X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Fmath%2Fcovariance-matrix.c;h=89660ba9c1e3f5fbc1f4168af2ef8af549a43c7d;hb=8829e1f148c279db0f19b9e3bd746ace07d2d7f1;hp=817f7ed3158c7a29772af63845c8a2575de4bd9a;hpb=ceb0823669b8cb6784fd4f793d28451e33dfd512;p=pspp-builds.git diff --git a/src/math/covariance-matrix.c b/src/math/covariance-matrix.c index 817f7ed3..89660ba9 100644 --- a/src/math/covariance-matrix.c +++ b/src/math/covariance-matrix.c @@ -1,5 +1,5 @@ /* PSPP - a program for statistical analysis. - Copyright (C) 2008 Free Software Foundation, Inc. + Copyright (C) 2008, 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 @@ -43,29 +43,228 @@ struct covariance_accumulator { const struct variable *v1; const struct variable *v2; - double product; const union value *val1; const union value *val2; + double dot_product; + double sum1; + double sum2; + double ssize; }; + + +struct covariance_matrix +{ + struct design_matrix *cov; + struct design_matrix *ssize; + struct hsh_table *ca; + struct moments1 **m1; + struct moments **m; + const struct variable **v_variables; + const struct interaction_variable **interactions; + size_t n_variables; + size_t n_intr; + int n_pass; + int missing_handling; + enum mv_class missing_value; + void (*accumulate) (struct covariance_matrix *, const struct ccase *, + const struct interaction_variable **, size_t); + void (*update_moments) (struct covariance_matrix *, size_t, double); +}; + + + +static struct hsh_table *covariance_hsh_create (size_t *); static hsh_hash_func covariance_accumulator_hash; -static unsigned int hash_numeric_alpha (const struct variable *, const struct variable *, +static unsigned int hash_numeric_alpha (const struct variable *, + const struct variable *, const union value *, size_t); static hsh_compare_func covariance_accumulator_compare; static hsh_free_func covariance_accumulator_free; +static void update_moments1 (struct covariance_matrix *, size_t, double); +static void update_moments2 (struct covariance_matrix *, size_t, double); +static struct covariance_accumulator *get_new_covariance_accumulator (const + struct + variable + *, + const + struct + variable + *, + const + union + value *, + const + union + value + *); +static void covariance_accumulate_listwise (struct covariance_matrix *, + const struct ccase *, + const struct interaction_variable **, + size_t); +static void covariance_accumulate_pairwise (struct covariance_matrix *, + const struct ccase *, + const struct interaction_variable **, + size_t); + +struct covariance_matrix * +covariance_matrix_init (size_t n_variables, + const struct variable *v_variables[], int n_pass, + int missing_handling, enum mv_class missing_value) +{ + size_t i; + struct covariance_matrix *result = NULL; + result = xmalloc (sizeof (*result)); + result->cov = NULL; + result->n_variables = n_variables; + result->ca = covariance_hsh_create (&result->n_variables); + result->m = NULL; + result->m1 = NULL; + result->n_intr = 0; + result->missing_handling = missing_handling; + result->missing_value = missing_value; + result->accumulate = (result->missing_handling == LISTWISE) ? + covariance_accumulate_listwise : covariance_accumulate_pairwise; + if (n_pass == ONE_PASS) + { + result->update_moments = update_moments1; + result->m1 = xnmalloc (n_variables, sizeof (*result->m1)); + for (i = 0; i < n_variables; i++) + { + result->m1[i] = moments1_create (MOMENT_MEAN); + } + } + else + { + result->update_moments = update_moments2; + result->m = xnmalloc (n_variables, sizeof (*result->m)); + for (i = 0; i < n_variables; i++) + { + result->m[i] = moments_create (MOMENT_MEAN); + } + } + result->v_variables = v_variables; + + result->n_pass = n_pass; + + return result; +} +void +covariance_interaction_set (struct covariance_matrix *cov, + const struct interaction_variable **intr, size_t n_intr) +{ + cov->interactions = intr; + cov->n_intr = n_intr; +} + +static size_t +get_n_rows (size_t n_variables, const struct variable *v_variables[]) +{ + size_t i; + size_t result = 0; + for (i = 0; i < n_variables; i++) + { + if (var_is_numeric (v_variables[i])) + { + result++; + } + else if (var_is_alpha (v_variables[i])) + { + size_t n_categories = cat_get_n_categories (v_variables[i]); + result += n_categories - 1; + } + } + return result; +} /* The covariances are stored in a DESIGN_MATRIX structure. */ struct design_matrix * -covariance_matrix_create (size_t n_variables, const struct variable *v_variables[]) +covariance_matrix_create (size_t n_variables, + const struct variable *v_variables[]) { - return design_matrix_create (n_variables, v_variables, (size_t) n_variables); + size_t n_rows = get_n_rows (n_variables, v_variables); + return design_matrix_create (n_variables, v_variables, n_rows); } -void covariance_matrix_destroy (struct design_matrix *x) +static size_t +get_n_rows_s (const struct variable *var) { - design_matrix_destroy (x); + size_t result = 0; + if (var_is_numeric (var)) + { + result++; + } + else + { + result += cat_get_n_categories (var) - 1; + } + return result; +} +static struct design_matrix * +covariance_matrix_create_s (struct covariance_matrix *cov) +{ + struct variable **v_variables; + size_t n_variables; + size_t n_rows = 0; + size_t i; + size_t j; + + n_variables = cov->n_variables + cov->n_intr; + v_variables = xnmalloc (n_variables, sizeof (*v_variables)); + for (i = 0; i < cov->n_variables; i++) + { + v_variables[i] = cov->v_variables[i]; + n_rows += get_n_rows_s (v_variables[i]); + } + for (j = 0; j < cov->n_intr; j++) + { + v_variables[i + j] = interaction_get_variable (cov->interactions[j]); + n_rows += get_n_rows_s (v_variables[i]); + } + return design_matrix_create (n_variables, v_variables, n_rows); +} + +static void +update_moments1 (struct covariance_matrix *cov, size_t i, double x) +{ + assert (cov->m1 != NULL); + moments1_add (cov->m1[i], x, 1.0); +} + +static void +update_moments2 (struct covariance_matrix *cov, size_t i, double x) +{ + assert (cov->m != NULL); + moments_pass_one (cov->m[i], x, 1.0); +} + +void +covariance_matrix_destroy (struct covariance_matrix *cov) +{ + size_t i; + + assert (cov != NULL); + design_matrix_destroy (cov->cov); + design_matrix_destroy (cov->ssize); + hsh_destroy (cov->ca); + if (cov->n_pass == ONE_PASS) + { + for (i = 0; i < cov->n_variables; i++) + { + moments1_destroy (cov->m1[i]); + } + free (cov->m1); + } + else + { + for (i = 0; i < cov->n_variables; i++) + { + moments_destroy (cov->m[i]); + } + free (cov->m); + } } /* @@ -74,53 +273,58 @@ void covariance_matrix_destroy (struct design_matrix *x) */ static void covariance_update_categorical_numeric (struct design_matrix *cov, double mean, - size_t row, - const struct variable *v2, double x, const union value *val2) + size_t row, + const struct variable *v2, double x, + const union value *val2) { size_t col; double tmp; - + assert (var_is_numeric (v2)); col = design_matrix_var_to_column (cov, v2); assert (val2 != NULL); - tmp = gsl_matrix_get (cov->m, row, col); - gsl_matrix_set (cov->m, row, col, (val2->f - mean) * x + tmp); - gsl_matrix_set (cov->m, col, row, (val2->f - mean) * x + tmp); + tmp = design_matrix_get_element (cov, row, col); + design_matrix_set_element (cov, row, col, (val2->f - mean) * x + tmp); + design_matrix_set_element (cov, col, row, (val2->f - mean) * x + tmp); } static void column_iterate (struct design_matrix *cov, const struct variable *v, double ssize, double x, const union value *val1, size_t row) { + int width = var_get_width (v); size_t col; size_t i; double y; double tmp; const union value *tmp_val; - col = design_matrix_var_to_column (cov, v); + col = design_matrix_var_to_column (cov, v); for (i = 0; i < cat_get_n_categories (v) - 1; i++) { col += i; y = -1.0 * cat_get_category_count (i, v) / ssize; tmp_val = cat_subscript_to_value (i, v); - if (compare_values (tmp_val, val1, v)) + if (!value_equal (tmp_val, val1, width)) { y += -1.0; } - tmp = gsl_matrix_get (cov->m, row, col); - gsl_matrix_set (cov->m, row, col, x * y + tmp); - gsl_matrix_set (cov->m, col, row, x * y + tmp); + tmp = design_matrix_get_element (cov, row, col); + design_matrix_set_element (cov, row, col, x * y + tmp); + design_matrix_set_element (cov, col, row, x * y + tmp); } } + /* Call this function in the second data pass. The central moments are MEAN1 and MEAN2. Any categorical variables should already have their values summarized in in its OBS_VALS element. */ -void covariance_pass_two (struct design_matrix *cov, double mean1, double mean2, - double ssize, const struct variable *v1, - const struct variable *v2, const union value *val1, const union value *val2) +void +covariance_pass_two (struct design_matrix *cov, double mean1, double mean2, + double ssize, const struct variable *v1, + const struct variable *v2, const union value *val1, + const union value *val2) { size_t row; size_t col; @@ -136,13 +340,13 @@ void covariance_pass_two (struct design_matrix *cov, double mean1, double mean2, row += i; x = -1.0 * cat_get_category_count (i, v1) / ssize; tmp_val = cat_subscript_to_value (i, v1); - if (compare_values (tmp_val, val1, v1)) + if (!value_equal (tmp_val, val1, var_get_width (v1))) { x += 1.0; } if (var_is_numeric (v2)) { - covariance_update_categorical_numeric (cov, mean2, row, + covariance_update_categorical_numeric (cov, mean2, row, v2, x, val2); } else @@ -155,22 +359,22 @@ void covariance_pass_two (struct design_matrix *cov, double mean1, double mean2, else if (var_is_alpha (v2)) { /* - Reverse the orders of V1, V2, etc. and put ourselves back - in the previous IF scope. + Reverse the orders of V1, V2, etc. and put ourselves back + in the previous IF scope. */ covariance_pass_two (cov, mean2, mean1, ssize, v2, v1, val2, val1); } else { /* - Both variables are numeric. - */ - row = design_matrix_var_to_column (cov, v1); + Both variables are numeric. + */ + row = design_matrix_var_to_column (cov, v1); col = design_matrix_var_to_column (cov, v2); x = (val1->f - mean1) * (val2->f - mean2); - x += gsl_matrix_get (cov->m, col, row); - gsl_matrix_set (cov->m, row, col, x); - gsl_matrix_set (cov->m, col, row, x); + x += design_matrix_get_element (cov, col, row); + design_matrix_set_element (cov, row, col, x); + design_matrix_set_element (cov, col, row, x); } } @@ -187,11 +391,13 @@ covariance_accumulator_hash (const void *h, const void *aux) const union value *val_max; /* - Order everything by the variables' indices. This ensures we get the - same key regardless of the order in which the variables are stored - and passed around. + Order everything by the variables' indices. This ensures we get the + same key regardless of the order in which the variables are stored + and passed around. */ - v_min = (var_get_dict_index (ca->v1) < var_get_dict_index (ca->v2)) ? ca->v1 : ca->v2; + v_min = + (var_get_dict_index (ca->v1) < + var_get_dict_index (ca->v2)) ? ca->v1 : ca->v2; v_max = (ca->v1 == v_min) ? ca->v2 : ca->v1; val_min = (v_min == ca->v1) ? ca->val1 : ca->val2; @@ -214,15 +420,9 @@ covariance_accumulator_hash (const void *h, const void *aux) } if (var_is_alpha (v_max) && var_is_alpha (v_min)) { - unsigned int tmp; - char *x = xnmalloc (1 + var_get_width (v_max) + var_get_width (v_min), sizeof (*x)); - strncpy (x, val_max->s, var_get_width (v_max)); - strncat (x, val_min->s, var_get_width (v_min)); - tmp = *n_vars * (*n_vars + 1 + idx_max) - + idx_min - + hsh_hash_string (x); - free (x); - return tmp; + unsigned hash = value_hash (val_max, var_get_width (v_max), 0); + hash = value_hash (val_min, var_get_width (v_min), hash); + return hash_int (*n_vars * (*n_vars + 1 + idx_max) + idx_min, hash); } return -1u; } @@ -233,62 +433,66 @@ covariance_accumulator_hash (const void *h, const void *aux) in a single data pass. Call covariance_accumulate () for each case in the data. */ -struct hsh_table * -covariance_hsh_create (size_t n_vars) +static struct hsh_table * +covariance_hsh_create (size_t *n_vars) { - return hsh_create (n_vars * (n_vars + 1) / 2, covariance_accumulator_compare, - covariance_accumulator_hash, covariance_accumulator_free, &n_vars); + return hsh_create (*n_vars * *n_vars, covariance_accumulator_compare, + covariance_accumulator_hash, covariance_accumulator_free, + n_vars); } -static void +static void covariance_accumulator_free (void *c_, const void *aux UNUSED) { struct covariance_accumulator *c = c_; assert (c != NULL); free (c); } -static int -match_nodes (const struct covariance_accumulator *c, const struct variable *v1, - const struct variable *v2, const union value *val1, - const union value *val2) + +static int +ordered_match_nodes (const struct covariance_accumulator *c, const struct variable *v1, + const struct variable *v2, const union value *val1, const union value *val2) { - if (var_get_dict_index (v1) == var_get_dict_index (c->v1) && - var_get_dict_index (v2) == var_get_dict_index (c->v2)) + size_t result; + size_t m; + + result = var_get_dict_index (v1) ^ var_get_dict_index (c->v1); + m = var_get_dict_index (v2) ^ var_get_dict_index (c->v2); + result = result|m; + if (var_is_alpha (v1)) { - if (var_is_numeric (v1) && var_is_numeric (v2)) - { - return 0; - } - if (var_is_numeric (v1) && var_is_alpha (v2)) - { - if (compare_values (val2, c->val2, v2)) - { - return 0; - } - } - if (var_is_alpha (v1) && var_is_numeric (v2)) + result |= value_compare_3way (val1, c->val1, var_get_width (v1)); + if (var_is_alpha (v2)) { - if (compare_values (val1, c->val1, v1)) - { - return 0; - } - } - if (var_is_alpha (v1) && var_is_alpha (v2)) - { - if (compare_values (val1, c->val1, v1)) - { - if (compare_values (val2, c->val2, v2)) - { - return 0; - } - } + result |= value_compare_3way (val2, c->val2, var_get_width (v2)); } } - else if (v2 == c->v1 && v1 == c->v2) + else if (var_is_alpha (v2)) { - return -match_nodes (c, v2, v1, val2, val1); + result |= value_compare_3way (val2, c->val2, var_get_width (v2)); } - return 1; + return result; +} + +/* + Hash comparison. Returns 0 for a match, or a non-zero int + otherwise. The sign of a non-zero return value *should* indicate the + position of C relative to the covariance_accumulator described by + the other arguments. But for now, it just returns 1 for any + non-match. This should be changed when someone figures out how to + compute a sensible sign for the return value. + */ +static int +match_nodes (const struct covariance_accumulator *c, + const struct variable *v1, const struct variable *v2, + const union value *val1, const union value *val2) +{ + size_t n; + size_t m; + + n = ordered_match_nodes (c, v1, v2, val1, val2); + m = ordered_match_nodes (c, v2, v1, val2, val1); + return (n & m); } /* @@ -296,29 +500,30 @@ match_nodes (const struct covariance_accumulator *c, const struct variable *v1, a struct hsh_table in src/libpspp/hash.c. */ static int -covariance_accumulator_compare (const void *a1_, const void *a2_, const void *aux UNUSED) +covariance_accumulator_compare (const void *a1_, const void *a2_, + const void *aux UNUSED) { - const struct covariance_accumulator *a1 = a1_; - const struct covariance_accumulator *a2 = a2_; + const struct covariance_accumulator *a1 = a1_; + const struct covariance_accumulator *a2 = a2_; if (a1 == NULL && a2 == NULL) return 0; if (a1 == NULL || a2 == NULL) return 1; - + return match_nodes (a1, a2->v1, a2->v2, a2->val1, a2->val2); } static unsigned int -hash_numeric_alpha (const struct variable *v1, const struct variable *v2, +hash_numeric_alpha (const struct variable *v1, const struct variable *v2, const union value *val, size_t n_vars) { unsigned int result = -1u; if (var_is_numeric (v1) && var_is_alpha (v2)) { result = n_vars * ((n_vars + 1) + var_get_dict_index (v1)) - + var_get_dict_index (v2) + hsh_hash_string (val->s); + + var_get_dict_index (v2) + value_hash (val, var_get_width (v2), 0); } else if (var_is_alpha (v1) && var_is_numeric (v2)) { @@ -329,8 +534,8 @@ hash_numeric_alpha (const struct variable *v1, const struct variable *v2, static double -update_product (const struct variable *v1, const struct variable *v2, const union value *val1, - const union value *val2) +update_product (const struct variable *v1, const struct variable *v2, + const union value *val1, const union value *val2) { assert (v1 != NULL); assert (v2 != NULL); @@ -346,191 +551,479 @@ update_product (const struct variable *v1, const struct variable *v2, const unio } if (var_is_numeric (v1) && var_is_alpha (v2)) { - return (val1->f); + return val1->f; } if (var_is_numeric (v2) && var_is_alpha (v1)) { - update_product (v2, v1, val2, val1); + return val2->f; + } + else + { + return 0.0; + } +} +static double +update_sum (const struct variable *var, const union value *val, double weight) +{ + assert (var != NULL); + assert (val != NULL); + if (var_is_alpha (var)) + { + return weight; + } + return val->f; +} +static struct covariance_accumulator * +get_new_covariance_accumulator (const struct variable *v1, + const struct variable *v2, + const union value *val1, + const union value *val2) +{ + if ((v1 != NULL) && (v2 != NULL) && (val1 != NULL) && (val2 != NULL)) + { + struct covariance_accumulator *ca; + ca = xmalloc (sizeof (*ca)); + ca->v1 = v1; + ca->v2 = v2; + ca->val1 = val1; + ca->val2 = val2; + return ca; + } + return NULL; +} + +static const struct variable ** +get_covariance_variables (const struct covariance_matrix *cov) +{ + return cov->v_variables; +} + +static void +update_hash_entry_intr (struct hsh_table *c, + const struct variable *v1, + const struct variable *v2, + const union value *val1, const union value *val2, + const struct interaction_value *i_val1, + const struct interaction_value *i_val2) +{ + struct covariance_accumulator *ca; + struct covariance_accumulator *new_entry; + double iv_f1; + double iv_f2; + + iv_f1 = interaction_value_get_nonzero_entry (i_val1); + iv_f2 = interaction_value_get_nonzero_entry (i_val2); + ca = get_new_covariance_accumulator (v1, v2, val1, val2); + ca->dot_product = update_product (ca->v1, ca->v2, ca->val1, ca->val2); + ca->dot_product *= iv_f1 * iv_f2; + ca->sum1 = update_sum (ca->v1, ca->val1, iv_f1); + ca->sum2 = update_sum (ca->v2, ca->val2, iv_f2); + ca->ssize = 1.0; + new_entry = hsh_insert (c, ca); + + if (new_entry != NULL) + { + new_entry->dot_product += ca->dot_product; + new_entry->ssize += 1.0; + new_entry->sum1 += ca->sum1; + new_entry->sum2 += ca->sum2; + /* + If DOT_PRODUCT is null, CA was not already in the hash + hable, so we don't free it because it was just inserted. + If DOT_PRODUCT was not null, CA is already in the hash table. + Unnecessary now, it must be freed here. + */ + free (ca); } - return 0.0; } + +static void +update_hash_entry (struct hsh_table *c, + const struct variable *v1, + const struct variable *v2, + const union value *val1, const union value *val2) +{ + struct covariance_accumulator *ca; + struct covariance_accumulator *new_entry; + + ca = get_new_covariance_accumulator (v1, v2, val1, val2); + ca->dot_product = update_product (ca->v1, ca->v2, ca->val1, ca->val2); + ca->sum1 = update_sum (ca->v1, ca->val1, 1.0); + ca->sum2 = update_sum (ca->v2, ca->val2, 1.0); + ca->ssize = 1.0; + new_entry = hsh_insert (c, ca); + + if (new_entry != NULL) + { + new_entry->dot_product += ca->dot_product; + new_entry->ssize += 1.0; + new_entry->sum1 += ca->sum1; + new_entry->sum2 += ca->sum2; + /* + If DOT_PRODUCT is null, CA was not already in the hash + hable, so we don't free it because it was just inserted. + If DOT_PRODUCT was not null, CA is already in the hash table. + Unnecessary now, it must be freed here. + */ + free (ca); + } +} + +static void +inner_intr_loop (struct covariance_matrix *cov, const struct ccase *ccase, const struct variable *var1, + const union value *val1, const struct interaction_variable **i_var, + const struct interaction_value *i_val1, size_t j) +{ + struct variable *var2; + union value *val2; + struct interaction_value *i_val2; + + var2 = interaction_get_variable (i_var[j]); + i_val2 = interaction_case_data (ccase, i_var[j]); + val2 = interaction_value_get (i_val2); + + if (!var_is_value_missing (var2, val2, cov->missing_value)) + { + update_hash_entry_intr (cov->ca, var1, var2, val1, val2, i_val1, i_val2); + } +} /* - Compute the covariance matrix in a single data-pass. + Compute the covariance