forked from bartvdbraak/blender
noise python module back from 2.4x, personal request from ant author Jimmy Haze
Changes: /* 2.5 update * Noise.setRandomSeed --> seed_set * Noise.randuvec --> random_unit_vector * Noise.vNoise --> noise_vector * Noise.vTurbulence --> turbulence_vector * Noise.multiFractal --> multi_fractal * Noise.cellNoise --> cell * Noise.cellNoiseV --> cell_vector * Noise.vlNoise --> vl_vector * Noise.heteroTerrain --> hetero_terrain * Noise.hybridMFractal --> hybrid_multi_fractal * Noise.fBm --> fractal * Noise.ridgedMFractal --> ridged_multi_fractal * * Const's * * Noise.NoiseTypes --> types * Noise.DistanceMetrics --> distance_metrics */
This commit is contained in:
parent
132a1f95c1
commit
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@ -61,6 +61,7 @@ PyObject *BaseMathObject_getWrapped( BaseMathObject *self, void * );
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void BaseMathObject_dealloc(BaseMathObject * self);
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void BaseMathObject_dealloc(BaseMathObject * self);
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PyObject *Mathutils_Init(void);
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PyObject *Mathutils_Init(void);
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PyObject *Noise_Init(void); /* lazy, saves having own header */
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PyObject *quat_rotation(PyObject *arg1, PyObject *arg2);
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PyObject *quat_rotation(PyObject *arg1, PyObject *arg2);
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760
source/blender/python/generic/noise.c
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760
source/blender/python/generic/noise.c
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@ -0,0 +1,760 @@
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/**
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* $Id$
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*
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* Blender.Noise BPython module implementation.
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* This submodule has functions to generate noise of various types.
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*
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* ***** BEGIN GPL LICENSE BLOCK *****
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*
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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., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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*
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* The Original Code is Copyright (C) 2001-2002 by NaN Holding BV.
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* All rights reserved.
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*
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* This is a new part of Blender.
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*
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* Contributor(s): eeshlo
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*
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* ***** END GPL LICENSE BLOCK *****
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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 "structseq.h"
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#include "BLI_blenlib.h"
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#include "DNA_texture_types.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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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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Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
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All rights reserved.
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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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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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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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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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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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/* 2.5 update
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* Noise.setRandomSeed --> seed_set
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* Noise.randuvec --> random_unit_vector
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* Noise.vNoise --> noise_vector
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* Noise.vTurbulence --> turbulence_vector
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* Noise.multiFractal --> multi_fractal
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* Noise.cellNoise --> cell
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* Noise.cellNoiseV --> cell_vector
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* Noise.vlNoise --> vl_vector
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* Noise.heteroTerrain --> hetero_terrain
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* Noise.hybridMFractal --> hybrid_multi_fractal
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* Noise.fBm --> fractal
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* Noise.ridgedMFractal --> ridged_multi_fractal
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*
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* Const's *
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* Noise.NoiseTypes --> types
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* Noise.DistanceMetrics --> distance_metrics
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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 unsigned long 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 unsigned long *next;
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PyObject *Noise_Init(void);
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/* initializes state[N] with a seed */
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static void init_genrand(unsigned long 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] =
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(1812433253UL *
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(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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}
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static void next_state(void)
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{
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unsigned long *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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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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for(j = M; --j; p++)
