1147 lines
39 KiB
C
1147 lines
39 KiB
C
/*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 2
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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*/
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/** \file
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* \ingroup mathutils
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*
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* This file defines the 'noise' module, a general purpose module to access
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* blenders noise functions.
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*/
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/************************/
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/* Blender Noise Module */
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/************************/
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#include <Python.h>
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#include "BLI_math.h"
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#include "BLI_noise.h"
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#include "BLI_utildefines.h"
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#include "DNA_texture_types.h"
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#include "../generic/py_capi_utils.h"
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#include "mathutils.h"
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#include "mathutils_noise.h"
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/*-----------------------------------------*/
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/* 'mersenne twister' random number generator */
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/*
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* A C-program for MT19937, with initialization improved 2002/2/10.
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* Coded by Takuji Nishimura and Makoto Matsumoto.
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* This is a faster version by taking Shawn Cokus's optimization,
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* Matthe Bellew's simplification, Isaku Wada's real version.
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*
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* Before using, initialize the state by using init_genrand(seed)
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* or init_by_array(init_key, key_length).
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*
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* Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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*
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* 3. The names of its contributors may not be used to endorse or promote
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* products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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* LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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* NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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* Any feedback is very welcome.
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* http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
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* email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
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*/
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/* Period parameters */
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#define N 624
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#define M 397
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#define MATRIX_A 0x9908b0dfUL /* constant vector a */
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#define UMASK 0x80000000UL /* most significant w-r bits */
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#define LMASK 0x7fffffffUL /* least significant r bits */
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#define MIXBITS(u, v) (((u)&UMASK) | ((v)&LMASK))
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#define TWIST(u, v) ((MIXBITS(u, v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL))
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static ulong state[N]; /* the array for the state vector */
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static int left = 1;
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static int initf = 0;
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static ulong *next;
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static float state_offset_vector[3 * 3];
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/* initializes state[N] with a seed */
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static void init_genrand(ulong s)
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{
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int j;
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state[0] = s & 0xffffffffUL;
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for (j = 1; j < N; j++) {
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state[j] = (1812433253UL * (state[j - 1] ^ (state[j - 1] >> 30)) + j);
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/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
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/* In the previous versions, MSBs of the seed affect */
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/* only MSBs of the array state[]. */
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/* 2002/01/09 modified by Makoto Matsumoto */
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state[j] &= 0xffffffffUL; /* for >32 bit machines */
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}
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left = 1;
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initf = 1;
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/* update vector offset */
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{
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const ulong *state_offset = &state[N - ARRAY_SIZE(state_offset_vector)];
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const float range = 32; /* range in both pos/neg direction */
