/dports/databases/percona57-client/boost_1_59_0/libs/accumulators/test/ |
H A D | covariance.cpp | 28 accumulator_set<double, stats<tag::covariance<double, tag::covariate1> > > acc; in test_stat() 29 …accumulator_set<std::vector<double>, stats<tag::covariance<double, tag::covariate1> > > acc2(sampl… in test_stat() 80 BOOST_CHECK_CLOSE((covariance(acc)), -1.75, epsilon); in test_stat() 81 BOOST_CHECK_CLOSE((covariance(acc2))[0], 1.75, epsilon); in test_stat() 82 BOOST_CHECK_CLOSE((covariance(acc2))[1], -1.125, epsilon); in test_stat() 83 BOOST_CHECK_CLOSE((covariance(acc3))[0], 1.75, epsilon); in test_stat() 84 BOOST_CHECK_CLOSE((covariance(acc3))[1], -1.125, epsilon); in test_stat() 85 BOOST_CHECK_CLOSE((covariance(acc4))(0,0), 0.125, epsilon); in test_stat() 86 BOOST_CHECK_CLOSE((covariance(acc4))(0,1), -0.25, epsilon); in test_stat() 87 BOOST_CHECK_CLOSE((covariance(acc4))(1,0), -0.125, epsilon); in test_stat() [all …]
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/dports/databases/mysqlwsrep57-server/boost_1_59_0/libs/accumulators/test/ |
H A D | covariance.cpp | 28 accumulator_set<double, stats<tag::covariance<double, tag::covariate1> > > acc; in test_stat() 29 …accumulator_set<std::vector<double>, stats<tag::covariance<double, tag::covariate1> > > acc2(sampl… in test_stat() 80 BOOST_CHECK_CLOSE((covariance(acc)), -1.75, epsilon); in test_stat() 81 BOOST_CHECK_CLOSE((covariance(acc2))[0], 1.75, epsilon); in test_stat() 82 BOOST_CHECK_CLOSE((covariance(acc2))[1], -1.125, epsilon); in test_stat() 83 BOOST_CHECK_CLOSE((covariance(acc3))[0], 1.75, epsilon); in test_stat() 84 BOOST_CHECK_CLOSE((covariance(acc3))[1], -1.125, epsilon); in test_stat() 85 BOOST_CHECK_CLOSE((covariance(acc4))(0,0), 0.125, epsilon); in test_stat() 86 BOOST_CHECK_CLOSE((covariance(acc4))(0,1), -0.25, epsilon); in test_stat() 87 BOOST_CHECK_CLOSE((covariance(acc4))(1,0), -0.125, epsilon); in test_stat() [all …]
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/dports/science/InsightToolkit/ITK-5.0.1/Modules/Segmentation/LevelSets/test/ |
H A D | itkVectorThresholdSegmentationLevelSetImageFilterTest.cxx | 84 CovarianceMatrixType covariance = CovarianceMatrixType( 3, 3 ); in itkVectorThresholdSegmentationLevelSetImageFilterTest() local 86 covariance[0][0] = 79.2225; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 87 covariance[1][1] = 81.0314; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 88 covariance[2][2] = 51.1744; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 89 covariance[0][1] = 72.4737; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 90 covariance[0][2] = 57.7892; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 91 covariance[1][2] = 61.9859; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 92 covariance[1][0] = covariance[0][1]; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 93 covariance[2][0] = covariance[0][2]; in itkVectorThresholdSegmentationLevelSetImageFilterTest() 94 covariance[2][1] = covariance[1][2]; in itkVectorThresholdSegmentationLevelSetImageFilterTest() [all …]
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/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/segmentation/src/ |
