/ndk/sources/cxx-stl/llvm-libc++/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/ |
ctor_double.pass.cpp | 25 assert(d.mean() == 1); 30 assert(d.mean() == 3.5);
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param_ctor.pass.cpp | 27 assert(p.mean() == 1); 33 assert(p.mean() == 10);
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ctor_param.pass.cpp | 27 assert(d.mean() == 0.25);
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param_assign.pass.cpp | 29 assert(p.mean() == .7);
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param_copy.pass.cpp | 28 assert(p.mean() == .125);
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eval.pass.cpp | 45 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 51 double d = (u[i] - mean); 62 double x_mean = d.mean(); 63 double x_var = d.mean(); 66 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 84 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 90 double d = (u[i] - mean); 101 double x_mean = d.mean(); 102 double x_var = d.mean(); 105 assert(std::abs((mean - x_mean) / x_mean) < 0.01) 123 double mean = std::accumulate(u.begin(), u.end(), 0.0) \/ u.size(); local [all...] |
eval_param.pass.cpp | 47 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 53 double d = (u[i] - mean); 64 double x_mean = p.mean(); 65 double x_var = p.mean(); 68 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 88 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 94 double d = (u[i] - mean); 105 double x_mean = p.mean(); 106 double x_var = p.mean(); 109 assert(std::abs((mean - x_mean) / x_mean) < 0.01) 129 double mean = std::accumulate(u.begin(), u.end(), 0.0) \/ u.size(); local [all...] |
/ndk/sources/cxx-stl/llvm-libc++/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/ |
ctor_double_double.pass.cpp | 15 // explicit normal_distribution(result_type mean = 0, result_type stddev = 1); 25 assert(d.mean() == 0); 31 assert(d.mean() == 14.5); 37 assert(d.mean() == 14.5);
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param_ctor.pass.cpp | 27 assert(p.mean() == 0); 34 assert(p.mean() == 10); 41 assert(p.mean() == 10);
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ctor_param.pass.cpp | 27 assert(d.mean() == 0.25);
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eval.pass.cpp | 42 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 48 double d = (u[i] - mean); 59 double x_mean = d.mean(); 63 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
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eval_param.pass.cpp | 43 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 49 double d = (u[i] - mean); 60 double x_mean = p.mean(); 64 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
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param_assign.pass.cpp | 29 assert(p.mean() == .75);
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param_copy.pass.cpp | 28 assert(p.mean() == 10);
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/external/webrtc/src/common_audio/vad/ |
vad_gmm.h | 19 // normal distribution with mean and standard deviation (|mean|, |std|). 23 // - mean : mean input in the statistical model, Q7. 29 // |delta| = (|input| - |mean|) / |std|^2. 33 // 1 / |std| * exp(-(|input| - |mean|)^2 / (2 * |std|^2)); 35 int16_t mean,
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vad_gmm.c | 25 // m = |mean| (Q7) 31 int16_t mean, 52 tmp16 = tmp16 - mean; // Q7 - Q7 = Q7
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/external/valgrind/main/VEX/test/ |
rounderr.c | 43 /* Compute the arithmetic mean of a dataset using the recurrence relation 44 mean_(n) = mean(n-1) + (data[n] - mean(n-1))/(n+1) */ 45 long double mean = 0; local 50 mean += (data[i * stride] - mean) / (i + 1); 52 return mean; 58 /* Compute the arithmetic mean of a dataset using the
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/external/opencv/cv/src/ |
cvadapthresh.cpp | 48 CvMat* mean = 0; local 70 mean = dst; 72 CV_CALL( mean = cvCreateMat( rows, cols, CV_8UC1 )); 74 CV_CALL( cvSmooth( src, mean, method == CV_ADAPTIVE_THRESH_MEAN_C ? 89 const uchar* m = mean->data.ptr + i*mean->step; 98 if( mean != dst ) 99 cvReleaseMat( &mean );
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/external/eigen/Eigen/src/Eigen2Support/ |
LeastSquares.h | 121 * 1 - center the data to the mean 142 // compute the mean of the data 143 VectorType mean = VectorType::Zero(size); local 145 mean += *(points[i]); 146 mean /= numPoints; 153 VectorType diff = (*(points[i]) - mean).conjugate(); 164 // plane pass trough the mean point: 165 result->offset() = - (result->normal().cwise()* mean).sum();
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/external/opencv/cxcore/src/ |
cxmean.cpp | 46 * Mean value over the region * 165 mean[0] = scale*(double)tmp##0 171 mean[0] = t0; \ 172 mean[1] = t1 179 mean[0] = t0; \ 180 mean[1] = t1; \ 181 mean[2] = t2 187 mean[0] = t0; \ 188 mean[1] = t1; \ 191 mean[2] = t0; 384 CvScalar mean = {{0,0,0,0}}; local [all...] |
/external/eigen/doc/examples/ |
tut_arithmetic_redux_basic.cpp | 12 cout << "Here is mat.mean(): " << mat.mean() << endl;
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/ndk/sources/cxx-stl/llvm-libc++/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/ |
eval.pass.cpp | 45 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 51 double d = (u[i] - mean); 66 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 84 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 90 double d = (u[i] - mean); 105 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 123 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 129 double d = (u[i] - mean); 144 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 162 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size() local [all...] |
eval_param.pass.cpp | 46 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 52 double d = (u[i] - mean); 67 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 86 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 92 double d = (u[i] - mean); 107 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 126 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local 132 double d = (u[i] - mean); 147 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 166 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size() local [all...] |
/ndk/sources/cxx-stl/llvm-libc++/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/ |
eval.pass.cpp | 45 double mean = std::accumulate(u.begin(), u.end(), local 52 double d = (u[i] - mean); 67 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 85 double mean = std::accumulate(u.begin(), u.end(), local 92 double d = (u[i] - mean); 107 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 125 double mean = std::accumulate(u.begin(), u.end(), local 132 double d = (u[i] - mean); 147 assert(std::abs((mean - x_mean) / x_mean) < 0.01); 165 double mean = std::accumulate(u.begin(), u.end() local 203 double mean = std::accumulate(u.begin(), u.end(), local 241 double mean = std::accumulate(u.begin(), u.end(), local [all...] |
/external/opencv/ml/src/ |
mltestset.cpp | 65 CvMat* mean = NULL; local 107 CV_CALL( mean = cvCreateMat( 1, num_features, CV_32FC1 ) ); 108 CV_CALL( cvSetZero( mean ) ); 114 CV_CALL( cvRandMVNormal( mean, cov, *samples ) ); 165 cvReleaseMat( &mean );
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