+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-/* ////////////////////////////////////////////////////////////////////
-//
-// Filling CvMat/IplImage instances with random numbers
-//
-// */
-
-#include "_cxcore.h"
-
-
-///////////////////////////// Functions Declaration //////////////////////////////////////
-
-/*
- Multiply-with-carry generator is used here:
- temp = ( A*X(n) + carry )
- X(n+1) = temp mod (2^32)
- carry = temp / (2^32)
-*/
-#define ICV_RNG_NEXT(x) ((uint64)(unsigned)(x)*1554115554 + ((x) >> 32))
-#define ICV_CVT_FLT(x) (((unsigned)(x) >> 9)|CV_1F)
-#define ICV_1D CV_BIG_INT(0x3FF0000000000000)
-#define ICV_CVT_DBL(x) (((uint64)(unsigned)(x) << 20)|((x) >> 44)|ICV_1D)
-
-/***************************************************************************************\
-* Pseudo-Random Number Generators (PRNGs) *
-\***************************************************************************************/
-
-#define ICV_IMPL_RAND_BITS( flavor, arrtype, cast_macro ) \
-static CvStatus CV_STDCALL \
-icvRandBits_##flavor##_C1R( arrtype* arr, int step, CvSize size, \
- uint64* state, const int* param ) \
-{ \
- uint64 temp = *state; \
- int small_flag = (param[12]|param[13]|param[14]|param[15]) <= 255; \
- step /= sizeof(arr[0]); \
- \
- for( ; size.height--; arr += step ) \
- { \
- int i, k = 3; \
- const int* p = param; \
- \
- if( !small_flag ) \
- { \
- for( i = 0; i <= size.width - 4; i += 4 ) \
- { \
- unsigned t0, t1; \
- \
- temp = ICV_RNG_NEXT(temp); \
- t0 = ((unsigned)temp & p[i + 12]) + p[i]; \
- temp = ICV_RNG_NEXT(temp); \
- t1 = ((unsigned)temp & p[i + 13]) + p[i+1]; \
- arr[i] = cast_macro((int)t0); \
- arr[i+1] = cast_macro((int)t1); \
- \
- temp = ICV_RNG_NEXT(temp); \
- t0 = ((unsigned)temp & p[i + 14]) + p[i+2]; \
- temp = ICV_RNG_NEXT(temp); \
- t1 = ((unsigned)temp & p[i + 15]) + p[i+3]; \
- arr[i+2] = cast_macro((int)t0); \
- arr[i+3] = cast_macro((int)t1); \
- \
- if( !--k ) \
- { \
- k = 3; \
- p -= 12; \
- } \
- } \
- } \
- else \
- { \
- for( i = 0; i <= size.width - 4; i += 4 ) \
- { \
- unsigned t0, t1, t; \
- \
- temp = ICV_RNG_NEXT(temp); \
- t = (unsigned)temp; \
- t0 = (t & p[i + 12]) + p[i]; \
- t1 = ((t >> 8) & p[i + 13]) + p[i+1]; \
- arr[i] = cast_macro((int)t0); \
- arr[i+1] = cast_macro((int)t1); \
- \
- t0 = ((t >> 16) & p[i + 14]) + p[i + 2]; \
- t1 = ((t >> 24) & p[i + 15]) + p[i + 3]; \
- arr[i+2] = cast_macro((int)t0); \
- arr[i+3] = cast_macro((int)t1); \
- \
- if( !--k ) \
- { \
- k = 3; \
- p -= 12; \
- } \
- } \
- } \
- \
- for( ; i < size.width; i++ ) \
- { \
- unsigned t0; \
- temp = ICV_RNG_NEXT(temp); \
- \
- t0 = ((unsigned)temp & p[i + 12]) + p[i]; \
- arr[i] = cast_macro((int)t0); \
- } \
- } \
- \
- *state = temp; \
- return CV_OK; \
-}
-
-
