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2288 行
112 KiB
2288 行
112 KiB
<?xml version="1.0"?>
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<doc>
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<assembly>
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<name>CSparse</name>
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</assembly>
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<members>
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<member name="T:CSparse.ColumnOrdering">
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<summary>
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Column ordering for AMD.
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</summary>
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</member>
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<member name="F:CSparse.ColumnOrdering.Natural">
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<summary>
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Natural ordering.
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</summary>
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</member>
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<member name="F:CSparse.ColumnOrdering.MinimumDegreeAtPlusA">
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<summary>
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Minimum degree ordering of (A'+A).
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</summary>
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</member>
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<member name="F:CSparse.ColumnOrdering.MinimumDegreeStS">
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<summary>
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Minimum degree ordering of (A'*A) with removal of dense rows (not suited for Cholesky).
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</summary>
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</member>
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<member name="F:CSparse.ColumnOrdering.MinimumDegreeAtA">
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<summary>
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Minimum degree ordering of (A'*A) (not suited for Cholesky).
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</summary>
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</member>
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<member name="T:CSparse.Complex.DenseMatrix">
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<summary>
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Dense matrix stored in column major order.
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</summary>
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.#ctor(System.Int32,System.Int32)">
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<summary>
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Initializes a new instance of the DenseMatrix class.
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</summary>
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.#ctor(System.Int32,System.Int32,System.Numerics.Complex[])">
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<summary>
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Initializes a new instance of the DenseMatrix class.
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</summary>
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.L1Norm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.InfinityNorm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.FrobeniusNorm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Clone">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Multiply(System.Numerics.Complex[],System.Numerics.Complex[])">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Multiply(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex,System.Numerics.Complex[])">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.TransposeMultiply(System.Numerics.Complex[],System.Numerics.Complex[])">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.TransposeMultiply(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex,System.Numerics.Complex[])">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Add(CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex},CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex})">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Multiply(CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex},CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex})">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.PointwiseMultiply(CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex},CSparse.Storage.DenseColumnMajorStorage{System.Numerics.Complex})">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.DenseMatrix.Equals(CSparse.Matrix{System.Numerics.Complex},System.Double)">
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<inheritdoc />
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</member>
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<member name="T:CSparse.Complex.SparseMatrix">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.#ctor(System.Int32,System.Int32)">
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<summary>
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Initializes a new instance of the SparseMatrix class.
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</summary>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.#ctor(System.Int32,System.Int32,System.Int32)">
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<summary>
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Initializes a new instance of the SparseMatrix class.
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</summary>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.#ctor(System.Int32,System.Int32,System.Numerics.Complex[],System.Int32[],System.Int32[])">
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<summary>
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Initializes a new instance of the SparseMatrix class.
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</summary>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.DropZeros(System.Double)">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Keep(System.Func{System.Int32,System.Int32,System.Numerics.Complex,System.Boolean})">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.L1Norm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.InfinityNorm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.FrobeniusNorm">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Multiply(System.Numerics.Complex[],System.Numerics.Complex[])">
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<summary>
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Multiplies a (m-by-n) matrix by a vector, y = A*x.
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</summary>
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<param name="x">Vector of length n (column count).</param>
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<param name="y">Vector of length m (row count), containing the result.</param>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Multiply(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex,System.Numerics.Complex[])">
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<summary>
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Multiplies a (m-by-n) matrix by a vector, y = alpha*A*x + beta*y.
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</summary>
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<param name="x">Vector of length n (column count).</param>
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<param name="y">Vector of length m (row count), containing the result.</param>
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<param name="alpha">Scalar to multiply with matrix.</param>
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<param name="beta">Scalar to multiply with vector y.</param>
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<remarks>
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Input values of vector y will be accumulated.
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</remarks>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.TransposeMultiply(System.Numerics.Complex[],System.Numerics.Complex[])">
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<summary>
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Multiplies the transpose of a (m-by-n) matrix by a vector, y = A'*x.
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</summary>
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<param name="x">Vector of length m (column count of A').</param>
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<param name="y">Vector of length n (row count of A'), containing the result.</param>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.TransposeMultiply(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex,System.Numerics.Complex[])">
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<summary>
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Multiplies the transpose of a (m-by-n) matrix by a vector, y = alpha*A'*x + beta*y.
