714 lines
		
	
	
		
			25 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
			
		
		
	
	
			714 lines
		
	
	
		
			25 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
/**
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 * $Id$
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 *
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 * Blender.Noise BPython module implementation.
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 * This submodule has functions to generate noise of various types.
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 * 
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 * ***** BEGIN GPL/BL DUAL LICENSE BLOCK *****
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 *
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 * This program is free software; you can redistribute it and/or
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 * modify it under the terms of the GNU General Public License
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 * as published by the Free Software Foundation; either version 2
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 * of the License, or (at your option) any later version. The Blender
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 * Foundation also sells licenses for use in proprietary software under
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 * the Blender License.  See http://www.blender.org/BL/ for information
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 * about this.
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 *
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 * This program is distributed in the hope that it will be useful,
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 * but WITHOUT ANY WARRANTY; without even the implied warranty of
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 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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 * GNU General Public License for more details.
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 *
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 * You should have received a copy of the GNU General Public License
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 * along with this program; if not, write to the Free Software Foundation,
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 * Inc., 59 Temple Place - Suite 330, Boston, MA	02111-1307, USA.
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 *
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 * The Original Code is Copyright (C) 2001-2002 by NaN Holding BV.
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 * All rights reserved.
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 *
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 * This is a new part of Blender.
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 *
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 * Contributor(s): eeshlo
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 *
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 * ***** END GPL/BL DUAL LICENSE BLOCK *****
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*/
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/************************/
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/* Blender Noise Module */
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/************************/
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#include <Python.h>
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#include "BLI_blenlib.h"
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#include "DNA_texture_types.h"
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#include "constant.h"
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/*-----------------------------------------*/
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/* 'mersenne twister' random number generator */
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/* 
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   A C-program for MT19937, with initialization improved 2002/2/10.
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   Coded by Takuji Nishimura and Makoto Matsumoto.
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   This is a faster version by taking Shawn Cokus's optimization,
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   Matthe Bellew's simplification, Isaku Wada's real version.
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   Before using, initialize the state by using init_genrand(seed) 
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   or init_by_array(init_key, key_length).
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   Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
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   All rights reserved.                          
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   Redistribution and use in source and binary forms, with or without
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   modification, are permitted provided that the following conditions
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   are met:
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     1. Redistributions of source code must retain the above copyright
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        notice, this list of conditions and the following disclaimer.
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     2. Redistributions in binary form must reproduce the above copyright
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        notice, this list of conditions and the following disclaimer in the
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        documentation and/or other materials provided with the distribution.
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     3. The names of its contributors may not be used to endorse or promote 
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        products derived from this software without specific prior written 
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        permission.
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   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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   A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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   CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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   EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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   PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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   PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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   LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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   NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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   SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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   Any feedback is very welcome.
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   http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
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   email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
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*/
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/* Period parameters */
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#define N 624
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#define M 397
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#define MATRIX_A 0x9908b0dfUL	/* constant vector a */