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for (j = 0; j < ARRAY_SIZE(state_offset_vector); j++, state_offset++) {
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/* overflow is fine here */
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state_offset_vector[j] = (float)(int)(*state_offset) * (1.0f / ((float)INT_MAX / range));
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}
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}
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}
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static void next_state(void)
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{
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ulong *p = state;
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int j;
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/* if init_genrand() has not been called, */
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/* a default initial seed is used */
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if (initf == 0) {
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init_genrand(5489UL);
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}
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left = N;
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next = state;
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for (j = N - M + 1; j--; p++) {
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*p = p[M] ^ TWIST(p[0], p[1]);
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}
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for (j = M; j--; p++) {
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*p = p[M - N] ^ TWIST(p[0], p[1]);
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}
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*p = p[M - N] ^ TWIST(p[0], state[0]);
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}
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/*------------------------------------------------------------*/
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static void setRndSeed(int seed)
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{
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if (seed == 0) {
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init_genrand(time(NULL));
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}
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else {
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init_genrand(seed);
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}
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}
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/* float number in range [0, 1) using the mersenne twister rng */
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static float frand(void)
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{
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ulong y;
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if (--left == 0) {
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next_state();
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}
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y = *next++;
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/* Tempering */
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y ^= (y >> 11);
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y ^= (y << 7) & 0x9d2c5680UL;
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y ^= (y << 15) & 0xefc60000UL;
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y ^= (y >> 18);
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return (float)y / 4294967296.f;
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}
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/*------------------------------------------------------------*/
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/* Utility Functions */
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/*------------------------------------------------------------*/
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#define BPY_NOISE_BASIS_ENUM_DOC \
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" :arg noise_basis: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', " \
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"'VORONOI_F1', 'VORONOI_F2', " \
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"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
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"'CELLNOISE'].\n" \
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" :type noise_basis: string\n"
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#define BPY_NOISE_METRIC_ENUM_DOC \
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" :arg distance_metric: Enumerator in ['DISTANCE', 'DISTANCE_SQUARED', 'MANHATTAN', " \
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"'CHEBYCHEV', " \
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"'MINKOVSKY', 'MINKOVSKY_HALF', 'MINKOVSKY_FOUR'].\n" \
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" :type distance_metric: string\n"
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/* Noise basis enum */
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#define DEFAULT_NOISE_TYPE TEX_STDPERLIN
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static PyC_FlagSet bpy_noise_types[] = {
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{TEX_BLENDER, "BLENDER"},
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{TEX_STDPERLIN, "PERLIN_ORIGINAL"},
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{TEX_NEWPERLIN, "PERLIN_NEW"},
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{TEX_VORONOI_F1, "VORONOI_F1"},
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{TEX_VORONOI_F2, "VORONOI_F2"},
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{TEX_VORONOI_F3, "VORONOI_F3"},
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{TEX_VORONOI_F4, "VORONOI_F4"},
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{TEX_VORONOI_F2F1, "VORONOI_F2F1"},
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{TEX_VORONOI_CRACKLE, "VORONOI_CRACKLE"},
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{TEX_CELLNOISE, "CELLNOISE"},
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{0, NULL},
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};
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/* Metric basis enum */
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#define DEFAULT_METRIC_TYPE TEX_DISTANCE