-#define ICV_IMPL_RAND( flavor, arrtype, worktype, cast_macro1, cast_macro2 )\
-static CvStatus CV_STDCALL \
-icvRand_##flavor##_C1R( arrtype* arr, int step, CvSize size, \
- uint64* state, const double* param ) \
-{ \
- uint64 temp = *state; \
- step /= sizeof(arr[0]); \
- \
- for( ; size.height--; arr += step ) \
- { \
- int i, k = 3; \
- const double* p = param; \
- \
- for( i = 0; i <= size.width - 4; i += 4 ) \
- { \
- worktype f0, f1; \
- Cv32suf t0, t1; \
- \
- temp = ICV_RNG_NEXT(temp); \
- t0.u = ICV_CVT_FLT(temp); \
- temp = ICV_RNG_NEXT(temp); \
- t1.u = ICV_CVT_FLT(temp); \
- f0 = cast_macro1( t0.f * p[i + 12] + p[i] ); \
- f1 = cast_macro1( t1.f * p[i + 13] + p[i + 1] ); \
- arr[i] = cast_macro2(f0); \
- arr[i+1] = cast_macro2(f1); \
- \
- temp = ICV_RNG_NEXT(temp); \
- t0.u = ICV_CVT_FLT(temp); \
- temp = ICV_RNG_NEXT(temp); \
- t1.u = ICV_CVT_FLT(temp); \
- f0 = cast_macro1( t0.f * p[i + 14] + p[i + 2] ); \
- f1 = cast_macro1( t1.f * p[i + 15] + p[i + 3] ); \
- arr[i+2] = cast_macro2(f0); \
- arr[i+3] = cast_macro2(f1); \
- \
- if( !--k ) \
- { \
- k = 3; \
- p -= 12; \
- } \
- } \
- \
- for( ; i < size.width; i++ ) \
- { \
- worktype f0; \
- Cv32suf t0; \
- \
- temp = ICV_RNG_NEXT(temp); \
- t0.u = ICV_CVT_FLT(temp); \
- f0 = cast_macro1( t0.f * p[i + 12] + p[i] ); \
- arr[i] = cast_macro2(f0); \
- } \
- } \
- \
- *state = temp; \
- return CV_OK; \
-}
-
-
-static CvStatus CV_STDCALL
-icvRand_64f_C1R( double* arr, int step, CvSize size,
- uint64* state, const double* param )
-{
- uint64 temp = *state;
- step /= sizeof(arr[0]);
-
- for( ; size.height--; arr += step )
- {
- int i, k = 3;
- const double* p = param;
-
- for( i = 0; i <= size.width - 4; i += 4 )
- {
- double f0, f1;
- Cv64suf t0, t1;
-
- temp = ICV_RNG_NEXT(temp);
- t0.u = ICV_CVT_DBL(temp);
- temp = ICV_RNG_NEXT(temp);
- t1.u = ICV_CVT_DBL(temp);
- f0 = t0.f * p[i + 12] + p[i];
- f1 = t1.f * p[i + 13] + p[i + 1];
- arr[i] = f0;
- arr[i+1] = f1;
-
- temp = ICV_RNG_NEXT(temp);
- t0.u = ICV_CVT_DBL(temp);
- temp = ICV_RNG_NEXT(temp);
- t1.u = ICV_CVT_DBL(temp);
- f0 = t0.f * p[i + 14] + p[i + 2];
- f1 = t1.f * p[i + 15] + p[i + 3];
- arr[i+2] = f0;
- arr[i+3] = f1;
-
- if( !--k )
- {
- k = 3;
- p -= 12;
- }
- }
-
- for( ; i < size.width; i++ )
- {
- double f0;
- Cv64suf t0;
-
- temp = ICV_RNG_NEXT(temp);
- t0.u = ICV_CVT_DBL(temp);
- f0 = t0.f * p[i + 12] + p[i];
- arr[i] = f0;
- }
- }
-
- *state = temp;
- return CV_OK;
-}
-
-
-/***************************************************************************************\
- The code below implements algorithm from the paper:
-
- G. Marsaglia and W.W. Tsang,
- The Monty Python method for generating random variables,
- ACM Transactions on Mathematical Software, Vol. 24, No. 3,
- Pages 341-350, September, 1998.