H A D | grabcut_segmentation.cpp | 598 …g.determinant = g.covariance (0,0)*(g.covariance (1,1)*g.covariance (2,2) - g.covariance (1,2)*g.c… in fit() 599 …- g.covariance (0,1)*(g.covariance (1,0)*g.covariance (2,2) - g.covariance (1,2)*g.covariance (2,0… in fit() 600 …+ g.covariance (0,2)*(g.covariance (1,0)*g.covariance (2,1) - g.covariance (1,1)*g.covariance (2,0… in fit() 603 …g.inverse (0,0) = (g.covariance (1,1)*g.covariance (2,2) - g.covariance (1,2)*g.covariance (2,1))… in fit() 604 …g.inverse (1,0) = -(g.covariance (1,0)*g.covariance (2,2) - g.covariance (1,2)*g.covariance (2,0))… in fit() 605 …g.inverse (2,0) = (g.covariance (1,0)*g.covariance (2,1) - g.covariance (1,1)*g.covariance (2,0))… in fit() 606 …g.inverse (0,1) = -(g.covariance (0,1)*g.covariance (2,2) - g.covariance (0,2)*g.covariance (2,1))… in fit() 607 …g.inverse (1,1) = (g.covariance (0,0)*g.covariance (2,2) - g.covariance (0,2)*g.covariance (2,0))… in fit() 608 …g.inverse (2,1) = -(g.covariance (0,0)*g.covariance (2,1) - g.covariance (0,1)*g.covariance (2,0))… in fit() 609 …g.inverse (0,2) = (g.covariance (0,1)*g.covariance (1,2) - g.covariance (0,2)*g.covariance (1,1))… in fit() [all …]
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/dports/math/openturns/openturns-1.18/python/doc/examples/reliability_sensitivity/reliability/ |
H A D | plot_proba_system_event.py | 83 def buildNormal(b, t, mu_S, covariance, delta_t=1e-5): argument 85 sigma[0, 0] = covariance(t, t)[0, 0] 86 sigma[0, 1] = covariance(t, t+delta_t)[0, 0] 87 sigma[1, 1] = covariance(t+delta_t, t+delta_t)[0, 0] 95 def buildCrossing(b, t, mu_S, covariance, R, delta_t=1e-5): argument 96 normal = buildNormal(b, t, mu_S, covariance, delta_t) 108 full = buildCrossing(b, t, mu_S, covariance, R, delta_t) 128 full = buildCrossing(b, t, mu_S, covariance, R, delta_t) 149 full = buildCrossing(b, t, mu_S, covariance, R, delta_t) 184 covariance = SquaredExponential([l/sqrt(2)], [sigma_S]) variable [all …]
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/covariance/ |
H A D | _empirical_covariance.py | 91 covariance = np.dot(X.T, X) / X.shape[0] 93 covariance = np.cov(X.T, bias=1) 95 if covariance.ndim == 0: 96 covariance = np.array([[covariance]]) 97 return covariance 174 def _set_covariance(self, covariance): argument 186 covariance = check_array(covariance) 188 self.covariance_ = covariance 191 self.precision_ = linalg.pinvh(covariance, check_finite=False) 231 covariance = empirical_covariance(X, assume_centered=self.assume_centered) [all …]
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/dports/science/InsightToolkit/ITK-5.0.1/Modules/Core/ImageFunction/include/ |
H A D | itkScatterMatrixImageFunction.hxx | 57 RealType covariance; in EvaluateAtIndex() local 66 covariance = vnl_matrix< PixelComponentRealType >(VectorDimension, VectorDimension); in EvaluateAtIndex() 67 covariance.fill(NumericTraits< PixelComponentRealType >::ZeroValue()); in EvaluateAtIndex() 71 covariance.fill( NumericTraits< PixelComponentRealType >::max() ); in EvaluateAtIndex() 72 return covariance; in EvaluateAtIndex() 77 covariance.fill( NumericTraits< PixelComponentRealType >::max() ); in EvaluateAtIndex() 78 return covariance; in EvaluateAtIndex() 99 covariance[dimx][dimy] += in EvaluateAtIndex() 109 covariance[dimx][dimy] /= double(size); in EvaluateAtIndex() 113 return ( covariance ); in EvaluateAtIndex()
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/dports/math/cgal/CGAL-5.3/include/CGAL/ |
