diff options
author | Campbell Barton <ideasman42@gmail.com> | 2012-01-31 08:59:57 +0400 |
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committer | Campbell Barton <ideasman42@gmail.com> | 2012-01-31 08:59:57 +0400 |
commit | 427cde6f166450916e90de0f769f65119ce79208 (patch) | |
tree | 6baed9a09f3f92264746ca1ae173269db5e47578 /source/blender | |
parent | b42feff554bbfa53bfd160da6fefef459fc07f02 (diff) |
svn cp \
https://svn.blender.org/svnroot/bf-blender/trunk/blender/source/blender/python/generic/noise_py_api.c@r42248 \
https://svn.blender.org/svnroot/bf-blender/trunk/blender/source/blender/python/mathutils/mathutils_noise.c
Diffstat (limited to 'source/blender')
-rw-r--r-- | source/blender/python/mathutils/mathutils_noise.c | 792 |
1 files changed, 792 insertions, 0 deletions
diff --git a/source/blender/python/mathutils/mathutils_noise.c b/source/blender/python/mathutils/mathutils_noise.c new file mode 100644 index 00000000000..902e64eb7c1 --- /dev/null +++ b/source/blender/python/mathutils/mathutils_noise.c @@ -0,0 +1,792 @@ +/* + * ***** BEGIN GPL LICENSE BLOCK ***** + * + * This program is free software; you can redistribute it and/or + * modify it under the terms of the GNU General Public License + * as published by the Free Software Foundation; either version 2 + * of the License, or (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program; if not, write to the Free Software Foundation, + * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. + * + * The Original Code is Copyright (C) 2001-2002 by NaN Holding BV. + * All rights reserved. + * + * This is a new part of Blender. + * + * Contributor(s): eeshlo, Campbell Barton + * + * ***** END GPL LICENSE BLOCK ***** + */ + +/** \file blender/python/generic/noise_py_api.c + * \ingroup pygen + * + * This file defines the 'noise' module, a general purpose module to access + * blenders noise functions. + */ + + +/************************/ +/* Blender Noise Module */ +/************************/ + +#include <Python.h> + +#include "structseq.h" + +#include "BLI_blenlib.h" +#include "BLI_utildefines.h" + +#include "DNA_texture_types.h" + +#include "noise_py_api.h" + +/*-----------------------------------------*/ +/* 'mersenne twister' random number generator */ + +/* + A C-program for MT19937, with initialization improved 2002/2/10. + Coded by Takuji Nishimura and Makoto Matsumoto. + This is a faster version by taking Shawn Cokus's optimization, + Matthe Bellew's simplification, Isaku Wada's real version. + + Before using, initialize the state by using init_genrand(seed) + or init_by_array(init_key, key_length). + + Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + 3. The names of its contributors may not be used to endorse or promote + products derived from this software without specific prior written + permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR + CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF + LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING + NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + + Any feedback is very welcome. + http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html + email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space) +*/ + +/* 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 + */ + +/* Period parameters */ +#define N 624 +#define M 397 +#define MATRIX_A 0x9908b0dfUL /* constant vector a */ +#define UMASK 0x80000000UL /* most significant w-r bits */ +#define LMASK 0x7fffffffUL /* least significant r bits */ +#define MIXBITS(u,v) (((u) & UMASK) | ((v) & LMASK)) +#define TWIST(u,v) ((MIXBITS(u,v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL)) + +static unsigned long state[N]; /* the array for the state vector */ +static int left = 1; +static int initf = 0; +static unsigned long *next; + +/* initializes state[N] with a seed */ +static void init_genrand(unsigned long s) +{ + int j; + state[0] = s & 0xffffffffUL; + for (j = 1; j < N; j++) { + state[j] = + (1812433253UL * + (state[j - 1] ^ (state[j - 1] >> 30)) + j); + /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ + /* In the previous versions, MSBs of the seed affect */ + /* only MSBs of the array state[]. */ + /* 