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*p = p[M - N] ^ TWIST(p[0], p[1]);
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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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else
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init_genrand(seed);
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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()
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{
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unsigned long y;
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if(--left == 0)
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next_state();
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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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/* returns random unit vector */
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static void randuvec(float v[3])
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{
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float r;
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v[2] = 2.f * frand() - 1.f;
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if((r = 1.f - v[2] * v[2]) > 0.f) {
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float a = (float)(6.283185307f * frand());
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r = (float)sqrt(r);
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v[0] = (float)(r * cos(a));
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v[1] = (float)(r * sin(a));
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} else
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v[2] = 1.f;
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}
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static PyObject *Noise_random(PyObject * self)
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{
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return PyFloat_FromDouble(frand());
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}
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static PyObject *Noise_random_unit_vector(PyObject * self)
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{
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float v[3] = {0.0f, 0.0f, 0.0f};
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randuvec(v);
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return Py_BuildValue("[fff]", v[0], v[1], v[2]);
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}
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/*---------------------------------------------------------------------*/
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/* Random seed init. Only used for MT random() & randuvec() */
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static PyObject *Noise_seed_set(PyObject * 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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setRndSeed(s);
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Py_RETURN_NONE;
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}
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/*-------------------------------------------------------------------------*/
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/* General noise */
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static PyObject *Noise_noise(PyObject * self, PyObject * args)
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{
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float x, y, z;
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int nb = 1;
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if(!PyArg_ParseTuple(args, "(fff)|i:noise", &x, &y, &z, &nb))
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return NULL;
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return PyFloat_FromDouble((2.0 * BLI_gNoise(1.0, x, y, z, 0, nb) - 1.0));
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}
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/*-------------------------------------------------------------------------*/
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/* General Vector noise */
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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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v[0] = (float)(2.0 * BLI_gNoise(1.f, x + 9.321f, y - 1.531f, z - 7.951f, 0,
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nb) - 1.0);
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v[1] = (float)(2.0 * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0);
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v[2] = (float)(2.0 * BLI_gNoise(1.f, x + 6.327f, y + 0.1671f, z - 2.672f, 0,
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nb) - 1.0);
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}
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static PyObject *Noise_vector(PyObject * self, PyObject * args)
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{
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float x, y, z, v[3];
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int nb = 1;
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if(!PyArg_ParseTuple(args, "(fff)|i:vector", &x, &y, &z, &nb))
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return NULL;
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noise_vector(x, y, z, nb, v);
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return Py_BuildValue("[fff]", v[0], v[1], v[2]);
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}
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/*---------------------------------------------------------------------------*/
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/* General turbulence */
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static float turb(float x, float y, float z, int oct, int hard, int nb,
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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)(2.0 * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0);
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if(hard)
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out = (float)fabs(out);
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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 * (2.0 * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0));
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if(hard)
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t = (float)fabs(t);
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out += t;
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}
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return out;
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}
