/dports/devel/spark/spark-2.1.1/mllib-local/src/test/scala/org/apache/spark/ml/util/ |
H A D | TestingUtilsSuite.scala | 23 import org.apache.spark.ml.linalg.{Matrices, Vectors} 267 assert(Matrices.dense(2, 1, Array(3.1, 3.5)) !~= 270 assert(Matrices.dense(0, 0, Array()) !~= 273 assert(Matrices.dense(0, 0, Array()) !~== 346 Matrices.dense(0, 0, Array()) absTol 1E-6) 349 Matrices.dense(0, 0, Array()) absTol 1E-6) 376 assert(Matrices.dense(2, 1, Array(3.1, 3.5)) !~= 379 assert(Matrices.dense(0, 0, Array()) !~= 382 assert(Matrices.dense(0, 0, Array()) !~== 455 Matrices.dense(0, 0, Array()) relTol 0.01) [all …]
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/dports/devel/spark/spark-2.1.1/mllib/src/test/scala/org/apache/spark/mllib/util/ |
H A D | TestingUtilsSuite.scala | 23 import org.apache.spark.mllib.linalg.{Matrices, Vectors} 267 assert(Matrices.dense(2, 1, Array(3.1, 3.5)) !~= 270 assert(Matrices.dense(0, 0, Array()) !~= 273 assert(Matrices.dense(0, 0, Array()) !~== 346 Matrices.dense(0, 0, Array()) absTol 1E-6) 349 Matrices.dense(0, 0, Array()) absTol 1E-6) 376 assert(Matrices.dense(2, 1, Array(3.1, 3.5)) !~= 379 assert(Matrices.dense(0, 0, Array()) !~= 382 assert(Matrices.dense(0, 0, Array()) !~== 455 Matrices.dense(0, 0, Array()) relTol 0.01) [all …]
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/dports/biology/p5-Bio-Phylo/Bio-Phylo-v2.0.1/t/ |
H A D | 31-phylip.t | 18 isa_ok( $matrix, 'Bio::Phylo::Matrices::Matrix' ); 22 isa_ok( $matrix->get_by_name('Species_1'), 'Bio::Phylo::Matrices::Datum' ); 23 isa_ok( $matrix->get_by_name('Species_2'), 'Bio::Phylo::Matrices::Datum' ); 24 isa_ok( $matrix->get_by_name('Species_3'), 'Bio::Phylo::Matrices::Datum' ); 25 isa_ok( $matrix->get_by_name('Species_4'), 'Bio::Phylo::Matrices::Datum' ); 34 isa_ok( $matrix, 'Bio::Phylo::Matrices::Matrix' ); 37 isa_ok( $matrix->get_by_name('Species_1'), 'Bio::Phylo::Matrices::Datum' ); 38 isa_ok( $matrix->get_by_name('Species_2'), 'Bio::Phylo::Matrices::Datum' ); 39 isa_ok( $matrix->get_by_name('Species_3'), 'Bio::Phylo::Matrices::Datum' ); 46 isa_ok( $matrix, 'Bio::Phylo::Matrices::Matrix' ); [all …]
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H A D | 24-bioperl-alignio.t | 2 use Bio::Phylo::Matrices::Matrix; 44 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 57 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 75 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 84 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 93 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 116 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 144 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $str->next_aln() ); 349 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl($aln); 468 $aln = Bio::Phylo::Matrices::Matrix->new_from_bioperl( $io->next_aln ); [all …]
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H A D | 10-matrices.t | 6 use Bio::Phylo::Matrices; 7 use Bio::Phylo::Matrices::Matrix; 8 use Bio::Phylo::Matrices::Datum; 11 ok( my $matrices = new Bio::Phylo::Matrices, '1 initialize obj' ); 19 ok( $matrices->insert( new Bio::Phylo::Matrices::Matrix ), '4 insert good' ); 27 my $datum1 = Bio::Phylo::Matrices::Datum->new( '-taxon' => $taxon1 ); 28 my $datum3 = Bio::Phylo::Matrices::Datum->new( '-taxon' => $taxon2 ); 31 my $matrix = Bio::Phylo::Matrices::Matrix->new( '-type' => 'DNA' );