matrix in a single data-pass. Cases with + missing values are dropped pairwise, in other words, only if one of + the two values necessary to accumulate the inner product is missing. + + Do not call this function directly. Call it through the struct + covariance_matrix ACCUMULATE member function, for example, + cov->accumulate (cov, ccase). */ -void -covariance_accumulate (struct hsh_table *cov, struct moments1 **m, - const struct ccase *ccase, const struct variable **vars, - size_t n_vars) +static void +covariance_accumulate_pairwise (struct covariance_matrix *cov, + const struct ccase *ccase, + const struct interaction_variable **i_var, + size_t n_intr) { size_t i; size_t j; - const union value *val; - struct covariance_accumulator *ca; - struct covariance_accumulator *entry; + const union value *val1; + const union value *val2; + const struct variable **v_variables; + const struct variable *var1; + const struct variable *var2; + struct interaction_value *i_val1 = NULL; + struct interaction_value *i_val2 = NULL; + + assert (cov != NULL); + assert (ccase != NULL); - assert (m != NULL); + v_variables = get_covariance_variables (cov); + assert (v_variables != NULL); - for (i = 0; i < n_vars; ++i) + for (i = 0; i < cov->n_variables; ++i) { - val = case_data (ccase, vars[i]); - if (var_is_alpha (vars[i])) + var1 = v_variables[i]; + val1 = case_data (ccase, var1); + if (!var_is_value_missing (var1, val1, cov->missing_value)) { - cat_value_update (vars[i], val); - } - else - { - moments1_add (m[i], val->f, 1.0); + cat_value_update (var1, val1); + if (var_is_numeric (var1)) + cov->update_moments (cov, i, val1->f); + + for (j = i; j < cov->n_variables; j++) + { + var2 = v_variables[j]; + val2 = case_data (ccase, var2); + if (!var_is_value_missing + (var2, val2, cov->missing_value)) + { + update_hash_entry (cov->ca, var1, var2, val1, val2); + } + } + for (j = 0; j < cov->n_intr; j++) + { + inner_intr_loop (cov, ccase, var1, val1, i_var, i_val1, j); + } } - for (j = i; j < n_vars; j++) + } + for (i = 0; i < cov->n_intr; i++) + { + var1 = interaction_get_variable (i_var[i]); + i_val1 = interaction_case_data (ccase, i_var[i]); + val1 = interaction_value_get (i_val1); + cat_value_update (var1, val1); + if (!var_is_value_missing (var1, val1, cov->missing_value)) { - ca = xmalloc (sizeof (*ca)); - ca->v1 = vars[i]; - ca->v2 = vars[j]; - ca->val1 = val; - ca->val2 = case_data (ccase, ca->v2); - ca->product = update_product (ca->v1, ca->v2, ca->val1, ca->val2); - entry = hsh_insert (cov, ca); - if (entry != NULL) + for (j = i; j < cov->n_intr; j++) { - entry->product += ca->product; - /* - If ENTRY is null, CA was not already in the hash - hable, so we don't free it because it was just inserted. - If ENTRY was not null, CA is already in the hash table. - Unnecessary now, it must be freed here. - */ - free (ca); + inner_intr_loop (cov, ccase, var1, val1, i_var, i_val1, j); } } } } -static void -covariance_matrix_insert (struct design_matrix *cov, const struct variable *v1, - const struct variable *v2, const union value *val1, - const union value *val2, double product) +/* + Compute the covariance matrix in a single data-pass. Cases with + missing values are dropped listwise. In other words, if one of the + values for any variable in a case is missing, the entire case is + skipped. + + The caller must use a casefilter to remove the cases with missing + values before calling covariance_accumulate_listwise. This function + assumes that CCASE has already passed through this filter, and + contains no missing values. + + Do not call this function directly. Call it through the struct + covariance_matrix ACCUMULATE member function, for example, + cov->accumulate (cov, ccase). + */ +static void +covariance_accumulate_listwise (struct covariance_matrix *cov, + const struct ccase *ccase, + const struct interaction_variable **i_var, + size_t n_intr) { - size_t row; - size_t col; size_t i; - const union value *tmp_val; + size_t j; + const union value *val1; + const union value *val2; + const struct