X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Ffactor.c;h=b93e5ea31eaba80a68a999de510710b67b27d4c2;hb=3b7a1d755ef39bb2fb78e94cba2d33a443bec624;hp=095d98ff35c5c0c290bae9cc3c6ab45f1fdd9afb;hpb=8736d8d715ddfb9fb7bd2ecfc075156892a47eee;p=pspp diff --git a/src/language/stats/factor.c b/src/language/stats/factor.c index 095d98ff35..b93e5ea31e 100644 --- a/src/language/stats/factor.c +++ b/src/language/stats/factor.c @@ -45,9 +45,8 @@ #include "math/correlation.h" #include "math/covariance.h" #include "math/moments.h" -#include "output/chart-item.h" #include "output/charts/scree.h" -#include "output/tab.h" +#include "output/pivot-table.h" #include "gettext.h" @@ -81,19 +80,19 @@ enum plot_opts enum print_opts { - PRINT_UNIVARIATE = 0x0001, - PRINT_DETERMINANT = 0x0002, - PRINT_INV = 0x0004, - PRINT_AIC = 0x0008, - PRINT_SIG = 0x0010, - PRINT_COVARIANCE = 0x0020, - PRINT_CORRELATION = 0x0040, - PRINT_ROTATION = 0x0080, - PRINT_EXTRACTION = 0x0100, - PRINT_INITIAL = 0x0200, - PRINT_KMO = 0x0400, - PRINT_REPR = 0x0800, - PRINT_FSCORE = 0x1000 + PRINT_UNIVARIATE = 1 << 0, + PRINT_DETERMINANT = 1 << 1, + PRINT_INV = 1 << 2, + PRINT_AIC = 1 << 3, + PRINT_SIG = 1 << 4, + PRINT_COVARIANCE = 1 << 5, + PRINT_CORRELATION = 1 << 6, + PRINT_ROTATION = 1 << 7, + PRINT_EXTRACTION = 1 << 8, + PRINT_INITIAL = 1 << 9, + PRINT_KMO = 1 << 10, + PRINT_REPR = 1 << 11, + PRINT_FSCORE = 1 << 12 }; enum rotation_type @@ -107,13 +106,13 @@ enum rotation_type typedef void (*rotation_coefficients) (double *x, double *y, double a, double b, double c, double d, - const gsl_matrix *loadings ); + const gsl_matrix *loadings); static void varimax_coefficients (double *x, double *y, double a, double b, double c, double d, - const gsl_matrix *loadings ) + const gsl_matrix *loadings) { *x = d - 2 * a * b / loadings->size1; *y = c - (a * a - b * b) / loadings->size1; @@ -122,7 +121,7 @@ varimax_coefficients (double *x, double *y, static void equamax_coefficients (double *x, double *y, double a, double b, double c, double d, - const gsl_matrix *loadings ) + const gsl_matrix *loadings) { *x = d - loadings->size2 * a * b / loadings->size1; *y = c - loadings->size2 * (a * a - b * b) / (2 * loadings->size1); @@ -133,8 +132,8 @@ quartimax_coefficients (double *x, double *y, double a UNUSED, double b UNUSED, double c, double d, const gsl_matrix *loadings UNUSED) { - *x = d ; - *y = c ; + *x = d; + *y = c; } static const rotation_coefficients rotation_coeff[] = { @@ -149,7 +148,6 @@ static const rotation_coefficients rotation_coeff[] = { static gsl_matrix * diag_rcp_sqrt (const gsl_matrix *C) { - int j; gsl_matrix *d = gsl_matrix_calloc (C->size1, C->size2); gsl_matrix *r = gsl_matrix_calloc (C->size1, C->size2); @@ -159,7 +157,7 @@ diag_rcp_sqrt (const gsl_matrix *C) C, GSL_LINALG_MOD_NONE, d); - for (j = 0 ; j < d->size2; ++j) + for (int j = 0; j < d->size2; ++j) { double e = gsl_matrix_get (d, j, j); e = 1.0 / sqrt (e); @@ -177,12 +175,11 @@ diag_rcp_sqrt (const gsl_matrix *C) static gsl_matrix * diag_rcp_inv_sqrt (const gsl_matrix *CCinv) { - int j; gsl_matrix *r = gsl_matrix_calloc (CCinv->size1, CCinv->size2); assert (CCinv->size1 == CCinv->size2); - for (j = 0 ; j < CCinv->size2; ++j) + for (int j = 0; j < CCinv->size2; ++j) { double e = gsl_matrix_get (CCinv, j, j); e = 1.0 / sqrt (e); @@ -234,12 +231,12 @@ struct idata gsl_matrix *analysis_matrix; /* A pointer to either mm.corr or mm.cov */ - gsl_vector *eval ; /* The eigenvalues */ - gsl_matrix *evec ; /* The eigenvectors */ + gsl_vector *eval; /* The eigenvalues */ + gsl_matrix *evec; /* The eigenvectors */ int n_extractions; - gsl_vector *msr ; /* Multiple Squared Regressions */ + gsl_vector *msr; /* Multiple Squared Regressions */ double detR; /* The determinant of the correlation matrix */ @@ -251,7 +248,7 @@ struct idata static struct idata * idata_alloc (size_t n_vars) { - struct idata *id = xzalloc (sizeof (*id)); + struct idata *id = XZALLOC (struct idata); id->n_extractions = 0; id->msr = gsl_vector_alloc (n_vars); @@ -278,18 +275,13 @@ idata_free (struct idata *id) static double ssq_row_od_n (const gsl_matrix *m, int j) { - int i; - double ss = 0; assert (m->size1 == m->size2); - assert (j < m->size1); - for (i = 0; i < m->size1; ++i) - { - if (i == j ) continue; + double ss = 0; + for (int i = 0; i < m->size1; ++i) + if (i != j) ss += pow2 (gsl_matrix_get (m, i, j)); - } - return ss; } @@ -297,21 +289,14 @@ ssq_row_od_n (const gsl_matrix *m, int j) static double ssq_od_n (const gsl_matrix *m, int n) { - int i, j; - double ss = 0; assert (m->size1 == m->size2); - assert (n < m->size1); - for (i = 0; i < m->size1; ++i) - { - for (j = 0; j < m->size2; ++j) - { - if (i == j) continue; - ss += pow2 (gsl_matrix_get (m, i, j)); - } - } - + double ss = 0; + for (int i = 0; i < m->size1; ++i) + for (int j = 0; j < m->size2; ++j) + if (i != j) + ss += pow2 (gsl_matrix_get (m, i, j)); return ss; } @@ -319,24 +304,19 @@ ssq_od_n (const gsl_matrix *m, int n) static gsl_matrix * anti_image_corr (const gsl_matrix *m, const struct idata *idata) { - int i, j; - gsl_matrix *a; assert (m->size1 == m->size2); - a = gsl_matrix_alloc (m->size1, m->size2); - - for (i = 0; i < m->size1; ++i) - { - for (j = 0; j < m->size2; ++j) - { - double *p = gsl_matrix_ptr (a, i, j); - *p = gsl_matrix_get (m, i, j); - *p /= sqrt (gsl_matrix_get (m, i, i) * - gsl_matrix_get (m, j, j)); - } - } + gsl_matrix *a = gsl_matrix_alloc (m->size1, m->size2); + for (int i = 0; i < m->size1; ++i) + for (int j = 0; j < m->size2; ++j) + { + double *p = gsl_matrix_ptr (a, i, j); + *p = gsl_matrix_get (m, i, j); + *p /= sqrt (gsl_matrix_get (m, i, i) * + gsl_matrix_get (m, j, j)); + } - for (i = 0; i < m->size1; ++i) + for (int i = 0; i < m->size1; ++i) { double r = ssq_row_od_n (idata->mm.corr, i); double u = ssq_row_od_n (a, i); @@ -349,22 +329,17 @@ anti_image_corr (const gsl_matrix *m, const struct idata *idata) static gsl_matrix * anti_image_cov (const gsl_matrix *m) { - int i, j; - gsl_matrix *a; assert (m->size1 == m->size2); - a = gsl_matrix_alloc (m->size1, m->size2); - - for (i = 0; i < m->size1; ++i) - { - for (j = 0; j < m->size2; ++j) - { - double *p = gsl_matrix_ptr (a, i, j); - *p = gsl_matrix_get (m, i, j); - *p /= gsl_matrix_get (m, i, i); - *p /= gsl_matrix_get (m, j, j); - } - } + gsl_matrix *a = gsl_matrix_alloc (m->size1, m->size2); + for (int i = 0; i < m->size1; ++i) + for (int j = 0; j < m->size2; ++j) + { + double *p = gsl_matrix_ptr (a, i, j); + *p = gsl_matrix_get (m, i, j); + *p /= gsl_matrix_get (m, i, i); + *p /= gsl_matrix_get (m, j, j); + } return a; } @@ -373,11 +348,9 @@ anti_image_cov (const gsl_matrix *m) static void dump_matrix (const gsl_matrix *m) { - size_t i, j; - - for (i = 0 ; i < m->size1; ++i) + for (int i = 0; i < m->size1; ++i) { - for (j = 0 ; j < m->size2; ++j) + for (int j = 0; j < m->size2; ++j) printf ("%02f ", gsl_matrix_get (m, i, j)); printf ("\n"); } @@ -386,11 +359,9 @@ dump_matrix (const gsl_matrix *m) static void dump_matrix_permute (const gsl_matrix *m, const gsl_permutation *p) { - size_t i, j; - - for (i = 0 ; i < m->size1; ++i) + for (int i = 0; i < m->size1; ++i) { - for (j = 0 ; j < m->size2; ++j) + for (int j = 0; j < m->size2; ++j) printf ("%02f ", gsl_matrix_get (m, gsl_permutation_get (p, i), j)); printf ("\n"); } @@ -400,11 +371,8 @@ dump_matrix_permute (const gsl_matrix *m, const gsl_permutation *p) static void dump_vector (const gsl_vector *v) { - size_t i; - for (i = 0 ; i < v->size; ++i) - { - printf ("%02f\n", gsl_vector_get (v, i)); - } + for (size_t i = 0; i < v->size; ++i) + printf ("%02f\n", gsl_vector_get (v, i)); printf ("\n"); } #endif @@ -413,10 +381,8 @@ dump_vector (const gsl_vector *v) static int n_extracted_factors (const struct cmd_factor *factor, struct idata *idata) { - int i; - /* If there is a cached value, then return that. */ - if ( idata->n_extractions != 0) + if (idata->n_extractions != 0) return idata->n_extractions; /* Otherwise, if the number of factors has been explicitly requested, @@ -428,7 +394,7 @@ n_extracted_factors (const struct cmd_factor *factor, struct idata *idata) } /* Use the MIN_EIGEN setting. */ - for (i = 0 ; i < idata->eval->size; ++i) + for (int i = 0; i < idata->eval->size; ++i) { double evali = fabs (gsl_vector_get (idata->eval, i)); @@ -444,15 +410,13 @@ n_extracted_factors (const struct cmd_factor *factor, struct idata *idata) /* Returns a newly allocated matrix identical to M. - It it the callers responsibility to free the returned value. + It is the callers responsibility to free the returned value. */ static gsl_matrix * matrix_dup (const gsl_matrix *m) { - gsl_matrix *n = gsl_matrix_alloc (m->size1, m->size2); - + gsl_matrix *n = gsl_matrix_alloc (m->size1, m->size2); gsl_matrix_memcpy (n, m); - return n; } @@ -507,30 +471,26 @@ squared_multiple_correlation (const gsl_matrix *corr, int var, struct smr_worksp http://www.visualstatistics.net/Visual%20Statistics%20Multimedia/multiple_regression_analysis.htm */ - int signum = 0; - gsl_matrix_view rxx; - gsl_matrix_memcpy (ws->m, corr); gsl_matrix_swap_rows (ws->m, 0, var); gsl_matrix_swap_columns (ws->m, 0, var); - rxx = gsl_matrix_submatrix (ws->m, 1, 1, ws->m->size1 - 1, ws->m->size1 - 1); + gsl_matrix_view rxx = gsl_matrix_submatrix (ws->m, 1, 1, ws->m->size1 - 1, ws->m->size1 - 1); + int signum = 0; gsl_linalg_LU_decomp (&rxx.matrix, ws->perm, &signum); gsl_linalg_LU_invert (&rxx.matrix, ws->perm, ws->inverse); - { - gsl_matrix_const_view rxy = gsl_matrix_const_submatrix (ws->m, 1, 0, ws->m->size1 - 1, 1); - gsl_matrix_const_view ryx = gsl_matrix_const_submatrix (ws->m, 0, 1, 1, ws->m->size1 - 1); + gsl_matrix_const_view rxy = gsl_matrix_const_submatrix (ws->m, 1, 0, ws->m->size1 - 1, 1); + gsl_matrix_const_view ryx = gsl_matrix_const_submatrix (ws->m, 0, 1, 1, ws->m->size1 - 1); - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, - 1.0, ws->inverse, &rxy.matrix, 0.0, ws->result1); + gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, + 1.0, ws->inverse, &rxy.matrix, 0.0, ws->result1); - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, - 1.0, &ryx.matrix, ws->result1, 0.0, ws->result2); - } + gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, + 1.0, &ryx.matrix, ws->result1, 0.0, ws->result2); return gsl_matrix_get (ws->result2, 0, 0); } @@ -545,10 +505,10 @@ struct factor_matrix_workspace size_t n_factors; gsl_eigen_symmv_workspace *eigen_ws; - gsl_vector *eval ; - gsl_matrix *evec ; + gsl_vector *eval; + gsl_matrix *evec; - gsl_matrix *gamma ; + gsl_matrix *gamma; gsl_matrix *r; }; @@ -588,14 +548,11 @@ static void perm_shift_apply (gsl_permutation *target, const gsl_permutation *p, size_t offset) { - size_t i; assert (target->size == p->size); assert (offset <= target->size); - for (i = 0; i < target->size - offset; ++i) - { - target->data[i] = p->data [i + offset]; - } + for (size_t i = 0; i < target->size - offset; ++i) + target->data[i] = p->data [i + offset]; } @@ -612,45 +569,37 @@ perm_shift_apply (gsl_permutation *target, const gsl_permutation *p, static void sort_matrix_indirect (const gsl_matrix *input, gsl_permutation *perm) { - const size_t n = perm->size; - const size_t m = input->size2; - int i, j; - gsl_matrix *mat ; - int column_n = 0; - int row_n = 0; - gsl_permutation *p; - assert (perm->size == input->size1); - p = gsl_permutation_alloc (n); + const size_t n = perm->size; + const size_t m = input->size2; + gsl_permutation *p = gsl_permutation_alloc (n); /* Copy INPUT into MAT, discarding the sign */ - mat = gsl_matrix_alloc (n, m); - for (i = 0 ; i < mat->size1; ++i) - { - for (j = 0 ; j < mat->size2; ++j) - { - double x = gsl_matrix_get (input, i, j); - gsl_matrix_set (mat, i, j, fabs (x)); - } - } + gsl_matrix *mat = gsl_matrix_alloc (n, m); + for (int i = 0; i < mat->size1; ++i) + for (int j = 0; j < mat->size2; ++j) + gsl_matrix_set (mat, i, j, fabs (gsl_matrix_get (input, i, j))); + int column_n = 0; + int row_n = 0; while (column_n < m && row_n < n) { gsl_vector_const_view columni = gsl_matrix_const_column (mat, column_n); gsl_sort_vector_index (p, &columni.vector); - for (i = 0 ; i < n; ++i) + int i; + for (i = 0; i < n; ++i) { gsl_vector_view row = gsl_matrix_row (mat, p->data[n - 1 - i]); size_t maxindex = gsl_vector_max_index (&row.vector); - if ( maxindex > column_n ) + if (maxindex > column_n) break; /* All subsequent elements of this row, are of no interest. So set them all to a highly negative value */ - for (j = column_n + 1; j < row.vector.size ; ++j) + for (int j = column_n + 1; j < row.vector.size; ++j) gsl_vector_set (&row.vector, j, -DBL_MAX); } @@ -663,7 +612,7 @@ sort_matrix_indirect (const gsl_matrix *input, gsl_permutation *perm) gsl_permutation_free (p); gsl_matrix_free (mat); - assert ( 0 == gsl_permutation_valid (perm)); + assert (0 == gsl_permutation_valid (perm)); /* We want the biggest value to be first */ gsl_permutation_reverse (perm); @@ -684,17 +633,11 @@ drot_go (double phi, double *l0, double *l1) static gsl_matrix * clone_matrix (const gsl_matrix *m) { - int j, k; gsl_matrix *c = gsl_matrix_calloc (m->size1, m->size2); - for (j = 0 ; j < c->size1; ++j) - { - for (k = 0 ; k < c->size2; ++k) - { - const double *v = gsl_matrix_const_ptr (m, j, k); - gsl_matrix_set (c, j, k, *v); - } - } + for (int j = 0; j < c->size1; ++j) + for (int k = 0; k < c->size2; ++k) + gsl_matrix_set (c, j, k, gsl_matrix_get (m, j, k)); return c; } @@ -703,15 +646,13 @@ clone_matrix (const gsl_matrix *m) static double initial_sv (const gsl_matrix *fm) { - int j, k; - double sv = 0.0; - for (j = 0 ; j < fm->size2; ++j) + for (int j = 0; j < fm->size2; ++j) { double l4s = 0; double l2s = 0; - for (k = j + 1 ; k < fm->size2; ++k) + for (int k = j + 1; k < fm->size2; ++k) { double lambda = gsl_matrix_get (fm, k, j); double lambda_sq = lambda * lambda; @@ -720,7 +661,7 @@ initial_sv (const gsl_matrix *fm) l4s += lambda_4; l2s += lambda_sq; } - sv += ( fm->size1 * l4s - (l2s * l2s) ) / (fm->size1 * fm->size1 ); + sv += (fm->size1 * l4s - (l2s * l2s)) / (fm->size1 * fm->size1); } return sv; } @@ -731,20 +672,15 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, gsl_matrix *result, gsl_vector *rotated_loadings, gsl_matrix *pattern_matrix, - gsl_matrix *factor_correlation_matrix - ) + gsl_matrix *factor_correlation_matrix) { - int j, k; - int i; - double prev_sv; - /* First get a normalised version of UNROT */ gsl_matrix *normalised = gsl_matrix_calloc (unrot->size1, unrot->size2); gsl_matrix *h_sqrt = gsl_matrix_calloc (communalities->size, communalities->size); - gsl_matrix *h_sqrt_inv ; + gsl_matrix *h_sqrt_inv; /* H is the diagonal matrix containing the absolute values of the communalities */ - for (i = 0 ; i < communalities->size ; ++i) + for (int i = 0; i < communalities->size; ++i) { double *ptr = gsl_matrix_ptr (h_sqrt, i, i); *ptr = fabs (gsl_vector_get (communalities, i)); @@ -753,7 +689,6 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, /* Take the square root of the communalities */ gsl_linalg_cholesky_decomp (h_sqrt); - /* Save a copy of h_sqrt and invert it */ h_sqrt_inv = clone_matrix (h_sqrt); gsl_linalg_cholesky_decomp (h_sqrt_inv); @@ -764,30 +699,24 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, gsl_matrix_free (h_sqrt_inv); - /* Now perform the rotation iterations */ - - prev_sv = initial_sv (normalised); - for (i = 0 ; i < cf->rotation_iterations ; ++i) + double prev_sv = initial_sv (normalised); + for (int i = 0; i < cf->rotation_iterations; ++i) { double sv = 0.0; - for (j = 0 ; j < normalised->size2; ++j) + for (int j = 0; j < normalised->size2; ++j) { /* These variables relate to the convergence criterium */ double l4s = 0; double l2s = 0; - for (k = j + 1 ; k < normalised->size2; ++k) + for (int k = j + 1; k < normalised->size2; ++k) { - int p; double a = 0.0; double b = 0.0; double c = 0.0; double d = 0.0; - double x, y; - double phi; - - for (p = 0; p < normalised->size1; ++p) + for (int p = 0; p < normalised->size1; ++p) { double jv = gsl_matrix_get (normalised, p, j); double kv = gsl_matrix_get (normalised, p, k); @@ -800,15 +729,15 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, d += 2 * u * v; } + double x, y; rotation_coeff [cf->rotation] (&x, &y, a, b, c, d, normalised); - - phi = atan2 (x, y) / 4.0 ; + double phi = atan2 (x, y) / 4.0; /* Don't bother rotating if the angle is small */ - if ( fabs (sin (phi) ) <= pow (10.0, -15.0)) + if (fabs (sin (phi)) <= pow (10.0, -15.0)) continue; - for (p = 0; p < normalised->size1; ++p) + for (int p = 0; p < normalised->size1; ++p) { double *lambda0 = gsl_matrix_ptr (normalised, p, j); double *lambda1 = gsl_matrix_ptr (normalised, p, k); @@ -816,19 +745,17 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, } /* Calculate the convergence criterium */ - { - double lambda = gsl_matrix_get (normalised, k, j); - double lambda_sq = lambda * lambda; - double lambda_4 = lambda_sq * lambda_sq; - - l4s += lambda_4; - l2s += lambda_sq; - } + double lambda = gsl_matrix_get (normalised, k, j); + double lambda_sq = lambda * lambda; + double lambda_4 = lambda_sq * lambda_sq; + + l4s += lambda_4; + l2s += lambda_sq; } - sv += ( normalised->size1 * l4s - (l2s * l2s) ) / (normalised->size1 * normalised->size1 ); + sv += (normalised->size1 * l4s - (l2s * l2s)) / (normalised->size1 * normalised->size1); } - if ( fabs (sv - prev_sv) <= cf->rconverge) + if (fabs (sv - prev_sv) <= cf->rconverge) break; prev_sv = sv; @@ -853,38 +780,27 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, gsl_permutation *perm = gsl_permutation_alloc (unrot->size2); - int signum; - int i, j; - - /* The following variables follow the notation by SPSS Statistical Algorithms - page 342 */ - gsl_matrix *L = gsl_matrix_calloc (unrot->size2, unrot->size2); + /* The following variables follow the notation by SPSS Statistical + Algorithms page 342. */ + gsl_matrix *L = gsl_matrix_calloc (unrot->size2, unrot->size2); gsl_matrix *P = clone_matrix (result); - gsl_matrix *D ; - gsl_matrix *Q ; - /* Vector of length p containing (indexed by i) \Sum^m_j {\lambda^2_{ij}} */ gsl_vector *rssq = gsl_vector_calloc (unrot->size1); - for (i = 0; i < P->size1; ++i) + for (int i = 0; i < P->size1; ++i) { double sum = 0; - for (j = 0; j < P->size2; ++j) - { - sum += gsl_matrix_get (result, i, j) - * gsl_matrix_get (result, i, j); - - } - + for (int j = 0; j < P->size2; ++j) + sum += gsl_matrix_get (result, i, j) * gsl_matrix_get (result, i, j); gsl_vector_set (rssq, i, sqrt (sum)); } - for (i = 0; i < P->size1; ++i) + for (int i = 0; i < P->size1; ++i) { - for (j = 0; j < P->size2; ++j) + for (int j = 0; j < P->size2; ++j) { double l = gsl_matrix_get (result, i, j); double r = gsl_vector_get (rssq, i); @@ -900,6 +816,7 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, GSL_LINALG_MOD_NONE, mm1); + int signum; gsl_linalg_LU_decomp (mm1, perm, &signum); gsl_linalg_LU_invert (mm1, perm, mm2); @@ -911,8 +828,8 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, P, GSL_LINALG_MOD_NONE, L); - D = diag_rcp_sqrt (L); - Q = gsl_matrix_calloc (unrot->size2, unrot->size2); + gsl_matrix *D = diag_rcp_sqrt (L); + gsl_matrix *Q = gsl_matrix_calloc (unrot->size2, unrot->size2); gsl_linalg_matmult_mod (L, GSL_LINALG_MOD_NONE, D, GSL_LINALG_MOD_NONE, @@ -929,7 +846,7 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, gsl_matrix *C = diag_rcp_inv_sqrt (QQinv); - gsl_matrix *Cinv = clone_matrix (C); + gsl_matrix *Cinv = clone_matrix (C); gsl_linalg_cholesky_decomp (Cinv); gsl_linalg_cholesky_invert (Cinv); @@ -978,11 +895,11 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, /* reflect negative sums and populate the rotated loadings vector*/ - for (i = 0 ; i < result->size2; ++i) + for (int i = 0; i < result->size2; ++i) { double ssq = 0.0; double sum = 0.0; - for (j = 0 ; j < result->size1; ++j) + for (int j = 0; j < result->size1; ++j) { double s = gsl_matrix_get (result, j, i); ssq += s * s; @@ -991,8 +908,8 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, gsl_vector_set (rotated_loadings, i, ssq); - if ( sum < 0 ) - for (j = 0 ; j < result->size1; ++j) + if (sum < 0) + for (int j = 0; j < result->size1; ++j) { double *lambda = gsl_matrix_ptr (result, j, i); *lambda = - *lambda; @@ -1000,7 +917,6 @@ rotate (const struct cmd_factor *cf, const gsl_matrix *unrot, } } - /* Get an approximation for the factor matrix into FACTORS, and the communalities into COMMUNALITIES. R is the matrix to be analysed. @@ -1010,9 +926,6 @@ static void iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matrix *factors, struct factor_matrix_workspace *ws) { - size_t i; - gsl_matrix_view mv ; - assert (r->size1 == r->size2); assert (r->size1 == communalities->size); @@ -1022,7 +935,7 @@ iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matri gsl_matrix_memcpy (ws->r, r); /* Apply Communalities to diagonal of correlation matrix */ - for (i = 0 ; i < communalities->size ; ++i) + for (size_t i = 0; i < communalities->size; ++i) { double *x = gsl_matrix_ptr (ws->r, i, i); *x = gsl_vector_get (communalities, i); @@ -1030,10 +943,10 @@ iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matri gsl_eigen_symmv (ws->r, ws->eval, ws->evec, ws->eigen_ws); - mv = gsl_matrix_submatrix (ws->evec, 0, 0, ws->evec->size1, ws->n_factors); + gsl_matrix_view mv = gsl_matrix_submatrix (ws->evec, 0, 0, ws->evec->size1, ws->n_factors); /* Gamma is the diagonal matrix containing the absolute values of the eigenvalues */ - for (i = 0 ; i < ws->n_factors ; ++i) + for (size_t i = 0; i < ws->n_factors; ++i) { double *ptr = gsl_matrix_ptr (ws->gamma, i, i); *ptr = fabs (gsl_vector_get (ws->eval, i)); @@ -1044,7 +957,7 @@ iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matri gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, &mv.matrix, ws->gamma, 0.0, factors); - for (i = 0 ; i < r->size1 ; ++i) + for (size_t i = 0; i < r->size1; ++i) { double h = the_communality (ws->evec, ws->eval, i, ws->n_factors); gsl_vector_set (communalities, i, h); @@ -1062,67 +975,66 @@ static void do_factor_by_matrix (const struct cmd_factor *factor, struct idata * int cmd_factor (struct lexer *lexer, struct dataset *ds) { - struct dictionary *dict = NULL; int n_iterations = 25; - struct cmd_factor factor; - factor.n_vars = 0; - factor.vars = NULL; - factor.method = METHOD_CORR; - factor.missing_type = MISS_LISTWISE; - factor.exclude = MV_ANY; - factor.print = PRINT_INITIAL | PRINT_EXTRACTION | PRINT_ROTATION; - factor.extraction = EXTRACTION_PC; - factor.n_factors = 0; - factor.min_eigen = SYSMIS; - factor.extraction_iterations = 25; - factor.rotation_iterations = 25; - factor.econverge = 0.001; - - factor.blank = 0; - factor.sort = false; - factor.plot = 0; - factor.rotation = ROT_VARIMAX; - factor.wv = NULL; - - factor.rconverge = 0.0001; + + struct cmd_factor factor = { + .n_vars = 0, + .vars = NULL, + .method = METHOD_CORR, + .missing_type = MISS_LISTWISE, + .exclude = MV_ANY, + .print = PRINT_INITIAL | PRINT_EXTRACTION | PRINT_ROTATION, + .extraction = EXTRACTION_PC, + .n_factors = 0, + .min_eigen = SYSMIS, + .extraction_iterations = 25, + .rotation_iterations = 25, + .econverge = 0.001, + + .blank = 0, + .sort = false, + .plot = 0, + .rotation = ROT_VARIMAX, + .wv = NULL, + + .rconverge = 0.0001, + }; lex_match (lexer, T_SLASH); + struct dictionary *dict = NULL; struct matrix_reader *mr = NULL; struct casereader *matrix_reader = NULL; + int vars_start, vars_end; if (lex_match_id (lexer, "VARIABLES")) { lex_match (lexer, T_EQUALS); dict = dataset_dict (ds); factor.wv = dict_get_weight (dict); + vars_start = lex_ofs (lexer); if (!parse_variables_const (lexer, dict, &factor.vars, &factor.n_vars, PV_NO_DUPLICATE | PV_NUMERIC)) goto error; + vars_end = lex_ofs (lexer) - 1; } else if (lex_match_id (lexer, "MATRIX")) { lex_match (lexer, T_EQUALS); - if (! lex_force_match_id (lexer, "IN")) + if (!lex_force_match_id (lexer, "IN")) goto error; if (!lex_force_match (lexer, T_LPAREN)) + goto error; + if (!lex_match_id (lexer, "CORR") && !lex_match_id (lexer, "COV")) { + lex_error (lexer, _("Matrix input for %s must be either COV or CORR"), + "FACTOR"); goto error; } - if (lex_match_id (lexer, "CORR")) - { - } - else if (lex_match_id (lexer, "COV")) - { - } - else - { - lex_error (lexer, _("Matrix input for %s must be either COV or CORR"), "FACTOR"); - goto error; - } - if (! lex_force_match (lexer, T_EQUALS)) + if (!lex_force_match (lexer, T_EQUALS)) goto error; + vars_start = lex_ofs (lexer); if (lex_match (lexer, T_ASTERISK)) { dict = dataset_dict (ds); @@ -1134,25 +1046,22 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) if (fh == NULL) goto error; - matrix_reader - = any_reader_open_and_decode (fh, NULL, &dict, NULL); + matrix_reader = any_reader_open_and_decode (fh, NULL, &dict, NULL); - if (! (matrix_reader && dict)) - { - goto error; - } + if (!