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</summary>
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<param name="x">Vector of length m (column count of A').</param>
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<param name="y">Vector of length n (row count of A'), containing the result.</param>
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<param name="alpha">Scalar to multiply with matrix.</param>
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<param name="beta">Scalar to multiply with vector y.</param>
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<remarks>
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Input values of vector y will be accumulated.
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</remarks>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Transpose(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Transpose this matrix (with complex conjugation) and store the result in given matrix.
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</summary>
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<param name="result"></param>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Add(System.Numerics.Complex,System.Numerics.Complex,CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Adds two matrices, C = alpha*A + beta*B, where A is current instance.
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</summary>
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<param name="alpha">Scalar factor for A, current instance.</param>
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<param name="beta">Scalar factor for B, other instance.</param>
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<param name="other">The matrix added to this instance.</param>
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<param name="result">Contains the sum.</param>
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<remarks>
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The (result) matrix has to be fully initialized and provide enough space for
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the nonzero entries of the sum. An upper bound is the sum of the nonzeros count
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of (this) and (other).
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</remarks>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Multiply(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Sparse matrix multiplication, C = A*B
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</summary>
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<param name="other">column-compressed matrix</param>
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<returns>C = A*B, null on error</returns>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.IsSymmetric">
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<summary>
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Evaluates whether this matrix is complex Hermitian.
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</summary>
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Equals(CSparse.Matrix{System.Numerics.Complex},System.Double)">
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<inheritdoc />
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</member>
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<member name="M:CSparse.Complex.SparseMatrix.Scatter(System.Int32,System.Numerics.Complex,System.Int32[],System.Numerics.Complex[],System.Int32,CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32)">
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<summary>
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Scatters and sums a sparse vector A(:,j) into a dense vector, x = x + beta * A(:,j).
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</summary>
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<param name="j">the column of A to use</param>
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<param name="beta">scalar multiplied by A(:,j)</param>
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<param name="w">size m, node i is marked if w[i] = mark</param>
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<param name="x">size m, ignored if null</param>
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<param name="mark">mark value of w</param>
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<param name="mat">pattern of x accumulated in C.i</param>
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<param name="nz">pattern of x placed in C starting at C.i[nz]</param>
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<returns>new value of nz, -1 on error</returns>
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</member>
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<member name="T:CSparse.Complex.Factorization.SparseCholesky">
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<summary>
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Sparse Cholesky decomposition (only upper triangular part is used).
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</summary>
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<remarks>
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See Chapter 4 (Cholesky factorization) in "Direct Methods for Sparse Linear Systems"
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by Tim Davis.
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</remarks>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering)">
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<summary>
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Creates a sparse Cholesky factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="order">Ordering method to use (natural or A+A').</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering,CSparse.IProgress)">
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<summary>
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Creates a sparse Cholesky factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="order">Ordering method to use (natural or A+A').</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[])">
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<summary>
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Creates a sparse Cholesky factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="p">Permutation.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[],CSparse.IProgress)">
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<summary>
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Creates a sparse Cholesky factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="p">Permutation.</param>
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</member>
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<member name="P:CSparse.Complex.Factorization.SparseCholesky.NonZerosCount">
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<summary>
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Gets the number of nonzeros of the L factor.
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</summary>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Solve(System.Numerics.Complex[],System.Numerics.Complex[])">
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<summary>
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Solves a system of linear equations, <c>Ax = b</c>.
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</summary>
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<param name="input">The right hand side vector, <c>b</c>.</param>
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<param name="result">The left hand side vector, <c>x</c>.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Update(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Sparse Cholesky update, L*L' + w*w'
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</summary>
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<param name="w">The update matrix.</param>
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<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Downdate(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Sparse Cholesky downdate, L*L' - w*w'
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</summary>
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<param name="w">The update matrix.</param>
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<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.UpDown(System.Int32,CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex})">
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<summary>
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Sparse Cholesky update/downdate, L*L' + sigma*w*w'
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</summary>
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<param name="sigma">1 = update or -1 = downdate</param>
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<param name="w">The update matrix.</param>
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<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.Factorize(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.IProgress)">
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<summary>
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Compute the Numeric Cholesky factorization, L = chol (A, [pinv parent cp]).