2002/01/09 modified by Makoto Matsumoto */ + state[j] &= 0xffffffffUL; /* for >32 bit machines */ + } + left = 1; + initf = 1; +} + +static void next_state(void) +{ + unsigned long *p = state; + int j; + + /* if init_genrand() has not been called, */ + /* a default initial seed is used */ + if (initf == 0) + init_genrand(5489UL); + + left = N; + next = state; + + for (j = N - M + 1; --j; p++) + *p = p[M] ^ TWIST(p[0], p[1]); + + for (j = M; --j; p++) + *p = p[M - N] ^ TWIST(p[0], p[1]); + + *p = p[M - N] ^ TWIST(p[0], state[0]); +} + +/*------------------------------------------------------------*/ + +static void setRndSeed(int seed) +{ + if (seed == 0) + init_genrand(time(NULL)); + else + init_genrand(seed); +} + +/* float number in range [0, 1) using the mersenne twister rng */ +static float frand(void) +{ + unsigned long y; + + if (--left == 0) + next_state(); + y = *next++; + + /* Tempering */ + y ^= (y >> 11); + y ^= (y << 7) & 0x9d2c5680UL; + y ^= (y << 15) & 0xefc60000UL; + y ^= (y >> 18); + + return (float) y / 4294967296.f; +} + +/*------------------------------------------------------------*/ + +/* returns random unit vector */ +static void randuvec(float v[3]) +{ + float r; + v[2] = 2.f * frand() - 1.f; + if ((r = 1.f - v[2] * v[2]) > 0.f) { + float a = (float)(6.283185307f * frand()); + r = (float)sqrt(r); + v[0] = (float)(r * cosf(a)); + v[1] = (float)(r * sinf(a)); + } + else { + v[2] = 1.f; + } +} + +static PyObject *Noise_random(PyObject *UNUSED(self)) +{ + return PyFloat_FromDouble(frand()); +} + +static PyObject *Noise_random_unit_vector(PyObject *UNUSED(self)) +{ + float v[3] = {0.0f, 0.0f, 0.0f}; + randuvec(v); + return Py_BuildValue("[fff]", v[0], v[1], v[2]); +} + +/*---------------------------------------------------------------------*/ + +/* Random seed init. Only used for MT random() & randuvec() */ + +static PyObject *Noise_seed_set(PyObject *UNUSED(self), PyObject *args) +{ + int s; + if (!PyArg_ParseTuple(args, "i:seed_set", &s)) + return NULL; + setRndSeed(s); + Py_RETURN_NONE; +} + +/*-------------------------------------------------------------------------*/ + +/* General noise */ + +static PyObject *Noise_noise(PyObject *UNUSED(self), PyObject *args) +{ + float x, y, z; + int nb = 1; + if (!PyArg_ParseTuple(args, "(fff)|i:noise", &x, &y, &z, &nb)) + return NULL; + + return PyFloat_FromDouble((2.0f * BLI_gNoise(1.0f, x, y, z, 0, nb) - 1.0f)); +} + +/*-------------------------------------------------------------------------*/ + +/* General Vector noise */ + +static void noise_vector(float x, float y, float z, int nb, float v[3]) +{ + /* Simply evaluate noise at 3 different positions */ + v[0]= (float)(2.0f * BLI_gNoise(1.f, x + 9.321f, y - 1.531f, z - 7.951f, 0, + nb) - 1.0f); + v[1]= (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f); + v[2]= (float)(2.0f * BLI_gNoise(1.f, x + 6.327f, y + 0.1671f, z - 2.672f, 0, + nb) - 1.0f); +} + +static PyObject *Noise_vector(PyObject *UNUSED(self), PyObject *args) +{ + float x, y, z, v[3]; + int nb = 1; + if (!PyArg_ParseTuple(args, "(fff)|i:vector", &x, &y, &z, &nb)) + return NULL; + noise_vector(x, y, z, nb, v); + return Py_BuildValue("[fff]", v[0], v[1], v[2]); +} + +/*---------------------------------------------------------------------------*/ + +/* General turbulence */ + +static float turb(float x, float y, float z, int oct, int hard, int nb, + float ampscale, float freqscale) +{ + float amp, out, t; + int i; + amp = 1.f; + out = (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f); + if (hard) + out = fabsf(out); + for (i = 1; i < oct; i++) { + amp *= ampscale; + x *= freqscale; + y *= freqscale; + z *= freqscale; + t = (float)(amp * (2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f)); + if (hard) + t = fabsf(t); + out += t; + } + return out; +} + +static PyObject *Noise_turbulence(PyObject *UNUSED(self), PyObject *args) +{ + float x, y, z; + int oct, hd, nb = 1; + float as = 0.5, fs = 2.0; + if (!PyArg_ParseTuple(args, "(fff)ii|iff:turbulence", &x, &y, &z, &oct, &hd, &nb, &as, &fs)) + return NULL; + + return PyFloat_FromDouble(turb(x, y, z, oct, hd, nb, as, fs)); +} + +/*--------------------------------------------------------------------------*/ + +/* Turbulence Vector */ + +static void vTurb(float x, float y, float z, int oct, int hard, int nb, + float ampscale, float freqscale, float v[3]) +{ + float amp, t[3]; + int i; + amp = 1.f; + noise_vector(x, y, z, nb, v); + if (hard) { + v[0] = fabsf(v[0]); + v[1] = fabsf(v[1]); + v[2] = fabsf(v[2]); + } + for (i = 1; i < oct; i++) { + amp *= ampscale; + x *= freqscale; + y *= freqscale; + z *= freqscale; + noise_vector(x, y, z, nb, t); + if (hard) { + t[0] = fabsf(t[0]); + t[1] = fabsf(t[1]); + t[2] = fabsf(t[2]); + } + v[0] += amp * t[0]; + v[1] += amp * t[1]; + v[2] += amp * t[2]; + } +} + +static PyObject *Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args) +{ + float x, y, z, v[3]; + int oct, hd, nb = 1; + float as = 0.5, fs = 2.0; + if (!PyArg_ParseTuple(args, "(fff)ii|iff:turbulence_vector", &x, &y, &z, &oct, &hd, &nb, &as, &fs)) + return NULL; + vTurb(x, y, z, oct, hd, nb, as, fs, v); + return Py_BuildValue("[fff]", v[0], v[1], v[2]); +} + +/*---------------------------------------------------------------------*/ + +/* F. Kenton Musgrave's fractal functions */ + +static PyObject *Noise_fractal(PyObject *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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 *UNUSED(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. */ + +PyDoc_STRVAR(random__doc__, +"() No arguments.\n\n\ +Returns a random floating point number in the range [0, 1)" +); + +PyDoc_STRVAR(random_unit_vector__doc__, +"() No arguments.\n\nReturns a random unit vector (3-float list)." +); + +PyDoc_STRVAR(seed_set__doc__, +"(seed value)\n\n\ +Initializes random number generator.\n\ +if seed is zero, the current time will be used instead." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(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." +); + +PyDoc_STRVAR(cell__doc__, +"((x,y,z) tuple)\n\n\ +returns cellnoise float value." +); + +PyDoc_STRVAR(cell_vector__doc__, +"((x,y,z) tuple)\n\n\ +returns cellnoise vector/point/color (3-float list)." +); + +PyDoc_STRVAR(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 *UNUSED(self)); +static PyObject *Noise_random_unit_vector(PyObject *UNUSED(self)); +static PyObject *Noise_seed_set(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_noise(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_vector(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_turbulence(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_fractal(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_vl_vector(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_hybrid_multi_fractal(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_voronoi(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_cell(PyObject *UNUSED(self), PyObject *args); +static PyObject *Noise_cell_vector(PyObject *UNUSED(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 */ + NULL, /* m_reload */ + NULL, /* m_traverse */ + NULL, /* m_clear */ + NULL, /* m_free */ +}; + +PyObject *BPyInit_noise(void) +{ + PyObject *submodule = PyModule_Create(&noise_module_def); + + /* use current time as seed for random number generator by default */ + setRndSeed(0); + + /* Constant noisetype dictionary */ + if (submodule) { + static PyStructSequence_Field noise_types_fields[] = { + {(char *)"BLENDER", NULL}, + {(char *)"STDPERLIN", NULL}, + {(char *)"NEWPERLIN", NULL}, + {(char *)"VORONOI_F1", NULL}, + {(char *)"VORONOI_F2", NULL}, + {(char *)"VORONOI_F3", NULL}, + {(char *)"VORONOI_F4", NULL}, + {(char *)"VORONOI_F2F1", NULL}, + {(char *)"VORONOI_CRACKLE", NULL}, + {(char *)"CELLNOISE", NULL}, + {NULL} + }; + + static PyStructSequence_Desc noise_types_info_desc = { + (char *)"noise.types", /* name */ + (char *)"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[] = { + {(char *)"DISTANCE", NULL}, + {(char *)"DISTANCE_SQUARED", NULL}, + {(char *)"MANHATTAN", NULL}, + {(char *)"CHEBYCHEV", NULL}, + {(char *)"MINKOVSKY_HALF", NULL}, + {(char *)"MINKOVSKY_FOUR", NULL}, + {(char *)"MINKOVSKY", NULL}, + {NULL} + }; + + static PyStructSequence_Desc noise_types_info_desc = { + (char *)"noise.distance_metrics", /* name */ + (char *)"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; +} |