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|
/*
* 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.
*/
/** \file
* \ingroup mathutils
*
* This file defines the 'noise' module, a general purpose module to access
* blenders noise functions.
*/
/************************/
/* Blender Noise Module */
/************************/
#include <Python.h>
#include "BLI_math.h"
#include "BLI_noise.h"
#include "BLI_utildefines.h"
#include "DNA_texture_types.h"
#include "../generic/py_capi_utils.h"
#include "mathutils.h"
#include "mathutils_noise.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)
*/
/* 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 ulong state[N]; /* the array for the state vector */
static int left = 1;
static int initf = 0;
static ulong *next;
static float state_offset_vector[3 * 3];
/* initializes state[N] with a seed */
static void init_genrand(ulong 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;
/* update vector offset */
{
const ulong *state_offset = &state[N - ARRAY_SIZE(state_offset_vector)];
const float range = 32; /* range in both pos/neg direction */
for (j = 0; j < ARRAY_SIZE(state_offset_vector); j++, state_offset++) {
/* overflow is fine here */
state_offset_vector[j] = (float)(int)(*state_offset) * (1.0f / ((float)INT_MAX / range));
}
}
}
static void next_state(void)
{
ulong *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)
{
ulong 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;
}
/*------------------------------------------------------------*/
/* Utility Functions */
/*------------------------------------------------------------*/
#define BPY_NOISE_BASIS_ENUM_DOC \
" :arg noise_basis: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', " \
"'VORONOI_F1', 'VORONOI_F2', " \
"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
"'CELLNOISE'].\n" \
" :type noise_basis: string\n"
#define BPY_NOISE_METRIC_ENUM_DOC \
" :arg distance_metric: Enumerator in ['DISTANCE', 'DISTANCE_SQUARED', 'MANHATTAN', " \
"'CHEBYCHEV', " \
"'MINKOVSKY', 'MINKOVSKY_HALF', 'MINKOVSKY_FOUR'].\n" \
" :type distance_metric: string\n"
/* Noise basis enum */
#define DEFAULT_NOISE_TYPE TEX_STDPERLIN
static PyC_FlagSet bpy_noise_types[] = {
{TEX_BLENDER, "BLENDER"},
{TEX_STDPERLIN, "PERLIN_ORIGINAL"},
{TEX_NEWPERLIN, "PERLIN_NEW"},
{TEX_VORONOI_F1, "VORONOI_F1"},
{TEX_VORONOI_F2, "VORONOI_F2"},
{TEX_VORONOI_F3, "VORONOI_F3"},
{TEX_VORONOI_F4, "VORONOI_F4"},
{TEX_VORONOI_F2F1, "VORONOI_F2F1"},
{TEX_VORONOI_CRACKLE, "VORONOI_CRACKLE"},
{TEX_CELLNOISE, "CELLNOISE"},
{0, NULL},
};
/* Metric basis enum */
#define DEFAULT_METRIC_TYPE TEX_DISTANCE
static PyC_FlagSet bpy_noise_metrics[] = {
{TEX_DISTANCE, "DISTANCE"},
{TEX_DISTANCE_SQUARED, "DISTANCE_SQUARED"},
{TEX_MANHATTAN, "MANHATTAN"},
{TEX_CHEBYCHEV, "CHEBYCHEV"},
{TEX_MINKOVSKY, "MINKOVSKY"},
{TEX_MINKOVSKY_HALF, "MINKOVSKY_HALF"},
{TEX_MINKOVSKY_FOUR, "MINKOVSKY_FOUR"},
{0, NULL},
};
/* Fills an array of length size with random numbers in the range (-1, 1)*/
static void rand_vn(float *array_tar, const int size)
{
float *array_pt = array_tar + (size - 1);
int i = size;
while (i--) {
*(array_pt--) = 2.0f * frand() - 1.0f;
}
}
/* Fills an array of length 3 with noise values */
static void noise_vector(float x, float y, float z, int nb, float v[3])
{
/* Simply evaluate noise at 3 different positions */
const float *ofs = state_offset_vector;
for (int j = 0; j < 3; j++) {
v[j] = (2.0f * BLI_gNoise(1.0f, x + ofs[0], y + ofs[1], z + ofs[2], 0, nb) - 1.0f);
ofs += 3;
}
}
/* Returns a turbulence value for a given position (x, y, z) */
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;
}
/* Fills an array of length 3 with the turbulence vector for a given
* position (x, y, z) */
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];
}
}
/*-------------------------DOC STRINGS ---------------------------*/
PyDoc_STRVAR(M_Noise_doc, "The Blender noise module");
/*------------------------------------------------------------*/
/* Python Functions */
/*------------------------------------------------------------*/
PyDoc_STRVAR(M_Noise_random_doc,
".. function:: random()\n"
"\n"
" Returns a random number in the range [0, 1).\n"
"\n"
" :return: The random number.\n"
" :rtype: float\n");
static PyObject *M_Noise_random(PyObject *UNUSED(self))
{
return PyFloat_FromDouble(frand());
}
PyDoc_STRVAR(M_Noise_random_unit_vector_doc,
".. function:: random_unit_vector(size=3)\n"
"\n"
" Returns a unit vector with random entries.\n"