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static PyObject *Noise_turbulence(PyObject * self, PyObject * args)
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{
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float x, y, z;
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int oct, hd, nb = 1;
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float as = 0.5, fs = 2.0;
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if(!PyArg_ParseTuple(args, "(fff)ii|iff:turbulence", &x, &y, &z, &oct, &hd, &nb, &as, &fs))
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return NULL;
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return PyFloat_FromDouble(turb(x, y, z, oct, hd, nb, as, fs));
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}
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/*--------------------------------------------------------------------------*/
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/* Turbulence Vector */
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static void vTurb(float x, float y, float z, int oct, int hard, int nb,
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float ampscale, float freqscale, 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] = (float)fabs(v[0]);
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v[1] = (float)fabs(v[1]);
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v[2] = (float)fabs(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] = (float)fabs(t[0]);
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t[1] = (float)fabs(t[1]);
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t[2] = (float)fabs(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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static PyObject *Noise_turbulence_vector(PyObject * self, PyObject * args)
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{
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float x, y, z, v[3];
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int oct, hd, nb = 1;
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float as = 0.5, fs = 2.0;
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if(!PyArg_ParseTuple(args, "(fff)ii|iff:turbulence_vector", &x, &y, &z, &oct, &hd, &nb, &as, &fs))
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return NULL;
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vTurb(x, y, z, oct, hd, nb, as, fs, v);
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return Py_BuildValue("[fff]", v[0], v[1], v[2]);
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}
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/*---------------------------------------------------------------------*/
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/* F. Kenton Musgrave's fractal functions */
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||||||
|
static PyObject *Noise_fractal(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, H, lac, oct;
|
||||||
|
int nb = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)fff|i:fractal", &x, &y, &z, &H, &lac, &oct, &nb))
|
||||||
|
return NULL;
|
||||||
|
return PyFloat_FromDouble(mg_fBm(x, y, z, H, lac, oct, nb));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_multi_fractal(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, H, lac, oct;
|
||||||
|
int nb = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)fff|i:multi_fractal", &x, &y, &z, &H, &lac, &oct, &nb))
|
||||||
|
return NULL;
|
||||||
|
|
||||||
|
return PyFloat_FromDouble(mg_MultiFractal(x, y, z, H, lac, oct, nb));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_vl_vector(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, d;
|
||||||
|
int nt1 = 1, nt2 = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)f|ii:vl_vector", &x, &y, &z, &d, &nt1, &nt2))
|
||||||
|
return NULL;
|
||||||
|
return PyFloat_FromDouble(mg_VLNoise(x, y, z, d, nt1, nt2));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*-------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_hetero_terrain(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, H, lac, oct, ofs;
|
||||||
|
int nb = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)ffff|i:hetero_terrain", &x, &y, &z, &H, &lac, &oct, &ofs, &nb))
|
||||||
|
return NULL;
|
||||||
|
|
||||||
|
return PyFloat_FromDouble(mg_HeteroTerrain(x, y, z, H, lac, oct, ofs, nb));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*-------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_hybrid_multi_fractal(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, H, lac, oct, ofs, gn;
|
||||||
|
int nb = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)fffff|i:hybrid_multi_fractal", &x, &y, &z, &H, &lac, &oct, &ofs, &gn, &nb))
|
||||||
|
return NULL;
|
||||||
|
|
||||||
|
return PyFloat_FromDouble(mg_HybridMultiFractal(x, y, z, H, lac, oct, ofs, gn, nb));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_ridged_multi_fractal(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, H, lac, oct, ofs, gn;
|
||||||
|
int nb = 1;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)fffff|i:ridged_multi_fractal", &x, &y, &z, &H, &lac, &oct, &ofs, &gn, &nb))
|
||||||
|
return NULL;
|
||||||
|
return PyFloat_FromDouble(mg_RidgedMultiFractal(x, y, z, H, lac, oct, ofs, gn, nb));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*-------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_voronoi(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, da[4], pa[12];
|
||||||
|
int dtype = 0;
|
||||||
|
float me = 2.5; /* default minkovsky exponent */
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff)|if:voronoi", &x, &y, &z, &dtype, &me))
|
||||||
|
return NULL;
|
||||||
|
voronoi(x, y, z, da, pa, me, dtype);
|
||||||
|
return Py_BuildValue("[[ffff][[fff][fff][fff][fff]]]",
|
||||||
|
da[0], da[1], da[2], da[3],
|
||||||
|
pa[0], pa[1], pa[2],
|
||||||
|
pa[3], pa[4], pa[5],
|
||||||
|
pa[6], pa[7], pa[8], pa[9], pa[10], pa[11]);
|
||||||
|
}
|
||||||
|
|
||||||
|
/*-------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_cell(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z;
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff):cell", &x, &y, &z))
|
||||||
|
return NULL;
|
||||||
|
|
||||||
|
return PyFloat_FromDouble(cellNoise(x, y, z));
|
||||||
|
}
|
||||||
|
|
||||||
|
/*--------------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static PyObject *Noise_cell_vector(PyObject * self, PyObject * args)
|
||||||
|
{
|
||||||
|
float x, y, z, ca[3];
|
||||||
|
if(!PyArg_ParseTuple(args, "(fff):cell_vector", &x, &y, &z))
|
||||||
|
return NULL;
|
||||||
|
cellNoiseV(x, y, z, ca);
|
||||||
|
return Py_BuildValue("[fff]", ca[0], ca[1], ca[2]);
|
||||||
|
}
|
||||||
|
|
||||||
|
/*--------------------------------------------------------------------------*/
|
||||||
|
/* For all other Blender modules, this stuff seems to be put in a header file.
|
||||||
|
This doesn't seem really appropriate to me, so I just put it here, feel free to change it.
