Campbell Barton
de13d0a80c
While \file doesn't need an argument, it can't have another doxy command after it.
1064 lines
34 KiB
C
1064 lines
34 KiB
C
/*
|
|
* 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 unsigned long state[N]; /* the array for the state vector */
|
|
static int left = 1;
|
|
static int initf = 0;
|
|
static unsigned long *next;
|
|
static float state_offset_vector[3 * 3];
|
|
|
|
/* 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;
|
|
|
|
/* update vector offset */
|
|
{
|
|
const unsigned long *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 / (INT_MAX / range));
|
|
}
|
|
}
|
|
}
|
|
|
|
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;
|
|
}
|
|
|
|
/*------------------------------------------------------------*/
|
|
/* 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|$s:fractal", (char **)kwlist,
|
|
&value, &H, &lac, &oct, &noise_basis_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "fractal") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "fractal: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_fBm(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_multi_fractal_doc,
|
|
".. function:: multi_fractal(position, H, lacunarity, octaves, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns multifractal noise value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal increment factor.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The multifractal noise value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "Offf|$s:multi_fractal", (char **)kwlist,
|
|
&value, &H, &lac, &oct, &noise_basis_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "multi_fractal") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "multi_fractal: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_MultiFractal(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_variable_lacunarity_doc,
|
|
".. function:: variable_lacunarity(position, distortion, noise_type1='PERLIN_ORIGINAL', noise_type2='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns variable lacunarity noise value, a distorted variety of noise, from noise type 1 distorted by noise type 2 at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg distortion: The amount of distortion.\n"
|
|
" :type distortion: float\n"
|
|
" :arg noise_type1: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', 'VORONOI_F1', 'VORONOI_F2', " \
|
|
"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
|
|
"'CELLNOISE'].\n"
|
|
" :type noise_type1: string\n"
|
|
" :arg noise_type2: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', 'VORONOI_F1', 'VORONOI_F2', " \
|
|
"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
|
|
"'CELLNOISE'].\n"
|
|
" :type noise_type2: string\n"
|
|
" :return: The variable lacunarity noise value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_variable_lacunarity(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "noise_type1", "noise_type2", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_type1_str = NULL, *noise_type2_str = NULL;
|
|
float d;
|
|
int noise_type1_enum = DEFAULT_NOISE_TYPE, noise_type2_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "Of|$ss:variable_lacunarity", (char **)kwlist,
|
|
&value, &d, &noise_type1_str, &noise_type2_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_type1_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_type1_str, &noise_type1_enum, "variable_lacunarity") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_type2_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_type2_str, &noise_type2_enum, "variable_lacunarity") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "variable_lacunarity: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_VLNoise(vec[0], vec[1], vec[2], d, noise_type1_enum, noise_type2_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_hetero_terrain_doc,
|
|
".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns the heterogeneous terrain value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n"
|
|
BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The heterogeneous terrain value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "Offff|$s:hetero_terrain", (char **)kwlist,
|
|