H A D | linear_least_squares_fitting_circles_2.h | 103 covariance[0] += transformation[0][0] + area * x0*x0; in linear_least_squares_fitting_2() 104 covariance[1] += transformation[0][1] + area * x0*y0; in linear_least_squares_fitting_2() 105 covariance[2] += transformation[1][1] + area * y0*y0; in linear_least_squares_fitting_2() 114 covariance[0] += -mass * (c.x() * c.x()); in linear_least_squares_fitting_2() 115 covariance[1] += -mass * (c.x() * c.y()); in linear_least_squares_fitting_2() 116 covariance[2] += -mass * (c.y() * c.y()); in linear_least_squares_fitting_2() 124 (covariance, eigen_values, eigen_vectors); in linear_least_squares_fitting_2() 220 covariance[0] += -mass * (c.x() * c.x()); in linear_least_squares_fitting_2() 221 covariance[1] += -mass * (c.x() * c.y()); in linear_least_squares_fitting_2() 222 covariance[2] += -mass * (c.y() * c.y()); in linear_least_squares_fitting_2() [all …]
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H A D | linear_least_squares_fitting_spheres_3.h | 51 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local 52 …assemble_covariance_matrix_3(first,beyond,covariance,c,k,(Sphere*) nullptr,tag, diagonalize_traits… in linear_least_squares_fitting_3() 55 return fitting_plane_3(covariance,c,plane,k,diagonalize_traits); in linear_least_squares_fitting_3() 82 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local 83 …assemble_covariance_matrix_3(first,beyond,covariance,c,k,(Sphere*) nullptr,tag, diagonalize_traits… in linear_least_squares_fitting_3() 86 return fitting_plane_3(covariance,c,plane,k,diagonalize_traits); in linear_least_squares_fitting_3() 114 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local 115 …assemble_covariance_matrix_3(first,beyond,covariance,c,k,(Sphere*) nullptr,tag, diagonalize_traits… in linear_least_squares_fitting_3() 119 return fitting_line_3(covariance,c,line,k,diagonalize_traits); in linear_least_squares_fitting_3() 146 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local [all …]
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/dports/math/openturns/openturns-1.18/python/test/ |
H A D | t_ExponentiallyDampedCosineModel_std.expout | 3 covariance matrix at t = 1.0 : [[ 0.297621 ]] 4 covariance matrix at t = -1.0 : [[ 0.297621 ]] 5 covariance matrix at t = 15.0 : [[ -3.05902e-07 ]] 6 discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= [[ 1 … 12 covariance matrix at t = 1.0 : [[ 0.113681 ]] 13 covariance matrix at t = -1.0 : [[ 0.113681 ]] 14 covariance matrix at t = 15.0 : [[ 3.05902e-07 ]] 15 discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= [[ 1 …
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H A D | t_ExponentialModel_std.expout | 3 covariance matrix at t = 1.0 : [[ 1.47152 ]] 4 covariance matrix at t = -1.0 : [[ 1.47152 ]] 5 covariance matrix at t = 15.0 : [[ 1.22361e-06 ]] 6 discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= [[ 4 … 14 covariance matrix at t = 1.0 : [[ 0.367879 0.735759 0 ] 17 covariance matrix at t = -1.0 : [[ 0.367879 0.735759 0 ] 20 covariance matrix at t = 15.0 : [[ 3.05902e-07 6.11805e-07 0 ] 23 discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= 12x12
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/dports/multimedia/gstreamer1-libav/gst-libav-1.16.2/gst-libs/ext/libav/libavutil/ |
H A D | pca.c | 33 double *covariance; member 50 pca->covariance= av_calloc(n*n, sizeof(double)); in ff_pca_init() 53 if (!pca->z || !pca->covariance || !pca->mean) { in ff_pca_init() 62 av_freep(&pca->covariance); in ff_pca_free() 75 pca->covariance[j + i*n] += v[i]*v[j]; in ff_pca_add() 92 pca->covariance[j + i*n] /= pca->count; in ff_pca() 94 pca->covariance[i + j*n] = pca->covariance[j + i*n]; in ff_pca() 96 eigenvalue[j]= pca->covariance[j + j*n]; in ff_pca() 105 sum += fabs(pca->covariance[j + i*n]); in ff_pca() 137 pca->covariance[j + i*n]=0.0; in ff_pca() [all …]