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/dports/devel/spark/spark-2.1.1/mllib-local/src/test/scala/org/apache/spark/ml/linalg/ |
H A D | MatricesSuite.scala | 43 Matrices.dense(3, 2, Array(0.0, 1.0, 2.0)) 281 val deMat2 = Matrices.eye(3) 282 val spMat2 = Matrices.speye(3) 283 val deMat3 = Matrices.eye(2) 284 val spMat3 = Matrices.speye(2) 333 Matrices.horzcat(Array(spMat1, spMat3)) 337 Matrices.horzcat(Array(deMat1, spMat3)) 383 Matrices.vertcat(Array(spMat1, spMat2)) 387 Matrices.vertcat(Array(deMat1, spMat2)) 463 val empty = Matrices.ones(0, 0) [all …]
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H A D | BreezeMatrixConversionSuite.scala | 26 val mat = Matrices.dense(3, 2, Array(0.0, 1.0, 2.0, 3.0, 4.0, 5.0)) 35 val mat = Matrices.fromBreeze(breeze).asInstanceOf[DenseMatrix] 40 val matTransposed = Matrices.fromBreeze(breeze.t).asInstanceOf[DenseMatrix] 50 val mat = Matrices.sparse(3, 2, colPtrs, rowIndices, values) 62 val mat = Matrices.fromBreeze(breeze).asInstanceOf[SparseMatrix] 66 val matTransposed = Matrices.fromBreeze(breeze.t).asInstanceOf[SparseMatrix]
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/dports/devel/spark/spark-2.1.1/mllib/src/test/java/org/apache/spark/mllib/linalg/ |
H A D | JavaMatricesSuite.java | 32 Matrix r = Matrices.rand(3, 4, rng); in randMatrixConstruction() 38 Matrix rn = Matrices.randn(3, 4, rng); in randMatrixConstruction() 58 Matrix r = Matrices.eye(2); in identityMatrixConstruction() 71 Matrix m = Matrices.diag(v); in diagonalMatrixConstruction() 72 Matrix sm = Matrices.diag(sv); in diagonalMatrixConstruction() 92 Matrix z = Matrices.zeros(2, 2); in zerosMatrixConstruction() 93 Matrix one = Matrices.ones(2, 2); in zerosMatrixConstruction() 131 Matrix deMat2 = Matrices.eye(3); in concatenateMatrices() 132 Matrix spMat2 = Matrices.speye(3); in concatenateMatrices() 133 Matrix deMat3 = Matrices.eye(2); in concatenateMatrices() [all …]
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/dports/devel/spark/spark-2.1.1/mllib/src/test/scala/org/apache/spark/mllib/linalg/ |
H A D | MatricesSuite.scala | 45 Matrices.dense(3, 2, Array(0.0, 1.0, 2.0)) 283 val deMat2 = Matrices.eye(3) 284 val spMat2 = Matrices.speye(3) 285 val deMat3 = Matrices.eye(2) 286 val spMat3 = Matrices.speye(2) 335 Matrices.horzcat(Array(spMat1, spMat3)) 339 Matrices.horzcat(Array(deMat1, spMat3)) 385 Matrices.vertcat(Array(spMat1, spMat2)) 389 Matrices.vertcat(Array(deMat1, spMat2)) 480 val empty = Matrices.ones(0, 0) [all …]
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H A D | BreezeMatrixConversionSuite.scala | 26 val mat = Matrices.dense(3, 2, Array(0.0, 1.0, 2.0, 3.0, 4.0, 5.0)) 35 val mat = Matrices.fromBreeze(breeze).asInstanceOf[DenseMatrix] 40 val matTransposed = Matrices.fromBreeze(breeze.t).asInstanceOf[DenseMatrix] 50 val mat = Matrices.sparse(3, 2, colPtrs, rowIndices, values) 62 val mat = Matrices.fromBreeze(breeze).asInstanceOf[SparseMatrix] 66 val matTransposed = Matrices.fromBreeze(breeze.t).asInstanceOf[SparseMatrix]