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#define UMASK 0x80000000UL	/* most significant w-r bits */
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#define LMASK 0x7fffffffUL	/* least significant r bits */
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#define MIXBITS(u,v) ( ((u) & UMASK) | ((v) & LMASK) )
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#define TWIST(u,v) ((MIXBITS(u,v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL))
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static unsigned long state[N];	/* the array for the state vector  */
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static int left = 1;
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static int initf = 0;
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static unsigned long *next;
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PyObject *Noise_Init(void);
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/* initializes state[N] with a seed */
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static void init_genrand( unsigned long s )
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{
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	int j;
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	state[0] = s & 0xffffffffUL;
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	for( j = 1; j < N; j++ ) {
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		state[j] =
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			( 1812433253UL *
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			  ( state[j - 1] ^ ( state[j - 1] >> 30 ) ) + j );
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		/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
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		/* In the previous versions, MSBs of the seed affect   */
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		/* only MSBs of the array state[].                        */
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		/* 2002/01/09 modified by Makoto Matsumoto             */
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		state[j] &= 0xffffffffUL;	/* for >32 bit machines */
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	}
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	left = 1;
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	initf = 1;
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}
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static void next_state( void )
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{
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	unsigned long *p = state;
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	int j;
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	/* if init_genrand() has not been called, */
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	/* a default initial seed is used         */
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	if( initf == 0 )
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		init_genrand( 5489UL );
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	left = N;
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	next = state;
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	for( j = N - M + 1; --j; p++ )
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		*p = p[M] ^ TWIST( p[0], p[1] );
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	for( j = M; --j; p++ )
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		*p = p[M - N] ^ TWIST( p[0], p[1] );
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	*p = p[M - N] ^ TWIST( p[0], state[0] );
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}
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/*------------------------------------------------------------*/
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static void setRndSeed( int seed )
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{
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	if( seed == 0 )
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		init_genrand( time( NULL ) );
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	else
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		init_genrand( seed );
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}
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/* float number in range [0, 1) using the mersenne twister rng */
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static float frand(  )
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{
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	unsigned long y;
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	if( --left == 0 )
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		next_state(  );
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	y = *next++;
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	/* Tempering */
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	y ^= ( y >> 11 );
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	y ^= ( y << 7 ) & 0x9d2c5680UL;
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	y ^= ( y << 15 ) & 0xefc60000UL;
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	y ^= ( y >> 18 );
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	return ( float ) y / 4294967296.f;
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}
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/*------------------------------------------------------------*/
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/* returns random unit vector */
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static void randuvec( float v[3] )
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{
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	float r;
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	v[2] = 2.f * frand(  ) - 1.f;
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	if( ( r = 1.f - v[2] * v[2] ) > 0.f ) {
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		float a = (float)(6.283185307f * frand(  ));
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		r = (float)sqrt( r );
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		v[0] = (float)(r * cos( a ));
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		v[1] = (float)(r * sin( a ));
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	} else
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		v[2] = 1.f;
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}
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static PyObject *Noise_random( PyObject * self )
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{
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	return Py_BuildValue( "f", frand(  ) );
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}
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static PyObject *Noise_randuvec( PyObject * self )
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{
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	float v[3];
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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_setRandomSeed( PyObject * self, PyObject * args )
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{
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	int s;
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	if( !PyArg_ParseTuple( args, "i", &s ) )
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		return NULL;
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	setRndSeed( s );
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	Py_INCREF( Py_None );
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	return Py_None;
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}
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/*-------------------------------------------------------------------------*/