(matrix_reader && dict)) + goto error; } + vars_end = lex_ofs (lexer) - 1; - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; - mr = create_matrix_reader_from_case_reader (dict, matrix_reader, - &factor.vars, &factor.n_vars); + mr = matrix_reader_create (dict, matrix_reader); + factor.vars = xmemdup (mr->cvars, mr->n_cvars * sizeof *mr->cvars); + factor.n_vars = mr->n_cvars; } else - { - goto error; - } + goto error; while (lex_token (lexer) != T_ENDCMD) { @@ -1163,13 +1072,14 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) struct const_var_set *vs; const struct variable **vars; size_t n_vars; - bool ok; lex_match (lexer, T_EQUALS); + vars_start = lex_ofs (lexer); vs = const_var_set_create_from_array (factor.vars, factor.n_vars); - ok = parse_const_var_set_vars (lexer, vs, &vars, &n_vars, - PV_NO_DUPLICATE | PV_NUMERIC); + vars_end = lex_ofs (lexer) - 1; + bool ok = parse_const_var_set_vars (lexer, vs, &vars, &n_vars, + PV_NO_DUPLICATE | PV_NUMERIC); const_var_set_destroy (vs); if (!ok) @@ -1178,6 +1088,13 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) free (factor.vars); factor.vars = vars; factor.n_vars = n_vars; + + if (mr) + { + free (mr->cvars); + mr->cvars = xmemdup (vars, n_vars * sizeof *vars); + mr->n_cvars = n_vars; + } } else if (lex_match_id (lexer, "PLOT")) { @@ -1206,16 +1123,12 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { if (lex_match_id (lexer, "COVARIANCE")) - { - factor.method = METHOD_COV; - } + factor.method = METHOD_COV; else if (lex_match_id (lexer, "CORRELATION")) - { - factor.method = METHOD_CORR; - } + factor.method = METHOD_CORR; else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "COVARIANCE", "CORRELATION"); goto error; } } @@ -1227,17 +1140,11 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) { /* VARIMAX and DEFAULT are defaults */ if (lex_match_id (lexer, "VARIMAX") || lex_match_id (lexer, "DEFAULT")) - { - factor.rotation = ROT_VARIMAX; - } + factor.rotation = ROT_VARIMAX; else if (lex_match_id (lexer, "EQUAMAX")) - { - factor.rotation = ROT_EQUAMAX; - } + factor.rotation = ROT_EQUAMAX; else if (lex_match_id (lexer, "QUARTIMAX")) - { - factor.rotation = ROT_QUARTIMAX; - } + factor.rotation = ROT_QUARTIMAX; else if (lex_match_id (lexer, "PROMAX")) { factor.promax_power = 5; @@ -1246,18 +1153,17 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) { factor.promax_power = lex_integer (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } factor.rotation = ROT_PROMAX; } else if (lex_match_id (lexer, "NOROTATE")) - { - factor.rotation = ROT_NONE; - } + factor.rotation = ROT_NONE; else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "DEFAULT", "VARIMAX", "EQUAMAX", + "QUARTIMAX", "PROMAX", "NOROTATE"); goto error; } } @@ -1270,34 +1176,34 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) { if (lex_match_id (lexer, "FACTORS")) { - if ( lex_force_match (lexer, T_LPAREN) - && lex_force_int (lexer)) + if (lex_force_match (lexer, T_LPAREN) + && lex_force_int (lexer)) { factor.n_factors = lex_integer (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } else if (lex_match_id (lexer, "MINEIGEN")) { - if ( lex_force_match (lexer, T_LPAREN) - && lex_force_num (lexer)) + if (lex_force_match (lexer, T_LPAREN) + && lex_force_num (lexer)) { factor.min_eigen = lex_number (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } else if (lex_match_id (lexer, "ECONVERGE")) { - if ( lex_force_match (lexer, T_LPAREN) - && lex_force_num (lexer)) + if (lex_force_match (lexer, T_LPAREN) + && lex_force_num (lexer)) { factor.econverge = lex_number (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } @@ -1308,18 +1214,18 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) { factor.rconverge = lex_number (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } else if (lex_match_id (lexer, "ITERATE")) { - if ( lex_force_match (lexer, T_LPAREN) - && lex_force_int (lexer)) + if (lex_force_match (lexer, T_LPAREN) + && lex_force_int_range (lexer, "ITERATE", 0, INT_MAX)) { n_iterations = lex_integer (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } @@ -1331,7 +1237,9 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) } else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "FACTORS", "MINEIGEN", + "ECONVERGE", "RCONVERGE", "ITERATE", + "DEFAULT"); goto error; } } @@ -1342,24 +1250,16 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { if (lex_match_id (lexer, "PAF")) - { - factor.extraction = EXTRACTION_PAF; - } + factor.extraction = EXTRACTION_PAF; else if (lex_match_id (lexer, "PC")) - { - factor.extraction = EXTRACTION_PC; - } + factor.extraction = EXTRACTION_PC; else if (lex_match_id (lexer, "PA1")) - { - factor.extraction = EXTRACTION_PC; - } + factor.extraction = EXTRACTION_PC; else if (lex_match_id (lexer, "DEFAULT")) - { - factor.extraction = EXTRACTION_PC; - } + factor.extraction = EXTRACTION_PC; else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "PAF", "PC", "PA1", "DEFAULT"); goto error; } } @@ -1371,17 +1271,15 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { if (lex_match_id (lexer, "SORT")) - { - factor.sort = true; - } + factor.sort = true; else if (lex_match_id (lexer, "BLANK")) { - if ( lex_force_match (lexer, T_LPAREN) - && lex_force_num (lexer)) + if (lex_force_match (lexer, T_LPAREN) + && lex_force_num (lexer)) { factor.blank = lex_number (lexer); lex_get (lexer); - if (! lex_force_match (lexer, T_RPAREN)) + if (!lex_force_match (lexer, T_RPAREN)) goto error; } } @@ -1392,7 +1290,7 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) } else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "SORT", "BLANK", "DEFAULT"); goto error; } } @@ -1404,50 +1302,30 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { if (lex_match_id (lexer, "UNIVARIATE")) - { - factor.print |= PRINT_UNIVARIATE; - } + factor.print |= PRINT_UNIVARIATE; else if (lex_match_id (lexer, "DET")) - { - factor.print |= PRINT_DETERMINANT; - } + factor.print |= PRINT_DETERMINANT; #if FACTOR_FULLY_IMPLEMENTED else if (lex_match_id (lexer, "INV")) { } #endif else if (lex_match_id (lexer, "AIC")) - { - factor.print |= PRINT_AIC; - } + factor.print |= PRINT_AIC; else if (lex_match_id (lexer, "SIG")) - { - factor.print |= PRINT_SIG; - } + factor.print |= PRINT_SIG; else if (lex_match_id (lexer, "CORRELATION")) - { - factor.print |= PRINT_CORRELATION; - } + factor.print |= PRINT_CORRELATION; else if (lex_match_id (lexer, "COVARIANCE")) - { - factor.print |= PRINT_COVARIANCE; - } + factor.print |= PRINT_COVARIANCE; else if (lex_match_id (lexer, "ROTATION")) - { - factor.print |= PRINT_ROTATION; - } + factor.print |= PRINT_ROTATION; else if (lex_match_id (lexer, "EXTRACTION")) - { - factor.print |= PRINT_EXTRACTION; - } + factor.print |= PRINT_EXTRACTION; else if (lex_match_id (lexer, "INITIAL")) - { - factor.print |= PRINT_INITIAL; - } + factor.print |= PRINT_INITIAL; else if (lex_match_id (lexer, "KMO")) - { - factor.print |= PRINT_KMO; - } + factor.print |= PRINT_KMO; #if FACTOR_FULLY_IMPLEMENTED else if (lex_match_id (lexer, "REPR")) { @@ -1457,18 +1335,19 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) } #endif else if (lex_match (lexer, T_ALL)) - { - factor.print = 0xFFFF; - } + factor.print = -1; else if (lex_match_id (lexer, "DEFAULT")) { - factor.print |= PRINT_INITIAL ; - factor.print |= PRINT_EXTRACTION ; - factor.print |= PRINT_ROTATION ; + factor.print |= PRINT_INITIAL; + factor.print |= PRINT_EXTRACTION; + factor.print |= PRINT_ROTATION; } else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "UNIVARIATE", "DET", "AIC", "SIG", + "CORRELATION", "COVARIANCE", "ROTATION", + "EXTRACTION", "INITIAL", "KMO", "ALL", + "DEFAULT"); goto error; } } @@ -1479,28 +1358,19 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { if (lex_match_id (lexer, "INCLUDE")) - { - factor.exclude = MV_SYSTEM; - } + factor.exclude = MV_SYSTEM; else if (lex_match_id (lexer, "EXCLUDE")) - { - factor.exclude = MV_ANY; - } + factor.exclude = MV_ANY; else if (lex_match_id (lexer, "LISTWISE")) - { - factor.missing_type = MISS_LISTWISE; - } + factor.missing_type = MISS_LISTWISE; else if (lex_match_id (lexer, "PAIRWISE")) - { - factor.missing_type = MISS_PAIRWISE; - } + factor.missing_type = MISS_PAIRWISE; else if (lex_match_id (lexer, "MEANSUB")) - { - factor.missing_type = MISS_MEANSUB; - } + factor.missing_type = MISS_MEANSUB; else { - lex_error (lexer, NULL); + lex_error_expecting (lexer, "INCLUDE", "EXCLUDE", "LISTWISE", + "PAIRRWISE", "MEANSUB"); goto error; } } @@ -1512,15 +1382,17 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) } } - if ( factor.rotation == ROT_NONE ) + if (factor.rotation == ROT_NONE) factor.print &= ~PRINT_ROTATION; if (factor.n_vars < 2) - msg (MW, _("Factor analysis on a