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Warning fixes continued

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This commit is contained in:
Andrey Kamaev
2012-06-09 15:00:04 +00:00
parent f6b451c607
commit f2d3b9b4a1
127 changed files with 6298 additions and 6277 deletions
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modules/core/test/test_ds.cpp
+4 -4
View File
@@ -1262,7 +1262,7 @@ int Core_SetTest::test_set_ops( int iters )
if( iter > iters/10 && cvtest::randInt(rng)%200 == 0 ) // clear set
{
int prev_count = cvset->total;
prev_count = cvset->total;
cvClearSet( cvset );
cvTsClearSimpleSet( sset );
@@ -1482,19 +1482,19 @@ int Core_GraphTest::test_graph_ops( int iters )
if( cvtest::randInt(rng) % 200 == 0 ) // clear graph
{
int prev_vtx_count = graph->total, prev_edge_count = graph->edges->total;
int prev_vtx_count2 = graph->total, prev_edge_count2 = graph->edges->total;
cvClearGraph( graph );
cvTsClearSimpleGraph( sgraph );
CV_TS_SEQ_CHECK_CONDITION( graph->active_count == 0 && graph->total == 0 &&
graph->first == 0 && graph->free_elems == 0 &&
(graph->free_blocks != 0 || prev_vtx_count == 0),
(graph->free_blocks != 0 || prev_vtx_count2 == 0),
"The graph is not empty after clearing" );
CV_TS_SEQ_CHECK_CONDITION( edges->active_count == 0 && edges->total == 0 &&
edges->first == 0 && edges->free_elems == 0 &&
(edges->free_blocks != 0 || prev_edge_count == 0),
(edges->free_blocks != 0 || prev_edge_count2 == 0),
"The graph is not empty after clearing" );
}
else if( op == 0 ) // add vertex
modules/core/test/test_mat.cpp
+83 -83
View File
@@ -22,25 +22,25 @@ void testReduce( const Mat& src, Mat& sum, Mat& avg, Mat& max, Mat& min, int dim
assert( src.channels() == 1 );
if( dim == 0 ) // row
{
sum.create( 1, src.cols, CV_64FC1 );
sum.create( 1, src.cols, CV_64FC1 );
max.create( 1, src.cols, CV_64FC1 );
min.create( 1, src.cols, CV_64FC1 );
}
else
{
sum.create( src.rows, 1, CV_64FC1 );
sum.create( src.rows, 1, CV_64FC1 );
max.create( src.rows, 1, CV_64FC1 );
min.create( src.rows, 1, CV_64FC1 );
}
sum.setTo(Scalar(0));
max.setTo(Scalar(-DBL_MAX));
min.setTo(Scalar(DBL_MAX));
const Mat_<Type>& src_ = src;
Mat_<double>& sum_ = (Mat_<double>&)sum;
Mat_<double>& min_ = (Mat_<double>&)min;
Mat_<double>& max_ = (Mat_<double>&)max;
if( dim == 0 )
{
for( int ri = 0; ri < src.rows; ri++ )
@@ -128,7 +128,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
else if ( dstType == CV_32S )
eps = 0.6;
}
assert( opRes.type() == CV_64FC1 );
Mat _dst, dst, diff;
reduce( src, _dst, dim, opType, dstType );
@@ -151,7 +151,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
getMatTypeStr( src.type(), srcTypeStr );
getMatTypeStr( dstType, dstTypeStr );
const char* dimStr = dim == 0 ? "ROWS" : "COLS";
sprintf( msg, "bad accuracy with srcType = %s, dstType = %s, opType = %s, dim = %s",
srcTypeStr.c_str(), dstTypeStr.c_str(), opTypeStr, dimStr );
ts->printf( cvtest::TS::LOG, msg );
@@ -164,10 +164,10 @@ int Core_ReduceTest::checkCase( int srcType, int dstType, int dim, Size sz )
{
int code = cvtest::TS::OK, tempCode;
Mat src, sum, avg, max, min;
src.create( sz, srcType );
randu( src, Scalar(0), Scalar(100) );
if( srcType == CV_8UC1 )
testReduce<uchar>( src, sum, avg, max, min, dim );
