apply back changes made since moving this file.
This commit is contained in:
Campbell Barton
@@ -25,8 +25,8 @@
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* ***** END GPL LICENSE BLOCK *****
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*/
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/** \file blender/python/generic/noise_py_api.c
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* \ingroup pygen
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/** \file blender/python/mathutils/mathutils_noise.c
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* \ingroup mathutils
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*
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* This file defines the 'noise' module, a general purpose module to access
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* blenders noise functions.
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@@ -42,11 +42,24 @@
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#include "structseq.h"
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#include "BLI_blenlib.h"
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#include "BLI_math.h"
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#include "BLI_utildefines.h"
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#include "MEM_guardedalloc.h"
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#include "DNA_texture_types.h"
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#include "noise_py_api.h"
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#include "mathutils.h"
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#include "mathutils_noise.h"
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/* 2.6 update
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* Moved to submodule of mathutils.
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* All vector functions now return mathutils.Vector
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* Updated docs to be compatible with autodocs generation.
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* Updated vector functions to use nD array functions.
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* noise.vl_vector --> noise.variable_lacunarity
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* noise.vector --> noise.noise_vector
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*/
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/*-----------------------------------------*/
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/* 'mersenne twister' random number generator */
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@@ -96,25 +109,6 @@
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email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
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*/
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/* 2.5 update
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* Noise.setRandomSeed --> seed_set
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* Noise.randuvec --> random_unit_vector
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* Noise.vNoise --> noise_vector
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* Noise.vTurbulence --> turbulence_vector
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* Noise.multiFractal --> multi_fractal
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* Noise.cellNoise --> cell
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* Noise.cellNoiseV --> cell_vector
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* Noise.vlNoise --> vl_vector
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* Noise.heteroTerrain --> hetero_terrain
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* Noise.hybridMFractal --> hybrid_multi_fractal
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* Noise.fBm --> fractal
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* Noise.ridgedMFractal --> ridged_multi_fractal
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*
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* Const's *
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* Noise.NoiseTypes --> types
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* Noise.DistanceMetrics --> distance_metrics
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*/
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/* Period parameters */
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#define N 624
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#define M 397
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@@ -198,91 +192,28 @@ static float frand(void)
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return (float) y / 4294967296.f;
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}
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/*------------------------------------------------------------*/
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/* Utility Functions */
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/*------------------------------------------------------------*/
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/* returns random unit vector */
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static void randuvec(float v[3])
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/* Fills an array of length size with random numbers in the range (-1, 1)*/
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static void rand_vn(float *array_tar, const int size)
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{
