1 #include "test_precomp.hpp"
6 class Core_RandTest : public cvtest::BaseTest
12 bool check_pdf(const Mat& hist, double scale, int dist_type,
13 double& refval, double& realval);
17 Core_RandTest::Core_RandTest()
21 static double chi2_p95(int n)
23 static float chi2_tab95[] = {
24 3.841f, 5.991f, 7.815f, 9.488f, 11.07f, 12.59f, 14.07f, 15.51f,
25 16.92f, 18.31f, 19.68f, 21.03f, 21.03f, 22.36f, 23.69f, 25.00f,
26 26.30f, 27.59f, 28.87f, 30.14f, 31.41f, 32.67f, 33.92f, 35.17f,
27 36.42f, 37.65f, 38.89f, 40.11f, 41.34f, 42.56f, 43.77f };
28 static const double xp = 1.64;
32 return chi2_tab95[n-1];
33 return n + sqrt((double)2*n)*xp + 0.6666666666666*(xp*xp - 1);
36 bool Core_RandTest::check_pdf(const Mat& hist, double scale,
37 int dist_type, double& refval, double& realval)
39 Mat hist0(hist.size(), CV_32F);
40 const int* H = (const int*)hist.data;
41 float* H0 = ((float*)hist0.data);
42 int i, hsz = hist.cols;
45 for( i = 0; i < hsz; i++ )
47 CV_Assert( fabs(1./sum - scale) < FLT_EPSILON );
49 if( dist_type == CV_RAND_UNI )
51 float scale0 = (float)(1./hsz);
52 for( i = 0; i < hsz; i++ )
57 double sum2 = 0, r = (hsz-1.)/2;
58 double alpha = 2*sqrt(2.)/r, beta = -alpha*r;
59 for( i = 0; i < hsz; i++ )
61 double x = i*alpha + beta;
62 H0[i] = (float)exp(-x*x);
66 for( i = 0; i < hsz; i++ )
67 H0[i] = (float)(H0[i]*sum2);
71 for( i = 0; i < hsz; i++ )
74 double b = H[i]*scale;
76 chi2 += (a - b)*(a - b)/(a + b);
80 double chi2_pval = chi2_p95(hsz - 1 - (dist_type == CV_RAND_NORMAL ? 2 : 0));
81 refval = chi2_pval*0.01;
82 return realval <= refval;
85 void Core_RandTest::run( int )
87 static int _ranges[][2] =
88 {{ 0, 256 }, { -128, 128 }, { 0, 65536 }, { -32768, 32768 },
89 { -1000000, 1000000 }, { -1000, 1000 }, { -1000, 1000 }};
91 const int MAX_SDIM = 10;
92 const int N = 2000000;
93 const int maxSlice = 1000;
94 const int MAX_HIST_SIZE = 1000;
97 RNG& rng = ts->get_rng();
98 RNG tested_rng = theRNG();
99 test_case_count = 200;
101 for( int idx = 0; idx < test_case_count; idx++ )
103 progress = update_progress( progress, idx, test_case_count, 0 );
104 ts->update_context( this, idx, false );
106 int depth = cvtest::randInt(rng) % (CV_64F+1);
107 int c, cn = (cvtest::randInt(rng) % 4) + 1;
108 int type = CV_MAKETYPE(depth, cn);
109 int dist_type = cvtest::randInt(rng) % (CV_RAND_NORMAL+1);
117 bool do_sphere_test = dist_type == CV_RAND_UNI;
121 arr[0].create(1, SZ, type);
122 arr[1].create(1, SZ, type);
123 bool fast_algo = dist_type == CV_RAND_UNI && depth < CV_32F;
125 for( c = 0; c < cn; c++ )
128 if( dist_type == CV_RAND_UNI )
130 a = (int)(cvtest::randInt(rng) % (_ranges[depth][1] -
131 _ranges[depth][0])) + _ranges[depth][0];
134 b = (int)(cvtest::randInt(rng) % (_ranges[depth][1] -
135 _ranges[depth][0])) + _ranges[depth][0];
137 while( abs(a-b) <= 1 );
141 unsigned r = (unsigned)(b - a);
142 fast_algo = fast_algo && r <= 256 && (r & (r-1)) == 0;
143 hsz = min((unsigned)(b - a), (unsigned)MAX_HIST_SIZE);
144 do_sphere_test = do_sphere_test && b - a >= 100;
148 int vrange = _ranges[depth][1] - _ranges[depth][0];
149 int meanrange = vrange/16;
150 int mindiv = MAX(vrange/20, 5);
151 int maxdiv = MIN(vrange/8, 10000);
153 a = cvtest::randInt(rng) % meanrange - meanrange/2 +
154 (_ranges[depth][0] + _ranges[depth][1])/2;
155 b = cvtest::randInt(rng) % (maxdiv - mindiv) + mindiv;
156 hsz = min((unsigned)b*9, (unsigned)MAX_HIST_SIZE);
160 hist[c].create(1, hsz, CV_32S);
163 cv::RNG saved_rng = tested_rng;
164 int maxk = fast_algo ? 0 : 1;
165 for( k = 0; k <= maxk; k++ )
167 tested_rng = saved_rng;
168 int sz = 0, dsz = 0, slice;
169 for( slice = 0; slice < maxSlice; slice++, sz += dsz )
171 dsz = slice+1 < maxSlice ? cvtest::randInt(rng) % (SZ - sz + 1) : SZ - sz;
172 Mat aslice = arr[k].colRange(sz, sz + dsz);
173 tested_rng.fill(aslice, dist_type, A, B);
177 if( maxk >= 1 && norm(arr[0], arr[1], NORM_INF) > eps)
179 ts->printf( cvtest::TS::LOG, "RNG output depends on the array lengths (some generated numbers get lost?)" );