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/* General noise */
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static PyObject *Noise_noise( PyObject * self, PyObject * args )
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{
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	float x, y, z;
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	int nb = 1;
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	if( !PyArg_ParseTuple( args, "(fff)|i", &x, &y, &z, &nb ) )
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		return NULL;
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	return PyFloat_FromDouble(
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			(double)(2.0 * BLI_gNoise( 1.0, x, y, z, 0, nb ) - 1.0) );
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}
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/*-------------------------------------------------------------------------*/
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/* General Vector noise */
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static void vNoise( float x, float y, float z, int nb, float v[3] )
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{
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	/* Simply evaluate noise at 3 different positions */
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	v[0] = (float)(2.0 * BLI_gNoise( 1.f, x + 9.321f, y - 1.531f, z - 7.951f, 0,
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				 nb ) - 1.0);
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	v[1] = (float)(2.0 * BLI_gNoise( 1.f, x, y, z, 0, nb ) - 1.0);
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	v[2] = (float)(2.0 * BLI_gNoise( 1.f, x + 6.327f, y + 0.1671f, z - 2.672f, 0,
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				 nb ) - 1.0);
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}
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static PyObject *Noise_vNoise( PyObject * self, PyObject * args )
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{
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	float x, y, z, v[3];
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	int nb = 1;
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	if( !PyArg_ParseTuple( args, "(fff)|i", &x, &y, &z, &nb ) )
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		return NULL;
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	vNoise( x, y, z, nb, v );
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	return Py_BuildValue( "[fff]", v[0], v[1], v[2] );
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}
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/*---------------------------------------------------------------------------*/
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/* General turbulence */
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static float turb( float x, float y, float z, int oct, int hard, int nb,
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		   float ampscale, float freqscale )
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{
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	float amp, out, t;
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	int i;
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	amp = 1.f;
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	out = (float)(2.0 * BLI_gNoise( 1.f, x, y, z, 0, nb ) - 1.0);
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	if( hard )
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		out = (float)fabs( out );
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	for( i = 1; i < oct; i++ ) {
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		amp *= ampscale;
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		x *= freqscale;
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		y *= freqscale;
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		z *= freqscale;
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		t = (float)(amp * ( 2.0 * BLI_gNoise( 1.f, x, y, z, 0, nb ) - 1.0 ));
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		if( hard )
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			t = (float)fabs( t );
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		out += t;
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	}
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	return out;
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}
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static PyObject *Noise_turbulence( PyObject * self, PyObject * args )
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{
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	float x, y, z;
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	int oct, hd, nb = 1;
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	float as = 0.5, fs = 2.0;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)ii|iff", &x, &y, &z, &oct, &hd, &nb, &as, &fs ) )
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		return NULL;
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	return PyFloat_FromDouble( (double)turb( x, y, z, oct, hd, nb, as, fs ) );
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}
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/*--------------------------------------------------------------------------*/
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/* Turbulence Vector */
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static void vTurb( float x, float y, float z, int oct, int hard, int nb,
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		   float ampscale, float freqscale, float v[3] )
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{
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	float amp, t[3];
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	int i;
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	amp = 1.f;
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	vNoise( x, y, z, nb, v );
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	if( hard ) {
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		v[0] = (float)fabs( v[0] );
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		v[1] = (float)fabs( v[1] );
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		v[2] = (float)fabs( v[2] );
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	}
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	for( i = 1; i < oct; i++ ) {
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		amp *= ampscale;
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		x *= freqscale;
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		y *= freqscale;
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		z *= freqscale;
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		vNoise( x, y, z, nb, t );
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		if( hard ) {
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			t[0] = (float)fabs( t[0] );
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			t[1] = (float)fabs( t[1] );
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			t[2] = (float)fabs( t[2] );
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		}
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		v[0] += amp * t[0];
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		v[1] += amp * t[1];
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		v[2] += amp * t[2];
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	}
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}
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static PyObject *Noise_vTurbulence( PyObject * self, PyObject * args )
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{
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	float x, y, z, v[3];