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float r;
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v[2] = 2.f * frand() - 1.f;
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if ((r = 1.f - v[2] * v[2]) > 0.f) {
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float a = (float)(6.283185307f * frand());
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r = (float)sqrt(r);
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v[0] = (float)(r * cosf(a));
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v[1] = (float)(r * sinf(a));
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}
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else {
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v[2] = 1.f;
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}
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float *array_pt = array_tar + (size-1);
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int i = size;
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while (i--) { *(array_pt--) = 2.0f * frand() - 1.0f; }
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}
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static PyObject *Noise_random(PyObject *UNUSED(self))
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{
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return PyFloat_FromDouble(frand());
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}
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static PyObject *Noise_random_unit_vector(PyObject *UNUSED(self))
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{
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float v[3] = {0.0f, 0.0f, 0.0f};
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randuvec(v);
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return Py_BuildValue("[fff]", v[0], v[1], v[2]);
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}
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/*---------------------------------------------------------------------*/
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/* Random seed init. Only used for MT random() & randuvec() */
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static PyObject *Noise_seed_set(PyObject *UNUSED(self), PyObject *args)
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||||
{
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int s;
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if (!PyArg_ParseTuple(args, "i:seed_set", &s))
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return NULL;
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setRndSeed(s);
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Py_RETURN_NONE;
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}
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||||
|
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/*-------------------------------------------------------------------------*/
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/* General noise */
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static PyObject *Noise_noise(PyObject *UNUSED(self), PyObject *args)
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{
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float x, y, z;
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int nb = 1;
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if (!PyArg_ParseTuple(args, "(fff)|i:noise", &x, &y, &z, &nb))
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return NULL;
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return PyFloat_FromDouble((2.0f * BLI_gNoise(1.0f, x, y, z, 0, nb) - 1.0f));
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}
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/*-------------------------------------------------------------------------*/
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||||
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/* General Vector noise */
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/* Fills an array of length 3 with noise values */
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static void noise_vector(float x, float y, float z, int nb, float v[3])
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{
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/* Simply evaluate noise at 3 different positions */
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v[0]= (float)(2.0f * BLI_gNoise(1.f, x + 9.321f, y - 1.531f, z - 7.951f, 0,
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nb) - 1.0f);
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v[1]= (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f);
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v[2]= (float)(2.0f * BLI_gNoise(1.f, x + 6.327f, y + 0.1671f, z - 2.672f, 0,
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nb) - 1.0f);
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v[0] = (float)(2.0f * BLI_gNoise(1.f, x + 9.321f, y - 1.531f, z - 7.951f, 0, nb) - 1.0f);
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v[1] = (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f);
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v[2] = (float)(2.0f * BLI_gNoise(1.f, x + 6.327f, y + 0.1671f, z - 2.672f, 0, nb) - 1.0f);
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}
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static PyObject *Noise_vector(PyObject *UNUSED(self), PyObject *args)
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{