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/dports/multimedia/ffmpeg/ffmpeg-4.4.1/libavutil/ |
H A D | pca.c | 33 double *covariance; member 50 pca->covariance= av_calloc(n*n, sizeof(double)); in ff_pca_init() 53 if (!pca->z || !pca->covariance || !pca->mean) { in ff_pca_init() 62 av_freep(&pca->covariance); in ff_pca_free() 75 pca->covariance[j + i*n] += v[i]*v[j]; in ff_pca_add() 92 pca->covariance[j + i*n] /= pca->count; in ff_pca() 94 pca->covariance[i + j*n] = pca->covariance[j + i*n]; in ff_pca() 96 eigenvalue[j]= pca->covariance[j + j*n]; in ff_pca() 105 sum += fabs(pca->covariance[j + i*n]); in ff_pca() 137 pca->covariance[j + i*n]=0.0; in ff_pca() [all …]
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/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/third_party/ffmpeg/libavutil/ |
H A D | pca.c | 33 double *covariance; member 50 pca->covariance= av_calloc(n*n, sizeof(double)); in ff_pca_init() 53 if (!pca->z || !pca->covariance || !pca->mean) { in ff_pca_init() 62 av_freep(&pca->covariance); in ff_pca_free() 75 pca->covariance[j + i*n] += v[i]*v[j]; in ff_pca_add() 92 pca->covariance[j + i*n] /= pca->count; in ff_pca() 94 pca->covariance[i + j*n] = pca->covariance[j + i*n]; in ff_pca() 96 eigenvalue[j]= pca->covariance[j + j*n]; in ff_pca() 105 sum += fabs(pca->covariance[j + i*n]); in ff_pca() 137 pca->covariance[j + i*n]=0.0; in ff_pca() [all …]
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/dports/www/chromium-legacy/chromium-88.0.4324.182/third_party/ffmpeg/libavutil/ |
H A D | pca.c | 33 double *covariance; member 50 pca->covariance= av_calloc(n*n, sizeof(double)); in ff_pca_init() 53 if (!pca->z || !pca->covariance || !pca->mean) { in ff_pca_init() 62 av_freep(&pca->covariance); in ff_pca_free() 75 pca->covariance[j + i*n] += v[i]*v[j]; in ff_pca_add() 92 pca->covariance[j + i*n] /= pca->count; in ff_pca() 94 pca->covariance[i + j*n] = pca->covariance[j + i*n]; in ff_pca() 96 eigenvalue[j]= pca->covariance[j + j*n]; in ff_pca() 105 sum += fabs(pca->covariance[j + i*n]); in ff_pca() 137 pca->covariance[j + i*n]=0.0; in ff_pca() [all …]
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/dports/multimedia/handbrake/ffmpeg-4.4/libavutil/ |
H A D | pca.c | 33 double *covariance; member 50 pca->covariance= av_calloc(n*n, sizeof(double)); in ff_pca_init() 53 if (!pca->z || !pca->covariance || !pca->mean) { in ff_pca_init() 62 av_freep(&pca->covariance); in ff_pca_free() 75 pca->covariance[j + i*n] += v[i]*v[j]; in ff_pca_add() 92 pca->covariance[j + i*n] /= pca->count; in ff_pca() 94 pca->covariance[i + j*n] = pca->covariance[j + i*n]; in ff_pca() 96 eigenvalue[j]= pca->covariance[j + j*n]; in ff_pca() 105 sum += fabs(pca->covariance[j + i*n]); in ff_pca() 137 pca->covariance[j + i*n]=0.0; in ff_pca() [all …]
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/core/metrics/ |
H A D | mahalanobis_distance.hpp | 76 covariance(arma::eye<arma::mat>(dimensionality, dimensionality)) { } in MahalanobisDistance() 84 MahalanobisDistance(arma::mat covariance) : in MahalanobisDistance() argument 85 covariance(std::move(covariance)) { } in MahalanobisDistance() 104 const arma::mat& Covariance() const { return covariance; } in Covariance() 111 arma::mat& Covariance() { return covariance; } in Covariance() 119 arma::mat covariance; member in mlpack::metric::MahalanobisDistance