-\***************************************************************************************/
-
-static CvStatus CV_STDCALL
-icvRandn_0_1_32f_C1R( float* arr, int len, uint64* state )
-{
- uint64 temp = *state;
- int i;
- temp = ICV_RNG_NEXT(temp);
-
- for( i = 0; i < len; i++ )
- {
- double x, y, v, ax, bx;
-
- for(;;)
- {
- x = ((int)temp)*1.167239e-9;
- temp = ICV_RNG_NEXT(temp);
- ax = fabs(x);
- v = 2.8658 - ax*(2.0213 - 0.3605*ax);
- y = ((unsigned)temp)*2.328306e-10;
- temp = ICV_RNG_NEXT(temp);
-
- if( y < v || ax < 1.17741 )
- break;
-
- bx = x;
- x = bx > 0 ? 0.8857913*(2.506628 - ax) : -0.8857913*(2.506628 - ax);
-
- if( y > v + 0.0506 )
- break;
-
- if( log(y) < .6931472 - .5*bx*bx )
- {
- x = bx;
- break;
- }
-
- if( log(1.8857913 - y) < .5718733-.5*x*x )
- break;
-
- do
- {
- v = ((int)temp)*4.656613e-10;
- x = -log(fabs(v))*.3989423;
- temp = ICV_RNG_NEXT(temp);
- y = -log(((unsigned)temp)*2.328306e-10);
- temp = ICV_RNG_NEXT(temp);
- }
- while( y+y < x*x );
-
- x = v > 0 ? 2.506628 + x : -2.506628 - x;
- break;
- }
-
- arr[i] = (float)x;
- }
- *state = temp;
- return CV_OK;
-}
-
-
-#define RAND_BUF_SIZE 96
-
-
-#define ICV_IMPL_RANDN( flavor, arrtype, worktype, cast_macro1, cast_macro2 ) \
-static CvStatus CV_STDCALL \
-icvRandn_##flavor##_C1R( arrtype* arr, int step, CvSize size, \
- uint64* state, const double* param ) \
-{ \
- float buffer[RAND_BUF_SIZE]; \
- step /= sizeof(arr[0]); \
- \
- for( ; size.height--; arr += step ) \
- { \
- int i, j, len = RAND_BUF_SIZE; \
- \
- for( i = 0; i < size.width; i += RAND_BUF_SIZE ) \
- { \
- int k = 3; \
- const double* p = param; \
- \
- if( i + len > size.width ) \
- len = size.width - i; \
- \
- icvRandn_0_1_32f_C1R( buffer, len, state ); \
- \
- for( j = 0; j <= len - 4; j += 4 ) \
- { \
- worktype f0, f1; \
- \
- f0 = cast_macro1( buffer[j]*p[j+12] + p[j] ); \
- f1 = cast_macro1( buffer[j+1]*p[j+13] + p[j+1] ); \
- arr[i+j] = cast_macro2(f0); \
- arr[i+j+1] = cast_macro2(f1); \
- \
- f0 = cast_macro1( buffer[j+2]*p[j+14] + p[j+2] ); \
- f1 = cast_macro1( buffer[j+3]*p[j+15] + p[j+3] ); \
- arr[i+j+2] = cast_macro2(f0); \
- arr[i+j+3] = cast_macro2(f1); \
- \
- if( --k == 0 ) \
- { \
- k = 3; \
- p -= 12; \
- } \
- } \
- \
- for( ; j < len; j++ ) \
- { \
- worktype f0 = cast_macro1( buffer[j]*p[j+12] + p[j] ); \
- arr[i+j] = cast_macro2(f0); \
- } \
- } \
- } \
- \
- return CV_OK; \
-}
-
-
-ICV_IMPL_RAND_BITS( 8u, uchar, CV_CAST_8U )
-ICV_IMPL_RAND_BITS( 16u, ushort, CV_CAST_16U )