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/dports/cad/leocad/leocad-21.06/common/ |
H A D | minifig.cpp | 294 lcMatrix44* Matrices = mMinifig.Matrices; in Calculate() local 316 Matrices[LC_MFW_HEAD] = lcMul(Mat, Root); in Calculate() 323 Matrices[LC_MFW_HATS] = lcMul(Mat, Matrices[LC_MFW_HEAD]); in Calculate() 330 Matrices[LC_MFW_HATS2] = lcMul(Mat, Matrices[LC_MFW_HATS]); in Calculate() 345 Matrices[LC_MFW_RARM] = lcMul(Mat, Root); in Calculate() 355 Matrices[LC_MFW_RHAND] = lcMul(Mat, Matrices[LC_MFW_RARM]); in Calculate() 364 Matrices[LC_MFW_RHANDA] = lcMul(Mat, Matrices[LC_MFW_RHAND]); in Calculate() 389 Matrices[LC_MFW_LHAND] = lcMul(Mat, Matrices[LC_MFW_LARM]); in Calculate() 398 Matrices[LC_MFW_LHANDA] = lcMul(Mat, Matrices[LC_MFW_LHAND]); in Calculate() 433 Matrices[LC_MFW_RLEGA] = lcMul(Mat, Matrices[LC_MFW_RLEG]); in Calculate() [all …]
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/dports/graphics/dataplot/dataplot-2c1b27601a3b7523449de612613eadeead9a8f70/lib/frmenus/help/ |
H A D | matrices.top | 1 ----- <~help\matrices.top> Matrices 3 Matrices 5 Matrices 7 Matrices Useful For Linear Algebra And Multivariate Analysis - 9 Matrices and matrix manipulation commands are useful 21 Matrices cannot be used in Dataplot except for these 26 Commands To Create Matrices 28 Matrices are created with the 49 element in column 3 and row 5). Matrices cannot be used
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/dports/devel/spark/spark-2.1.1/mllib-local/src/test/scala/org/apache/spark/ml/stat/distribution/ |
H A D | MultivariateGaussianSuite.scala | 21 import org.apache.spark.ml.linalg.{Matrices, Vectors} 32 val sigma1 = Matrices.dense(1, 1, Array(1.0)) 37 val sigma2 = Matrices.dense(1, 1, Array(4.0)) 48 val sigma1 = Matrices.dense(2, 2, Array(1.0, 0.0, 0.0, 1.0)) 53 val sigma2 = Matrices.dense(2, 2, Array(4.0, -1.0, -1.0, 2.0)) 64 val sigma = Matrices.dense(2, 2, Array(1.0, 1.0, 1.0, 1.0)) 74 val sigma = Matrices.dense(4, 4, Array(
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/dports/devel/spark/spark-2.1.1/mllib/src/test/scala/org/apache/spark/mllib/stat/distribution/ |
H A D | MultivariateGaussianSuite.scala | 21 import org.apache.spark.mllib.linalg.{Matrices, Vectors} 31 val sigma1 = Matrices.dense(1, 1, Array(1.0)) 36 val sigma2 = Matrices.dense(1, 1, Array(4.0)) 47 val sigma1 = Matrices.dense(2, 2, Array(1.0, 0.0, 0.0, 1.0)) 52 val sigma2 = Matrices.dense(2, 2, Array(4.0, -1.0, -1.0, 2.0)) 63 val sigma = Matrices.dense(2, 2, Array(1.0, 1.0, 1.0, 1.0)) 73 val sigma = Matrices.dense(4, 4, Array(
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/dports/biology/p5-Bio-Phylo/Bio-Phylo-v2.0.1/ |
H A D | MANIFEST | 18 lib/Bio/Phylo/Matrices.pm 19 lib/Bio/Phylo/Matrices/Character.pm 20 lib/Bio/Phylo/Matrices/Characters.pm 21 lib/Bio/Phylo/Matrices/Datatype.pm 24 lib/Bio/Phylo/Matrices/Datatype/Dna.pm 29 lib/Bio/Phylo/Matrices/Datatype/Rna.pm 33 lib/Bio/Phylo/Matrices/Datum.pm 34 lib/Bio/Phylo/Matrices/DatumRole.pm 35 lib/Bio/Phylo/Matrices/Matrix.pm 36 lib/Bio/Phylo/Matrices/MatrixRole.pm [all …]