|
||||||
|
In the original module I actually kept the docs stings with the functions themselves,
|
||||||
|
but I grouped them here so that it can easily be moved to a header if anyone thinks that is necessary. */
|
||||||
|
|
||||||
|
static char random__doc__[] = "() No arguments.\n\n\
|
||||||
|
Returns a random floating point number in the range [0, 1)";
|
||||||
|
|
||||||
|
static char random_unit_vector__doc__[] =
|
||||||
|
"() No arguments.\n\nReturns a random unit vector (3-float list).";
|
||||||
|
|
||||||
|
static char seed_set__doc__[] = "(seed value)\n\n\
|
||||||
|
Initializes random number generator.\n\
|
||||||
|
if seed is zero, the current time will be used instead.";
|
||||||
|
|
||||||
|
static char noise__doc__[] = "((x,y,z) tuple, [noisetype])\n\n\
|
||||||
|
Returns general noise of the optional specified type.\n\
|
||||||
|
Optional argument noisetype determines the type of noise, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char noise_vector__doc__[] = "((x,y,z) tuple, [noisetype])\n\n\
|
||||||
|
Returns noise vector (3-float list) of the optional specified type.\
|
||||||
|
Optional argument noisetype determines the type of noise, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char turbulence__doc__[] =
|
||||||
|
"((x,y,z) tuple, octaves, hard, [noisebasis], [ampscale], [freqscale])\n\n\
|
||||||
|
Returns general turbulence value using the optional specified noisebasis function.\n\
|
||||||
|
octaves (integer) is the number of noise values added.\n\
|
||||||
|
hard (bool), when false (0) returns 'soft' noise, when true (1) returns 'hard' noise (returned value always positive).\n\
|
||||||
|
Optional arguments:\n\
|
||||||
|
noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.\n\
|
||||||
|
ampscale sets the amplitude scale value of the noise frequencies added, 0.5 by default.\n\
|
||||||
|
freqscale sets the frequency scale factor, 2.0 by default.";
|
||||||
|
|
||||||
|
static char turbulence_vector__doc__[] =
|
||||||
|
"((x,y,z) tuple, octaves, hard, [noisebasis], [ampscale], [freqscale])\n\n\
|
||||||
|
Returns general turbulence vector (3-float list) using the optional specified noisebasis function.\n\
|
||||||
|
octaves (integer) is the number of noise values added.\n\
|
||||||
|
hard (bool), when false (0) returns 'soft' noise, when true (1) returns 'hard' noise (returned vector always positive).\n\
|
||||||
|
Optional arguments:\n\
|
||||||
|
noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.\n\
|
||||||
|
ampscale sets the amplitude scale value of the noise frequencies added, 0.5 by default.\n\
|
||||||
|
freqscale sets the frequency scale factor, 2.0 by default.";
|
||||||
|
|
||||||
|
static char fractal__doc__[] =
|
||||||
|
"((x,y,z) tuple, H, lacunarity, octaves, [noisebasis])\n\n\
|
||||||
|
Returns Fractal Brownian Motion noise value(fBm).\n\
|
||||||
|
H is the fractal increment parameter.\n\
|
||||||
|
lacunarity is the gap between successive frequencies.\n\
|
||||||
|
octaves is the number of frequencies in the fBm.\n\
|
||||||
|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char multi_fractal__doc__[] =
|
||||||
|
"((x,y,z) tuple, H, lacunarity, octaves, [noisebasis])\n\n\
|
||||||
|
Returns Multifractal noise value.\n\
|
||||||
|
H determines the highest fractal dimension.\n\
|
||||||
|
lacunarity is gap between successive frequencies.\n\
|
||||||
|
octaves is the number of frequencies in the fBm.\n\
|
||||||
|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char vl_vector__doc__[] =
|
||||||
|
"((x,y,z) tuple, distortion, [noisetype1], [noisetype2])\n\n\
|
||||||
|
Returns Variable Lacunarity Noise value, a distorted variety of noise.\n\
|
||||||
|
distortion sets the amount of distortion.\n\
|
||||||
|
Optional arguments noisetype1 and noisetype2 set the noisetype to distort and the noisetype used for the distortion respectively.\n\
|
||||||
|