single variable is not useful.")); + lex_ofs_msg (lexer, SW, vars_start, vars_end, + _("Factor analysis on a single variable is not useful.")); if (factor.n_vars < 1) { - msg (ME, _("Factor analysis without variables is not possible.")); + lex_ofs_error (lexer, vars_start, vars_end, + _("Factor analysis without variables is not possible.")); goto error; } @@ -1528,30 +1400,30 @@ cmd_factor (struct lexer *lexer, struct dataset *ds) { struct idata *id = idata_alloc (factor.n_vars); - while (next_matrix_from_reader (&id->mm, mr, - factor.vars, factor.n_vars)) + while (matrix_reader_next (&id->mm, mr, NULL)) { do_factor_by_matrix (&factor, id); - gsl_matrix_free (id->mm.corr); - id->mm.corr = NULL; - gsl_matrix_free (id->mm.cov); - id->mm.cov = NULL; + gsl_matrix_free (id->ai_cov); + id->ai_cov = NULL; + gsl_matrix_free (id->ai_cor); + id->ai_cor = NULL; + + matrix_material_uninit (&id->mm); } idata_free (id); } else - if ( ! run_factor (ds, &factor)) + if (!run_factor (ds, &factor)) goto error; - - destroy_matrix_reader (mr); + matrix_reader_destroy (mr); free (factor.vars); return CMD_SUCCESS; - error: - destroy_matrix_reader (mr); +error: + matrix_reader_destroy (mr); free (factor.vars); return CMD_FAILURE; } @@ -1570,7 +1442,7 @@ run_factor (struct dataset *ds, const struct cmd_factor *factor) while (casegrouper_get_next_group (grouper, &group)) { - if ( factor->missing_type == MISS_LISTWISE ) + if (factor->missing_type == MISS_LISTWISE) group = casereader_create_filter_missing (group, factor->vars, factor->n_vars, factor->exclude, NULL, NULL); @@ -1588,16 +1460,13 @@ run_factor (struct dataset *ds, const struct cmd_factor *factor) static double the_communality (const gsl_matrix *evec, const gsl_vector *eval, int n, int n_factors) { - size_t i; - - double comm = 0; - assert (n >= 0); assert (n < eval->size); assert (n < evec->size1); assert (n_factors <= eval->size); - for (i = 0 ; i < n_factors; ++i) + double comm = 0; + for (size_t i = 0; i < n_factors; ++i) { double evali = fabs (gsl_vector_get (eval, i)); @@ -1621,9 +1490,9 @@ static void show_scree (const struct cmd_factor *f, const struct idata *idata) { struct scree *s; - const char *label ; + const char *label; - if ( !(f->plot & PLOT_SCREE) ) + if (!(f->plot & PLOT_SCREE)) return; @@ -1638,162 +1507,101 @@ static void show_communalities (const struct cmd_factor * factor, const gsl_vector *initial, const gsl_vector *extracted) { - int i; - int c = 0; - const int heading_columns = 1; - int nc = heading_columns; - const int heading_rows = 1; - const int nr = heading_rows + factor->n_vars; - struct tab_table *t; - - if (factor->print & PRINT_EXTRACTION) - nc++; - - if (factor->print & PRINT_INITIAL) - nc++; - - /* No point having a table with only headings */ - if (nc <= 1) + if (!(factor->print & (PRINT_INITIAL | PRINT_EXTRACTION))) return; - t = tab_create (nc, nr); - - tab_title (t, _("Communalities")); + struct pivot_table *table = pivot_table_create (N_("Communalities")); - tab_headers (t, heading_columns, 0, heading_rows, 0); - - c = 1; + struct pivot_dimension *communalities = pivot_dimension_create ( + table, PIVOT_AXIS_COLUMN, N_("Communalities")); if (factor->print & PRINT_INITIAL) - tab_text (t, c++, 0, TAB_CENTER | TAT_TITLE, _("Initial")); - + pivot_category_create_leaves (communalities->root, N_("Initial")); if (factor->print & PRINT_EXTRACTION) - tab_text (t, c++, 0, TAB_CENTER | TAT_TITLE, _("Extraction")); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - - for (i = 0 ; i < factor->n_vars; ++i) + pivot_category_create_leaves (communalities->root, N_("Extraction")); + + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); + + for (size_t i = 0; i < factor->n_vars; ++i) { - c = 0; - tab_text (t, c++, i + heading_rows, TAT_TITLE, var_to_string (factor->vars[i])); + int row = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (factor->vars[i])); + int col = 0; if (factor->print & PRINT_INITIAL) - tab_double (t, c++, i + heading_rows, 0, gsl_vector_get (initial, i), NULL, RC_OTHER); - + pivot_table_put2 (table, col++, row, pivot_value_new_number ( + gsl_vector_get (initial, i))); if (factor->print & PRINT_EXTRACTION) - tab_double (t, c++, i + heading_rows, 0, gsl_vector_get (extracted, i), NULL, RC_OTHER); + pivot_table_put2 (table, col++, row, pivot_value_new_number ( + gsl_vector_get (extracted, i))); } - tab_submit (t); + pivot_table_submit (table); } +static struct pivot_dimension * +create_numeric_dimension (struct pivot_table *table, + enum pivot_axis_type axis_type, const char *name, + size_t n, bool show_label) +{ + struct pivot_dimension *d = pivot_dimension_create (table, axis_type, name); + d->root->show_label = show_label; + for (int i = 0; i < n; ++i) + pivot_category_create_leaf (d->root, pivot_value_new_integer (i + 1)); + return d; +} static void show_factor_matrix (const struct cmd_factor *factor, const struct idata *idata, const char *title, const gsl_matrix *fm) { - int i; + struct pivot_table *table = pivot_table_create (title); const int n_factors = idata->n_extractions; + create_numeric_dimension ( + table, PIVOT_AXIS_COLUMN, + factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"), + n_factors, true); - const int heading_columns = 1; - const int heading_rows = 2; - const int nr = heading_rows + factor->n_vars; - const int nc = heading_columns + n_factors; - gsl_permutation *perm; - - struct tab_table *t = tab_create (nc, nr); - - /* - if ( factor->extraction == EXTRACTION_PC ) - tab_title (t, _("Component Matrix")); - else - tab_title (t, _("Factor Matrix")); - */ - - tab_title (t, "%s", title); - - tab_headers (t, heading_columns, 0, heading_rows, 0); - - if ( factor->extraction == EXTRACTION_PC ) - tab_joint_text (t, - 1, 0, - nc - 1, 0, - TAB_CENTER | TAT_TITLE, _("Component")); - else - tab_joint_text (t, - 1, 0, - nc - 1, 0, - TAB_CENTER | TAT_TITLE, _("Factor")); - - - tab_hline (t, TAL_1, heading_columns, nc - 1, 1); - - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 1, - nc - 1, nr - 1); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); /* Initialise to the identity permutation */ - perm = gsl_permutation_calloc (factor->n_vars); + gsl_permutation *perm = gsl_permutation_calloc (factor->n_vars); - if ( factor->sort) + if (factor->sort) sort_matrix_indirect (fm, perm); - for (i = 0 ; i < n_factors; ++i) + for (size_t i = 0; i < factor->n_vars; ++i) { - tab_text_format (t, heading_columns + i, 1, TAB_CENTER | TAT_TITLE, _("%d"), i + 1); - } - - for (i = 0 ; i < factor->n_vars; ++i) - { - int j; const int matrix_row = perm->data[i]; - tab_text (t, 0, i + heading_rows, TAT_TITLE, var_to_string (factor->vars[matrix_row])); - for (j = 0 ; j < n_factors; ++j) + int var_idx = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (factor->vars[matrix_row])); + + for (size_t j = 0; j < n_factors; ++j) { double x = gsl_matrix_get (fm, matrix_row, j); - - if ( fabs (x) < factor->blank) + if (fabs (x) < factor->blank) continue; - tab_double (t, heading_columns + j, heading_rows + i, 0, x, NULL, RC_OTHER); + pivot_table_put2 (table, j, var_idx, pivot_value_new_number (x)); } } gsl_permutation_free (perm); - tab_submit (t); + pivot_table_submit (table); } +static void +put_variance (struct pivot_table *table, int row, int phase_idx, + double lambda, double percent, double cum) +{ + double entries[] = { lambda, percent, cum }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + pivot_table_put3 (table, i, phase_idx, row, + pivot_value_new_number (entries[i])); +} static void show_explained_variance (const struct cmd_factor * factor, @@ -1802,517 +1610,229 @@ show_explained_variance (const struct cmd_factor * factor, const gsl_vector *extracted_eigenvalues, const gsl_vector *rotated_loadings) { - size_t i; - int c = 0; - const int heading_columns = 1; - const int heading_rows = 2; - const int nr = heading_rows + factor->n_vars; - - struct tab_table *t ; - - double i_total = 0.0; - double i_cum = 0.0; - - double e_total = 0.0; - double e_cum = 0.0; - - double r_cum = 0.0; - - int nc = heading_columns; - - if (factor->print & PRINT_EXTRACTION) - nc += 3; - - if (factor->print & PRINT_INITIAL) - nc += 3; - - if (factor->print & PRINT_ROTATION) - { - nc += factor->rotation == ROT_PROMAX ? 1 : 3; - } - - /* No point having a table with only headings */ - if ( nc <= heading_columns) + if (!