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</summary>
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<returns>Numeric Cholesky factorization</returns>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.SymbolicAnalysis(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[])">
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<summary>
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Ordering and symbolic analysis for a Cholesky factorization.
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</summary>
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<param name="A">Matrix to factorize.</param>
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<param name="p">Permutation.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseCholesky.PermuteSym(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[],System.Boolean)">
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<summary>
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Permutes a symmetric sparse matrix. C = PAP' where A and C are symmetric.
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</summary>
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<param name="A">column-compressed matrix (only upper triangular part is used)</param>
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<param name="pinv">size n, inverse permutation</param>
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<param name="values">allocate pattern only if false, values and pattern otherwise</param>
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<returns>Permuted matrix, C = PAP'</returns>
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</member>
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<member name="T:CSparse.Complex.Factorization.SparseLU">
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<summary>
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Sparse LU decomposition.
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</summary>
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<remarks>
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See Chapter 6 (LU factorization) in "Direct Methods for Sparse Linear Systems"
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by Tim Davis.
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</remarks>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering,System.Double)">
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<summary>
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Creates a LU factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="order">Ordering method to use (natural or A+A').</param>
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<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering,System.Double,CSparse.IProgress)">
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<summary>
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Creates a LU factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="order">Ordering method to use (natural or A+A').</param>
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<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[],System.Double)">
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<summary>
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Creates a LU factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="p">Permutation.</param>
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<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[],System.Double,CSparse.IProgress)">
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<summary>
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Creates a LU factorization.
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</summary>
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<param name="A">Column-compressed matrix, symmetric positive definite.</param>
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<param name="p">Permutation.</param>
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<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
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</member>
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<member name="P:CSparse.Complex.Factorization.SparseLU.NonZerosCount">
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<summary>
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Gets the number of nonzeros in both L and U factors together.
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</summary>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Solve(System.Numerics.Complex[],System.Numerics.Complex[])">
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<summary>
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Solves a system of linear equations, <c>Ax = b</c>.
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</summary>
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<param name="input">The right hand side vector, <c>b</c>.</param>
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<param name="result">The left hand side vector, <c>x</c>.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.SolveTranspose(System.Numerics.Complex[],System.Numerics.Complex[])">
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<summary>
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Solves a system of linear equations, <c>A'x = b</c>.
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</summary>
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<param name="input">The right hand side vector, <c>b</c>.</param>
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<param name="result">The left hand side vector, <c>x</c>.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.Factorize(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Double,CSparse.IProgress)">
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<summary>
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[L,U,pinv] = lu(A, [q lnz unz]). lnz and unz can be guess.
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</summary>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.SymbolicAnalysis(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32[])">
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<summary>
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Symbolic ordering and analysis for LU.
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</summary>
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<param name="A"></param>
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<param name="p">Permutation.</param>
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</member>
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<member name="M:CSparse.Complex.Factorization.SparseLU.SolveSp(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32,System.Int32[],System.Numerics.Complex[],System.Int32[],System.Boolean)">
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<summary>
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Solve Gx=b(:,k), where G is either upper (lo=false) or lower (lo=true)
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triangular.
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</summary>
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<param name="G">lower or upper triangular matrix in column-compressed form</param>
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<param name="B">right hand side, b=B(:,k)</param>
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<param name="k">use kth column of B as right hand side</param>
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<param name="xi">size 2*n, nonzero pattern of x in xi[top..n-1]</param>
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<param name="x">size n, x in x[xi[top..n-1]]</param>
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<param name="pinv">mapping of rows to columns of G, ignored if null</param>
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<param name="lo">true if lower triangular, false if upper</param>
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<returns>top, -1 in error</returns>
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</member>
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<member name="T:CSparse.Complex.Factorization.SparseQR">
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<summary>
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|
Sparse QR decomposition.