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float x, y, z, v[3];
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int nb = 1;
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if (!PyArg_ParseTuple(args, "(fff)|i:vector", &x, &y, &z, &nb))
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return NULL;
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noise_vector(x, y, z, nb, v);
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return Py_BuildValue("[fff]", v[0], v[1], v[2]);
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}
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||||
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||||
/*---------------------------------------------------------------------------*/
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||||
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||||
/* General turbulence */
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||||
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||||
/* Returns a turbulence value for a given position (x, y, z) */
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||||
static float turb(float x, float y, float z, int oct, int hard, int nb,
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||||
float ampscale, float freqscale)
|
||||
{
|
||||
@@ -305,21 +236,8 @@ static float turb(float x, float y, float z, int oct, int hard, int nb,
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return out;
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||||
}
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||||
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static PyObject *Noise_turbulence(PyObject *UNUSED(self), PyObject *args)
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||||
{
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float x, y, z;
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||||
int oct, hd, nb = 1;
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||||
float as = 0.5, fs = 2.0;
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||||
if (!PyArg_ParseTuple(args, "(fff)ii|iff:turbulence", &x, &y, &z, &oct, &hd, &nb, &as, &fs))
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||||
return NULL;
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||||
|
||||
return PyFloat_FromDouble(turb(x, y, z, oct, hd, nb, as, fs));
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||||
}
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||||
|
||||
/*--------------------------------------------------------------------------*/
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||||
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/* Turbulence Vector */
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||||
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||||
/* Fills an array of length 3 with the turbulence vector for a given
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position (x, y, z) */
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||||
static void vTurb(float x, float y, float z, int oct, int hard, int nb,
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float ampscale, float freqscale, float v[3])
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{
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||||
@@ -349,444 +267,645 @@ static void vTurb(float x, float y, float z, int oct, int hard, int nb,
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||||
}
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||||
}
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||||
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||||
static PyObject *Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args)
|
||||
/*-------------------------DOC STRINGS ---------------------------*/
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||||
PyDoc_STRVAR(M_Noise_doc,
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"The Blender noise module"
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||||
);
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||||
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||||
/*------------------------------------------------------------*/
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||||
/* Python Functions */
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||||
/*------------------------------------------------------------*/
|
||||
|
||||
PyDoc_STRVAR(M_Noise_random_doc,
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".. function:: random()\n"
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||||
"\n"
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||||
" Returns a random number in the range [0, 1].\n"
|
||||
"\n"
|
||||
" :return: The random number.\n"
|
||||
" :rtype: float\n"
|
||||
);
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||||
static PyObject *M_Noise_random(PyObject *UNUSED(self))
|
||||
{
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||||
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]);
|
||||
return PyFloat_FromDouble(frand());
|
||||
}
|
||||
|
||||
/*---------------------------------------------------------------------*/
|
||||
|
||||
/* F. Kenton Musgrave's fractal functions */
|
||||
|
||||
static PyObject *Noise_fractal(PyObject *UNUSED(self), PyObject *args)
|
||||
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.\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)
|
||||
{
|
||||
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));
|
||||
}
|
||||
float vec[4] = {0.0f, 0.0f, 0.0f, 0.0f};
|
||||