-ICV_IMPL_RAND_BITS( 16s, short, CV_CAST_16S )
-ICV_IMPL_RAND_BITS( 32s, int, CV_CAST_32S )
-
-ICV_IMPL_RAND( 8u, uchar, int, cvFloor, CV_CAST_8U )
-ICV_IMPL_RAND( 16u, ushort, int, cvFloor, CV_CAST_16U )
-ICV_IMPL_RAND( 16s, short, int, cvFloor, CV_CAST_16S )
-ICV_IMPL_RAND( 32s, int, int, cvFloor, CV_CAST_32S )
-ICV_IMPL_RAND( 32f, float, float, CV_CAST_32F, CV_NOP )
-
-ICV_IMPL_RANDN( 8u, uchar, int, cvRound, CV_CAST_8U )
-ICV_IMPL_RANDN( 16u, ushort, int, cvRound, CV_CAST_16U )
-ICV_IMPL_RANDN( 16s, short, int, cvRound, CV_CAST_16S )
-ICV_IMPL_RANDN( 32s, int, int, cvRound, CV_CAST_32S )
-ICV_IMPL_RANDN( 32f, float, float, CV_CAST_32F, CV_NOP )
-ICV_IMPL_RANDN( 64f, double, double, CV_CAST_64F, CV_NOP )
-
-static void icvInitRandTable( CvFuncTable* fastrng_tab,
- CvFuncTable* rng_tab,
- CvFuncTable* normal_tab )
-{
- fastrng_tab->fn_2d[CV_8U] = (void*)icvRandBits_8u_C1R;
- fastrng_tab->fn_2d[CV_8S] = 0;
- fastrng_tab->fn_2d[CV_16U] = (void*)icvRandBits_16u_C1R;
- fastrng_tab->fn_2d[CV_16S] = (void*)icvRandBits_16s_C1R;
- fastrng_tab->fn_2d[CV_32S] = (void*)icvRandBits_32s_C1R;
-
- rng_tab->fn_2d[CV_8U] = (void*)icvRand_8u_C1R;
- rng_tab->fn_2d[CV_8S] = 0;
- rng_tab->fn_2d[CV_16U] = (void*)icvRand_16u_C1R;
- rng_tab->fn_2d[CV_16S] = (void*)icvRand_16s_C1R;
- rng_tab->fn_2d[CV_32S] = (void*)icvRand_32s_C1R;
- rng_tab->fn_2d[CV_32F] = (void*)icvRand_32f_C1R;
- rng_tab->fn_2d[CV_64F] = (void*)icvRand_64f_C1R;
-
- normal_tab->fn_2d[CV_8U] = (void*)icvRandn_8u_C1R;
- normal_tab->fn_2d[CV_8S] = 0;
- normal_tab->fn_2d[CV_16U] = (void*)icvRandn_16u_C1R;
- normal_tab->fn_2d[CV_16S] = (void*)icvRandn_16s_C1R;
- normal_tab->fn_2d[CV_32S] = (void*)icvRandn_32s_C1R;
- normal_tab->fn_2d[CV_32F] = (void*)icvRandn_32f_C1R;
- normal_tab->fn_2d[CV_64F] = (void*)icvRandn_64f_C1R;
-}
-
-
-CV_IMPL void
-cvRandArr( CvRNG* rng, CvArr* arr, int disttype, CvScalar param1, CvScalar param2 )
-{
- static CvFuncTable rng_tab[2], fastrng_tab;
- static int inittab = 0;
-
- CV_FUNCNAME( "cvRandArr" );
-
- __BEGIN__;
-
- int is_nd = 0;
- CvMat stub, *mat = (CvMat*)arr;
- int type, depth, channels;
- double dparam[2][12];
- int iparam[2][12];
- void* param = dparam;
- int i, fast_int_mode = 0;
- int mat_step = 0;
- CvSize size;
- CvFunc2D_1A2P func = 0;
- CvMatND stub_nd;
- CvNArrayIterator iterator_state, *iterator = 0;
-
- if( !inittab )
- {
- icvInitRandTable( &fastrng_tab, &rng_tab[CV_RAND_UNI],
- &rng_tab[CV_RAND_NORMAL] );
- inittab = 1;
- }
-
- if( !rng )
- CV_ERROR( CV_StsNullPtr, "Null pointer to RNG state" );