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	int oct, hd, nb = 1;
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	float as = 0.5, fs = 2.0;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)ii|iff", &x, &y, &z, &oct, &hd, &nb, &as, &fs ) )
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		return NULL;
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	vTurb( x, y, z, oct, hd, nb, as, fs, v );
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	return Py_BuildValue( "[fff]", v[0], v[1], v[2] );
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}
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/*---------------------------------------------------------------------*/
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/* F. Kenton Musgrave's fractal functions */
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static PyObject *Noise_fBm( PyObject * self, PyObject * args )
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{
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	float x, y, z, H, lac, oct;
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	int nb = 1;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)fff|i", &x, &y, &z, &H, &lac, &oct, &nb ) )
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		return NULL;
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	return PyFloat_FromDouble( (double)mg_fBm( x, y, z, H, lac, oct, nb ) );
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}
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/*------------------------------------------------------------------------*/
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static PyObject *Noise_multiFractal( PyObject * self, PyObject * args )
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{
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	float x, y, z, H, lac, oct;
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	int nb = 1;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)fff|i", &x, &y, &z, &H, &lac, &oct, &nb ) )
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		return NULL;
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	return PyFloat_FromDouble( (double)mg_MultiFractal( x, y, z, H, lac, oct, nb ) );
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}
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/*------------------------------------------------------------------------*/
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static PyObject *Noise_vlNoise( PyObject * self, PyObject * args )
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{
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	float x, y, z, d;
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	int nt1 = 1, nt2 = 1;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)f|ii", &x, &y, &z, &d, &nt1, &nt2 ) )
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		return NULL;
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	return PyFloat_FromDouble( (double)mg_VLNoise( x, y, z, d, nt1, nt2 ) );
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}
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/*-------------------------------------------------------------------------*/
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static PyObject *Noise_heteroTerrain( PyObject * self, PyObject * args )
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{
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	float x, y, z, H, lac, oct, ofs;
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	int nb = 1;
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	if( !PyArg_ParseTuple
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	    ( args, "(fff)ffff|i", &x, &y, &z, &H, &lac, &oct, &ofs, &nb ) )
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		return NULL;
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	return PyFloat_FromDouble(
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			(double)mg_HeteroTerrain( x, y, z, H, lac, oct, ofs, nb ) );
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}
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/*-------------------------------------------------------------------------*/
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static PyObject *Noise_hybridMFractal( PyObject * self, PyObject * args )
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{
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	float x, y, z, H, lac, oct, ofs, gn;
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	int nb = 1;
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	if( !PyArg_ParseTuple
 | 
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	    ( args, "(fff)fffff|i", &x, &y, &z, &H, &lac, &oct, &ofs, &gn,
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	      &nb ) )
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		return NULL;
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	return PyFloat_FromDouble(
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			(double)mg_HybridMultiFractal( x, y, z, H, lac, oct, ofs, gn, nb) );
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}
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/*------------------------------------------------------------------------*/
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static PyObject *Noise_ridgedMFractal( PyObject * self, PyObject * args )
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{
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	float x, y, z, H, lac, oct, ofs, gn;
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	int nb = 1;
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	if( !PyArg_ParseTuple
 | 
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	    ( args, "(fff)fffff|i", &x, &y, &z, &H, &lac, &oct, &ofs, &gn,
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	      &nb ) )
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		return NULL;
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	return PyFloat_FromDouble(
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			(double)mg_RidgedMultiFractal( x, y, z, H, lac, oct, ofs, gn, nb) );
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						|
}
 | 
						|
 | 
						|
/*-------------------------------------------------------------------------*/
 | 
						|
 | 
						|
static PyObject *Noise_voronoi( PyObject * self, PyObject * args )
 | 
						|
{
 | 
						|
	float x, y, z, da[4], pa[12];
 | 
						|
	int dtype = 0;
 | 
						|
	float me = 2.5;		/* default minkovsky exponent */
 | 
						|
	if( !PyArg_ParseTuple( args, "(fff)|if", &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[12] );
 | 
						|
}
 | 
						|
 | 
						|
/*-------------------------------------------------------------------------*/
 | 
						|
 | 
						|
static PyObject *Noise_cellNoise( PyObject * self, PyObject * args )
 | 
						|
{
 | 
						|
	float x, y, z;
 | 
						|
	if( !PyArg_ParseTuple( args, "(fff)", &x, &y, &z ) )
 | 
						|
		return NULL;
 | 
						|
	return Py_BuildValue( "f", cellNoise( x, y, z ) );
 | 
						|
}
 | 
						|
 | 
						|
/*--------------------------------------------------------------------------*/
 | 
						|
 | 
						|
static PyObject *Noise_cellNoiseV( PyObject * self, PyObject * args )
 | 
						|
{
 | 
						|
	float x, y, z, ca[3];
 | 
						|
	if( !PyArg_ParseTuple( args, "(fff)", &x, &y, &z ) )
 | 
						|
		return NULL;
 | 
						|
	cellNoiseV( x, y, z, ca );
 | 
						|
	return Py_BuildValue( "[fff]", ca[0], ca[1], ca[2] );
 | 
						|
}
 | 
						|
 | 
						|
/*--------------------------------------------------------------------------*/
 | 
						|
/* For all other Blender modules, this stuff seems to be put in a header file.
 | 
						|
   This doesn't seem really appropriate to me, so I just put it here, feel free to change it.