variable **v_variables; + struct interaction_value *i_val1 = NULL; + struct interaction_value *i_val2 = NULL; assert (cov != NULL); + assert (ccase != NULL); - row = design_matrix_var_to_column (cov, v1); - if (var_is_alpha (v1)) + v_variables = get_covariance_variables (cov); + assert (v_variables != NULL); + + for (i = 0; i < cov->n_variables; ++i) { - i = 0; - tmp_val = cat_subscript_to_value (i, v1); - while (!compare_values (tmp_val, val1, v1)) + val1 = case_data (ccase, v_variables[i]); + cat_value_update (v_variables[i], val1); + if (var_is_numeric (v_variables[i])) + cov->update_moments (cov, i, val1->f); + + for (j = i; j < cov->n_variables; j++) { - i++; - tmp_val = cat_subscript_to_value (i, v1); + update_hash_entry (cov->ca, v_variables[i], v_variables[j], + val1, val2); } - row += i; - if (var_is_numeric (v2)) + } +} + +/* + Call this function during the data pass. Each case will be added to + a hash containing all values of the covariance matrix. After the + data have been passed, call covariance_matrix_compute to put the + values in the struct covariance_matrix. + */ +void +covariance_matrix_accumulate (struct covariance_matrix *cov, + const struct ccase *ccase, void **aux, size_t n_intr) +{ + cov->accumulate (cov, ccase, (const struct interaction_variable **) aux, n_intr); +} + +/* + Return the value corresponding to subscript TARGET. If that value corresponds + to the origin, return NULL. + */ +static const union value * +get_value_from_subscript (const struct design_matrix *dm, size_t target) +{ + const union value *result = NULL; + const struct variable *var; + size_t i; + + var = design_matrix_col_to_var (dm, target); + if (var_is_numeric (var)) + { + return NULL; + } + for (i = 0; i < cat_get_n_categories (var); i++) + { + result = cat_subscript_to_value (i, var); + if (dm_get_exact_subscript (dm, var, result) == target) { - col = design_matrix_var_to_column (cov, v2); + return result; } - else + } + return NULL; +} + +static bool +is_covariance_contributor (const struct covariance_accumulator *ca, const struct design_matrix *dm, + size_t i, size_t j) +{ + size_t k; + const struct variable *v1; + const struct variable *v2; + + assert (dm != NULL); + v1 = design_matrix_col_to_var (dm, i); + v2 = design_matrix_col_to_var (dm, j); + if (var_get_dict_index (v1) == var_get_dict_index(ca->v1)) + { + if (var_get_dict_index (v2) == var_get_dict_index (ca->v2)) { - col = design_matrix_var_to_column (cov, v2); - i = 0; - tmp_val = cat_subscript_to_value (i, v1); - while (!compare_values (tmp_val, val1, v1)) + k = dm_get_exact_subscript (dm, v1, ca->val1); + if (k == i) { - i++; - tmp_val = cat_subscript_to_value (i, v1); - } - col += i; + k = dm_get_exact_subscript (dm, v2, ca->val2); + if (k == j) + { + return true; + } + } } - } - else + } + else if (var_get_dict_index (v1) == var_get_dict_index (ca->v2)) + { + if (var_get_dict_index (v2) == var_get_dict_index (ca->v1)) + { + k = dm_get_exact_subscript (dm, v1, ca->val2); + if (k == i) + { + k = dm_get_exact_subscript (dm, v2, ca->val1); + if (k == j) + { + return true; + } + } + } + } + + return false; +} +static double +get_sum (const struct covariance_matrix *cov, size_t i) +{ + size_t k; + double mean; + double n; + const struct variable *var; + const union value *val = NULL; + + assert ( cov != NULL); + var = design_matrix_col_to_var (cov->cov, i); + if (var != NULL) { - if (var_is_numeric (v2)) + if (var_is_alpha (var)) { - col = design_matrix_var_to_column (cov, v2); + val = get_value_from_subscript (cov->cov, i); + k = cat_value_find (var, val); + return cat_get_category_count (k, var); } else { - covariance_matrix_insert (cov, v2, v1, val2, val1, product); + k = 0; + while (cov->v_variables[k] != var && k < cov->n_variables) + { + k++; + } + if (k < cov->n_variables) + { + moments1_calculate (cov->m1[k], &n, &mean, NULL, NULL, NULL); + return mean * n; + } } } - gsl_matrix_set (cov->m, row, col, product); - gsl_matrix_set (cov->m, col, row, product); + + return 0.0; } - -static double -get_center (const struct