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 5 (Orthogonal methods) in "Direct Methods for Sparse Linear Systems"
|
|
by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Factorization.SparseQR.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering)">
|
|
<summary>
|
|
Creates a sparse QR factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Factorization.SparseQR.Create(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},CSparse.ColumnOrdering,CSparse.IProgress)">
|
|
<summary>
|
|
Creates a sparse QR factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Factorization.SparseQR.Solve(System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Solves a system of linear equations, <c>Ax = b</c>.
|
|
</summary>
|
|
<param name="input">The right hand side vector, <c>b</c>.</param>
|
|
<param name="result">The left hand side vector, <c>x</c>.</param>
|
|
<remarks>
|
|
Let A be a m-by-n matrix. If m >= n a least-squares problem (min |Ax-b|)
|
|
is solved. If m < n the underdetermined system is solved.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Factorization.SparseQR.CreateHouseholder(System.Numerics.Complex[],System.Int32,System.Double@,System.Int32)">
|
|
<summary>
|
|
Create a Householder reflection [v,beta,s]=house(x), overwrite x with v,
|
|
where (I-beta*v*v')*x = s*e1 and e1 = [1 0 ... 0]'.
|
|
</summary>
|
|
<remarks>
|
|
Note that this CXSparse version is different than CSparse. See Higham,
|
|
Accuracy and Stability of Num Algorithms, 2nd ed, 2002, page 357.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Factorization.SparseQR.ApplyHouseholder(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Int32,System.Double,System.Numerics.Complex[])">
|
|
<summary>
|
|
Apply the ith Householder vector to x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.SolverHelper.SolveLower(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Numerics.Complex[])">
|
|
<summary>
|
|
Solve a lower triangular system by forward elimination, Lx=b.
|
|
</summary>
|
|
<param name="L"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Complex.SolverHelper.SolveLowerTranspose(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Numerics.Complex[])">
|
|
<summary>
|
|
Solve L'x=b where x and b are dense.
|
|
</summary>
|
|
<param name="L"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Complex.SolverHelper.SolveUpper(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Numerics.Complex[])">
|
|
<summary>
|
|
Solve an upper triangular system by backward elimination, Ux=b.
|
|
</summary>
|
|
<param name="U"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Complex.SolverHelper.SolveUpperTranspose(CSparse.Storage.CompressedColumnStorage{System.Numerics.Complex},System.Numerics.Complex[])">
|
|
<summary>
|
|
Solve U'x=b where x and b are dense.
|
|
</summary>
|
|
<param name="U"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="T:CSparse.Complex.Vector">
|
|
<summary>
|
|
Vector helper methods.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Copy(System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Copy one vector to another.
|
|
</summary>
|
|
<param name="src">The source array.</param>
|
|
<param name="dst">The destination array.</param>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Copy(System.Numerics.Complex[],System.Numerics.Complex[],System.Int32)">
|
|
<summary>
|
|
Copy one vector to another.
|
|
</summary>
|
|
<param name="src">The source array.</param>
|
|
<param name="dst">The destination array.</param>
|
|
<param name="n">Number of values to copy.</param>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Create(System.Int32,System.Numerics.Complex)">
|
|
<summary>
|
|
Create a new vector.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Clone(System.Numerics.Complex[])">
|
|
<summary>
|
|
Clone the given vector.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Clear(System.Numerics.Complex[])">
|
|
<summary>
|
|
Set vector values to zero.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.DotProduct(System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Computes the dot product of two vectors.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.PointwiseMultiply(System.Numerics.Complex[],System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Computes the pointwise product of two vectors.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Norm(System.Numerics.Complex[])">
|
|
<summary>
|
|
Computes the norm of a vector.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.NormRobust(System.Numerics.Complex[])">
|
|
<summary>
|
|
Computes the norm of a vector avoiding overflow, sqrt( x' * x ).
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Scale(System.Numerics.Complex,System.Numerics.Complex[])">
|
|
<summary>
|
|
Scales a vector by a given factor, x = alpha * x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Axpy(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Add a scaled vector t o another vector, y = y + alpha * x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Complex.Vector.Add(System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex,System.Numerics.Complex[],System.Numerics.Complex[])">
|
|
<summary>
|
|
Add two scaled vectors, z = alpha * x + beta * y.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Constants">
|
|
<summary>
|
|
Constants used in the library.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Constants.SizeOfInt">
|
|
<summary>
|
|
The size of an int in bytes.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Constants.SizeOfDouble">
|
|
<summary>
|
|
The size of a double in bytes.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Constants.EqualsThreshold">
|
|
<summary>
|
|
The default threshold used for matrix values comparision.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Constants.SizeOfComplex">
|
|
<summary>
|
|
The size of a Complex in bytes (should be 2 * SizeOfDouble).