else if( srcType == CV_8SC1 )
@@ -182,110 +182,108 @@ int Core_ReduceTest::checkCase( int srcType, int dstType, int dim, Size sz )
testReduce<float>( src, sum, avg, max, min, dim );
else if( srcType == CV_64FC1 )
testReduce<double>( src, sum, avg, max, min, dim );
else
else
assert( 0 );
// 1. sum
tempCode = checkOp( src, dstType, CV_REDUCE_SUM, sum, dim );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// 2. avg
tempCode = checkOp( src, dstType, CV_REDUCE_AVG, avg, dim );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// 3. max
tempCode = checkOp( src, dstType, CV_REDUCE_MAX, max, dim );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// 4. min
tempCode = checkOp( src, dstType, CV_REDUCE_MIN, min, dim );
code = tempCode != cvtest::TS::OK ? tempCode : code;
return code;
}
int Core_ReduceTest::checkDim( int dim, Size sz )
{
int code = cvtest::TS::OK, tempCode;
// CV_8UC1
tempCode = checkCase( CV_8UC1, CV_8UC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_8UC1, CV_32SC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_8UC1, CV_32FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_8UC1, CV_64FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// CV_16UC1
tempCode = checkCase( CV_16UC1, CV_32FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_16UC1, CV_64FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// CV_16SC1
tempCode = checkCase( CV_16SC1, CV_32FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_16SC1, CV_64FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// CV_32FC1
tempCode = checkCase( CV_32FC1, CV_32FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkCase( CV_32FC1, CV_64FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
// CV_64FC1
tempCode = checkCase( CV_64FC1, CV_64FC1, dim, sz );
code = tempCode != cvtest::TS::OK ? tempCode : code;
return code;
}
int Core_ReduceTest::checkSize( Size sz )
{
int code = cvtest::TS::OK, tempCode;
tempCode = checkDim( 0, sz ); // rows
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkDim( 1, sz ); // cols
tempCode = checkDim( 1, sz ); // cols
code = tempCode != cvtest::TS::OK ? tempCode : code;
return code;
}
void Core_ReduceTest::run( int )
{
int code = cvtest::TS::OK, tempCode;
tempCode = checkSize( Size(1,1) );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkSize( Size(1,100) );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkSize( Size(100,1) );
code = tempCode != cvtest::TS::OK ? tempCode : code;
tempCode = checkSize( Size(1000,500) );
code = tempCode != cvtest::TS::OK ? tempCode : code;
ts->set_failed_test_info( code );
}
#define CHECK_C
Size sz(200, 500);
class Core_PCATest : public cvtest::BaseTest
{
public:
@@ -293,41 +291,43 @@ public:
protected:
void run(int)
{
const Size sz(200, 500);
double diffPrjEps, diffBackPrjEps,
prjEps, backPrjEps,
evalEps, evecEps;
int maxComponents = 100;
Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
RNG& rng = ts->get_rng();
RNG& rng = ts->get_rng();
rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
// 1. check C++ PCA & ROW
Mat rPrjTestPoints = rPCA.project( rTestPoints );
Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
Mat avg(1, sz.width, CV_32FC1 );
reduce( rPoints, avg, 0, CV_REDUCE_AVG );
Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