See NoiseTypes, both are STDPERLIN by default.";
|
||||||
|
|
||||||
|
static char hetero_terrain__doc__[] =
|
||||||
|
"((x,y,z) tuple, H, lacunarity, octaves, offset, [noisebasis])\n\n\
|
||||||
|
returns Heterogeneous Terrain value\n\
|
||||||
|
H determines the fractal dimension of the roughest areas.\n\
|
||||||
|
lacunarity is the gap between successive frequencies.\n\
|
||||||
|
octaves is the number of frequencies in the fBm.\n\
|
||||||
|
offset raises the terrain from 'sea level'.\n\
|
||||||
|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char hybrid_multi_fractal__doc__[] =
|
||||||
|
"((x,y,z) tuple, H, lacunarity, octaves, offset, gain, [noisebasis])\n\n\
|
||||||
|
returns Hybrid Multifractal value.\n\
|
||||||
|
H determines the fractal dimension of the roughest areas.\n\
|
||||||
|
lacunarity is the gap between successive frequencies.\n\
|
||||||
|
octaves is the number of frequencies in the fBm.\n\
|
||||||
|
offset raises the terrain from 'sea level'.\n\
|
||||||
|
gain scales the values.\n\
|
||||||
|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char ridged_multi_fractal__doc__[] =
|
||||||
|
"((x,y,z) tuple, H, lacunarity, octaves, offset, gain [noisebasis])\n\n\
|
||||||
|
returns Ridged Multifractal value.\n\
|
||||||
|
H determines the fractal dimension of the roughest areas.\n\
|
||||||
|
lacunarity is the gap between successive frequencies.\n\
|
||||||
|
octaves is the number of frequencies in the fBm.\n\
|
||||||
|
offset raises the terrain from 'sea level'.\n\
|
||||||
|
gain scales the values.\n\
|
||||||
|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
|
||||||
|
|
||||||
|
static char voronoi__doc__[] =
|
||||||
|
"((x,y,z) tuple, distance_metric, [exponent])\n\n\
|
||||||
|
returns a list, containing a list of distances in order of closest feature,\n\
|
||||||
|
and a list containing the positions of the four closest features\n\
|
||||||
|
Optional arguments:\n\
|
||||||
|
distance_metric: see DistanceMetrics, default is DISTANCE\n\
|
||||||
|
exponent is only used with MINKOVSKY, default is 2.5.";
|
||||||
|
|
||||||
|
static char cell__doc__[] = "((x,y,z) tuple)\n\n\
|
||||||
|
returns cellnoise float value.";
|
||||||
|
|
||||||
|
static char cell_vector__doc__[] = "((x,y,z) tuple)\n\n\
|
||||||
|
returns cellnoise vector/point/color (3-float list).";
|
||||||
|
|
||||||
|
static char Noise__doc__[] = "Blender Noise and Turbulence Module\n\n\
|
||||||
|
This module can be used to generate noise of various types.\n\
|
||||||
|
This can be used for terrain generation, to create textures,\n\
|
||||||
|
make animations more 'animated', object deformation, etc.\n\
|
||||||
|
As an example, this code segment when scriptlinked to a framechanged event,\n\
|
||||||
|
will make the camera sway randomly about, by changing parameters this can\n\
|
||||||
|
look like anything from an earthquake to a very nervous or maybe even drunk cameraman...\n\
|
||||||
|
(the camera needs an ipo with at least one Loc & Rot key for this to work!):\n\
|
||||||
|
\n\
|
||||||
|
\tfrom Blender import Get, Scene, Noise\n\
|
||||||
|
\n\
|
||||||
|
\t####################################################\n\
|
||||||
|
\t# This controls jitter speed\n\
|
||||||
|
\tsl = 0.025\n\
|
||||||
|
\t# This controls the amount of position jitter\n\
|
||||||
|
\tsp = 0.1\n\
|
||||||
|
\t# This controls the amount of rotation jitter\n\
|
||||||
|
\tsr = 0.25\n\
|
||||||
|
\t####################################################\n\
|
||||||
|
\n\
|
||||||
|
\ttime = Get('curtime')\n\
|
||||||
|
\tob = Scene.GetCurrent().getCurrentCamera()\n\
|
||||||
|
\tps = (sl*time, sl*time, sl*time)\n\
|
||||||
|
\t# To add jitter only when the camera moves, use this next line instead\n\
|
||||||
|
\t#ps = (sl*ob.LocX, sl*ob.LocY, sl*ob.LocZ)\n\
|
||||||
|
\trv = Noise.turbulence_vector(ps, 3, 0, Noise.NoiseTypes.NEWPERLIN)\n\
|
||||||
|
\tob.dloc = (sp*rv[0], sp*rv[1], sp*rv[2])\n\
