-
- if (cmd->dump_coding)
- {
- struct pivot_table *t = covariance_dump_enc_header (cov);
- for (reader = input;
- (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- covariance_dump_enc (cov, c, t);
- }
-
- pivot_table_submit (t);
- }
-
- {
- const gsl_matrix *ucm = covariance_calculate_unnormalized (cov);
- gsl_matrix *cm = gsl_matrix_alloc (ucm->size1, ucm->size2);
- gsl_matrix_memcpy (cm, ucm);
-
- // dump_matrix (cm);
-
- ws.total_ssq = gsl_matrix_get (cm, 0, 0);
-
- reg_sweep (cm, 0);
-
- /*
- Store the overall SSE.
- */
- ws.ssq = gsl_vector_alloc (cm->size1);
- gsl_vector_set (ws.ssq, 0, gsl_matrix_get (cm, 0, 0));
- switch (cmd->ss_type)
- {
- case 1:
- ssq_type1 (cov, ws.ssq, cmd);
- break;
- case 2:
- ssq_type2 (cov, ws.ssq, cmd);
- break;
- case 3:
- ssq_type3 (cov, ws.ssq, cmd);
- break;
- default:
- NOT_REACHED ();
- break;
- }
- // dump_matrix (cm);
- gsl_matrix_free (cm);
- }
-
- if (!taint_has_tainted_successor (taint))
- output_glm (cmd, &ws);
-
- gsl_vector_free (ws.ssq);
-
- covariance_destroy (cov);
- moments_destroy (ws.totals);
-
- taint_destroy (taint);
-}
-
-static void
-put_glm_row (struct pivot_table *table, int row,
- double a, double b, double c, double d, double e)
-{
- double entries[] = { a, b, c, d, e };
-
- for (size_t col = 0; col < sizeof entries / sizeof *entries; col++)
- if (entries[col] != SYSMIS)
- pivot_table_put2 (table, col, row,
- pivot_value_new_number (entries[col]));
-}
-
-static void
-output_glm (const struct glm_spec *cmd, const struct glm_workspace *ws)
-{
- struct pivot_table *table = pivot_table_create (
- N_("Tests of Between-Subjects Effects"));
-
- pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
- (cmd->ss_type == 1 ? N_("Type I Sum Of Squares")
- : cmd->ss_type == 2 ? N_("Type II Sum Of Squares")
- : N_("Type III Sum Of Squares")), PIVOT_RC_OTHER,
- N_("df"), PIVOT_RC_COUNT,
- N_("Mean Square"), PIVOT_RC_OTHER,
- N_("F"), PIVOT_RC_OTHER,
- N_("Sig."), PIVOT_RC_SIGNIFICANCE);
-
- struct pivot_dimension *source = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Source"),
- cmd->intercept ? N_("Corrected Model") : N_("Model"));
-
- double n_total, mean;
- moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
-
- double df_corr = 1.0 + categoricals_df_total (ws->cats);
-
- double mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
- double intercept_ssq = pow2 (mean * n_total) / n_total;
- if (cmd->intercept)
- {
- int row = pivot_category_create_leaf (
- source->root, pivot_value_new_text (N_("Intercept")));
-
- /* The intercept for unbalanced models is of limited use and
- nobody knows how to calculate it properly */
- if (categoricals_isbalanced (ws->cats))
- {
- const double df = 1.0;
- const double F = intercept_ssq / df / mse;
- put_glm_row (table, row, intercept_ssq, 1.0, intercept_ssq / df,
- F, gsl_cdf_fdist_Q (F, df, n_total - df_corr));
- }
- }
-
- double ssq_effects = 0.0;
- for (int f = 0; f < cmd->n_interactions; ++f)
- {
- double df = categoricals_df (ws->cats, f);
- double ssq = gsl_vector_get (ws->ssq, f + 1);
- ssq_effects += ssq;
- if (!cmd->intercept)
- {
- df++;
- ssq += intercept_ssq;
- }
- double F = ssq / df / mse;
-
- struct string str = DS_EMPTY_INITIALIZER;
- interaction_to_string (cmd->interactions[f], &str);
- int row = pivot_category_create_leaf (
- source->root, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
-
- put_glm_row (table, row, ssq, df, ssq / df, F,
- gsl_cdf_fdist_Q (F, df, n_total - df_corr));
- }
-
- {
- /* Model / Corrected Model */
- double df = df_corr;
- double ssq = ws->total_ssq - gsl_vector_get (ws->ssq, 0);
- if (cmd->intercept)
- df--;
- else
- ssq += intercept_ssq;
- double F = ssq / df / mse;
- put_glm_row (table, 0, ssq, df, ssq / df, F,
- gsl_cdf_fdist_Q (F, df, n_total - df_corr));
- }
-
- {
- int row = pivot_category_create_leaf (source->root,
- pivot_value_new_text (N_("Error")));
- const double df = n_total - df_corr;
- const double ssq = gsl_vector_get (ws->ssq, 0);
- const double mse = ssq / df;
- put_glm_row (table, row, ssq, df, mse, SYSMIS, SYSMIS);
- }
-
- {
- int row = pivot_category_create_leaf (source->root,
- pivot_value_new_text (N_("Total")));
- put_glm_row (table, row, ws->total_ssq + intercept_ssq, n_total,
- SYSMIS, SYSMIS, SYSMIS);
- }
-
- if (cmd->intercept)
- {
- int row = pivot_category_create_leaf (
- source->root, pivot_value_new_text (N_("Corrected Total")));
- put_glm_row (table, row, ws->total_ssq, n_total - 1.0, SYSMIS,
- SYSMIS, SYSMIS);
- }
-
- pivot_table_submit (table);
-}
-
-#if 0
-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");
-}
-#endif
-
-
-\f
-static struct interaction *
-parse_design_term (struct lexer *lexer, const struct dictionary *dict)
-{
- struct interaction *iact = interaction_create (NULL);
- do
- {
- struct variable *var = parse_variable (lexer, dict);
- if (!var)
- goto error;
- interaction_add_variable (iact, var);
-
- if (lex_match (lexer, T_LPAREN) || lex_match_id (lexer, "WITHIN"))
- {
- lex_next_error (lexer, -1, -1,
- "Nested variables are not yet implemented.");
- goto error;
- }
- }
- while (lex_match (lexer, T_ASTERISK));
-
- return iact;
-
-error:
- interaction_destroy (iact);
- return NULL;
-}
projects / pspp / blobdiff