 | 
						|
   In the original module I actually kept the docs stings with the functions themselves,
 | 
						|
   but I grouped them here so that it can easily be moved to a header if anyone thinks that is necessary. */
 | 
						|
 | 
						|
static char random__doc__[] = "() No arguments.\n\n\
 | 
						|
Returns a random floating point number in the range [0, 1)";
 | 
						|
 | 
						|
static char randuvec__doc__[] =
 | 
						|
	"() No arguments.\n\nReturns a random unit vector (3-float list).";
 | 
						|
 | 
						|
static char setRandomSeed__doc__[] = "(seed value)\n\n\
 | 
						|
Initializes random number generator.\n\
 | 
						|
if seed is zero, the current time will be used instead.";
 | 
						|
 | 
						|
static char noise__doc__[] = "((x,y,z) tuple, [noisetype])\n\n\
 | 
						|
Returns general noise of the optional specified type.\n\
 | 
						|
Optional argument noisetype determines the type of noise, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char vNoise__doc__[] = "((x,y,z) tuple, [noisetype])\n\n\
 | 
						|
Returns noise vector (3-float list) of the optional specified type.\
 | 
						|
Optional argument noisetype determines the type of noise, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char turbulence__doc__[] =
 | 
						|
	"((x,y,z) tuple, octaves, hard, [noisebasis], [ampscale], [freqscale])\n\n\
 | 
						|
Returns general turbulence value using the optional specified noisebasis function.\n\
 | 
						|
octaves (integer) is the number of noise values added.\n\
 | 
						|
hard (bool), when false (0) returns 'soft' noise, when true (1) returns 'hard' noise (returned value always positive).\n\
 | 
						|
Optional arguments:\n\
 | 
						|
noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.\n\
 | 
						|
ampscale sets the amplitude scale value of the noise frequencies added, 0.5 by default.\n\
 | 
						|
freqscale sets the frequency scale factor, 2.0 by default.";
 | 
						|
 | 
						|
static char vTurbulence__doc__[] =
 | 
						|
	"((x,y,z) tuple, octaves, hard, [noisebasis], [ampscale], [freqscale])\n\n\
 | 
						|
Returns general turbulence vector (3-float list) using the optional specified noisebasis function.\n\
 | 
						|
octaves (integer) is the number of noise values added.\n\
 | 
						|
hard (bool), when false (0) returns 'soft' noise, when true (1) returns 'hard' noise (returned vector always positive).\n\
 | 
						|
Optional arguments:\n\
 | 
						|
noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.\n\
 | 
						|
ampscale sets the amplitude scale value of the noise frequencies added, 0.5 by default.\n\
 | 
						|
freqscale sets the frequency scale factor, 2.0 by default.";
 | 
						|
 | 
						|
static char fBm__doc__[] =
 | 
						|
	"((x,y,z) tuple, H, lacunarity, octaves, [noisebasis])\n\n\
 | 
						|
Returns Fractal Brownian Motion noise value(fBm).\n\
 | 
						|
H is the fractal increment parameter.\n\
 | 
						|
lacunarity is the gap between successive frequencies.\n\
 | 
						|
octaves is the number of frequencies in the fBm.\n\
 | 
						|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char multiFractal__doc__[] =
 | 
						|
	"((x,y,z) tuple, H, lacunarity, octaves, [noisebasis])\n\n\
 | 
						|
Returns Multifractal noise value.\n\
 | 
						|
H determines the highest fractal dimension.\n\
 | 
						|
lacunarity is gap between successive frequencies.\n\
 | 
						|
octaves is the number of frequencies in the fBm.\n\
 | 
