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Diffstat (limited to 'source/blender/blenlib/intern/math_statistics.c')
| -rw-r--r-- | source/blender/blenlib/intern/math_statistics.c | 116 |
1 files changed, 116 insertions, 0 deletions
diff --git a/source/blender/blenlib/intern/math_statistics.c b/source/blender/blenlib/intern/math_statistics.c new file mode 100644 index 00000000000..a8cb8e2c40d --- /dev/null +++ b/source/blender/blenlib/intern/math_statistics.c @@ -0,0 +1,116 @@ +/* + * ***** BEGIN GPL LICENSE BLOCK ***** + * + * This program is free software; you can redistribute it and/or + * modify it under the terms of the GNU General Public License + * as published by the Free Software Foundation; either version 2 + * of the License, or (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program; if not, write to the Free Software Foundation, + * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. + * + * The Original Code is Copyright (C) 2015 by Blender Foundation. + * All rights reserved. + * + * The Original Code is: all of this file. + * + * ***** END GPL LICENSE BLOCK ***** + * */ + +/** \file blender/blenlib/intern/math_statistics.c + * \ingroup bli + */ + +#include "MEM_guardedalloc.h" + +#include "BLI_math.h" +#include "BLI_utildefines.h" + +#include "BLI_strict_flags.h" + +/********************************** Covariance Matrices *********************************/ + +/** + * \brief Compute the covariance matrix of given set of nD coordinates. + * + * \param n the dimension of the vectors (and hence, of the covariance matrix to compute). + * \param cos_vn the nD points to compute covariance from. + * \param nbr_cos_vn the number of nD coordinates in cos_vn. + * \param center the center (or mean point) of cos_vn. If NULL, it is assumed cos_vn is already centered. + * \param use_sample_correction whether to apply sample correction + * (i.e. get 'sample varince' instead of 'population variance'). + * \return r_covmat the computed covariance matrix. + */ +void BLI_covariance_m_vn_ex( + const int n, const float *cos_vn, const int nbr_cos_vn, const float *center, const bool use_sample_correction, + float *r_covmat) +{ + int i, j, k; + + /* Note about that division: see https://en.wikipedia.org/wiki/Bessel%27s_correction. + * In a nutshell, it must be 1 / (n - 1) for 'sample data', and 1 / n for 'population data'... + */ + const float covfac = 1.0f / (float)(use_sample_correction ? nbr_cos_vn - 1 : nbr_cos_vn); + + memset(r_covmat, 0, sizeof(*r_covmat) * (size_t)(n * n)); + +#pragma omp parallel for default(shared) private(i, j, k) schedule(static) if ((nbr_cos_vn * n) >= 10000) + for (i = 0; i < n; i++) { + for (j = i; j < n; j++) { + r_covmat[i * n + j] = 0.0f; + if (center) { + for (k = 0; k < nbr_cos_vn; k++) { + r_covmat[i * n + j] += (cos_vn[k * n + i] - center[i]) * (cos_vn[k * n + j] - center[j]); + } + } + else { + for (k = 0; k < nbr_cos_vn; k++) { + r_covmat[i * n + j] += cos_vn[k * n + i] * cos_vn[k * n + j]; + } + } + r_covmat[i * n + j] *= covfac; + } + } + /* Covariance matrices are always symetrical, so we can compute only one half of it (as done above), + * and copy it to the other half! */ + for (i = 1; i < n; i++) { + for (j = 0; j < i; j++) { + r_covmat[i * n + j] = r_covmat[j * n + i]; + } + } +} + +/** + * \brief Compute the covariance matrix of given set of 3D coordinates. + * + * \param cos_v3 the 3D points to compute covariance from. + * \param nbr_cos_v3 the number of 3D coordinates in cos_v3. + * \return r_covmat the computed covariance matrix. + * \return r_center the computed center (mean) of 3D points (may be NULL). + */ +void BLI_covariance_m3_v3n( + const float (*cos_v3)[3], const int nbr_cos_v3, const bool use_sample_correction, + float r_covmat[3][3], float r_center[3]) +{ + float center[3]; + const float mean_fac = 1.0f / (float)nbr_cos_v3; + int i; + + zero_v3(center); + for (i = 0; i < nbr_cos_v3; i++) { + /* Applying mean_fac here rather than once at the end reduce compute errors... */ + madd_v3_v3fl(center, cos_v3[i], mean_fac); + } + + if (r_center) { + copy_v3_v3(r_center, center); + } + + BLI_covariance_m_vn_ex(3, (const float *)cos_v3, nbr_cos_v3, center, use_sample_correction, (float *)r_covmat); +} |