(factor->print & (PRINT_INITIAL | PRINT_EXTRACTION | PRINT_ROTATION))) return; - t = tab_create (nc, nr); - - tab_title (t, _("Total Variance Explained")); + struct pivot_table *table = pivot_table_create ( + N_("Total Variance Explained")); - tab_headers (t, heading_columns, 0, heading_rows, 0); + pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Total"), PIVOT_RC_OTHER, + /* xgettext:no-c-format */ + N_("% of Variance"), PIVOT_RC_PERCENT, + /* xgettext:no-c-format */ + N_("Cumulative %"), PIVOT_RC_PERCENT); - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - tab_hline (t, TAL_1, 1, nc - 1, 1); - - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - - - if ( factor->extraction == EXTRACTION_PC) - tab_text (t, 0, 1, TAB_LEFT | TAT_TITLE, _("Component")); - else - tab_text (t, 0, 1, TAB_LEFT | TAT_TITLE, _("Factor")); - - c = 1; + struct pivot_dimension *phase = pivot_dimension_create ( + table, PIVOT_AXIS_COLUMN, N_("Phase")); if (factor->print & PRINT_INITIAL) - { - tab_joint_text (t, c, 0, c + 2, 0, TAB_CENTER | TAT_TITLE, _("Initial Eigenvalues")); - c += 3; - } + pivot_category_create_leaves (phase->root, N_("Initial Eigenvalues")); if (factor->print & PRINT_EXTRACTION) - { - tab_joint_text (t, c, 0, c + 2, 0, TAB_CENTER | TAT_TITLE, _("Extraction Sums of Squared Loadings")); - c += 3; - } + pivot_category_create_leaves (phase->root, + N_("Extraction Sums of Squared Loadings")); if (factor->print & PRINT_ROTATION) - { - const int width = factor->rotation == ROT_PROMAX ? 0 : 2; - tab_joint_text (t, c, 0, c + width, 0, TAB_CENTER | TAT_TITLE, _("Rotation Sums of Squared Loadings")); - c += width + 1; - } + pivot_category_create_leaves (phase->root, + N_("Rotation Sums of Squared Loadings")); - for (i = 0; i < (nc - heading_columns + 2) / 3 ; ++i) - { - tab_text (t, i * 3 + 1, 1, TAB_CENTER | TAT_TITLE, _("Total")); - - tab_vline (t, TAL_2, heading_columns + i * 3, 0, nr - 1); - - if (i == 2 && factor->rotation == ROT_PROMAX) - continue; + struct pivot_dimension *components = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, + factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor")); - /* xgettext:no-c-format */ - tab_text (t, i * 3 + 2, 1, TAB_CENTER | TAT_TITLE, _("% of Variance")); - tab_text (t, i * 3 + 3, 1, TAB_CENTER | TAT_TITLE, _("Cumulative %")); - } - - for (i = 0 ; i < initial_eigenvalues->size; ++i) + double i_total = 0.0; + for (size_t i = 0; i < initial_eigenvalues->size; ++i) i_total += gsl_vector_get (initial_eigenvalues, i); - if ( factor->extraction == EXTRACTION_PAF) - { - e_total = factor->n_vars; - } - else - { - e_total = i_total; - } + double e_total = (factor->extraction == EXTRACTION_PAF + ? factor->n_vars + : i_total); - for (i = 0 ; i < factor->n_vars; ++i) + double i_cum = 0.0; + double e_cum = 0.0; + double r_cum = 0.0; + for (size_t i = 0; i < factor->n_vars; ++i) { const double i_lambda = gsl_vector_get (initial_eigenvalues, i); - double i_percent = 100.0 * i_lambda / i_total ; + double i_percent = 100.0 * i_lambda / i_total; + i_cum += i_percent; const double e_lambda = gsl_vector_get (extracted_eigenvalues, i); - double e_percent = 100.0 * e_lambda / e_total ; - - c = 0; + double e_percent = 100.0 * e_lambda / e_total; + e_cum += e_percent; - tab_text_format (t, c++, i + heading_rows, TAB_LEFT | TAT_TITLE, _("%zu"), i + 1); + int row = pivot_category_create_leaf ( + components->root, pivot_value_new_integer (i + 1)); - i_cum += i_percent; - e_cum += e_percent; + int phase_idx = 0; /* Initial Eigenvalues */ if (factor->print & PRINT_INITIAL) - { - tab_double (t, c++, i + heading_rows, 0, i_lambda, NULL, RC_OTHER); - tab_double (t, c++, i + heading_rows, 0, i_percent, NULL, RC_OTHER); - tab_double (t, c++, i + heading_rows, 0, i_cum, NULL, RC_OTHER); - } - - - if (factor->print & PRINT_EXTRACTION) - { - if (i < idata->n_extractions) - { - /* Sums of squared loadings */ - tab_double (t, c++, i + heading_rows, 0, e_lambda, NULL, RC_OTHER); - tab_double (t, c++, i + heading_rows, 0, e_percent, NULL, RC_OTHER); - tab_double (t, c++, i + heading_rows, 0, e_cum, NULL, RC_OTHER); - } - } + put_variance (table, row, phase_idx++, i_lambda, i_percent, i_cum); - if (rotated_loadings != NULL) + if (i < idata->n_extractions) { - const double r_lambda = gsl_vector_get (rotated_loadings, i); - double r_percent = 100.0 * r_lambda / e_total ; + if (factor->print & PRINT_EXTRACTION) + put_variance (table, row, phase_idx++, e_lambda, e_percent, e_cum); - if (factor->print & PRINT_ROTATION) + if (rotated_loadings != NULL && factor->print & PRINT_ROTATION) { - if (i < idata->n_extractions) - { - r_cum += r_percent; - tab_double (t, c++, i + heading_rows, 0, r_lambda, NULL, RC_OTHER); - if (factor->rotation != ROT_PROMAX) - { - tab_double (t, c++, i + heading_rows, 0, r_percent, NULL, RC_OTHER); - tab_double (t, c++, i + heading_rows, 0, r_cum, NULL, RC_OTHER); - } - } + double r_lambda = gsl_vector_get (rotated_loadings, i); + double r_percent = 100.0 * r_lambda / e_total; + if (factor->rotation == ROT_PROMAX) + r_lambda = r_percent = SYSMIS; + + r_cum += r_percent; + put_variance (table, row, phase_idx++, r_lambda, r_percent, + r_cum); } } } - tab_submit (t); + pivot_table_submit (table); } - static void show_factor_correlation (const struct cmd_factor * factor, const gsl_matrix *fcm) { - size_t i, j; - const int heading_columns = 1; - const int heading_rows = 1; - const int nr = heading_rows + fcm->size2; - const int nc = heading_columns + fcm->size1; - struct tab_table *t = tab_create (nc, nr); + struct pivot_table *table = pivot_table_create ( + N_("Factor Correlation Matrix")); - tab_title (t, _("Factor Correlation Matrix")); + create_numeric_dimension ( + table, PIVOT_AXIS_ROW, + factor->extraction == EXTRACTION_PC ? N_("Component") : N_("Factor"), + fcm->size2, true); - tab_headers (t, heading_columns, 0, heading_rows, 0); + create_numeric_dimension (table, PIVOT_AXIS_COLUMN, N_("Factor 2"), + fcm->size1, false); - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); + for (size_t i = 0; i < fcm->size1; ++i) + for (size_t j = 0; j < fcm->size2; ++j) + pivot_table_put2 (table, j, i, + pivot_value_new_number (gsl_matrix_get (fcm, i, j))); - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - tab_hline (t, TAL_1, 1, nc - 1, 1); - - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - - - if ( factor->extraction == EXTRACTION_PC) - tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Component")); - else - tab_text (t, 0, 0, TAB_LEFT | TAT_TITLE, _("Factor")); + pivot_table_submit (table); +} - for (i = 0 ; i < fcm->size1; ++i) +static void +add_var_dims (struct pivot_table *table, const struct cmd_factor *factor) +{ + for (int i = 0; i < 2; i++) { - tab_text_format (t, heading_columns + i, 0, TAB_CENTER | TAT_TITLE, _("%zu"), i + 1); - } + struct pivot_dimension *d = pivot_dimension_create ( + table, i ? PIVOT_AXIS_ROW : PIVOT_AXIS_COLUMN, + N_("Variables")); - for (i = 0 ; i < fcm->size2; ++i) - { - tab_text_format (t, 0, heading_rows + i, TAB_CENTER | TAT_TITLE, _("%zu"), i + 1); + for (size_t j = 0; j < factor->n_vars; j++) + pivot_category_create_leaf ( + d->root, pivot_value_new_variable (factor->vars[j])); } - - - for (i = 0 ; i < fcm->size1; ++i) - { - for (j = 0 ; j < fcm->size2; ++j) - tab_double (t, heading_columns + j, heading_rows + i, 0, - gsl_matrix_get (fcm, i, j), NULL, RC_OTHER); - } - - tab_submit (t); } static void show_aic (const struct cmd_factor *factor, const struct idata *idata) { - struct tab_table *t ; - size_t i; - - const int heading_rows = 1; - const int heading_columns = 2; - - const int nc = heading_columns + factor->n_vars; - const int nr = heading_rows + 2 * factor->n_vars; - if ((factor->print & PRINT_AIC) == 0) return; - t = tab_create (nc, nr); - - tab_title (t, _("Anti-Image Matrices")); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - - tab_headers (t, heading_columns, 0, heading_rows, 0); - - tab_vline (t, TAL_2, 2, 0, nr - 1); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - - for (i = 0; i < factor->n_vars; ++i) - tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i])); + struct pivot_table *table = pivot_table_create (N_("Anti-Image Matrices")); - tab_text (t, 0, heading_rows, TAT_TITLE, _("Anti-image Covariance")); - tab_hline (t, TAL_1, 0, nc - 1, heading_rows + factor->n_vars); - tab_text (t, 0, heading_rows + factor->n_vars, TAT_TITLE, _("Anti-image