float norm = 2.0f;
|
||||
int size = 3;
|
||||
|
||||
/*------------------------------------------------------------------------*/
|
||||
|
||||
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))
|
||||
if (!PyArg_ParseTuple(args, "|i:random_vector", &size))
|
||||
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))
|
||||
if (size > 4 || size < 2) {
|
||||
PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
|
||||
return NULL;
|
||||
return PyFloat_FromDouble(mg_VLNoise(x, y, z, d, nt1, nt2));
|
||||
}
|
||||
|
||||
while (norm == 0.0f || norm >= 1.0f) {
|
||||
rand_vn(vec, size);
|
||||
norm = normalize_vn(vec, size);
|
||||
}
|
||||
|
||||
return Vector_CreatePyObject(vec, size, Py_NEW, NULL);
|
||||
}
|
||||
|
||||
/*-------------------------------------------------------------------------*/
|
||||
|
||||
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 */
|
||||
/* This is dumb, most people will want a unit vector anyway, since this doesn't have uniform distribution over a sphere*/
|
||||
/*
|
||||
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);
|
||||
PyDoc_STRVAR(M_Noise_random_vector_doc,
|
||||
".. function:: random_vector(size=3)\n"
|
||||
"\n"
|
||||
" Returns a vector with random entries in the range [0, 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)
|
||||
{
|
||||
float vec[4]= {0.0f, 0.0f, 0.0f, 0.0f};
|
||||
int size= 3;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "|i:random_vector", &size))
|
||||
return NULL;
|
||||
|
||||
if (size > 4 || size < 2) {
|
||||
PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
|
||||
return NULL;
|
||||
}
|
||||
|
||||
rand_vn(vec, size);
|
||||
|
||||
return Vector_CreatePyObject(vec, size, Py_NEW, NULL);
|
||||
}
|
||||
*/
|
||||
|
||||
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__},
|
||||
PyDoc_STRVAR(M_Noise_seed_set_doc,
|
||||
".. function:: seed_set(seed)\n"
|
||||
"\n"
|
||||
" Sets the random seed used for random_unit_vector, random_vector and random.\n"
|
||||
"\n"
|
||||
" :arg seed: Seed used for the random generator.\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=noise.types.STDPERLIN)\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 at.\n"
|
||||
" :type position: :class:`mathutils.Vector`\n"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The noise value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_noise(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
int nb = 1;
|
||||
if (!PyArg_ParseTuple(args, "O|i:noise", &value, &nb))
|
||||
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, nb) - 1.0f));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_noise_vector_doc,
|
||||
".. function:: noise_vector(position, noise_basis=noise.types.STDPERLIN)\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 at.\n"
|
||||
" :type position: :class:`mathutils.Vector`\n"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The noise vector.\n"
|
||||
" :rtype: :class:`mathutils.Vector`\n"
|
||||
);
|
||||
static PyObject *M_Noise_noise_vector(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3], r_vec[3];
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "O|i:noise_vector", &value, &nb))
|
||||
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], nb, r_vec);
|
||||
|
||||
return Vector_CreatePyObject(r_vec, 3, Py_NEW, NULL);
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_turbulence_doc,
|
||||
".. function:: turbulence(position, octaves, hard, noise_basis=noise.types.STDPERLIN, 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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in mathutils.noise.types or int\n"
|
||||
" :arg amplitude_scale: The amplitude scaling factor.\n"
|
||||
" :type amplitude_scale: float\n"
|
||||
" :arg frequency_scale: The frequency scaling factor\n"
|
||||
" :type frequency_scale: Value in noise.types or int\n"
|
||||
" :return: The turbulence value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_turbulence(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
int oct, hd, nb = 1;
|
||||
float as = 0.5f, fs = 2.0f;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Oii|iff:turbulence", &value, &oct, &hd, &nb, &as, &fs))
|
||||
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, nb, as, fs));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_turbulence_vector_doc,
|
||||
".. function:: turbulence_vector(position, octaves, hard, noise_basis=noise.types.STDPERLIN, 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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in mathutils.noise.types or int\n"
|
||||
" :arg amplitude_scale: The amplitude scaling factor.\n"
|
||||
" :type amplitude_scale: float\n"
|
||||
" :arg frequency_scale: The frequency scaling factor\n"
|
||||
" :type frequency_scale: Value in noise.types or int\n"
|
||||
" :return: The turbulence vector.\n"
|
||||
" :rtype: :class:`mathutils.Vector`\n"
|
||||
);
|
||||
static PyObject *M_Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3], r_vec[3];
|
||||
int oct, hd, nb = 1;
|
||||
float as =0.5f, fs = 2.0f;
|
||||
if (!PyArg_ParseTuple(args, "Oii|iff:turbulence_vector", &value, &oct, &hd, &nb, &as, &fs))
|
||||
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, nb, as, fs, r_vec);
|
||||
return Vector_CreatePyObject(r_vec, 3, Py_NEW, NULL);
|
||||
}
|
||||
|
||||
/* F. Kenton Musgrave's fractal functions */
|
||||
PyDoc_STRVAR(M_Noise_fractal_doc,
|
||||