						|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char vlNoise__doc__[] =
 | 
						|
	"((x,y,z) tuple, distortion, [noisetype1], [noisetype2])\n\n\
 | 
						|
Returns Variable Lacunarity Noise value, a distorted variety of noise.\n\
 | 
						|
distortion sets the amount of distortion.\n\
 | 
						|
Optional arguments noisetype1 and noisetype2 set the noisetype to distort and the noisetype used for the distortion respectively.\n\
 | 
						|
See NoiseTypes, both are STDPERLIN by default.";
 | 
						|
 | 
						|
static char heteroTerrain__doc__[] =
 | 
						|
	"((x,y,z) tuple, H, lacunarity, octaves, offset, [noisebasis])\n\n\
 | 
						|
returns Heterogeneous Terrain value\n\
 | 
						|
H determines the fractal dimension of the roughest areas.\n\
 | 
						|
lacunarity is the gap between successive frequencies.\n\
 | 
						|
octaves is the number of frequencies in the fBm.\n\
 | 
						|
offset raises the terrain from 'sea level'.\n\
 | 
						|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char hybridMFractal__doc__[] =
 | 
						|
	"((x,y,z) tuple, H, lacunarity, octaves, offset, gain, [noisebasis])\n\n\
 | 
						|
returns Hybrid Multifractal value.\n\
 | 
						|
H determines the fractal dimension of the roughest areas.\n\
 | 
						|
lacunarity is the gap between successive frequencies.\n\
 | 
						|
octaves is the number of frequencies in the fBm.\n\
 | 
						|
offset raises the terrain from 'sea level'.\n\
 | 
						|
gain scales the values.\n\
 | 
						|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char ridgedMFractal__doc__[] =
 | 
						|
	"((x,y,z) tuple, H, lacunarity, octaves, offset, gain [noisebasis])\n\n\
 | 
						|
returns Ridged Multifractal value.\n\
 | 
						|
H determines the fractal dimension of the roughest areas.\n\
 | 
						|
lacunarity is the gap between successive frequencies.\n\
 | 
						|
octaves is the number of frequencies in the fBm.\n\
 | 
						|
offset raises the terrain from 'sea level'.\n\
 | 
						|
gain scales the values.\n\
 | 
						|
Optional argument noisebasis determines the type of noise used for the turbulence, STDPERLIN by default, see NoiseTypes.";
 | 
						|
 | 
						|
static char voronoi__doc__[] =
 | 
						|
	"((x,y,z) tuple, distance_metric, [exponent])\n\n\
 | 
						|
returns a list, containing a list of distances in order of closest feature,\n\
 | 
						|
and a list containing the positions of the four closest features\n\
 | 
						|
Optional arguments:\n\
 | 
						|
distance_metric: see DistanceMetrics, default is DISTANCE\n\
 | 
						|
exponent is only used with MINKOVSKY, default is 2.5.";
 | 
						|
 | 
						|
static char cellNoise__doc__[] = "((x,y,z) tuple)\n\n\
 | 
						|
returns cellnoise float value.";
 | 
						|
 | 
						|
static char cellNoiseV__doc__[] = "((x,y,z) tuple)\n\n\
 | 
						|
returns cellnoise vector/point/color (3-float list).";
 | 
						|
 | 
						|
static char Noise__doc__[] = "Blender Noise and Turbulence Module\n\n\
 | 
						|
This module can be used to generate noise of various types.\n\
 | 
						|
This can be used for terrain generation, to create textures,\n\
 | 
						|
make animations more 'animated', object deformation, etc.\n\
 | 
						|
As an example, this code segment when scriptlinked to a framechanged event,\n\
 | 
						|
will make the camera sway randomly about, by changing parameters this can\n\
 | 
						|
look like anything from an earthquake to a very nervous or maybe even drunk cameraman...\n\