Correlation")); + add_var_dims (table, factor); - for (i = 0; i < factor->n_vars; ++i) - { - tab_text (t, 1, i + heading_rows, TAT_TITLE, - var_to_string (factor->vars[i])); - - tab_text (t, 1, factor->n_vars + i + heading_rows, TAT_TITLE, - var_to_string (factor->vars[i])); - } - - for (i = 0; i < factor->n_vars; ++i) - { - int j; - for (j = 0; j < factor->n_vars; ++j) - { - tab_double (t, heading_columns + i, heading_rows + j, 0, - gsl_matrix_get (idata->ai_cov, i, j), NULL, RC_OTHER); - } + pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Statistics"), + N_("Anti-image Covariance"), + N_("Anti-image Correlation")); + for (size_t i = 0; i < factor->n_vars; ++i) + for (size_t j = 0; j < factor->n_vars; ++j) + { + double cov = gsl_matrix_get (idata->ai_cov, i, j); + pivot_table_put3 (table, i, j, 0, pivot_value_new_number (cov)); - for (j = 0; j < factor->n_vars; ++j) - { - tab_double (t, heading_columns + i, factor->n_vars + heading_rows + j, 0, - gsl_matrix_get (idata->ai_cor, i, j), NULL, RC_OTHER); - } - } + double corr = gsl_matrix_get (idata->ai_cor, i, j); + pivot_table_put3 (table, i, j, 1, pivot_value_new_number (corr)); + } - tab_submit (t); + pivot_table_submit (table); } static void show_correlation_matrix (const struct cmd_factor *factor, const struct idata *idata) { - struct tab_table *t ; - size_t i, j; - int y_pos_corr = -1; - int y_pos_sig = -1; - int suffix_rows = 0; - - const int heading_rows = 1; - const int heading_columns = 2; - - int nc = heading_columns ; - int nr = heading_rows ; - int n_data_sets = 0; - - if (factor->print & PRINT_CORRELATION) - { - y_pos_corr = n_data_sets; - n_data_sets++; - nc = heading_columns + factor->n_vars; - } - - if (factor->print & PRINT_SIG) - { - y_pos_sig = n_data_sets; - n_data_sets++; - nc = heading_columns + factor->n_vars; - } - - nr += n_data_sets * factor->n_vars; - - if (factor->print & PRINT_DETERMINANT) - suffix_rows = 1; - - /* If the table would contain only headings, don't bother rendering it */ - if (nr <= heading_rows && suffix_rows == 0) + if (!(factor->print & (PRINT_CORRELATION | PRINT_SIG | PRINT_DETERMINANT))) return; - t = tab_create (nc, nr + suffix_rows); + struct pivot_table *table = pivot_table_create (N_("Correlation Matrix")); - tab_title (t, _("Correlation Matrix")); - - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - - if (nr > heading_rows) + if (factor->print & (PRINT_CORRELATION | PRINT_SIG)) { - tab_headers (t, heading_columns, 0, heading_rows, 0); - - tab_vline (t, TAL_2, 2, 0, nr - 1); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - - for (i = 0; i < factor->n_vars; ++i) - tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i])); - - - for (i = 0 ; i < n_data_sets; ++i) - { - int y = heading_rows + i * factor->n_vars; - size_t v; - for (v = 0; v < factor->n_vars; ++v) - tab_text (t, 1, y + v, TAT_TITLE, var_to_string (factor->vars[v])); - - tab_hline (t, TAL_1, 0, nc - 1, y); - } + add_var_dims (table, factor); + struct pivot_dimension *statistics = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Statistics")); if (factor->print & PRINT_CORRELATION) - { - const double y = heading_rows + y_pos_corr; - tab_text (t, 0, y, TAT_TITLE, _("Correlations")); - - for (i = 0; i < factor->n_vars; ++i) - { - for (j = 0; j < factor->n_vars; ++j) - tab_double (t, heading_columns + j, y + i, 0, gsl_matrix_get (idata->mm.corr, i, j), NULL, RC_OTHER); - } - } - + pivot_category_create_leaves (statistics->root, N_("Correlation"), + PIVOT_RC_CORRELATION); if (factor->print & PRINT_SIG) - { - const double y = heading_rows + y_pos_sig * factor->n_vars; - tab_text (t, 0, y, TAT_TITLE, _("Sig. (1-tailed)")); + pivot_category_create_leaves (statistics->root, N_("Sig. (1-tailed)"), + PIVOT_RC_SIGNIFICANCE); - for (i = 0; i < factor->n_vars; ++i) - { - for (j = 0; j < factor->n_vars; ++j) - { - double rho = gsl_matrix_get (idata->mm.corr, i, j); - double w = gsl_matrix_get (idata->mm.n, i, j); - - if (i == j) - continue; + int stat_idx = 0; + if (factor->print & PRINT_CORRELATION) + { + for (int i = 0; i < factor->n_vars; ++i) + for (int j = 0; j < factor->n_vars; ++j) + { + double corr = gsl_matrix_get (idata->mm.corr, i, j); + pivot_table_put3 (table, j, i, stat_idx, + pivot_value_new_number (corr)); + } + stat_idx++; + } - tab_double (t, heading_columns + j, y + i, 0, significance_of_correlation (rho, w), NULL, RC_PVALUE); - } - } - } + if (factor->print & PRINT_SIG) + { + for (int i = 0; i < factor->n_vars; ++i) + for (int j = 0; j < factor->n_vars; ++j) + if (i != j) + { + double rho = gsl_matrix_get (idata->mm.corr, i, j); + double w = gsl_matrix_get (idata->mm.n, i, j); + double sig = significance_of_correlation (rho, w); + pivot_table_put3 (table, j, i, stat_idx, + pivot_value_new_number (sig)); + } + stat_idx++; + } } if (factor->print & PRINT_DETERMINANT) { - tab_text (t, 0, nr, TAB_LEFT | TAT_TITLE, _("Determinant")); - - tab_double (t, 1, nr, 0, idata->detR, NULL, RC_OTHER); + struct pivot_value *caption = pivot_value_new_user_text_nocopy ( + xasprintf ("%s: %.2f", _("Determinant"), idata->detR)); + pivot_table_set_caption (table, caption); } - tab_submit (t); + pivot_table_submit (table); } static void show_covariance_matrix (const struct cmd_factor *factor, const struct idata *idata) { - struct tab_table *t ; - size_t i, j; - int y_pos_corr = -1; - int suffix_rows = 0; - - const int heading_rows = 1; - const int heading_columns = 1; - - int nc = heading_columns ; - int nr = heading_rows ; - int n_data_sets = 0; - - if (factor->print & PRINT_COVARIANCE) - { - y_pos_corr = n_data_sets; - n_data_sets++; - nc = heading_columns + factor->n_vars; - } - - nr += n_data_sets * factor->n_vars; - - /* If the table would contain only headings, don't bother rendering it */ - if (nr <= heading_rows && suffix_rows == 0) + if (!(factor->print & PRINT_COVARIANCE)) return; - t = tab_create (nc, nr + suffix_rows); - - tab_title (t, _("Covariance Matrix")); + struct pivot_table *table = pivot_table_create (N_("Covariance Matrix")); + add_var_dims (table, factor); - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - - if (nr > heading_rows) - { - tab_headers (t, heading_columns, 0, heading_rows, 0); - - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); - - - for (i = 0; i < factor->n_vars; ++i) - tab_text (t, heading_columns + i, 0, TAT_TITLE, var_to_string (factor->vars[i])); - - - for (i = 0 ; i < n_data_sets; ++i) - { - int y = heading_rows + i * factor->n_vars; - size_t v; - for (v = 0; v < factor->n_vars; ++v) - tab_text (t, heading_columns -1, y + v, TAT_TITLE, var_to_string (factor->vars[v])); - - tab_hline (t, TAL_1, 0, nc - 1, y); - } - - if (factor->print & PRINT_COVARIANCE) - { - const double y = heading_rows + y_pos_corr; - - for (i = 0; i < factor->n_vars; ++i) - { - for (j = 0; j < factor->n_vars; ++j) - tab_double (t, heading_columns + j, y + i, 0, gsl_matrix_get (idata->mm.cov, i, j), NULL, RC_OTHER); - } - } - } + for (int i = 0; i < factor->n_vars; ++i) + for (int j = 0; j < factor->n_vars; ++j) + { + double cov = gsl_matrix_get (idata->mm.cov, i, j); + pivot_table_put2 (table, j, i, pivot_value_new_number (cov)); + } - tab_submit (t); + pivot_table_submit (table); } @@ -2325,7 +1845,7 @@ do_factor (const struct cmd_factor *factor, struct casereader *r) idata->cvm = covariance_1pass_create (factor->n_vars, factor->vars, factor->wv, factor->exclude, true); - for ( ; (c = casereader_read (r) ); case_unref (c)) + for (; (c = casereader_read (r)); case_unref (c)) { covariance_accumulate (idata->cvm, c); } @@ -2356,9 +1876,10 @@ do_factor (const struct cmd_factor *factor, struct casereader *r) static void do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) { - if (!idata->mm.cov && !idata->mm.corr) + if (!idata->mm.cov && !