/************************************************************************* * Copyright (c) 2011 AT&T Intellectual Property * All rights reserved. This program and the accompanying materials * are made available under the terms of the Eclipse Public License v1.0 * which accompanies this distribution, and is available at * https://www.eclipse.org/legal/epl-v10.html * * Contributors: Details at https://graphviz.org *************************************************************************/ #include #include #include #include #include #include #include #include static int num_pairs = 4; void PCA_alloc(DistType ** coords, int dim, int n, double **new_coords, int new_dim) { double sum; int i, j, k; double **eigs = gv_calloc(new_dim, sizeof(double *)); for (i = 0; i < new_dim; i++) eigs[i] = gv_calloc(dim, sizeof(double)); double *evals = gv_calloc(new_dim, sizeof(double)); double **DD = gv_calloc(dim, sizeof(double *)); // dim×dim matrix: coords×coordsᵀ double *storage_ptr = gv_calloc(dim * dim, sizeof(double)); for (i = 0; i < dim; i++) { DD[i] = storage_ptr; storage_ptr += dim; } for (i = 0; i < dim; i++) { for (j = 0; j <= i; j++) { /* compute coords[i]*coords[j] */ sum = 0; for (k = 0; k < n; k++) { sum += coords[i][k] * coords[j][k]; } DD[i][j] = DD[j][i] = sum; } } power_iteration(DD, dim, new_dim, eigs, evals); for (j = 0; j < new_dim; j++) { for (i = 0; i < n; i++) { sum = 0; for (k = 0; k < dim; k++) { sum += coords[k][i] * eigs[j][k]; } new_coords[j][i] = sum; } } for (i = 0; i < new_dim; i++) free(eigs[i]); free(eigs); free(evals); free(DD[0]); free(DD); } bool iterativePCA_1D(double **coords, int dim, int n, double *new_direction) { vtx_data *laplacian; float **mat1 = NULL; double **mat = NULL; double eval; /* Given that first projection of 'coords' is 'coords[0]' compute another projection direction 'new_direction' that scatters points that are close in 'coords[0]' */ /* find the nodes that were close in 'coords[0]' */ /* and construct appropriate Laplacian */ closest_pairs2graph(coords[0], n, num_pairs * n, &laplacian); /* Compute coords*Lap*coords^T */ mult_sparse_dense_mat_transpose(laplacian, coords, n, dim, &mat1); mult_dense_mat_d(coords, mat1, dim, n, dim, &mat); free(mat1[0]); free(mat1); /* Compute direction */ return power_iteration(mat, dim, 1, &new_direction, &eval); /* ?? When is mat freed? */ }