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/dports/lang/racket/racket-8.3/share/pkgs/math-lib/math/private/statistics/ |
H A D | correlation.rkt | 10 (provide covariance/means 12 covariance 15 (: covariance* (Symbol Real Real (Sequenceof Real) (Sequenceof Real) (Option (Sequenceof Real)) 17 (define (covariance* name mx my xs ys ws bias) 31 (adjust-covariance m2 n bias)) 33 (: covariance/means (case-> (Real Real (Sequenceof Real) (Sequenceof Real) 37 (define (covariance/means mx my xs ys [ws #f] #:bias [bias #f]) 38 (covariance* 'covariance/means mx my xs ys ws bias)) 43 (define (covariance xs ys [ws #f] #:bias [bias #f]) function 44 (covariance* 'covariance (mean xs ws) (mean ys ws) xs ys ws bias)) [all …]
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/dports/graphics/open3d/Open3D-0.2/src/Core/Geometry/ |
H A D | EstimateNormals.cpp | 86 Eigen::Matrix3d covariance; in ComputeNormal() local 102 covariance(0, 0) = cumulants(3) - cumulants(0) * cumulants(0); in ComputeNormal() 103 covariance(1, 1) = cumulants(6) - cumulants(1) * cumulants(1); in ComputeNormal() 104 covariance(2, 2) = cumulants(8) - cumulants(2) * cumulants(2); in ComputeNormal() 105 covariance(0, 1) = cumulants(4) - cumulants(0) * cumulants(1); in ComputeNormal() 106 covariance(1, 0) = covariance(0, 1); in ComputeNormal() 107 covariance(0, 2) = cumulants(5) - cumulants(0) * cumulants(2); in ComputeNormal() 108 covariance(2, 0) = covariance(0, 2); in ComputeNormal() 109 covariance(1, 2) = cumulants(7) - cumulants(1) * cumulants(2); in ComputeNormal() 110 covariance(2, 1) = covariance(1, 2); in ComputeNormal() [all …]
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H A D | PointCloud.cpp | 166 Eigen::Matrix3d covariance; in ComputePointCloudMeanAndCovariance() local 170 covariance(0, 0) = cumulants(3) - cumulants(0) * cumulants(0); in ComputePointCloudMeanAndCovariance() 171 covariance(1, 1) = cumulants(6) - cumulants(1) * cumulants(1); in ComputePointCloudMeanAndCovariance() 172 covariance(2, 2) = cumulants(8) - cumulants(2) * cumulants(2); in ComputePointCloudMeanAndCovariance() 173 covariance(0, 1) = cumulants(4) - cumulants(0) * cumulants(1); in ComputePointCloudMeanAndCovariance() 174 covariance(1, 0) = covariance(0, 1); in ComputePointCloudMeanAndCovariance() 176 covariance(2, 0) = covariance(0, 2); in ComputePointCloudMeanAndCovariance() 178 covariance(2, 1) = covariance(1, 2); in ComputePointCloudMeanAndCovariance() 179 return std::make_tuple(mean, covariance); in ComputePointCloudMeanAndCovariance() 187 Eigen::Matrix3d covariance; in ComputePointCloudMahalanobisDistance() local [all …]
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/dports/graphics/py-open3d-python/Open3D-0.2/src/Core/Geometry/ |
H A D | EstimateNormals.cpp | 86 Eigen::Matrix3d covariance; in ComputeNormal() local 102 covariance(0, 0) = cumulants(3) - cumulants(0) * cumulants(0); in ComputeNormal() 103 covariance(1, 1) = cumulants(6) - cumulants(1) * cumulants(1); in ComputeNormal() 104 covariance(2, 2) = cumulants(8) - cumulants(2) * cumulants(2); in ComputeNormal() 105 covariance(0, 1) = cumulants(4) - cumulants(0) * cumulants(1); in ComputeNormal() 106 covariance(1, 0) = covariance(0, 1); in ComputeNormal() 107 covariance(0, 2) = cumulants(5) - cumulants(0) * cumulants(2); in ComputeNormal() 108 covariance(2, 0) = covariance(0, 2); in ComputeNormal() 109 covariance(1, 2) = cumulants(7) - cumulants(1) * cumulants(2); in ComputeNormal() 110 covariance(2, 1) = covariance(1, 2); in ComputeNormal() [all …]