".. function:: fractal(position, H, lacunarity, octaves, noise_basis=noise.types.STDPERLIN)\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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The fractal Brownian motion noise value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_fractal(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float H, lac, oct;
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Offf|i:fractal", &value, &H, &lac, &oct, &nb))
|
||||
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, nb));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_multi_fractal_doc,
|
||||
".. function:: multi_fractal(position, H, lacunarity, octaves, noise_basis=noise.types.STDPERLIN)\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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The multifractal noise value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float H, lac, oct;
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Offf|i:multi_fractal", &value, &H, &lac, &oct, &nb))
|
||||
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, nb));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_variable_lacunarity_doc,
|
||||
".. function:: variable_lacunarity(position, distortion, noise_type1=noise.types.STDPERLIN, noise_type2=noise.types.STDPERLIN)\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 at.\n"
|
||||
" :type position: :class:`mathutils.Vector`\n"
|
||||
" :arg distortion: The amount of distortion.\n"
|
||||
" :type distortion: float\n"
|
||||
" :arg noise_type1: The type of noise to be distorted.\n"
|
||||
" :type noise_type1: Value in noise.types or int\n"
|
||||
" :arg noise_type2: The type of noise used to distort noise_type1.\n"
|
||||
" :type noise_type2: Value in noise.types or int\n"
|
||||
" :return: The variable lacunarity noise value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_variable_lacunarity(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float d;
|
||||
int nt1 = 1, nt2 = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Of|ii:variable_lacunarity", &value, &d, &nt1, &nt2))
|
||||
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, nt1, nt2));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_hetero_terrain_doc,
|
||||
".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, noise_basis=noise.types.STDPERLIN)\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 at.\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 noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The heterogeneous terrain value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float H, lac, oct, ofs;
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Offff|i:hetero_terrain", &value, &H, &lac, &oct, &ofs, &nb))
|
||||
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, nb));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_hybrid_multi_fractal_doc,
|
||||
".. function:: hybrid_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis=noise.types.STDPERLIN)\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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The hybrid multifractal value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_hybrid_multi_fractal(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float H, lac, oct, ofs, gn;
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Offfff|i:hybrid_multi_fractal", &value, &H, &lac, &oct, &ofs, &gn, &nb))
|
||||
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, nb));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_ridged_multi_fractal_doc,
|
||||
".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis=noise.types.STDPERLIN)\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 at.\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"
|
||||
" :arg noise_basis: The type of noise to be evaluated.\n"
|
||||
" :type noise_basis: Value in noise.types or int\n"
|
||||
" :return: The ridged multifractal value.\n"
|
||||
" :rtype: float\n"
|
||||
);
|
||||
static PyObject *M_Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
float vec[3];
|
||||
float H, lac, oct, ofs, gn;
|
||||
int nb = 1;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "Offfff|i:ridged_multi_fractal", &value, &H, &lac, &oct, &ofs, &gn, &nb))
|
||||
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, nb));
|
||||
}
|
||||
|
||||
PyDoc_STRVAR(M_Noise_voronoi_doc,
|
||||
".. function:: voronoi(position, distance_metric=noise.distance_metrics.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 at.\n"
|
||||
" :type position: :class:`mathutils.Vector`\n"
|
||||
" :arg distance_metric: Method of measuring distance.\n"
|
||||
" :type distance_metric: Value in noise.distance_metrics or int\n"
|
||||
" :arg exponent: The exponent for Minkovsky 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`s\n"
|
||||
);
|
||||
static PyObject *M_Noise_voronoi(PyObject *UNUSED(self), PyObject *args)
|
||||
{
|
||||
PyObject *value;
|
||||
PyObject *list;
|
||||
float vec[3];
|
||||
float da[4], pa[12];
|
||||
int dtype = 0;
|
||||
float me = 2.5f; /* default minkovsky exponent */
|
||||
|
||||
int i;
|
||||
|
||||
if (!PyArg_ParseTuple(args, "O|if:voronoi", &value, &dtype, &me))
|
||||
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, dtype);
|
||||
|
||||
for (i = 0; i < 4; i++) {
|
||||
PyList_SET_ITEM(list, i, Vector_CreatePyObject(pa + 3 * i, 3, Py_NEW, NULL));
|
||||
}
|
||||
|
||||
return Py_BuildValue("[[ffff]O]", da[0], da[1], da[2], da[3], list);
|
||||
}
|
||||
|
||||
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 at.\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 at.\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(NULL, 3, Py_NEW, 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, M_Noise_random_unit_vector_doc},