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static PyC_FlagSet bpy_noise_metrics[] = {
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{TEX_DISTANCE, "DISTANCE"},
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{TEX_DISTANCE_SQUARED, "DISTANCE_SQUARED"},
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{TEX_MANHATTAN, "MANHATTAN"},
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{TEX_CHEBYCHEV, "CHEBYCHEV"},
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{TEX_MINKOVSKY, "MINKOVSKY"},
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{TEX_MINKOVSKY_HALF, "MINKOVSKY_HALF"},
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{TEX_MINKOVSKY_FOUR, "MINKOVSKY_FOUR"},
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{0, NULL},
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};
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/* Fills an array of length size with random numbers in the range (-1, 1)*/
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static void rand_vn(float *array_tar, const int size)
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{
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float *array_pt = array_tar + (size - 1);
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int i = size;
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while (i--) {
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*(array_pt--) = 2.0f * frand() - 1.0f;
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}
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}
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/* Fills an array of length 3 with noise values */
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static void noise_vector(float x, float y, float z, int nb, float v[3])
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{
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/* Simply evaluate noise at 3 different positions */
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const float *ofs = state_offset_vector;
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for (int j = 0; j < 3; j++) {
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v[j] = (2.0f * BLI_gNoise(1.0f, x + ofs[0], y + ofs[1], z + ofs[2], 0, nb) - 1.0f);
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ofs += 3;
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}
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}
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/* Returns a turbulence value for a given position (x, y, z) */
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static float turb(
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float x, float y, float z, int oct, int hard, int nb, float ampscale, float freqscale)
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{
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float amp, out, t;
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int i;
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amp = 1.f;
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out = (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f);
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if (hard) {
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out = fabsf(out);
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}
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for (i = 1; i < oct; i++) {
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amp *= ampscale;
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x *= freqscale;
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y *= freqscale;
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z *= freqscale;
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t = (float)(amp * (2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f));
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if (hard) {
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t = fabsf(t);
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}
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out += t;
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}
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return out;
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}
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/* Fills an array of length 3 with the turbulence vector for a given
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* position (x, y, z) */
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static void vTurb(float x,
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float y,
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float z,
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int oct,
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int hard,
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int nb,
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float ampscale,
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float freqscale,
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float v[3])
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{
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float amp, t[3];
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int i;
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amp = 1.f;
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noise_vector(x, y, z, nb, v);
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if (hard) {
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v[0] = fabsf(v[0]);
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v[1] = fabsf(v[1]);
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v[2] = fabsf(v[2]);
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}
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for (i = 1; i < oct; i++) {
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amp *= ampscale;
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x *= freqscale;
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y *= freqscale;
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z *= freqscale;
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noise_vector(x, y, z, nb, t);
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if (hard) {
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t[0] = fabsf(t[0]);
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t[1] = fabsf(t[1]);
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t[2] = fabsf(t[2]);
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}