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H A D | PointCloud.cpp | 166 Eigen::Matrix3d covariance; in ComputePointCloudMeanAndCovariance() local 170 covariance(0, 0) = cumulants(3) - cumulants(0) * cumulants(0); in ComputePointCloudMeanAndCovariance() 171 covariance(1, 1) = cumulants(6) - cumulants(1) * cumulants(1); in ComputePointCloudMeanAndCovariance() 172 covariance(2, 2) = cumulants(8) - cumulants(2) * cumulants(2); in ComputePointCloudMeanAndCovariance() 173 covariance(0, 1) = cumulants(4) - cumulants(0) * cumulants(1); in ComputePointCloudMeanAndCovariance() 174 covariance(1, 0) = covariance(0, 1); in ComputePointCloudMeanAndCovariance() 176 covariance(2, 0) = covariance(0, 2); in ComputePointCloudMeanAndCovariance() 178 covariance(2, 1) = covariance(1, 2); in ComputePointCloudMeanAndCovariance() 179 return std::make_tuple(mean, covariance); in ComputePointCloudMeanAndCovariance() 187 Eigen::Matrix3d covariance; in ComputePointCloudMahalanobisDistance() local [all …]
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/dports/audio/praat/praat-6.2.03/external/gsl/ |
H A D | gsl_statistics__covariance_source.c | 21 FUNCTION(compute,covariance) (const BASE data1[], const size_t stride1, 27 FUNCTION(compute,covariance) (const BASE data1[], const size_t stride1, 34 long double covariance = 0 ; 43 covariance += (delta1 * delta2 - covariance) / (i + 1); 46 return covariance ; 55 const double covariance = FUNCTION(compute,covariance) (data1, stride1, 60 return covariance * ((double)n / (double)(n - 1)); 64 FUNCTION(gsl_stats,covariance) (const BASE data1[], const size_t stride1,
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/dports/math/openturns/openturns-1.18/python/src/ |
H A D | TensorizedCovarianceModel_doc.i.in | 2 "Multivariate covariance function defined as a tensorization of covariance models. 7 Collection of covariance models :math:`(C_k)_{1 \leq k \leq K}` of dimension :math:`d_k`. 11 The tensorized covariance model defines a multivariate covariance model of dimension :math:`d\geq 1… 12 from the tensorization of a given collection of covariance models. 13 This allows to create a higher dimension covariance model by combining models of smaller dimensions… 15 The input dimension of each covariance model in the collection must be the same. 19 Its covariance function :math:`C : \cD \times \cD \rightarrow \cS_d^+(\Rset)` is defined from the … 30 The amplitude of the covariance function is :math:`\Tr{\sigma} =(\Tr{\sigma}_{1}, \dots, \Tr{\sigma… 32 …^0=(\theta_{k,1}^0,\hdots,\theta_{k,n}^0)` be the initial scale of the covariance model :math:`C_k… 37 Create a tensorized covariance function from the tensorization of an absolute exponential function,… [all …]
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H A D | CovarianceModelImplementation_doc.i.in | 4 Base class for covariance models." 13 "Compute the covariance function for scalar model. 29 covariance : float 60 Container of the cross covariance 65 The cross-covariance is the evaluation of the covariance model 104 covariance matrix: 314 covariance function." 430 covariance function. 445 covariance function. 499 "Evaluate the covariance function. [all …]
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