-
- if( CV_IS_MATND(mat) )
- {
- iterator = &iterator_state;
- CV_CALL( cvInitNArrayIterator( 1, &arr, 0, &stub_nd, iterator ));
- type = CV_MAT_TYPE(iterator->hdr[0]->type);
- size = iterator->size;
- is_nd = 1;
- }
- else
- {
- if( !CV_IS_MAT(mat))
- {
- int coi = 0;
- CV_CALL( mat = cvGetMat( mat, &stub, &coi ));
-
- if( coi != 0 )
- CV_ERROR( CV_BadCOI, "COI is not supported" );
- }
-
- type = CV_MAT_TYPE( mat->type );
- size = cvGetMatSize( mat );
- mat_step = mat->step;
-
- if( mat->height > 1 && CV_IS_MAT_CONT( mat->type ))
- {
- size.width *= size.height;
- mat_step = CV_STUB_STEP;
- size.height = 1;
- }
- }
-
- depth = CV_MAT_DEPTH( type );
- channels = CV_MAT_CN( type );
- size.width *= channels;
-
- if( disttype == CV_RAND_UNI )
- {
- if( depth <= CV_32S )
- {
- for( i = 0, fast_int_mode = 1; i < channels; i++ )
- {
- int t0 = iparam[0][i] = cvCeil( param1.val[i] );
- int t1 = iparam[1][i] = cvFloor( param2.val[i] ) - t0;
- double diff = param1.val[i] - param2.val[i];
-
- fast_int_mode &= INT_MIN <= diff && diff <= INT_MAX && (t1 & (t1 - 1)) == 0;
- }
- }
-
- if( fast_int_mode )
- {
- for( i = 0; i < channels; i++ )
- iparam[1][i]--;
-
- for( ; i < 12; i++ )
- {
- int t0 = iparam[0][i - channels];
- int t1 = iparam[1][i - channels];
-
- iparam[0][i] = t0;
- iparam[1][i] = t1;
- }
-
- CV_GET_FUNC_PTR( func, (CvFunc2D_1A2P)(fastrng_tab.fn_2d[depth]));
- param = iparam;
- }
- else
- {
- for( i = 0; i < channels; i++ )
- {
- double t0 = param1.val[i];
- double t1 = param2.val[i];
-
- dparam[0][i] = t0 - (t1 - t0);
- dparam[1][i] = t1 - t0;
- }
-
- CV_GET_FUNC_PTR( func, (CvFunc2D_1A2P)(rng_tab[0].fn_2d[depth]));
- }
- }
- else if( disttype == CV_RAND_NORMAL )
- {
- for( i = 0; i < channels; i++ )
- {
- double t0 = param1.val[i];
- double t1 = param2.val[i];
-
- dparam[0][i] = t0;
- dparam[1][i] = t1;
- }
-
- CV_GET_FUNC_PTR( func, (CvFunc2D_1A2P)(rng_tab[1].fn_2d[depth]));
- }
- else
- {
- CV_ERROR( CV_StsBadArg, "Unknown distribution type" );
- }
-
- if( !fast_int_mode )
- {
- for( i = channels; i < 12; i++ )
- {
- double t0 = dparam[0][i - channels];
- double t1 = dparam[1][i - channels];
-
- dparam[0][i] = t0;
- dparam[1][i] = t1;
- }
- }
-
- if( !is_nd )
- {
- IPPI_CALL( func( mat->data.ptr, mat_step, size, rng, param ));
- }
- else
- {
- do
- {
- IPPI_CALL( func( iterator->ptr[0], CV_STUB_STEP, size, rng, param ));
- }
- while( cvNextNArraySlice( iterator ));
- }
-
- __END__;
-}
-
-/* End of file. */
projects / opencv / blobdiff