 | 
						|
(the camera needs an ipo with at least one Loc & Rot key for this to work!):\n\
 | 
						|
\n\
 | 
						|
\tfrom Blender import Get, Scene, Noise\n\
 | 
						|
\n\
 | 
						|
\t####################################################\n\
 | 
						|
\t# This controls jitter speed\n\
 | 
						|
\tsl = 0.025\n\
 | 
						|
\t# This controls the amount of position jitter\n\
 | 
						|
\tsp = 0.1\n\
 | 
						|
\t# This controls the amount of rotation jitter\n\
 | 
						|
\tsr = 0.25\n\
 | 
						|
\t####################################################\n\
 | 
						|
\n\
 | 
						|
\ttime = Get('curtime')\n\
 | 
						|
\tob = Scene.GetCurrent().getCurrentCamera()\n\
 | 
						|
\tps = (sl*time, sl*time, sl*time)\n\
 | 
						|
\t# To add jitter only when the camera moves, use this next line instead\n\
 | 
						|
\t#ps = (sl*ob.LocX, sl*ob.LocY, sl*ob.LocZ)\n\
 | 
						|
\trv = Noise.vTurbulence(ps, 3, 0, Noise.NoiseTypes.NEWPERLIN)\n\
 | 
						|
\tob.dloc = (sp*rv[0], sp*rv[1], sp*rv[2])\n\
 | 
						|
\tob.drot = (sr*rv[0], sr*rv[1], sr*rv[2])\n\
 | 
						|
\n";
 | 
						|
 | 
						|
/* Just in case, declarations for a header file */
 | 
						|
/*
 | 
						|
static PyObject *Noise_random(PyObject *self);
 | 
						|
static PyObject *Noise_randuvec(PyObject *self);
 | 
						|
static PyObject *Noise_setRandomSeed(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_noise(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_vNoise(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_turbulence(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_vTurbulence(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_fBm(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_multiFractal(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_vlNoise(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_heteroTerrain(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_hybridMFractal(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_ridgedMFractal(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_voronoi(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_cellNoise(PyObject *self, PyObject *args);
 | 
						|
static PyObject *Noise_cellNoiseV(PyObject *self, PyObject *args);
 | 
						|
*/
 | 
						|
 | 
						|
static PyMethodDef NoiseMethods[] = {
 | 
						|
	{"setRandomSeed", ( PyCFunction ) Noise_setRandomSeed, METH_VARARGS,
 | 
						|
	 setRandomSeed__doc__},
 | 
						|
	{"random", ( PyCFunction ) Noise_random, METH_NOARGS, random__doc__},
 | 
						|
	{"randuvec", ( PyCFunction ) Noise_randuvec, METH_NOARGS,
 | 
						|
	 randuvec__doc__},
 | 
						|
	{"noise", ( PyCFunction ) Noise_noise, METH_VARARGS, noise__doc__},
 | 
						|
	{"vNoise", ( PyCFunction ) Noise_vNoise, METH_VARARGS, vNoise__doc__},
 | 
						|
	{"turbulence", ( PyCFunction ) Noise_turbulence, METH_VARARGS,
 | 
						|
	 turbulence__doc__},
 | 
						|
	{"vTurbulence", ( PyCFunction ) Noise_vTurbulence, METH_VARARGS,
 | 
						|
	 vTurbulence__doc__},
 | 
						|
	{"fBm", ( PyCFunction ) Noise_fBm, METH_VARARGS, fBm__doc__},
 | 
						|
	{"multiFractal", ( PyCFunction ) Noise_multiFractal, METH_VARARGS,
 | 
						|
	 multiFractal__doc__},
 | 
						|
	{"vlNoise", ( PyCFunction ) Noise_vlNoise, METH_VARARGS,
 | 
						|
	 vlNoise__doc__},
 | 
						|
	{"heteroTerrain", ( PyCFunction ) Noise_heteroTerrain, METH_VARARGS,
 | 
						|
	 heteroTerrain__doc__},
 | 
						|
	{"hybridMFractal", ( PyCFunction ) Noise_hybridMFractal, METH_VARARGS,