|
||||
/*{"random_vector", (PyCFunction) M_Noise_random_vector, METH_VARARGS, M_Noise_random_vector_doc},*/
|
||||
{"noise", (PyCFunction) M_Noise_noise, METH_VARARGS, M_Noise_noise_doc},
|
||||
{"noise_vector", (PyCFunction) M_Noise_noise_vector, METH_VARARGS, M_Noise_noise_vector_doc},
|
||||
{"turbulence", (PyCFunction) M_Noise_turbulence, METH_VARARGS, M_Noise_turbulence_doc},
|
||||
{"turbulence_vector", (PyCFunction) M_Noise_turbulence_vector, METH_VARARGS, M_Noise_turbulence_vector_doc},
|
||||
{"fractal", (PyCFunction) M_Noise_fractal, METH_VARARGS, M_Noise_fractal_doc},
|
||||
{"multi_fractal", (PyCFunction) M_Noise_multi_fractal, METH_VARARGS, M_Noise_multi_fractal_doc},
|
||||
{"variable_lacunarity", (PyCFunction) M_Noise_variable_lacunarity, METH_VARARGS, M_Noise_variable_lacunarity_doc},
|
||||
{"hetero_terrain", (PyCFunction) M_Noise_hetero_terrain, METH_VARARGS, M_Noise_hetero_terrain_doc},
|
||||
{"hybrid_multi_fractal", (PyCFunction) M_Noise_hybrid_multi_fractal, METH_VARARGS, M_Noise_hybrid_multi_fractal_doc},
|
||||
{"ridged_multi_fractal", (PyCFunction) M_Noise_ridged_multi_fractal, METH_VARARGS, M_Noise_ridged_multi_fractal_doc},
|
||||
{"voronoi", (PyCFunction) M_Noise_voronoi, METH_VARARGS, 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 noise_module_def = {
|
||||
static struct PyModuleDef M_Noise_module_def = {
|
||||
PyModuleDef_HEAD_INIT,
|
||||
"noise", /* m_name */
|
||||
Noise__doc__, /* m_doc */
|
||||
"mathutils.noise", /* m_name */
|
||||
M_Noise_doc, /* m_doc */
|
||||
0, /* m_size */
|
||||
NoiseMethods, /* m_methods */
|
||||
M_Noise_methods, /* m_methods */
|
||||
NULL, /* m_reload */
|
||||
NULL, /* m_traverse */
|
||||
NULL, /* m_clear */
|
||||
NULL, /* m_free */
|
||||
};
|
||||
|
||||
PyObject *BPyInit_noise(void)
|
||||
/*----------------------------MODULE INIT-------------------------*/
|
||||
PyMODINIT_FUNC PyInit_mathutils_noise(void)
|
||||
{
|
||||
PyObject *submodule = PyModule_Create(&noise_module_def);
|
||||
PyObject *submodule = PyModule_Create(&M_Noise_module_def);
|
||||
PyObject *item_types, *item_metrics;
|
||||
|
||||
/* use current time as seed for random number generator by default */
|
||||
setRndSeed(0);
|
||||
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}
|
||||
};
|
||||
PyModule_AddObject(submodule, "types", (item_types = PyInit_mathutils_noise_types()));
|
||||
PyDict_SetItemString(PyThreadState_GET()->interp->modules, "noise.types", item_types);
|
||||
Py_INCREF(item_types);
|
||||
|
||||
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);
|
||||
}
|
||||
PyModule_AddObject(submodule, "distance_metrics", (item_metrics = PyInit_mathutils_noise_metrics()));
|
||||
PyDict_SetItemString(PyThreadState_GET()->interp->modules, "noise.distance_metrics", item_metrics);
|
||||
Py_INCREF(item_metrics);
|
||||
|
||||
return submodule;
|
||||
}
|
||||
|
||||
/*----------------------------SUBMODULE INIT-------------------------*/
|
||||
static struct PyModuleDef M_NoiseTypes_module_def = {
|
||||
PyModuleDef_HEAD_INIT,
|
||||
"mathutils.noise.types", /* m_name */
|
||||
NULL, /* m_doc */
|
||||
0, /* m_size */
|
||||
NULL, /* m_methods */
|
||||
NULL, /* m_reload */
|
||||
NULL, /* m_traverse */
|
||||
NULL, /* m_clear */
|
||||
NULL, /* m_free */
|
||||
};
|
||||
|
||||
PyMODINIT_FUNC PyInit_mathutils_noise_types(void)
|
||||
{
|
||||
PyObject *submodule = PyModule_Create(&M_NoiseTypes_module_def);
|
||||
|
||||
PyModule_AddIntConstant(submodule, (char *)"BLENDER", TEX_BLENDER);
|
||||
PyModule_AddIntConstant(submodule, (char *)"STDPERLIN", TEX_STDPERLIN);
|
||||
PyModule_AddIntConstant(submodule, (char *)"NEWPERLIN", TEX_NEWPERLIN);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_F1", TEX_VORONOI_F1);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_F2", TEX_VORONOI_F2);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_F3", TEX_VORONOI_F3);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_F4", TEX_VORONOI_F4);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_F2F1", TEX_VORONOI_F2F1);
|
||||
PyModule_AddIntConstant(submodule, (char *)"VORONOI_CRACKLE", TEX_VORONOI_CRACKLE);
|
||||
PyModule_AddIntConstant(submodule, (char *)"CELLNOISE", TEX_CELLNOISE);
|
||||
|
||||
return submodule;
|
||||
}
|
||||
|
||||
static struct PyModuleDef M_NoiseMetrics_module_def = {
|
||||
PyModuleDef_HEAD_INIT,
|
||||
"mathutils.noise.distance_metrics", /* m_name */
|
||||
NULL, /* m_doc */
|
||||
0, /* m_size */
|
||||
NULL, /* m_methods */
|
||||
NULL, /* m_reload */
|
||||
NULL, /* m_traverse */
|
||||
NULL, /* m_clear */
|
||||
NULL, /* m_free */
|
||||
};
|
||||
|
||||
PyMODINIT_FUNC PyInit_mathutils_noise_metrics(void)
|
||||
{
|
||||
PyObject *submodule = PyModule_Create(&M_NoiseMetrics_module_def);
|
||||
|
||||
PyModule_AddIntConstant(submodule, (char *)"DISTANCE", TEX_DISTANCE);
|
||||
PyModule_AddIntConstant(submodule, (char *)"DISTANCE_SQUARED", TEX_DISTANCE_SQUARED);
|
||||
PyModule_AddIntConstant(submodule, (char *)"MANHATTAN", TEX_MANHATTAN);
|
||||
PyModule_AddIntConstant(submodule, (char *)"CHEBYCHEV", TEX_CHEBYCHEV);
|
||||
PyModule_AddIntConstant(submodule, (char *)"MINKOVSKY_HALF", TEX_MINKOVSKY_HALF);
|
||||
PyModule_AddIntConstant(submodule, (char *)"MINKOVSKY_FOUR", TEX_MINKOVSKY_FOUR);
|
||||
PyModule_AddIntConstant(submodule, (char *)"MINKOVSKY", TEX_MINKOVSKY);
|
||||
|
||||
return submodule;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user