variable *v, const union value *val, - const struct variable **vars, const struct moments1 **m, size_t n_vars, - size_t ssize) +static void +update_ssize (struct design_matrix *dm, size_t i, size_t j, struct covariance_accumulator *ca) { - size_t i = 0; - - while ((var_get_dict_index (vars[i]) != var_get_dict_index(v)) && (i < n_vars)) + const struct variable *var; + double tmp; + var = design_matrix_col_to_var (dm, i); + if (var_get_dict_index (ca->v1) == var_get_dict_index (var)) { - i++; - } - if (var_is_numeric (v)) + var = design_matrix_col_to_var (dm, j); + if (var_get_dict_index (ca->v2) == var_get_dict_index (var)) + { + tmp = design_matrix_get_element (dm, i, j); + tmp += ca->ssize; + design_matrix_set_element (dm, i, j, tmp); + } + } +} +static void +covariance_accumulator_to_matrix (struct covariance_matrix *cov) +{ + size_t i; + size_t j; + double sum_i = 0.0; + double sum_j = 0.0; + double tmp = 0.0; + struct covariance_accumulator *entry; + struct hsh_iterator iter; + + cov->cov = covariance_matrix_create_s (cov); + cov->ssize = covariance_matrix_create_s (cov); + entry = hsh_first (cov->ca, &iter); + while (entry != NULL) { - double mean; - moments1_calculate (m[i], NULL, &mean, NULL, NULL, NULL); - return mean; + entry = hsh_next (cov->ca, &iter); } - else + + for (i = 0; i < design_matrix_get_n_cols (cov->cov); i++) { - i = cat_value_find (v, val); - return (cat_get_category_count (i, v) / ssize); + sum_i = get_sum (cov, i); + for (j = i; j < design_matrix_get_n_cols (cov->cov); j++) + { + sum_j = get_sum (cov, j); + entry = hsh_first (cov->ca, &iter); + while (entry != NULL) + { + update_ssize (cov->ssize, i, j, entry); + /* + We compute the centered, un-normalized covariance matrix. + */ + if (is_covariance_contributor (entry, cov->cov, i, j)) + { + design_matrix_set_element (cov->cov, i, j, entry->dot_product); + } + entry = hsh_next (cov->ca, &iter); + } + tmp = design_matrix_get_element (cov->cov, i, j); + tmp -= sum_i * sum_j / design_matrix_get_element (cov->ssize, i, j); + design_matrix_set_element (cov->cov, i, j, tmp); + design_matrix_set_element (cov->cov, j, i, tmp); + } } - return 0.0; } + /* - Subtract the product of the means. + Call this function after passing the data. */ -static double -center_entry (const struct covariance_accumulator *ca, const struct variable **vars, - const struct moments1 **m, size_t n_vars, size_t ssize) +void +covariance_matrix_compute (struct covariance_matrix *cov) { - double m1; - double m2; - double result = 0.0; - - m1 = get_center (ca->v1, ca->val1, vars, m, n_vars, ssize); - m2 = get_center (ca->v2, ca->val2, vars, m, n_vars, ssize); - result = ca->product - ssize * m1 * m2; - return result; + if (cov->n_pass == ONE_PASS) + { + covariance_accumulator_to_matrix (cov); + } } -/* - The first moments in M should be stored in the order corresponding - to the order of VARS. So, for example, VARS[0] has its moments in - M[0], VARS[1] has its moments in M[1], etc. - */ struct design_matrix * -covariance_accumulator_to_matrix (struct hsh_table *cov, const struct moments1 **m, - const struct variable **vars, size_t n_vars, size_t ssize) +covariance_to_design (const struct covariance_matrix *c) { - double tmp; - struct covariance_accumulator *entry; - struct design_matrix *result = NULL; - struct hsh_iterator iter; - - result = covariance_matrix_create (n_vars, vars); - - entry = hsh_first (cov, &iter); - - while (entry != NULL) + if (c != NULL) { - /* - We compute the centered, un-normalized covariance matrix. - */ - tmp = center_entry (entry, vars, m, n_vars, ssize); - covariance_matrix_insert (result, entry->v1, entry->v2, entry->val1, - entry->val2, tmp); - entry = hsh_next (cov, &iter); + return c->cov; } + return NULL; +} +size_t +covariance_matrix_get_n_rows (const struct covariance_matrix *c) +{ + return design_matrix_get_n_rows (c->cov); +} - return result; +double +covariance_matrix_get_element (const struct covariance_matrix *c, size_t row, size_t col) +{ + return (design_matrix_get_element (c->cov, row, col)); }