|
||||||
|
\tob.drot = (sr*rv[0], sr*rv[1], sr*rv[2])\n\
|
||||||
|
\n";
|
||||||
|
|
||||||
|
/* Just in case, declarations for a header file */
|
||||||
|
/*
|
||||||
|
static PyObject *Noise_random(PyObject *self);
|
||||||
|
static PyObject *Noise_random_unit_vector(PyObject *self);
|
||||||
|
static PyObject *Noise_seed_set(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_noise(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_vector(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_turbulence(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_turbulence_vector(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_fractal(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_multi_fractal(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_vl_vector(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_hetero_terrain(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_hybrid_multi_fractal(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_ridged_multi_fractal(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_voronoi(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_cell(PyObject *self, PyObject *args);
|
||||||
|
static PyObject *Noise_cell_vector(PyObject *self, PyObject *args);
|
||||||
|
*/
|
||||||
|
|
||||||
|
static PyMethodDef NoiseMethods[] = {
|
||||||
|
{"seed_set", (PyCFunction) Noise_seed_set, METH_VARARGS, seed_set__doc__},
|
||||||
|
{"random", (PyCFunction) Noise_random, METH_NOARGS, random__doc__},
|
||||||
|
{"random_unit_vector", (PyCFunction) Noise_random_unit_vector, METH_NOARGS, random_unit_vector__doc__},
|
||||||
|
{"noise", (PyCFunction) Noise_noise, METH_VARARGS, noise__doc__},
|
||||||
|
{"vector", (PyCFunction) Noise_vector, METH_VARARGS, noise_vector__doc__},
|
||||||
|
{"turbulence", (PyCFunction) Noise_turbulence, METH_VARARGS, turbulence__doc__},
|
||||||
|
{"turbulence_vector", (PyCFunction) Noise_turbulence_vector, METH_VARARGS, turbulence_vector__doc__},
|
||||||
|
{"fractal", (PyCFunction) Noise_fractal, METH_VARARGS, fractal__doc__},
|
||||||
|
{"multi_fractal", (PyCFunction) Noise_multi_fractal, METH_VARARGS, multi_fractal__doc__},
|
||||||
|
{"vl_vector", (PyCFunction) Noise_vl_vector, METH_VARARGS, vl_vector__doc__},
|
||||||
|
{"hetero_terrain", (PyCFunction) Noise_hetero_terrain, METH_VARARGS, hetero_terrain__doc__},
|
||||||
|
{"hybrid_multi_fractal", (PyCFunction) Noise_hybrid_multi_fractal, METH_VARARGS, hybrid_multi_fractal__doc__},
|
||||||
|
{"ridged_multi_fractal", (PyCFunction) Noise_ridged_multi_fractal, METH_VARARGS, ridged_multi_fractal__doc__},
|
||||||
|
{"voronoi", (PyCFunction) Noise_voronoi, METH_VARARGS, voronoi__doc__},
|
||||||
|
{"cell", (PyCFunction) Noise_cell, METH_VARARGS, cell__doc__},
|
||||||
|
{"cell_vector", (PyCFunction) Noise_cell_vector, METH_VARARGS, cell_vector__doc__},
|
||||||
|
{NULL, NULL, 0, NULL}
|
||||||
|
};
|
||||||
|
|
||||||
|
/*----------------------------------------------------------------------*/
|
||||||
|
|
||||||
|
static struct PyModuleDef noise_module_def = {
|
||||||
|
PyModuleDef_HEAD_INIT,
|
||||||
|
"noise", /* m_name */
|
||||||
|
Noise__doc__, /* m_doc */
|
||||||
|
0, /* m_size */
|
||||||
|
NoiseMethods, /* m_methods */
|
||||||
|
0, /* m_reload */
|
||||||
|
0, /* m_traverse */
|
||||||
|
0, /* m_clear */
|
||||||
|
0, /* m_free */
|
||||||
|
};
|
||||||
|
|
||||||
|
PyObject *Noise_Init(void)
|
||||||
|
{
|
||||||
|
PyObject *submodule = PyModule_Create(&noise_module_def);
|
||||||
|
PyDict_SetItemString(PySys_GetObject("modules"), noise_module_def.m_name, submodule);
|
||||||
|
|
||||||
|
/* use current time as seed for random number generator by default */
|
||||||
|
setRndSeed(0);
|
||||||
|
|
||||||
|
/* Constant noisetype dictionary */
|
||||||
|
if(submodule) {
|
||||||
|
static PyStructSequence_Field noise_types_fields[] = {
|
||||||
|
{"BLENDER", ""},
|
||||||
|
{"STDPERLIN", ""},
|
||||||
|