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Double.DenseMatrix">
|
|
<summary>
|
|
Dense matrix stored in column major order.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the DenseMatrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.#ctor(System.Int32,System.Int32,System.Double[])">
|
|
<summary>
|
|
Initializes a new instance of the DenseMatrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.L1Norm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.InfinityNorm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.FrobeniusNorm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Clone">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Multiply(System.Double[],System.Double[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Multiply(System.Double,System.Double[],System.Double,System.Double[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.TransposeMultiply(System.Double[],System.Double[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.TransposeMultiply(System.Double,System.Double[],System.Double,System.Double[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Add(CSparse.Storage.DenseColumnMajorStorage{System.Double},CSparse.Storage.DenseColumnMajorStorage{System.Double})">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Multiply(CSparse.Storage.DenseColumnMajorStorage{System.Double},CSparse.Storage.DenseColumnMajorStorage{System.Double})">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.PointwiseMultiply(CSparse.Storage.DenseColumnMajorStorage{System.Double},CSparse.Storage.DenseColumnMajorStorage{System.Double})">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.DenseMatrix.Equals(CSparse.Matrix{System.Double},System.Double)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="T:CSparse.Double.SparseMatrix">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the SparseMatrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.#ctor(System.Int32,System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the SparseMatrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.#ctor(System.Int32,System.Int32,System.Double[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Initializes a new instance of the SparseMatrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.DropZeros(System.Double)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Keep(System.Func{System.Int32,System.Int32,System.Double,System.Boolean})">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.L1Norm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.InfinityNorm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.FrobeniusNorm">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Multiply(System.Double[],System.Double[])">
|
|
<summary>
|
|
Multiplies a (m-by-n) matrix by a vector, y = A*x.
|
|
</summary>
|
|
<param name="x">Vector of length n (column count).</param>
|
|
<param name="y">Vector of length m (row count), containing the result.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Multiply(System.Double,System.Double[],System.Double,System.Double[])">
|
|
<summary>
|
|
Multiplies a (m-by-n) matrix by a vector, y = alpha*A*x + beta*y.
|
|
</summary>
|
|
<param name="x">Vector of length n (column count).</param>
|
|
<param name="y">Vector of length m (row count), containing the result.</param>
|
|
<param name="alpha">Scalar to multiply with matrix.</param>
|
|
<param name="beta">Scalar to multiply with vector y.</param>
|
|
<remarks>
|
|
Input values of vector y will be accumulated.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.TransposeMultiply(System.Double[],System.Double[])">
|
|
<summary>
|
|
Multiplies the transpose of a (m-by-n) matrix by a vector, y = A'*x.
|
|
</summary>
|
|
<param name="x">Vector of length m (column count of A').</param>
|
|
<param name="y">Vector of length n (row count of A'), containing the result.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.TransposeMultiply(System.Double,System.Double[],System.Double,System.Double[])">
|
|
<summary>
|
|
Multiplies the transpose of a (m-by-n) matrix by a vector, y = alpha*A'*x + beta*y.
|
|
</summary>
|
|
<param name="x">Vector of length m (column count of A').</param>
|
|
<param name="y">Vector of length n (row count of A'), containing the result.</param>
|
|
<param name="alpha">Scalar to multiply with matrix.</param>
|
|
<param name="beta">Scalar to multiply with vector y.</param>
|
|
<remarks>
|
|
Input values of vector y will be accumulated.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Add(System.Double,System.Double,CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Adds two matrices, C = alpha*A + beta*B, where A is current instance.
|
|
</summary>
|
|
<param name="alpha">Scalar factor for A, current instance.</param>
|
|
<param name="beta">Scalar factor for B, other instance.</param>
|
|
<param name="other">The matrix added to this instance.</param>
|
|
<param name="result">Contains the sum.</param>
|
|
<remarks>
|
|
The (result) matrix has to be fully initialized and provide enough space for
|
|
the nonzero entries of the sum. An upper bound is the sum of the nonzeros count
|
|
of (this) and (other).