Q = Qt * Q;
Q = Q /(float)rPoints.rows;
eigen( Q, eval, evec );
/*SVD svd(Q);
evec = svd.vt;
eval = svd.w;*/
Mat subEval( maxComponents, 1, eval.type(), eval.data ),
subEvec( maxComponents, evec.cols, evec.type(), evec.data );
#ifdef CHECK_C
Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
#endif
// check eigen()
double eigenEps = 1e-6;
double err;
@@ -335,7 +335,7 @@ protected:
{
Mat v = evec.row(i).t();
Mat Qv = Q * v;
Mat lv = eval.at<float>(i,0) * v;
err = norm( Qv, lv );
if( err > eigenEps )
@@ -370,7 +370,7 @@ protected:
absdiff(rPCA.eigenvectors, subEvec, tmp);
double mval = 0; Point mloc;
minMaxLoc(tmp, 0, &mval, 0, &mloc);
ts->printf( cvtest::TS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
ts->printf( cvtest::TS::LOG, "max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
@@ -380,7 +380,7 @@ protected:
}
}
}
prjEps = 1.265, backPrjEps = 1.265;
for( int i = 0; i < rTestPoints.rows; i++ )
{
@@ -404,7 +404,7 @@ protected:
return;
}
}
// 2. check C++ PCA & COL
cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
diffPrjEps = 1, diffBackPrjEps = 1;
@@ -423,7 +423,7 @@ protected:
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
return;
}
#ifdef CHECK_C
// 3. check C PCA & ROW
_points = rPoints;
@@ -435,11 +435,11 @@ protected:
backPrjTestPoints.create(rPoints.size(), rPoints.type() );
_prjTestPoints = prjTestPoints;
_backPrjTestPoints = backPrjTestPoints;
cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
err = norm(prjTestPoints, rPrjTestPoints, CV_RELATIVE_L2);
if( err > diffPrjEps )
{
@@ -454,7 +454,7 @@ protected:
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
return;
}
// 3. check C PCA & COL
_points = cPoints;
_testPoints = cTestPoints;
@@ -463,11 +463,11 @@ protected:
evec = evec.t(); _evec = evec;
prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
err = norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
if( err > diffPrjEps )
{
@@ -490,9 +490,9 @@ class Core_ArrayOpTest : public cvtest::BaseTest
{
public:
Core_ArrayOpTest();
~Core_ArrayOpTest();
~Core_ArrayOpTest();
protected:
void run(int);
void run(int);
};
@@ -536,7 +536,7 @@ static double getValue(SparseMat& M, const int* idx, RNG& rng)
d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
phv = &hv;
}
const uchar* ptr = d == 2 ? M.ptr(idx[0], idx[1], false, phv) :
d == 3 ? M.ptr(idx[0], idx[1], idx[2], false, phv) :
M.ptr(idx, false, phv);
@@ -560,7 +560,7 @@ static void eraseValue(SparseMat& M, const int* idx, RNG& rng)
d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
phv = &hv;
}
if( d == 2 )
M.erase(idx[0], idx[1], phv);
else if( d == 3 )
@@ -584,7 +584,7 @@ static void setValue(SparseMat& M, const int* idx, double value, RNG& rng)
d == 3 ? M.hash(idx[0], idx[1], idx[2]) : M.hash(idx);
phv = &hv;
}
uchar* ptr = d == 2 ? M.ptr(idx[0], idx[1], true, phv) :
d == 3 ? M.ptr(idx[0], idx[1], idx[2], true, phv) :
M.ptr(idx, true, phv);
@@ -599,7 +599,7 @@ static void setValue(SparseMat& M, const int* idx, double value, RNG& rng)
void Core_ArrayOpTest::run( int /* start_from */)
{
int errcount = 0;
// dense matrix operations
{
int sz3[] = {5, 10, 15};
@@ -608,7 +608,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
RNG rng;
rng.fill(A, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