{"NEWPERLIN", ""},
|
||||||
|
{"VORONOI_F1", ""},
|
||||||
|
{"VORONOI_F2", ""},
|
||||||
|
{"VORONOI_F3", ""},
|
||||||
|
{"VORONOI_F4", ""},
|
||||||
|
{"VORONOI_F2F1", ""},
|
||||||
|
{"VORONOI_CRACKLE", ""},
|
||||||
|
{"CELLNOISE", ""},
|
||||||
|
{0}
|
||||||
|
};
|
||||||
|
|
||||||
|
static PyStructSequence_Desc noise_types_info_desc = {
|
||||||
|
"noise.types", /* name */
|
||||||
|
"Noise type", /* doc */
|
||||||
|
noise_types_fields, /* fields */
|
||||||
|
(sizeof(noise_types_fields)/sizeof(PyStructSequence_Field)) - 1
|
||||||
|
};
|
||||||
|
|
||||||
|
static PyTypeObject NoiseType;
|
||||||
|
|
||||||
|
PyObject *noise_types;
|
||||||
|
|
||||||
|
int pos = 0;
|
||||||
|
|
||||||
|
PyStructSequence_InitType(&NoiseType, &noise_types_info_desc);
|
||||||
|
|
||||||
|
noise_types = PyStructSequence_New(&NoiseType);
|
||||||
|
if (noise_types == NULL) {
|
||||||
|
return NULL;
|
||||||
|
}
|
||||||
|
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_BLENDER));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_STDPERLIN));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_NEWPERLIN));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_F1));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_F2));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_F3));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_F4));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_F2F1));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_VORONOI_CRACKLE));
|
||||||
|
PyStructSequence_SET_ITEM(noise_types, pos++, PyLong_FromLong(TEX_CELLNOISE));
|
||||||
|
|
||||||
|
PyModule_AddObject(submodule, "types", noise_types);
|
||||||
|
}
|
||||||
|
|
||||||
|
if(submodule) {
|
||||||
|
static PyStructSequence_Field distance_metrics_fields[] = {
|
||||||
|
{"DISTANCE", ""},
|
||||||
|
{"DISTANCE_SQUARED", ""},
|
||||||
|
{"MANHATTAN", ""},
|
||||||
|
{"CHEBYCHEV", ""},
|
||||||
|
{"MINKOVSKY_HALF", ""},
|
||||||
|
{"MINKOVSKY_FOUR", ""},
|
||||||
|
{"MINKOVSKY", ""},
|
||||||
|
{0}
|
||||||
|
};
|
||||||
|
|
||||||
|
static PyStructSequence_Desc noise_types_info_desc = {
|
||||||
|
"noise.distance_metrics", /* name */
|
||||||
|
"Distance Metrics for noise module.", /* doc */
|
||||||
|
distance_metrics_fields, /* fields */
|
||||||
|
(sizeof(distance_metrics_fields)/sizeof(PyStructSequence_Field)) - 1
|
||||||
|
};
|
||||||
|
|
||||||
|
static PyTypeObject DistanceMetrics;
|
||||||
|
|
||||||
|
PyObject *distance_metrics;
|
||||||
|
|
||||||
|
int pos = 0;
|
||||||
|
|
||||||
|
PyStructSequence_InitType(&DistanceMetrics, &noise_types_info_desc);
|
||||||
|
|
||||||
|
distance_metrics = PyStructSequence_New(&DistanceMetrics);
|
||||||
|
if (distance_metrics == NULL) {
|
||||||
|
return NULL;
|
||||||
|
}
|
||||||
|
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_DISTANCE));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_DISTANCE_SQUARED));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_MANHATTAN));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_CHEBYCHEV));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_MINKOVSKY_HALF));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_MINKOVSKY_FOUR));
|
||||||
|
PyStructSequence_SET_ITEM(distance_metrics, pos++, PyLong_FromLong(TEX_MINKOVSKY));
|
||||||
|
|
||||||
|
PyModule_AddObject(submodule, "distance_metrics", distance_metrics);
|
||||||
|
}
|
||||||
|
|
||||||
|
return submodule;
|
||||||
|
}
|
@ -149,6 +149,7 @@ void BPy_init_modules( void )
|
|||||||
/* stand alone utility modules not related to blender directly */
|
/* stand alone utility modules not related to blender directly */
|
||||||
Geometry_Init();
|
Geometry_Init();
|
||||||
Mathutils_Init();
|
Mathutils_Init();
|
||||||
|
Noise_Init();
|
||||||
BGL_Init();
|
BGL_Init();
|
||||||
BLF_Init();
|
BLF_Init();
|
||||||
IDProp_Init_Types();
|
IDProp_Init_Types();
|
||||||
|
Loading…
Reference in New Issue
Block a user