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Multiply(CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Sparse matrix multiplication, C = A*B
|
|
</summary>
|
|
<param name="other">column-compressed matrix</param>
|
|
<returns>C = A*B, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Equals(CSparse.Matrix{System.Double},System.Double)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Double.SparseMatrix.Scatter(System.Int32,System.Double,System.Int32[],System.Double[],System.Int32,CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32)">
|
|
<summary>
|
|
Scatters and sums a sparse vector A(:,j) into a dense vector, x = x + beta * A(:,j).
|
|
</summary>
|
|
<param name="j">the column of A to use</param>
|
|
<param name="beta">scalar multiplied by A(:,j)</param>
|
|
<param name="w">size m, node i is marked if w[i] = mark</param>
|
|
<param name="x">size m, ignored if null</param>
|
|
<param name="mark">mark value of w</param>
|
|
<param name="mat">pattern of x accumulated in C.i</param>
|
|
<param name="nz">pattern of x placed in C starting at C.i[nz]</param>
|
|
<returns>new value of nz, -1 on error</returns>
|
|
</member>
|
|
<member name="T:CSparse.Double.Factorization.SparseCholesky">
|
|
<summary>
|
|
Sparse Cholesky decomposition (only upper triangular part is used).
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 4 (Cholesky factorization) in "Direct Methods for Sparse Linear Systems"
|
|
by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering)">
|
|
<summary>
|
|
Creates a sparse Cholesky factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering,CSparse.IProgress)">
|
|
<summary>
|
|
Creates a sparse Cholesky factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[])">
|
|
<summary>
|
|
Creates a sparse Cholesky factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="p">Permutation.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Create(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[],CSparse.IProgress)">
|
|
<summary>
|
|
Creates a sparse Cholesky factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="p">Permutation.</param>
|
|
</member>
|
|
<member name="P:CSparse.Double.Factorization.SparseCholesky.NonZerosCount">
|
|
<summary>
|
|
Gets the number of nonzeros of the L factor.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Solve(System.Double[],System.Double[])">
|
|
<summary>
|
|
Solves a system of linear equations, <c>Ax = b</c>.
|
|
</summary>
|
|
<param name="input">The right hand side vector, <c>b</c>.</param>
|
|
<param name="result">The left hand side vector, <c>x</c>.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Update(CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Sparse Cholesky update, L*L' + w*w'
|
|
</summary>
|
|
<param name="w">The update matrix.</param>
|
|
<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Downdate(CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Sparse Cholesky downdate, L*L' - w*w'
|
|
</summary>
|
|
<param name="w">The update matrix.</param>
|
|
<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.UpDown(System.Int32,CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Sparse Cholesky update/downdate, L*L' + sigma*w*w'
|
|
</summary>
|
|
<param name="sigma">1 = update or -1 = downdate</param>
|
|
<param name="w">The update matrix.</param>
|
|
<returns>False, if updated matrix is not positive definite, otherwise true.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.Factorize(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.IProgress)">
|
|
<summary>
|
|
Compute the Numeric Cholesky factorization, L = chol (A, [pinv parent cp]).
|
|
</summary>
|
|
<returns>Numeric Cholesky factorization</returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.SymbolicAnalysis(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[])">
|
|
<summary>
|
|
Ordering and symbolic analysis for a Cholesky factorization.
|
|
</summary>
|
|
<param name="A">Matrix to factorize.</param>
|
|
<param name="p">Permutation.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseCholesky.PermuteSym(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Permutes a symmetric sparse matrix. C = PAP' where A and C are symmetric.
|
|
</summary>
|
|
<param name="A">column-compressed matrix (only upper triangular part is used)</param>
|
|
<param name="pinv">size n, inverse permutation</param>
|
|
<param name="values">allocate pattern only if false, values and pattern otherwise</param>
|
|
<returns>Permuted matrix, C = PAP'</returns>
|
|
</member>
|
|
<member name="T:CSparse.Double.Factorization.SparseLDL">
|
|
<summary>
|
|
Sparse LDL' factorization.
|
|
</summary>
|
|
<remarks>
|
|
If A is positive definite then the factorization will be accurate. A can be
|
|
indefinite (with negative values on the diagonal D), but in this case no
|
|
guarantee of accuracy is provided, since no numeric pivoting is performed.