 | 
						|
	 hybridMFractal__doc__},
 | 
						|
	{"ridgedMFractal", ( PyCFunction ) Noise_ridgedMFractal, METH_VARARGS,
 | 
						|
	 ridgedMFractal__doc__},
 | 
						|
	{"voronoi", ( PyCFunction ) Noise_voronoi, METH_VARARGS,
 | 
						|
	 voronoi__doc__},
 | 
						|
	{"cellNoise", ( PyCFunction ) Noise_cellNoise, METH_VARARGS,
 | 
						|
	 cellNoise__doc__},
 | 
						|
	{"cellNoiseV", ( PyCFunction ) Noise_cellNoiseV, METH_VARARGS,
 | 
						|
	 cellNoiseV__doc__},
 | 
						|
	{NULL, NULL, 0, NULL}
 | 
						|
};
 | 
						|
 | 
						|
/*----------------------------------------------------------------------*/
 | 
						|
 | 
						|
PyObject *Noise_Init(void)
 | 
						|
{
 | 
						|
	PyObject *NoiseTypes, *DistanceMetrics,
 | 
						|
		*md =
 | 
						|
		Py_InitModule3( "Blender.Noise", NoiseMethods, Noise__doc__ );
 | 
						|
 | 
						|
        /* use current time as seed for random number generator by default */
 | 
						|
	setRndSeed( 0 );	
 | 
						|
 | 
						|
	/* Constant noisetype dictionary */
 | 
						|
	NoiseTypes = PyConstant_New(  );
 | 
						|
	if( NoiseTypes ) {
 | 
						|
		BPy_constant *nt = ( BPy_constant * ) NoiseTypes;
 | 
						|
		PyConstant_Insert( nt, "BLENDER",
 | 
						|
				 PyInt_FromLong( TEX_BLENDER ) );
 | 
						|
		PyConstant_Insert( nt, "STDPERLIN",
 | 
						|
				 PyInt_FromLong( TEX_STDPERLIN ) );
 | 
						|
		PyConstant_Insert( nt, "NEWPERLIN",
 | 
						|
				 PyInt_FromLong( TEX_NEWPERLIN ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_F1",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_F1 ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_F2",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_F2 ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_F3",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_F3 ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_F4",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_F4 ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_F2F1",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_F2F1 ) );
 | 
						|
		PyConstant_Insert( nt, "VORONOI_CRACKLE",
 | 
						|
				 PyInt_FromLong( TEX_VORONOI_CRACKLE ) );
 | 
						|
		PyConstant_Insert( nt, "CELLNOISE",
 | 
						|
				 PyInt_FromLong( TEX_CELLNOISE ) );
 | 
						|
		PyModule_AddObject( md, "NoiseTypes", NoiseTypes );
 | 
						|
	}
 | 
						|
 | 
						|
	/* Constant distance metric dictionary for voronoi */
 | 
						|
	DistanceMetrics = PyConstant_New(  );
 | 
						|
	if( DistanceMetrics ) {
 | 
						|
		BPy_constant *dm = ( BPy_constant * ) DistanceMetrics;
 | 
						|
		PyConstant_Insert( dm, "DISTANCE",
 | 
						|
				 PyInt_FromLong( TEX_DISTANCE ) );
 | 
						|
		PyConstant_Insert( dm, "DISTANCE_SQUARED",
 | 
						|
				 PyInt_FromLong( TEX_DISTANCE_SQUARED ) );
 | 
						|
		PyConstant_Insert( dm, "MANHATTAN",
 | 
						|
				 PyInt_FromLong( TEX_MANHATTAN ) );
 | 
						|
		PyConstant_Insert( dm, "CHEBYCHEV",
 | 
						|
				 PyInt_FromLong( TEX_CHEBYCHEV ) );
 | 
						|
		PyConstant_Insert( dm, "MINKOVSKY_HALF",
 | 
						|
				 PyInt_FromLong( TEX_MINKOVSKY_HALF ) );
 | 
						|
		PyConstant_Insert( dm, "MINKOVSKY_FOUR",
 | 
						|
				 PyInt_FromLong( TEX_MINKOVSKY_FOUR ) );
 | 
						|
		PyConstant_Insert( dm, "MINKOVSKY",
 | 
						|
				 PyInt_FromLong( TEX_MINKOVSKY ) );
 | 
						|
		PyModule_AddObject( md, "DistanceMetrics", DistanceMetrics );
 | 
						|
	}
 | 
						|
 | 
						|
	return md;
 | 
						|
}
 |