rng.fill(B, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
int idx0[] = {3,4,5}, idx1[] = {0, 9, 7};
float val0 = 130;
Scalar val1(-1000, 30, 3, 8);
@@ -617,12 +617,12 @@ void Core_ArrayOpTest::run( int /* start_from */)
cvSetND(&matB, idx0, val1);
cvSet3D(&matB, idx1[0], idx1[1], idx1[2], -val1);
Ptr<CvMatND> matC = cvCloneMatND(&matB);
if( A.at<float>(idx0[0], idx0[1], idx0[2]) != val0 ||
A.at<float>(idx1[0], idx1[1], idx1[2]) != -val0 ||
cvGetReal3D(&matA, idx0[0], idx0[1], idx0[2]) != val0 ||
cvGetRealND(&matA, idx1) != -val0 ||
Scalar(B.at<Vec4s>(idx0[0], idx0[1], idx0[2])) != val1 ||
Scalar(B.at<Vec4s>(idx1[0], idx1[1], idx1[2])) != -val1 ||
Scalar(cvGet3D(matC, idx0[0], idx0[1], idx0[2])) != val1 ||
@@ -633,7 +633,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
errcount++;
}
}
RNG rng;
const int MAX_DIM = 5, MAX_DIM_SZ = 10;
// sparse matrix operations
@@ -647,7 +647,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
vector<double> all_vals2;
string sidx, min_sidx, max_sidx;
double min_val=0, max_val=0;
int p = 1;
for( k = 0; k < dims; k++ )
{
@@ -656,7 +656,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
}
SparseMat M( dims, size, depth );
map<string, double> M0;
int nz0 = (unsigned)rng % max(p/5,10);
nz0 = min(max(nz0, 1), p);
all_vals.resize(nz0);
@@ -676,12 +676,12 @@ void Core_ArrayOpTest::run( int /* start_from */)
_all_vals2.convertTo(_all_vals2_f, CV_32F);
_all_vals2_f.convertTo(_all_vals2, CV_64F);
}
minMaxLoc(_all_vals, &min_val, &max_val);
double _norm0 = norm(_all_vals, CV_C);
double _norm1 = norm(_all_vals, CV_L1);
double _norm2 = norm(_all_vals, CV_L2);
for( i = 0; i < nz0; i++ )
{
for(;;)
@@ -708,18 +708,18 @@ void Core_ArrayOpTest::run( int /* start_from */)
break;
}
}
Ptr<CvSparseMat> M2 = (CvSparseMat*)M;
MatND Md;
M.copyTo(Md);
SparseMat M3; SparseMat(Md).convertTo(M3, Md.type(), 2);
int nz1 = (int)M.nzcount(), nz2 = (int)M3.nzcount();
double norm0 = norm(M, CV_C);
double norm1 = norm(M, CV_L1);
double norm2 = norm(M, CV_L2);
double eps = depth == CV_32F ? FLT_EPSILON*100 : DBL_EPSILON*1000;
if( nz1 != nz0 || nz2 != nz0)
{
errcount++;
@@ -727,7 +727,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
si, nz1, nz2, nz0 );
break;
}
if( fabs(norm0 - _norm0) > fabs(_norm0)*eps ||
fabs(norm1 - _norm1) > fabs(_norm1)*eps ||
fabs(norm2 - _norm2) > fabs(_norm2)*eps )
@@ -737,10 +737,10 @@ void Core_ArrayOpTest::run( int /* start_from */)
si, norm0, norm1, norm2, _norm0, _norm1, _norm2 );
break;
}
int n = (unsigned)rng % max(p/5,10);
n = min(max(n, 1), p) + nz0;
for( i = 0; i < n; i++ )
{
double val1, val2, val3, val0;
@@ -760,7 +760,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
val1 = getValue(M, idx, rng);
val2 = getValue(M2, idx);
val3 = getValue(M3, idx, rng);
if( val1 != val0 || val2 != val0 || fabs(val3 - val0*2) > fabs(val0*2)*FLT_EPSILON )
{
errcount++;
@@ -768,7 +768,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
break;
}
}
for( i = 0; i < n; i++ )
{
double val1, val2;
@@ -792,9 +792,9 @@ void Core_ArrayOpTest::run( int /* start_from */)
errcount++;
ts->printf(cvtest::TS::LOG, "SparseMat: after deleting M[%s], it is =%g/%g (while it should be 0)\n", sidx.c_str(), val1, val2 );
break;
}
}
}
int nz = (int)M.nzcount();