&value, &H, &lac, &oct, &ofs, &noise_basis_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "hetero_terrain") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "hetero_terrain: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_HeteroTerrain(vec[0], vec[1], vec[2], H, lac, oct, ofs, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_hybrid_multi_fractal_doc,
|
|
".. function:: hybrid_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns hybrid multifractal value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n"
|
|
" :arg gain: Scaling applied to the values.\n"
|
|
" :type gain: float\n"
|
|
BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The hybrid multifractal value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_hybrid_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs, gn;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "Offfff|$s:hybrid_multi_fractal", (char **)kwlist,
|
|
&value, &H, &lac, &oct, &ofs, &gn, &noise_basis_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "hybrid_multi_fractal") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "hybrid_multi_fractal: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_HybridMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_ridged_multi_fractal_doc,
|
|
".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis='PERLIN_ORIGINAL')\n"
|
|
"\n"
|
|
" Returns ridged multifractal value from the noise basis at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :arg H: The fractal dimension of the roughest areas.\n"
|
|
" :type H: float\n"
|
|
" :arg lacunarity: The gap between successive frequencies.\n"
|
|
" :type lacunarity: float\n"
|
|
" :arg octaves: The number of different noise frequencies used.\n"
|
|
" :type octaves: int\n"
|
|
" :arg offset: The height of the terrain above 'sea level'.\n"
|
|
" :type offset: float\n"
|
|
" :arg gain: Scaling applied to the values.\n"
|
|
" :type gain: float\n"
|
|
BPY_NOISE_BASIS_ENUM_DOC
|
|
" :return: The ridged multifractal value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
|
|
PyObject *value;
|
|
float vec[3];
|
|
const char *noise_basis_str = NULL;
|
|
float H, lac, oct, ofs, gn;
|
|
int noise_basis_enum = DEFAULT_NOISE_TYPE;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "Offfff|$s:ridged_multi_fractal", (char **)kwlist,
|
|
&value, &H, &lac, &oct, &ofs, &gn, &noise_basis_str))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!noise_basis_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_types, noise_basis_str, &noise_basis_enum, "ridged_multi_fractal") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "ridged_multi_fractal: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(mg_RidgedMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_voronoi_doc,
|
|
".. function:: voronoi(position, distance_metric='DISTANCE', exponent=2.5)\n"
|
|
"\n"
|
|
" Returns a list of distances to the four closest features and their locations.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
BPY_NOISE_METRIC_ENUM_DOC
|
|
" :arg exponent: The exponent for Minkowski distance metric.\n"
|
|
" :type exponent: float\n"
|
|
" :return: A list of distances to the four closest features and their locations.\n"
|
|
" :rtype: list of four floats, list of four :class:`mathutils.Vector` types\n"
|
|
);
|
|
static PyObject *M_Noise_voronoi(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
|
|
{
|
|
static const char *kwlist[] = {"", "distance_metric", "exponent", NULL};
|
|
PyObject *value;
|
|
PyObject *list;
|
|
PyObject *ret;
|
|
float vec[3];
|
|
const char *metric_str = NULL;
|
|
float da[4], pa[12];
|
|
int metric_enum = DEFAULT_METRIC_TYPE;
|
|
float me = 2.5f; /* default minkowski exponent */
|
|
|
|
int i;
|
|
|
|
if (!PyArg_ParseTupleAndKeywords(
|
|
args, kw, "O|$sf:voronoi", (char **)kwlist,
|
|
&value, &metric_str, &me))
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (!metric_str) {
|
|
/* pass through */
|
|
}
|
|
else if (PyC_FlagSet_ValueFromID(
|
|
bpy_noise_metrics, metric_str, &metric_enum, "voronoi") == -1)
|
|
{
|
|
return NULL;
|
|
}
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "voronoi: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
list = PyList_New(4);
|
|
|
|
voronoi(vec[0], vec[1], vec[2], da, pa, me, metric_enum);
|
|
|
|
for (i = 0; i < 4; i++) {
|
|
PyObject *v = Vector_CreatePyObject(pa + 3 * i, 3, NULL);