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v[0] += amp * t[0];
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v[1] += amp * t[1];
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v[2] += amp * t[2];
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}
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}
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/*-------------------------DOC STRINGS ---------------------------*/
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PyDoc_STRVAR(M_Noise_doc, "The Blender noise module");
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/*------------------------------------------------------------*/
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/* Python Functions */
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/*------------------------------------------------------------*/
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PyDoc_STRVAR(M_Noise_random_doc,
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".. function:: random()\n"
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"\n"
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" Returns a random number in the range [0, 1).\n"
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"\n"
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" :return: The random number.\n"
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" :rtype: float\n");
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static PyObject *M_Noise_random(PyObject *UNUSED(self))
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{
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return PyFloat_FromDouble(frand());
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}
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PyDoc_STRVAR(M_Noise_random_unit_vector_doc,
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".. function:: random_unit_vector(size=3)\n"
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"\n"
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" Returns a unit vector with random entries.\n"
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"\n"
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" :arg size: The size of the vector to be produced, in the range [2, 4].\n"
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" :type size: int\n"
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" :return: The random unit vector.\n"
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" :rtype: :class:`mathutils.Vector`\n");
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static PyObject *M_Noise_random_unit_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
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{
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static const char *kwlist[] = {"size", NULL};
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float vec[4] = {0.0f, 0.0f, 0.0f, 0.0f};
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float norm = 2.0f;
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int size = 3;
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if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_unit_vector", (char **)kwlist, &size)) {
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return NULL;
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}
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if (size > 4 || size < 2) {
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PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
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return NULL;
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}
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while (norm == 0.0f || norm > 1.0f) {
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rand_vn(vec, size);
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norm = normalize_vn(vec, size);
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}
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return Vector_CreatePyObject(vec, size, NULL);
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}
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PyDoc_STRVAR(M_Noise_random_vector_doc,
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".. function:: random_vector(size=3)\n"
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"\n"
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" Returns a vector with random entries in the range (-1, 1).\n"
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"\n"
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" :arg size: The size of the vector to be produced.\n"
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" :type size: int\n"
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" :return: The random vector.\n"
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" :rtype: :class:`mathutils.Vector`\n");
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static PyObject *M_Noise_random_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
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{
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static const char *kwlist[] = {"size", NULL};
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float *vec = NULL;
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int size = 3;
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if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_vector", (char **)kwlist, &size)) {
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return NULL;
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}
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if (size < 2) {
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PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
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return NULL;
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}
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vec = PyMem_New(float, size);
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rand_vn(vec, size);
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return Vector_CreatePyObject_alloc(vec, size, NULL);
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}
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PyDoc_STRVAR(M_Noise_seed_set_doc,
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".. function:: seed_set(seed)\n"
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"\n"