"\n"
" :arg size: The size of the vector to be produced, in the range [2, 4].\n"
" :type size: int\n"
" :return: The random unit vector.\n"
" :rtype: :class:`mathutils.Vector`\n");
static PyObject *M_Noise_random_unit_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"size", NULL};
float vec[4] = {0.0f, 0.0f, 0.0f, 0.0f};
float norm = 2.0f;
int size = 3;
if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_unit_vector", (char **)kwlist, &size)) {
return NULL;
}
if (size > 4 || size < 2) {
PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
return NULL;
}
while (norm == 0.0f || norm > 1.0f) {
rand_vn(vec, size);
norm = normalize_vn(vec, size);
}
return Vector_CreatePyObject(vec, size, NULL);
}
PyDoc_STRVAR(M_Noise_random_vector_doc,
".. function:: random_vector(size=3)\n"
"\n"
" Returns a vector with random entries in the range (-1, 1).\n"
"\n"
" :arg size: The size of the vector to be produced.\n"
" :type size: int\n"
" :return: The random vector.\n"
" :rtype: :class:`mathutils.Vector`\n");
static PyObject *M_Noise_random_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"size", NULL};
float *vec = NULL;
int size = 3;
if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_vector", (char **)kwlist, &size)) {
return NULL;
}
if (size < 2) {
PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
return NULL;
}
vec = PyMem_New(float, size);
rand_vn(vec, size);
return Vector_CreatePyObject_alloc(vec, size, NULL);
}
PyDoc_STRVAR(M_Noise_seed_set_doc,
".. function:: seed_set(seed)\n"
"\n"
" Sets the random seed used for random_unit_vector, and random.\n"
"\n"
" :arg seed: Seed used for the random generator.\n"
" When seed is zero, the current time will be used instead.\n"
" :type seed: int\n");
static PyObject *M_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;
}
PyDoc_STRVAR(M_Noise_noise_doc,
".. function:: noise(position, noise_basis='PERLIN_ORIGINAL')\n"
"\n"
" 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)
{
static const char *kwlist[] = {"", "noise_basis", NULL};
PyObject *value;
float vec[3];
const char *noise_basis_str = NULL;
int noise_basis_enum = DEFAULT_NOISE_TYPE;
if (!PyArg_ParseTupleAndKeywords(
args, kw, "O|$s:noise", (char **)kwlist, &value, &noise_basis_str)) {
return NULL;
}
if (!noise_basis_str) {
/* pass through */
}
else if (PyC_FlagSet_ValueFromID(bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise") ==
-1) {
return NULL;
}
if (mathutils_array_parse(vec, 3, 3, value, "noise: invalid 'position' arg") == -1) {
return NULL;
}
return PyFloat_FromDouble(
(2.0f * BLI_gNoise(1.0f, vec[0], vec[1], vec[2], 0, noise_basis_enum) - 1.0f));
}
PyDoc_STRVAR(M_Noise_noise_vector_doc,
".. function:: noise_vector(position, noise_basis='PERLIN_ORIGINAL')\n"
"\n"
" Returns the noise vector from the noise basis at the specified position.\n"
"\n"
" :arg position: The position to evaluate the selected noise function.\n"
" :type position: :class:`mathutils.Vector`\n" BPY_NOISE_BASIS_ENUM_DOC
" :return: The noise vector.\n"
" :rtype: :class:`mathutils.Vector`\n");
static PyObject *M_Noise_noise_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"", "noise_basis", NULL};
PyObject *value;
float vec[3], r_vec[3];
const char *noise_basis_str = NULL;
int noise_basis_enum = DEFAULT_NOISE_TYPE;
if (!PyArg_ParseTupleAndKeywords(
args, kw, "O|$s:noise_vector", (char **)kwlist, &value, &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, "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|$s:fractal",
(char **)kwlist,
&value,
&H,
&lac,
&oct,
&noise_basis_str)) {
return NULL;
}
if (!noise_basis_str) {
/* pass through */
}
else if (PyC_FlagSet_ValueFromID(
bpy_noise_types, noise_basis_str, &noise_basis_enum, "fractal") == -1) {
return NULL;
}
if (mathutils_array_parse(vec, 3, 3, value, "fractal: invalid 'position' arg") == -1) {
return NULL;
}
return PyFloat_FromDouble(BLI_mg_fBm(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
}
PyDoc_STRVAR(
M_Noise_multi_fractal_doc,
".. function:: multi_fractal(position, H, lacunarity, octaves, "
"noise_basis='PERLIN_ORIGINAL')\n"
"\n"
" Returns multifractal noise value from the noise basis at the specified position.\n"
"\n"
" :arg position: The position to evaluate the selected noise function.\n"
" :type position: :class:`mathutils.Vector`\n"
" :arg H: The fractal increment factor.\n"
" :type H: float\n"
" :arg lacunarity: The gap between successive frequencies.\n"
" :type lacunarity: float\n"