|
|
PyList_SET_ITEM(list, i, v);
|
|
}
|
|
|
|
ret = Py_BuildValue("[[ffff]O]", da[0], da[1], da[2], da[3], list);
|
|
Py_DECREF(list);
|
|
return ret;
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_cell_doc,
|
|
".. function:: cell(position)\n"
|
|
"\n"
|
|
" Returns cell noise value at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :return: The cell noise value.\n"
|
|
" :rtype: float\n"
|
|
);
|
|
static PyObject *M_Noise_cell(PyObject *UNUSED(self), PyObject *args)
|
|
{
|
|
PyObject *value;
|
|
float vec[3];
|
|
|
|
if (!PyArg_ParseTuple(args, "O:cell", &value))
|
|
return NULL;
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "cell: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
return PyFloat_FromDouble(cellNoise(vec[0], vec[1], vec[2]));
|
|
}
|
|
|
|
PyDoc_STRVAR(M_Noise_cell_vector_doc,
|
|
".. function:: cell_vector(position)\n"
|
|
"\n"
|
|
" Returns cell noise vector at the specified position.\n"
|
|
"\n"
|
|
" :arg position: The position to evaluate the selected noise function.\n"
|
|
" :type position: :class:`mathutils.Vector`\n"
|
|
" :return: The cell noise vector.\n"
|
|
" :rtype: :class:`mathutils.Vector`\n"
|
|
);
|
|
static PyObject *M_Noise_cell_vector(PyObject *UNUSED(self), PyObject *args)
|
|
{
|
|
PyObject *value;
|
|
float vec[3], r_vec[3];
|
|
|
|
if (!PyArg_ParseTuple(args, "O:cell_vector", &value))
|
|
return NULL;
|
|
|
|
if (mathutils_array_parse(vec, 3, 3, value, "cell_vector: invalid 'position' arg") == -1)
|
|
return NULL;
|
|
|
|
cellNoiseV(vec[0], vec[1], vec[2], r_vec);
|
|
return Vector_CreatePyObject(r_vec, 3, NULL);
|
|
}
|
|
|
|
static PyMethodDef M_Noise_methods[] = {
|
|
{"seed_set", (PyCFunction) M_Noise_seed_set, METH_VARARGS, M_Noise_seed_set_doc},
|
|
{"random", (PyCFunction) M_Noise_random, METH_NOARGS, M_Noise_random_doc},
|
|
{"random_unit_vector", (PyCFunction) M_Noise_random_unit_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_random_unit_vector_doc},
|
|
{"random_vector", (PyCFunction) M_Noise_random_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_random_vector_doc},
|
|
{"noise", (PyCFunction) M_Noise_noise, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_doc},
|
|
{"noise_vector", (PyCFunction) M_Noise_noise_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_vector_doc},
|
|
{"turbulence", (PyCFunction) M_Noise_turbulence, METH_VARARGS | METH_KEYWORDS, M_Noise_turbulence_doc},
|
|
{"turbulence_vector", (PyCFunction) M_Noise_turbulence_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_turbulence_vector_doc},
|
|
{"fractal", (PyCFunction) M_Noise_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_fractal_doc},
|
|
{"multi_fractal", (PyCFunction) M_Noise_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_multi_fractal_doc},
|
|
{"variable_lacunarity", (PyCFunction) M_Noise_variable_lacunarity, METH_VARARGS | METH_KEYWORDS, M_Noise_variable_lacunarity_doc},
|
|
{"hetero_terrain", (PyCFunction) M_Noise_hetero_terrain, METH_VARARGS | METH_KEYWORDS, M_Noise_hetero_terrain_doc},
|
|
{"hybrid_multi_fractal", (PyCFunction) M_Noise_hybrid_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_hybrid_multi_fractal_doc},
|
|
{"ridged_multi_fractal", (PyCFunction) M_Noise_ridged_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_ridged_multi_fractal_doc},
|
|
{"voronoi", (PyCFunction) M_Noise_voronoi, METH_VARARGS | METH_KEYWORDS, M_Noise_voronoi_doc},
|
|
{"cell", (PyCFunction) M_Noise_cell, METH_VARARGS, M_Noise_cell_doc},
|
|
{"cell_vector", (PyCFunction) M_Noise_cell_vector, METH_VARARGS, M_Noise_cell_vector_doc},
|
|
{NULL, NULL, 0, NULL},
|
|
};
|
|
|
|
static struct PyModuleDef M_Noise_module_def = {
|
|
PyModuleDef_HEAD_INIT,
|
|
"mathutils.noise", /* m_name */
|
|
M_Noise_doc, /* m_doc */
|
|
0, /* m_size */
|
|
M_Noise_methods, /* m_methods */
|
|
NULL, /* m_reload */
|
|
NULL, /* m_traverse */
|
|
NULL, /* m_clear */
|
|
NULL, /* m_free */
|
|
};
|
|
|
|
/*----------------------------MODULE INIT-------------------------*/
|
|
PyMODINIT_FUNC PyInit_mathutils_noise(void)
|
|
{
|
|
PyObject *submodule = PyModule_Create(&M_Noise_module_def);
|
|
|
|
/* use current time as seed for random number generator by default */
|
|
setRndSeed(0);
|
|
|
|
return submodule;
|
|
}
|