if( nz != 0 )
{
@@ -802,7 +802,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
ts->printf(cvtest::TS::LOG, "The number of non-zero elements after removing all the elements = %d (while it should be 0)\n", nz );
break;
}
int idx1[MAX_DIM], idx2[MAX_DIM];
double val1 = 0, val2 = 0;
M3 = SparseMat(Md);
@@ -816,7 +816,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
min_val, max_val, min_sidx.c_str(), max_sidx.c_str());
break;
}
minMaxIdx(Md, &val1, &val2, idx1, idx2);
s1 = idx2string(idx1, dims), s2 = idx2string(idx2, dims);
if( (min_val < 0 && (val1 != min_val || s1 != min_sidx)) ||
@@ -829,7 +829,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
break;
}
}
ts->set_failed_test_info(errcount == 0 ? cvtest::TS::OK : cvtest::TS::FAIL_INVALID_OUTPUT);
}
modules/core/test/test_rand.cpp
+36 -36
View File
@@ -27,7 +27,7 @@ static double chi2_p95(int n)
36.42f, 37.65f, 38.89f, 40.11f, 41.34f, 42.56f, 43.77f };
static const double xp = 1.64;
CV_Assert(n >= 1);
if( n <= 30 )
return chi2_tab95[n-1];
return n + sqrt((double)2*n)*xp + 0.6666666666666*(xp*xp - 1);
@@ -40,12 +40,12 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
const int* H = (const int*)hist.data;
float* H0 = ((float*)hist0.data);
int i, hsz = hist.cols;
double sum = 0;
for( i = 0; i < hsz; i++ )
sum += H[i];
CV_Assert( fabs(1./sum - scale) < FLT_EPSILON );
if( dist_type == CV_RAND_UNI )
{
float scale0 = (float)(1./hsz);
@@ -54,19 +54,19 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
}
else
{
double sum = 0, r = (hsz-1.)/2;
double sum2 = 0, r = (hsz-1.)/2;
double alpha = 2*sqrt(2.)/r, beta = -alpha*r;
for( i = 0; i < hsz; i++ )
{
double x = i*alpha + beta;
H0[i] = (float)exp(-x*x);
sum += H0[i];
sum2 += H0[i];
}
sum = 1./sum;
sum2 = 1./sum2;
for( i = 0; i < hsz; i++ )
H0[i] = (float)(H0[i]*sum);
H0[i] = (float)(H0[i]*sum2);
}
double chi2 = 0;
for( i = 0; i < hsz; i++ )
{
@@ -76,7 +76,7 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
chi2 += (a - b)*(a - b)/(a + b);
}
realval = chi2;
double chi2_pval = chi2_p95(hsz - 1 - (dist_type == CV_RAND_NORMAL ? 2 : 0));
refval = chi2_pval*0.01;
return realval <= refval;
@@ -87,22 +87,22 @@ void Core_RandTest::run( int )
static int _ranges[][2] =
{{ 0, 256 }, { -128, 128 }, { 0, 65536 }, { -32768, 32768 },
{ -1000000, 1000000 }, { -1000, 1000 }, { -1000, 1000 }};
const int MAX_SDIM = 10;
const int N = 2000000;
const int maxSlice = 1000;
const int MAX_HIST_SIZE = 1000;
int progress = 0;
RNG& rng = ts->get_rng();
RNG tested_rng = theRNG();
test_case_count = 200;
for( int idx = 0; idx < test_case_count; idx++ )
{
progress = update_progress( progress, idx, test_case_count, 0 );
ts->update_context( this, idx, false );
int depth = cvtest::randInt(rng) % (CV_64F+1);
int c, cn = (cvtest::randInt(rng) % 4) + 1;
int type = CV_MAKETYPE(depth, cn);
@@ -113,15 +113,15 @@ void Core_RandTest::run( int )
double eps = 1.e-4;
if (depth == CV_64F)
eps = 1.e-7;
bool do_sphere_test = dist_type == CV_RAND_UNI;
Mat arr[2], hist[4];
int W[] = {0,0,0,0};
arr[0].create(1, SZ, type);
arr[1].create(1, SZ, type);
bool fast_algo = dist_type == CV_RAND_UNI && depth < CV_32F;
for( c = 0; c < cn; c++ )
{
int a, b, hsz;
@@ -137,7 +137,7 @@ void Core_RandTest::run( int )
while( abs(a-b) <= 1 );
if( a > b )