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" Sets the random seed used for random_unit_vector, and random.\n"
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"\n"
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" :arg seed: Seed used for the random generator.\n"
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" When seed is zero, the current time will be used instead.\n"
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" :type seed: int\n");
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static PyObject *M_Noise_seed_set(PyObject *UNUSED(self), PyObject *args)
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{
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int s;
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if (!PyArg_ParseTuple(args, "i:seed_set", &s)) {
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return NULL;
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}
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setRndSeed(s);
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Py_RETURN_NONE;
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}
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PyDoc_STRVAR(M_Noise_noise_doc,
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|
".. function:: noise(position, noise_basis='PERLIN_ORIGINAL')\n"
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"\n"
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|
" Returns noise value from the noise basis at the position specified.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The noise value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_noise(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
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{
|
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static const char *kwlist[] = {"", "noise_basis", NULL};
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|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
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int noise_basis_enum = DEFAULT_NOISE_TYPE;
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|
|
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if (!PyArg_ParseTupleAndKeywords(
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args, kw, "O|$s:noise", (char **)kwlist, &value, &noise_basis_str)) {
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return NULL;
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}
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|
|
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if (!noise_basis_str) {
|
|
/* pass through */
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|
}
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else if (PyC_FlagSet_ValueFromID(bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise") ==
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-1) {
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return NULL;
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}
|
|
|
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if (mathutils_array_parse(vec, 3, 3, value, "noise: invalid 'position' arg") == -1) {
|
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return NULL;
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|
}
|
|
|
|
return PyFloat_FromDouble(
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(2.0f * BLI_gNoise(1.0f, vec[0], vec[1], vec[2], 0, noise_basis_enum) - 1.0f));
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}
|
|
|
|
PyDoc_STRVAR(M_Noise_noise_vector_doc,
|
|
".. function:: noise_vector(position, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns the noise vector from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n" BPY_NOISE_BASIS_ENUM_DOC
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|
" :return: The noise vector.\n"
|
|
" :rtype: :class:`mathutils.Vector`\n");
|
|
static PyObject *M_Noise_noise_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3], r_vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
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args, kw, "O|$s:noise_vector", (char **)kwlist, &value, &noise_basis_str)) {
|
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return NULL;
|
|
}
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|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise_vector") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "noise_vector: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
noise_vector(vec[0], vec[1], vec[2], noise_basis_enum, r_vec);
|
|
|
|
return Vector_CreatePyObject(r_vec, 3, NULL);
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_turbulence_doc,
|
|
".. function:: turbulence(position, octaves, hard, noise_basis='PERLIN_ORIGINAL', "
|
|
"amplitude_scale=0.5, frequency_scale=2.0)\n"
|
|
"\n"
|
|
" Returns the turbulence value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or "
|
|
"soft (smooth transitions).\n"
|
|
" :type hard: boolean\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :arg amplitude_scale: The amplitude scaling factor.\n"
|
|
" :type amplitude_scale: float\n"
|
|
" :arg frequency_scale: The frequency scaling factor\n"
|
|
" :type frequency_scale: float\n"
|
|
" :return: The turbulence value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_turbulence(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {
|
|
"", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
float as = 0.5f, fs = 2.0f;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Oii|$sff:turbulence",
|
|
(char **)kwlist,
|
|
&value,
|
|
&oct,
|
|
&hd,
|
|
&noise_basis_str,
|
|
&as,
|
|
&fs)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "turbulence: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(turb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_turbulence_vector_doc,
|
|
".. function:: turbulence_vector(position, octaves, hard, "
|
|
"noise_basis='PERLIN_ORIGINAL', amplitude_scale=0.5, frequency_scale=2.0)\n"
|
|
"\n"
|
|
" Returns the turbulence vector from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or "
|
|
"soft (smooth transitions).\n"
|
|
" :type hard: :boolean\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :arg amplitude_scale: The amplitude scaling factor.\n"
|
|
" :type amplitude_scale: float\n"
|
|
" :arg frequency_scale: The frequency scaling factor\n"
|
|
" :type frequency_scale: float\n"
|
|
" :return: The turbulence vector.\n"
|
|
" :rtype: :class:`mathutils.Vector`\n");
|
|
static PyObject *M_Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {
|
|
"", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
|
|
PyObject *value;
|
|
float vec[3], r_vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
float as = 0.5f, fs = 2.0f;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Oii|$sff:turbulence_vector",
|
|
(char **)kwlist,
|
|
&value,
|
|
&oct,
|
|
&hd,
|
|
&noise_basis_str,
|
|
&as,
|
|
&fs)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence_vector") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "turbulence_vector: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
vTurb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs, r_vec);
|
|
|
|
return Vector_CreatePyObject(r_vec, 3, NULL);
|
|
}
|
|
|
|
/* F. Kenton Musgrave's fractal functions */
|
|
PyDoc_STRVAR(
|
|
M_Noise_fractal_doc,
|
|
".. function:: fractal(position, H, lacunarity, octaves, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns the fractal Brownian motion (fBm) noise value from the noise basis at the "
|
|
"specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal increment factor.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The fractal Brownian motion noise value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Offf|$s:fractal",
|
|
(char **)kwlist,
|
|
&value,
|
|
&H,
|
|
&lac,
|
|
&oct,
|
|
&noise_basis_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "fractal") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "fractal: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(mg_fBm(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(
|
|
M_Noise_multi_fractal_doc,
|
|
".. function:: multi_fractal(position, H, lacunarity, octaves, "
|
|
"noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns multifractal noise value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal increment factor.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The multifractal noise value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Offf|$s:multi_fractal",
|
|
(char **)kwlist,
|
|
&value,
|
|
&H,
|
|
&lac,
|
|
&oct,
|
|
&noise_basis_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "multi_fractal") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "multi_fractal: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(
|
|
mg_MultiFractal(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_variable_lacunarity_doc,
|
|
".. function:: variable_lacunarity(position, distortion, "
|
|
"noise_type1='PERLIN_ORIGINAL', noise_type2='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns variable lacunarity noise value, a distorted variety of noise, from "
|
|
"noise type 1 distorted by noise type 2 at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg distortion: The amount of distortion.\n"
|
|
" :type distortion: float\n"
|
|
" :arg noise_type1: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', "
|
|
"'VORONOI_F1', 'VORONOI_F2', "
|
|
"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', "
|
|
"'CELLNOISE'].\n"
|
|
" :type noise_type1: string\n"
|
|
" :arg noise_type2: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', "
|
|
"'VORONOI_F1', 'VORONOI_F2', "
|
|
"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', "
|
|
"'CELLNOISE'].\n"
|
|
" :type noise_type2: string\n"
|
|
" :return: The variable lacunarity noise value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_variable_lacunarity(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "noise_type1", "noise_type2", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_type1_str = NULL, *noise_type2_str = NULL;
|
|
float d;
|
|
int noise_type1_enum = DEFAULT_NOISE_TYPE, noise_type2_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Of|$ss:variable_lacunarity",
|
|
(char **)kwlist,
|
|
&value,
|
|
&d,
|
|
&noise_type1_str,
|
|
&noise_type2_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_type1_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_type1_str, &noise_type1_enum, "variable_lacunarity") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_type2_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_type2_str, &noise_type2_enum, "variable_lacunarity") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "variable_lacunarity: invalid 'position' arg") ==
|
|
-1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(
|
|
mg_VLNoise(vec[0], vec[1], vec[2], d, noise_type1_enum, noise_type2_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(
|
|
M_Noise_hetero_terrain_doc,
|
|
".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, "
|
|
"noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns the heterogeneous terrain value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The heterogeneous terrain value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Offff|$s:hetero_terrain",
|
|
(char **)kwlist,
|
|
&value,
|
|
&H,
|
|
&lac,
|
|
&oct,
|
|
&ofs,
|
|
&noise_basis_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "hetero_terrain") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "hetero_terrain: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(
|
|
mg_HeteroTerrain(vec[0], vec[1], vec[2], H, lac, oct, ofs, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(
|
|
M_Noise_hybrid_multi_fractal_doc,
|
|
".. function:: hybrid_multi_fractal(position, H, lacunarity, octaves, offset, gain, "
|
|
"noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns hybrid multifractal value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n"
|
|
" :arg gain: Scaling applied to the values.\n"
|
|
" :type gain: float\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The hybrid multifractal value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_hybrid_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs, gn;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Offfff|$s:hybrid_multi_fractal",
|
|
(char **)kwlist,
|
|
&value,
|
|
&H,
|
|
&lac,
|
|
&oct,
|
|
&ofs,
|
|
&gn,
|
|
&noise_basis_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "hybrid_multi_fractal") ==
|
|
-1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "hybrid_multi_fractal: invalid 'position' arg") ==
|
|
-1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(
|
|
mg_HybridMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(
|
|
M_Noise_ridged_multi_fractal_doc,
|
|
".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, "
|
|
"noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns ridged multifractal value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n"
|
|
" :arg gain: Scaling applied to the values.\n"