(idata->mm.corr && idata->mm.var_matrix)) { - msg (ME, _("The dataset has no complete covariance or correlation matrix.")); + msg (ME, _("The dataset has no covariance matrix or a " + "correlation matrix along with standard deviations.")); return; } @@ -2379,10 +1900,9 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) idata->ai_cov = anti_image_cov (r_inv); idata->ai_cor = anti_image_corr (r_inv, idata); - int i; double sum_ssq_r = 0; double sum_ssq_a = 0; - for (i = 0; i < r_inv->size1; ++i) + for (int i = 0; i < r_inv->size1; ++i) { sum_ssq_r += ssq_od_n (idata->mm.corr, i); sum_ssq_a += ssq_od_n (idata->ai_cor, i); @@ -2406,118 +1926,76 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) gsl_matrix_free (tmp); } - if ( factor->print & PRINT_UNIVARIATE) + if (factor->print & PRINT_UNIVARIATE + && idata->mm.n && idata->mm.mean_matrix && idata->mm.var_matrix) { - const struct fmt_spec *wfmt = factor->wv ? var_get_print_format (factor->wv) : & F_8_0; - const int nc = 4; - int i; - - const int heading_columns = 1; - const int heading_rows = 1; - - const int nr = heading_rows + factor->n_vars; - - struct tab_table *t = tab_create (nc, nr); - tab_set_format (t, RC_WEIGHT, wfmt); - tab_title (t, _("Descriptive Statistics")); - - tab_headers (t, heading_columns, 0, heading_rows, 0); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); + struct pivot_table *table = pivot_table_create ( + N_("Descriptive Statistics")); + pivot_table_set_weight_var (table, factor->wv); - /* Vertical lines */ - tab_box (t, - -1, -1, - -1, TAL_1, - heading_columns, 0, - nc - 1, nr - 1); + pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Mean"), PIVOT_RC_OTHER, + N_("Std. Deviation"), PIVOT_RC_OTHER, + N_("Analysis N"), PIVOT_RC_COUNT); - tab_hline (t, TAL_1, 0, nc - 1, heading_rows); - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); - tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Mean")); - tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation")); - tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Analysis N")); - - for (i = 0 ; i < factor->n_vars; ++i) + for (size_t i = 0; i < factor->n_vars; ++i) { const struct variable *v = factor->vars[i]; - tab_text (t, 0, i + heading_rows, TAB_LEFT | TAT_TITLE, var_to_string (v)); - tab_double (t, 1, i + heading_rows, 0, gsl_matrix_get (idata->mm.mean_matrix, i, i), NULL, RC_OTHER); - tab_double (t, 2, i + heading_rows, 0, sqrt (gsl_matrix_get (idata->mm.var_matrix, i, i)), NULL, RC_OTHER); - tab_double (t, 3, i + heading_rows, 0, gsl_matrix_get (idata->mm.n, i, i), NULL, RC_WEIGHT); + int row = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (v)); + + double entries[] = { + gsl_matrix_get (idata->mm.mean_matrix, i, i), + sqrt (gsl_matrix_get (idata->mm.var_matrix, i, i)), + gsl_matrix_get (idata->mm.n, i, i), + }; + for (size_t j = 0; j < sizeof entries / sizeof *entries; j++) + pivot_table_put2 (table, j, row, + pivot_value_new_number (entries[j])); } - tab_submit (t); + pivot_table_submit (table); } - if (factor->print & PRINT_KMO) + if (factor->print & PRINT_KMO && idata->mm.n) { - int i; - double df = factor->n_vars * (factor->n_vars - 1) / 2; - - double w = 0; - - - double xsq; - - const int heading_columns = 2; - const int heading_rows = 0; - - const int nr = heading_rows + 4; - const int nc = heading_columns + 1; - - - - struct tab_table *t = tab_create (nc, nr); - tab_title (t, _("KMO and Bartlett's Test")); - - - tab_headers (t, heading_columns, 0, heading_rows, 0); - - /* Outline the box */ - tab_box (t, - TAL_2, TAL_2, - -1, -1, - 0, 0, - nc - 1, nr - 1); - - tab_vline (t, TAL_2, heading_columns, 0, nr - 1); - - tab_text (t, 0, 0, TAT_TITLE | TAB_LEFT, _("Kaiser-Meyer-Olkin Measure of Sampling Adequacy")); - - tab_double (t, 2, 0, 0, sum_ssq_r / (sum_ssq_r + sum_ssq_a), NULL, RC_OTHER); - - tab_text (t, 0, 1, TAT_TITLE | TAB_LEFT, _("Bartlett's Test of Sphericity")); - - tab_text (t, 1, 1, TAT_TITLE, _("Approx. Chi-Square")); - tab_text (t, 1, 2, TAT_TITLE, _("df")); - tab_text (t, 1, 3, TAT_TITLE, _("Sig.")); - + struct pivot_table *table = pivot_table_create ( + N_("KMO and Bartlett's Test")); + + struct pivot_dimension *statistics = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Statistics"), + N_("Kaiser-Meyer-Olkin Measure of Sampling Adequacy"), PIVOT_RC_OTHER); + pivot_category_create_group ( + statistics->root, N_("Bartlett's Test of Sphericity"), + N_("Approx. Chi-Square"), PIVOT_RC_OTHER, + N_("df"), PIVOT_RC_INTEGER, + N_("Sig."), PIVOT_RC_SIGNIFICANCE); /* The literature doesn't say what to do for the value of W when missing values are involved. The best thing I can think of is to take the mean average. */ - w = 0; - for (i = 0; i < idata->mm.n->size1; ++i) + double w = 0; + for (int i = 0; i < idata->mm.n->size1; ++i) w += gsl_matrix_get (idata->mm.n, i, i); w /= idata->mm.n->size1; - xsq = w - 1 - (2 * factor->n_vars + 5) / 6.0; - xsq *= -log (idata->detR); - - tab_double (t, 2, 1, 0, xsq, NULL, RC_OTHER); - tab_double (t, 2, 2, 0, df, NULL, RC_INTEGER); - tab_double (t, 2, 3, 0, gsl_cdf_chisq_Q (xsq, df), NULL, RC_PVALUE); - - - tab_submit (t); + double xsq = ((w - 1 - (2 * factor->n_vars + 5) / 6.0) + * -log (idata->detR)); + double df = factor->n_vars * (factor->n_vars - 1) / 2; + double entries[] = { + sum_ssq_r / (sum_ssq_r + sum_ssq_a), + xsq, + df, + gsl_cdf_chisq_Q (xsq, df) + }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + pivot_table_put1 (table, i, pivot_value_new_number (entries[i])); + + pivot_table_submit (table); } show_correlation_matrix (factor, idata); @@ -2562,16 +2040,15 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) const gsl_vector *extracted_eigenvalues = NULL; gsl_vector *initial_communalities = gsl_vector_alloc (factor->n_vars); gsl_vector *extracted_communalities = gsl_vector_alloc (factor->n_vars); - size_t i; struct factor_matrix_workspace *fmw = factor_matrix_workspace_alloc (idata->msr->size, idata->n_extractions); gsl_matrix *factor_matrix = gsl_matrix_calloc (factor->n_vars, fmw->n_factors); - if ( factor->extraction == EXTRACTION_PAF) + if (factor->extraction == EXTRACTION_PAF) { gsl_vector *diff = gsl_vector_alloc (idata->msr->size); struct smr_workspace *ws = ws_create (idata->analysis_matrix); - for (i = 0 ; i < factor->n_vars ; ++i) + for (size_t i = 0; i < factor->n_vars; ++i) { double r2 = squared_multiple_correlation (idata->analysis_matrix, i, ws); @@ -2581,7 +2058,7 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) gsl_vector_memcpy (initial_communalities, idata->msr); - for (i = 0; i < factor->extraction_iterations; ++i) + for (size_t i = 0; i < factor->extraction_iterations; ++i) { double min, max; gsl_vector_memcpy (diff, idata->msr); @@ -2592,7 +2069,7 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) gsl_vector_minmax (diff, &min, &max); - if ( fabs (min) < factor->econverge && fabs (max) < factor->econverge) + if (fabs (min) < factor->econverge && fabs (max) < factor->econverge) break; } gsl_vector_free (diff); @@ -2604,7 +2081,7 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) } else if (factor->extraction == EXTRACTION_PC) { - for (i = 0; i < factor->n_vars; ++i) + for (size_t i = 0; i < factor->n_vars; ++i) gsl_vector_set (initial_communalities, i, communality (idata, i, factor->n_vars)); gsl_vector_memcpy (extracted_communalities, initial_communalities); @@ -2619,7 +2096,7 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) show_aic (factor, idata); show_communalities (factor, initial_communalities, extracted_communalities); - if ( factor->rotation != ROT_NONE) + if (factor->rotation != ROT_NONE) { rotated_factors = gsl_matrix_calloc (factor_matrix->size1, factor_matrix->size2); rotated_loadings = gsl_vector_calloc (factor_matrix->size2); @@ -2640,27 +2117,31 @@ do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata) show_scree (factor, idata); show_factor_matrix (factor, idata, - factor->extraction == EXTRACTION_PC ? _("Component Matrix") : _("Factor Matrix"), + (factor->extraction == EXTRACTION_PC + ? N_("Component Matrix") : N_("Factor Matrix")), factor_matrix); - if ( factor->rotation == ROT_PROMAX) + if (factor->rotation == ROT_PROMAX) { - show_factor_matrix (factor, idata, _("Pattern Matrix"), pattern_matrix); + show_factor_matrix (factor, idata, N_("Pattern Matrix"), + pattern_matrix); gsl_matrix_free (pattern_matrix); } - if ( factor->rotation != ROT_NONE) + if (factor->rotation != ROT_NONE) { show_factor_matrix (factor, idata, - (factor->rotation == ROT_PROMAX) ? _("Structure Matrix") : - (factor->extraction == EXTRACTION_PC ? _("Rotated Component Matrix") : - _("Rotated Factor Matrix")), + (factor->rotation == ROT_PROMAX + ? N_("Structure Matrix") + : factor->extraction == EXTRACTION_PC + ? N_("Rotated Component Matrix") + : N_("Rotated Factor Matrix")), rotated_factors); gsl_matrix_free (rotated_factors); } - if ( factor->rotation == ROT_PROMAX) + if (factor->rotation == ROT_PROMAX) { show_factor_correlation (factor, fcm); gsl_matrix_free (fcm);