" :arg octaves: The number of different noise frequencies used.\n"
" :type octaves: int\n" BPY_NOISE_BASIS_ENUM_DOC
" :return: The multifractal noise value.\n"
" :rtype: float\n");
static PyObject *M_Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
PyObject *value;
float vec[3];
const char *noise_basis_str = NULL;
float H, lac, oct;
int noise_basis_enum = DEFAULT_NOISE_TYPE;
if (!PyArg_ParseTupleAndKeywords(args,
kw,
"Offf|$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(
BLI_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|$ss:variable_lacunarity",
(char **)kwlist,
&value,
&d,
&noise_type1_str,
&noise_type2_str)) {
return NULL;
}
if (!noise_type1_str) {
/* pass through */
}
else if (PyC_FlagSet_ValueFromID(
bpy_noise_types, noise_type1_str, &noise_type1_enum, "variable_lacunarity") == -1) {
return NULL;
}
if (!noise_type2_str) {
/* pass through */
}
else if (PyC_FlagSet_ValueFromID(
bpy_noise_types, noise_type2_str, &noise_type2_enum, "variable_lacunarity") == -1) {
return NULL;
}
if (mathutils_array_parse(vec, 3, 3, value, "variable_lacunarity: invalid 'position' arg") ==
-1) {
return NULL;
}
return PyFloat_FromDouble(
BLI_mg_VLNoise(vec[0], vec[1], vec[2], d, noise_type1_enum, noise_type2_enum));
}
PyDoc_STRVAR(
M_Noise_hetero_terrain_doc,
".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, "
"noise_basis='PERLIN_ORIGINAL')\n"
"\n"
" Returns the heterogeneous terrain value from the noise basis at the specified position.\n"
"\n"
" :arg position: The position to evaluate the selected noise function.\n"
" :type position: :class:`mathutils.Vector`\n"
" :arg H: The fractal dimension of the roughest areas.\n"
" :type H: float\n"
" :arg lacunarity: The gap between successive frequencies.\n"
" :type lacunarity: float\n"
" :arg octaves: The number of different noise frequencies used.\n"
" :type octaves: int\n"
" :arg offset: The height of the terrain above 'sea level'.\n"
" :type offset: float\n" BPY_NOISE_BASIS_ENUM_DOC
" :return: The heterogeneous terrain value.\n"
" :rtype: float\n");
static PyObject *M_Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"", "", "", "", "", "noise_basis", NULL};
PyObject *value;
float vec[3];
const char *noise_basis_str = NULL;
float H, lac, oct, ofs;
int noise_basis_enum = DEFAULT_NOISE_TYPE;
if (!PyArg_ParseTupleAndKeywords(args,
kw,
"Offff|$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(
BLI_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|$s:hybrid_multi_fractal",
(char **)kwlist,
&value,
&H,
&lac,
&oct,
&ofs,
&gn,
&noise_basis_str)) {
return NULL;
}
if (!noise_basis_str) {
/* pass through */
}
else if (PyC_FlagSet_ValueFromID(
bpy_noise_types, noise_basis_str, &noise_basis_enum, "hybrid_multi_fractal") ==
-1) {
return NULL;
}
if (mathutils_array_parse(vec, 3, 3, value, "hybrid_multi_fractal: invalid 'position' arg") ==
-1) {
return NULL;
}
return PyFloat_FromDouble(
BLI_mg_HybridMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
}
PyDoc_STRVAR(
M_Noise_ridged_multi_fractal_doc,
".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, "
"noise_basis='PERLIN_ORIGINAL')\n"
"\n"
" Returns ridged multifractal value from the noise basis at the specified position.\n"
"\n"
" :arg position: The position to evaluate the selected noise function.\n"
" :type position: :class:`mathutils.Vector`\n"
" :arg H: The fractal dimension of the roughest areas.\n"
" :type H: float\n"
" :arg lacunarity: The gap between successive frequencies.\n"
" :type lacunarity: float\n"
" :arg octaves: The number of different noise frequencies used.\n"
" :type octaves: int\n"
" :arg offset: The height of the terrain above 'sea level'.\n"
" :type offset: float\n"
" :arg gain: Scaling applied to the values.\n"
" :type gain: float\n" BPY_NOISE_BASIS_ENUM_DOC
" :return: The ridged multifractal value.\n"
" :rtype: float\n");
static PyObject *M_Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
{
static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
PyObject *value;
float vec[3];
const char *noise_basis_str = NULL;
float H, lac, oct, ofs, gn;
int noise_basis_enum = DEFAULT_NOISE_TYPE;
if (!PyArg_ParseTupleAndKeywords(args,
kw,
"Offfff|$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(
BLI_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);
BLI_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(BLI_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;
}
BLI_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;
}
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