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/dports/devel/spark/spark-2.1.1/mllib/src/test/scala/org/apache/spark/mllib/clustering/ |
H A D | GaussianMixtureSuite.scala | 21 import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors} 38 val Esigma = Matrices.dense(2, 2, Array(2.0 / 3.0, -2.0 / 3.0, -2.0 / 3.0, 2.0 / 3.0)) 57 new MultivariateGaussian(Vectors.dense(-1.0), Matrices.dense(1, 1, Array(1.0))), 58 new MultivariateGaussian(Vectors.dense(1.0), Matrices.dense(1, 1, Array(1.0))) 64 val Esigma = Array(Matrices.dense(1, 1, Array(1.1098)), Matrices.dense(1, 1, Array(0.86644))) 102 val Esigma = Matrices.dense(3, 3, 122 new MultivariateGaussian(Vectors.dense(-1.0), Matrices.dense(1, 1, Array(1.0))), 123 new MultivariateGaussian(Vectors.dense(1.0), Matrices.dense(1, 1, Array(1.0))) 128 val Esigma = Array(Matrices.dense(1, 1, Array(1.1098)), Matrices.dense(1, 1, Array(0.86644)))
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/dports/math/R-cran-SparseM/SparseM/demo/ |
H A D | 00Index | 1 Binding Binding and Indexing for Sparse Matrices 2 Coercion Coercion of Matrices into Various New Classes 4 LinearAlgebra Basic Linear Algebra for Sparse Matrices 6 Visualization Visualization Tools for Sparse Matrices
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/dports/math/fricas/fricas-1.3.7/pre-generated/target/share/hypertex/pages/ |
H A D | MATRIX.ht | 25 \menudownlink{{9.56.1. Creating Matrices}}{ugxMatrixCreatePage} 26 \menudownlink{{9.56.2. Operations on Matrices}}{ugxMatrixOpsPage} 33 \newcommand{\ugxMatrixCreateTitle}{Creating Matrices} 37 \begin{page}{ugxMatrixCreatePage}{9.56.1. Creating Matrices} 78 %-% \HDindex{matrix!diagonal}{ugxMatrixCreatePage}{9.56.1.}{Creating Matrices} 97 %-% \HDindex{matrix!copying}{ugxMatrixCreatePage}{9.56.1.}{Creating Matrices} 115 %-% \HDindex{matrix!submatrix of}{ugxMatrixCreatePage}{9.56.1.}{Creating Matrices} 151 Matrices can be joined either horizontally or vertically to make 189 \newcommand{\ugxMatrixOpsTitle}{Operations on Matrices} 193 \begin{page}{ugxMatrixOpsPage}{9.56.2. Operations on Matrices} [all …]
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/dports/biology/viennarna/ViennaRNA-2.4.18/doc/latex/ |
H A D | group__dp__matrices.tex | 1 \hypertarget{group__dp__matrices}{}\doxysection{The Dynamic Programming Matrices} 2 …bel{group__dp__matrices}\index{The Dynamic Programming Matrices@{The Dynamic Programming Matrices}} 13 Collaboration diagram for The Dynamic Programming Matrices\+: 155 \index{The Dynamic Programming Matrices@{The Dynamic Programming Matrices}!vrna\_mx\_type\_e@{vrna\… 156 …x\_type\_e@{vrna\_mx\_type\_e}!The Dynamic Programming Matrices@{The Dynamic Programming Matrices}} 195 \index{The Dynamic Programming Matrices@{The Dynamic Programming Matrices}!vrna\_mx\_add@{vrna\_mx\… 196 …{vrna\_mx\_add@{vrna\_mx\_add}!The Dynamic Programming Matrices@{The Dynamic Programming Matrices}} 229 \index{The Dynamic Programming Matrices@{The Dynamic Programming Matrices}!vrna\_mx\_mfe\_free@{vrn… 230 …fe\_free@{vrna\_mx\_mfe\_free}!The Dynamic Programming Matrices@{The Dynamic Programming Matrices}} 251 \index{The Dynamic Programming Matrices@{The Dynamic Programming Matrices}!vrna\_mx\_pf\_free@{vrna… [all …]