180 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
184 for( c = 0; c < cn; c++ )
186 const uchar* data = arr[0].data;
187 int* H = hist[c].ptr<int>();
188 int HSZ = hist[c].cols;
189 double minVal = dist_type == CV_RAND_UNI ? A[c] : A[c] - B[c]*4;
190 double maxVal = dist_type == CV_RAND_UNI ? B[c] : A[c] + B[c]*4;
191 double scale = HSZ/(maxVal - minVal);
192 double delta = -minVal*scale;
194 hist[c] = Scalar::all(0);
196 for( i = c; i < SZ*cn; i += cn )
198 double val = depth == CV_8U ? ((const uchar*)data)[i] :
199 depth == CV_8S ? ((const schar*)data)[i] :
200 depth == CV_16U ? ((const ushort*)data)[i] :
201 depth == CV_16S ? ((const short*)data)[i] :
202 depth == CV_32S ? ((const int*)data)[i] :
203 depth == CV_32F ? ((const float*)data)[i] :
204 ((const double*)data)[i];
205 int ival = cvFloor(val*scale + delta);
206 if( (unsigned)ival < (unsigned)HSZ )
211 else if( dist_type == CV_RAND_UNI )
213 if( (minVal <= val && val < maxVal) || (depth >= CV_32F && val == maxVal) )
215 H[ival < 0 ? 0 : HSZ-1]++;
225 if( dist_type == CV_RAND_UNI && W[c] != SZ )
227 ts->printf( cvtest::TS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n",
229 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
232 if( dist_type == CV_RAND_NORMAL && W[c] < SZ*.90)
234 ts->printf( cvtest::TS::LOG, "Normal RNG gave too many values out of the range (%g+4*%g,%g+4*%g) on channel %d/%d\n",
235 A[c], B[c], A[c], B[c], c, cn);
236 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
239 double refval = 0, realval = 0;
241 if( !check_pdf(hist[c], 1./W[c], dist_type, refval, realval) )
243 ts->printf( cvtest::TS::LOG, "RNG failed Chi-square test "
244 "(got %g vs probable maximum %g) on channel %d/%d\n",
245 realval, refval, c, cn);
246 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
251 // Monte-Carlo test. Compute volume of SDIM-dimensional sphere
252 // inscribed in [-1,1]^SDIM cube.
255 int SDIM = cvtest::randInt(rng) % (MAX_SDIM-1) + 2;
256 int N0 = (SZ*cn/SDIM), n = 0;
258 const uchar* data = arr[0].data;
259 double scale[4], delta[4];
260 for( c = 0; c < cn; c++ )
262 scale[c] = 2./(B[c] - A[c]);
263 delta[c] = -A[c]*scale[c] - 1;
266 for( i = k = c = 0; i <= SZ*cn - SDIM; i++, k++, c++ )
268 double val = depth == CV_8U ? ((const uchar*)data)[i] :
269 depth == CV_8S ? ((const schar*)data)[i] :
270 depth == CV_16U ? ((const ushort*)data)[i] :
271 depth == CV_16S ? ((const short*)data)[i] :
272 depth == CV_32S ? ((const int*)data)[i] :
273 depth == CV_32F ? ((const float*)data)[i] : ((const double*)data)[i];
274 c &= c < cn ? -1 : 0;
275 val = val*scale[c] + delta[c];
285 double V = ((double)n/N0)*(1 << SDIM);
287 // the theoretically computed volume
289 double V0 = sdim + 1;
290 for( sdim += 2; sdim <= SDIM; sdim += 2 )
293 if( fabs(V - V0) > 0.3*fabs(V0) )
295 ts->printf( cvtest::TS::LOG, "RNG failed %d-dim sphere volume test (got %g instead of %g)\n",
297 ts->printf( cvtest::TS::LOG, "depth = %d, N0 = %d\n", depth, N0);
298 ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
305 TEST(Core_Rand, quality) { Core_RandTest test; test.safe_run(); }
308 class Core_RandRangeTest : public cvtest::BaseTest
311 Core_RandRangeTest() {}
312 ~Core_RandRangeTest() {}
316 Mat a(Size(1280, 720), CV_8U, Scalar(20));
317 Mat af(Size(1280, 720), CV_32F, Scalar(20));
318 theRNG().fill(a, RNG::UNIFORM, -DBL_MAX, DBL_MAX);
319 theRNG().fill(af, RNG::UNIFORM, -DBL_MAX, DBL_MAX);
320 int n0 = 0, n255 = 0, nx = 0;
321 int nfmin = 0, nfmax = 0, nfx = 0;
323 for( int i = 0; i < a.rows; i++ )
324 for( int j = 0; j < a.cols; j++ )
326 int v = a.at<uchar>(i,j);
327 double vf = af.at<float>(i,j);
329 else if( v == 255 ) n255++;
331 if( vf < FLT_MAX*-0.999f ) nfmin++;
332 else if( vf > FLT_MAX*0.999f ) nfmax++;
335 CV_Assert( n0 > nx*2 && n255 > nx*2 );
336 CV_Assert( nfmin > nfx*2 && nfmax > nfx*2 );
340 TEST(Core_Rand, range) { Core_RandRangeTest test; test.safe_run(); }