std::swap(a, b);
unsigned r = (unsigned)(b - a);
fast_algo = fast_algo && r <= 256 && (r & (r-1)) == 0;
hsz = min((unsigned)(b - a), (unsigned)MAX_HIST_SIZE);
@@ -149,7 +149,7 @@ void Core_RandTest::run( int )
int meanrange = vrange/16;
int mindiv = MAX(vrange/20, 5);
int maxdiv = MIN(vrange/8, 10000);
a = cvtest::randInt(rng) % meanrange - meanrange/2 +
(_ranges[depth][0] + _ranges[depth][1])/2;
b = cvtest::randInt(rng) % (maxdiv - mindiv) + mindiv;
@@ -157,9 +157,9 @@ void Core_RandTest::run( int )
}
A[c] = a;
B[c] = b;
hist[c].create(1, hsz, CV_32S);
hist[c].create(1, hsz, CV_32S);
}
cv::RNG saved_rng = tested_rng;
int maxk = fast_algo ? 0 : 1;
for( k = 0; k <= maxk; k++ )
@@ -173,14 +173,14 @@ void Core_RandTest::run( int )
tested_rng.fill(aslice, dist_type, A, B);
}
}
if( maxk >= 1 && norm(arr[0], arr[1], NORM_INF) > eps)
{
ts->printf( cvtest::TS::LOG, "RNG output depends on the array lengths (some generated numbers get lost?)" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return;
}
for( c = 0; c < cn; c++ )
{
const uchar* data = arr[0].data;
@@ -190,9 +190,9 @@ void Core_RandTest::run( int )
double maxVal = dist_type == CV_RAND_UNI ? B[c] : A[c] + B[c]*4;
double scale = HSZ/(maxVal - minVal);
double delta = -minVal*scale;
hist[c] = Scalar::all(0);
for( i = c; i < SZ*cn; i += cn )
{
double val = depth == CV_8U ? ((const uchar*)data)[i] :
@@ -221,7 +221,7 @@ void Core_RandTest::run( int )
}
}
}
if( dist_type == CV_RAND_UNI && W[c] != SZ )
{
ts->printf( cvtest::TS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n",
@@ -237,7 +237,7 @@ void Core_RandTest::run( int )
return;
}
double refval = 0, realval = 0;
if( !check_pdf(hist[c], 1./W[c], dist_type, refval, realval) )
{
ts->printf( cvtest::TS::LOG, "RNG failed Chi-square test "
@@ -247,13 +247,13 @@ void Core_RandTest::run( int )
return;
}
}
// Monte-Carlo test. Compute volume of SDIM-dimensional sphere
// inscribed in [-1,1]^SDIM cube.
if( do_sphere_test )
{
int SDIM = cvtest::randInt(rng) % (MAX_SDIM-1) + 2;
int N0 = (SZ*cn/SDIM), N = 0;
int N0 = (SZ*cn/SDIM), n = 0;
double r2 = 0;
const uchar* data = arr[0].data;
double scale[4], delta[4];
@@ -262,7 +262,7 @@ void Core_RandTest::run( int )
scale[c] = 2./(B[c] - A[c]);
delta[c] = -A[c]*scale[c] - 1;
}
for( i = k = c = 0; i <= SZ*cn - SDIM; i++, k++, c++ )
{
double val = depth == CV_8U ? ((const uchar*)data)[i] :
@@ -276,20 +276,20 @@ void Core_RandTest::run( int )
r2 += val*val;
if( k == SDIM-1 )
{
N += r2 <= 1;
n += r2 <= 1;
r2 = 0;
k = -1;
}
}
double V = ((double)N/N0)*(1 << SDIM);
double V = ((double)n/N0)*(1 << SDIM);
// the theoretically computed volume
int sdim = SDIM % 2;
double V0 = sdim + 1;
for( sdim += 2; sdim <= SDIM; sdim += 2 )
V0 *= 2*CV_PI/sdim;
if( fabs(V - V0) > 0.3*fabs(V0) )
{
ts->printf( cvtest::TS::LOG, "RNG failed %d-dim sphere volume test (got %g instead of %g)\n",
@@ -309,7 +309,7 @@ class Core_RandRangeTest : public cvtest::BaseTest
{
public:
Core_RandRangeTest() {}
~Core_RandRangeTest() {}
~Core_RandRangeTest() {}
protected:
void run(int)
{
@@ -319,7 +319,7 @@ protected:
theRNG().fill(af, RNG::UNIFORM, -DBL_MAX, DBL_MAX);
int n0 = 0, n255 = 0, nx = 0;
int nfmin = 0, nfmax = 0, nfx = 0;
for( int i = 0; i < a.rows; i++ )
for( int j = 0; j < a.cols; j++ )
{