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/dports/cad/opencascade/opencascade-7.6.0/src/IGESSolid/ |
H A D | IGESSolid_SolidAssembly.cxx | 33 const Handle(IGESGeom_HArray1OfTransformationMatrix)& Matrices) in Init() argument 35 if (Items->Lower() != 1 || Matrices->Lower() != 1 || in Init() 36 Items->Length() != Matrices->Length()) in Init() 40 theMatrices = Matrices; in Init()
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/dports/math/giacxcas/CoCoALib-0.99700/src/CoCoA-5/packages/ |
H A D | CoLA.cpkg5 | 116 If len(ARGV) = 1 then Matrices := ARGV[1]; EndIf; 119 K := RingOf(Matrices[1]); 120 S := NumRows(Matrices[1]); 121 N := len(Matrices); 122 Foreach M in Matrices Do 128 //If IsEmpty(Matrices) Then Return ideal(1); EndIf; 131 Mi := Matrices[i]; 133 Mj := Matrices[j]; 139 if K<>CoeffRing(P) or NumIndets(P)<len(Matrices) then 140 error("K<>CoeffRing(P) or NumIndets(P)<len(Matrices)"); [all …]
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/dports/math/cocoalib/CoCoALib-0.99712/src/CoCoA-5/packages/ |
H A D | CoLA.cpkg5 | 116 If len(ARGV) = 1 then Matrices := ARGV[1]; EndIf; 119 K := RingOf(Matrices[1]); 120 S := NumRows(Matrices[1]); 121 N := len(Matrices); 122 Foreach M in Matrices Do 128 //If IsEmpty(Matrices) Then Return ideal(1); EndIf; 131 Mi := Matrices[i]; 133 Mj := Matrices[j]; 139 if K<>CoeffRing(P) or NumIndets(P)<len(Matrices) then 140 error("K<>CoeffRing(P) or NumIndets(P)<len(Matrices)"); [all …]
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/dports/textproc/fox-xml/fox-4.1.2-91-g9c6716e/common/test/ |
H A D | run_tests.sh | 31 echo Matrices: 55 echo Matrices: 70 echo Matrices: 180 echo Matrices 293 echo Matrices
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/dports/emulators/mednafen/mednafen/src/psx/ |
H A D | gte.cpp | 100 static Matrices_t Matrices; variable 194 memset(Matrices.All, 0, sizeof(Matrices.All)); in GTE_Power() 231 SFVARN(Matrices.Raw16, "&Matrices.Raw16[0][0]"), in GTE_StateAction() 314 Matrices.Raw[we][which] = (value << 16) | (value >> 16); in GTE_WriteCR() 316 Matrices.Raw[we][which] = value; in GTE_WriteCR() 895 if(matrix == &Matrices.AbbyNormal) in MultiplyMatrixByVector() 1007 MultiplyMatrixByVector(&Matrices.All[mx], v, cv, sf, lm); in MVMVA() 1105 MultiplyMatrixByVector(&Matrices.Color, tmp_vector, CRVectors.B, sf, lm); in NormColor() 1369 MAC[1] = ((Matrices.Rot.MX[1][1] * IR3) - (Matrices.Rot.MX[2][2] * IR2)) >> sf; in OP() 1370 MAC[2] = ((Matrices.Rot.MX[2][2] * IR1) - (Matrices.Rot.MX[0][0] * IR3)) >> sf; in OP() [all …]
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/dports/math/octave/octave-6.4.0/doc/interpreter/ |
H A D | octave.texi | 179 * Sparse Matrices:: 289 * Matrices:: 298 Matrices 300 * Empty Matrices:: 630 * Rearranging Matrices:: 631 * Special Utility Matrices:: 632 * Famous Matrices:: 693 Sparse Matrices 703 * Creating Sparse Matrices:: 768 * Vector Rotation Matrices:: [all …]
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