|
|
" :type gain: float\n" BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The ridged multifractal value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs, gn;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(args,
|
|
kw,
|
|
"Offfff|$s:ridged_multi_fractal",
|
|
(char **)kwlist,
|
|
&value,
|
|
&H,
|
|
&lac,
|
|
&oct,
|
|
&ofs,
|
|
&gn,
|
|
&noise_basis_str)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "ridged_multi_fractal") ==
|
|
-1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "ridged_multi_fractal: invalid 'position' arg") ==
|
|
-1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(
|
|
mg_RidgedMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_voronoi_doc,
|
|
".. function:: voronoi(position, distance_metric='DISTANCE', exponent=2.5)\n"
|
|
"\n"
|
|
" Returns a list of distances to the four closest features and their locations.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n" BPY_NOISE_METRIC_ENUM_DOC
|
|
" :arg exponent: The exponent for Minkowski distance metric.\n"
|
|
" :type exponent: float\n"
|
|
" :return: A list of distances to the four closest features and their locations.\n"
|
|
" :rtype: list of four floats, list of four :class:`mathutils.Vector` types\n");
|
|
static PyObject *M_Noise_voronoi(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "distance_metric", "exponent", NULL};
|
|
PyObject *value;
|
|
PyObject *list;
|
|
PyObject *ret;
|
|
float vec[3];
|
|
const char *metric_str = NULL;
|
|
float da[4], pa[12];
|
|
int metric_enum = DEFAULT_METRIC_TYPE;
|
|
float me = 2.5f; /* default minkowski exponent */
|
|
|
|
int i;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "O|$sf:voronoi", (char **)kwlist, &value, &metric_str, &me)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (!metric_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(bpy_noise_metrics, metric_str, &metric_enum, "voronoi") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "voronoi: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
list = PyList_New(4);
|
|
|
|
voronoi(vec[0], vec[1], vec[2], da, pa, me, metric_enum);
|
|
|
|
for (i = 0; i < 4; i++) {
|
|
PyObject *v = Vector_CreatePyObject(pa + 3 * i, 3, NULL);
|
|
PyList_SET_ITEM(list, i, v);
|
|
}
|
|
|
|
ret = Py_BuildValue("[[ffff]O]", da[0], da[1], da[2], da[3], list);
|
|
Py_DECREF(list);
|
|
return ret;
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_cell_doc,
|
|
".. function:: cell(position)\n"
|
|
"\n"
|
|
" Returns cell noise value at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :return: The cell noise value.\n"
|
|
" :rtype: float\n");
|
|
static PyObject *M_Noise_cell(PyObject *UNUSED(self), PyObject *args)
|
|
{
|
|
PyObject *value;
|
|
float vec[3];
|
|
|
|
if (!PyArg_ParseTuple(args, "O:cell", &value)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "cell: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
return PyFloat_FromDouble(cellNoise(vec[0], vec[1], vec[2]));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_cell_vector_doc,
|
|
".. function:: cell_vector(position)\n"
|
|
"\n"
|
|
" Returns cell noise vector at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :return: The cell noise vector.\n"
|
|
" :rtype: :class:`mathutils.Vector`\n");
|
|
static PyObject *M_Noise_cell_vector(PyObject *UNUSED(self), PyObject *args)
|
|
{
|
|
PyObject *value;
|
|
float vec[3], r_vec[3];
|
|
|
|
if (!PyArg_ParseTuple(args, "O:cell_vector", &value)) {
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "cell_vector: invalid 'position' arg") == -1) {
|
|
return NULL;
|
|
}
|
|
|
|
cellNoiseV(vec[0], vec[1], vec[2], r_vec);
|
|
return Vector_CreatePyObject(r_vec, 3, NULL);
|
|
}
|
|
|
|
static PyMethodDef M_Noise_methods[] = {
|
|
{"seed_set", (PyCFunction)M_Noise_seed_set, METH_VARARGS, M_Noise_seed_set_doc},
|
|
{"random", (PyCFunction)M_Noise_random, METH_NOARGS, M_Noise_random_doc},
|
|
{"random_unit_vector",
|
|
(PyCFunction)M_Noise_random_unit_vector,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_random_unit_vector_doc},
|
|
{"random_vector",
|
|
(PyCFunction)M_Noise_random_vector,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_random_vector_doc},
|
|
{"noise", (PyCFunction)M_Noise_noise, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_doc},
|
|
{"noise_vector",
|
|
(PyCFunction)M_Noise_noise_vector,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_noise_vector_doc},
|
|
{"turbulence",
|
|
(PyCFunction)M_Noise_turbulence,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_turbulence_doc},
|
|
{"turbulence_vector",
|
|
(PyCFunction)M_Noise_turbulence_vector,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_turbulence_vector_doc},
|
|
{"fractal", (PyCFunction)M_Noise_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_fractal_doc},
|
|
{"multi_fractal",
|
|
(PyCFunction)M_Noise_multi_fractal,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_multi_fractal_doc},
|
|
{"variable_lacunarity",
|
|
(PyCFunction)M_Noise_variable_lacunarity,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_variable_lacunarity_doc},
|
|
{"hetero_terrain",
|
|
(PyCFunction)M_Noise_hetero_terrain,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_hetero_terrain_doc},
|
|
{"hybrid_multi_fractal",
|
|
(PyCFunction)M_Noise_hybrid_multi_fractal,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_hybrid_multi_fractal_doc},
|
|
{"ridged_multi_fractal",
|
|
(PyCFunction)M_Noise_ridged_multi_fractal,
|
|
METH_VARARGS | METH_KEYWORDS,
|
|
M_Noise_ridged_multi_fractal_doc},
|
|
{"voronoi", (PyCFunction)M_Noise_voronoi, METH_VARARGS | METH_KEYWORDS, M_Noise_voronoi_doc},
|
|
{"cell", (PyCFunction)M_Noise_cell, METH_VARARGS, M_Noise_cell_doc},
|
|
{"cell_vector", (PyCFunction)M_Noise_cell_vector, METH_VARARGS, M_Noise_cell_vector_doc},
|
|
{NULL, NULL, 0, NULL},
|
|
};
|
|
|
|
static struct PyModuleDef M_Noise_module_def = {
|
|
PyModuleDef_HEAD_INIT,
|
|
"mathutils.noise", /* m_name */
|
|
M_Noise_doc, /* m_doc */
|
|
0, /* m_size */
|
|
M_Noise_methods, /* m_methods */
|
|
NULL, /* m_reload */
|
|
NULL, /* m_traverse */
|
|
NULL, /* m_clear */
|
|
NULL, /* m_free */
|
|
};
|
|
|
|
/*----------------------------MODULE INIT-------------------------*/
|
|
PyMODINIT_FUNC PyInit_mathutils_noise(void)
|
|
{
|
|
PyObject *submodule = PyModule_Create(&M_Noise_module_def);
|
|
|
|
/* use current time as seed for random number generator by default */
|
|
setRndSeed(0);
|
|
|
|
return submodule;
|
|
}
|