|
|
|
|
Only the diagonal and upper triangular part of A (or PAP' if a permutation
|
|
P is provided) is accessed. The lower triangular parts of the matrix A or
|
|
PAP' can be present, but they are ignored.
|
|
</remarks>
|
|
</member>
|
|
<member name="P:CSparse.Double.Factorization.SparseLDL.NonZerosCount">
|
|
<summary>
|
|
Gets the number of nonzeros of the L.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLDL.Solve(System.Double[],System.Double[])">
|
|
<summary>
|
|
Solves a linear system Ax=b, where A is symmetric positive definite.
|
|
</summary>
|
|
<param name="input">Right hand side b.</param>
|
|
<param name="result">Solution vector x.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLDL.SymbolicAnalysis(CSparse.ColumnOrdering,CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Ordering and symbolic analysis for a LDL' factorization.
|
|
</summary>
|
|
<param name="order">Column ordering.</param>
|
|
<param name="A">Matrix to factorize.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLDL.Factorize(CSparse.Storage.CompressedColumnStorage{System.Double})">
|
|
<summary>
|
|
Compute the numeric LDL' factorization of PAP'.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Double.Factorization.SparseLU">
|
|
<summary>
|
|
Sparse LU decomposition.
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 6 (LU factorization) in "Direct Methods for Sparse Linear Systems"
|
|
by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering,System.Double)">
|
|
<summary>
|
|
Creates a LU factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering,System.Double,CSparse.IProgress)">
|
|
<summary>
|
|
Creates a LU factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[],System.Double)">
|
|
<summary>
|
|
Creates a LU factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="p">Permutation.</param>
|
|
<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Create(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[],System.Double,CSparse.IProgress)">
|
|
<summary>
|
|
Creates a LU factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="p">Permutation.</param>
|
|
<param name="tol">Partial pivoting tolerance (form 0.0 to 1.0).</param>
|
|
</member>
|
|
<member name="P:CSparse.Double.Factorization.SparseLU.NonZerosCount">
|
|
<summary>
|
|
Gets the number of nonzeros in both L and U factors together.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Solve(System.Double[],System.Double[])">
|
|
<summary>
|
|
Solves a system of linear equations, <c>Ax = b</c>.
|
|
</summary>
|
|
<param name="input">The right hand side vector, <c>b</c>.</param>
|
|
<param name="result">The left hand side vector, <c>x</c>.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.SolveTranspose(System.Double[],System.Double[])">
|
|
<summary>
|
|
Solves a system of linear equations, <c>A'x = b</c>.
|
|
</summary>
|
|
<param name="input">The right hand side vector, <c>b</c>.</param>
|
|
<param name="result">The left hand side vector, <c>x</c>.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.Factorize(CSparse.Storage.CompressedColumnStorage{System.Double},System.Double,CSparse.IProgress)">
|
|
<summary>
|
|
[L,U,pinv] = lu(A, [q lnz unz]). lnz and unz can be guess.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.SymbolicAnalysis(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32[])">
|
|
<summary>
|
|
Symbolic ordering and analysis for LU.
|
|
</summary>
|
|
<param name="A"></param>
|
|
<param name="p">Permutation.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseLU.SolveSp(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32,System.Int32[],System.Double[],System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Solve Gx=b(:,k), where G is either upper (lo=false) or lower (lo=true)
|
|
triangular.
|
|
</summary>
|
|
<param name="G">lower or upper triangular matrix in column-compressed form</param>
|
|
<param name="B">right hand side, b=B(:,k)</param>
|
|
<param name="k">use kth column of B as right hand side</param>
|
|
<param name="xi">size 2*n, nonzero pattern of x in xi[top..n-1]</param>
|
|
<param name="x">size n, x in x[xi[top..n-1]]</param>
|
|
<param name="pinv">mapping of rows to columns of G, ignored if null</param>
|
|
<param name="lo">true if lower triangular, false if upper</param>
|
|
<returns>top, -1 in error</returns>
|
|
</member>
|
|
<member name="T:CSparse.Double.Factorization.SparseQR">
|
|
<summary>
|
|
Sparse QR decomposition.
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 5 (Orthogonal methods) in "Direct Methods for Sparse Linear Systems"
|
|
by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseQR.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering)">
|
|
<summary>
|
|
Creates a sparse QR factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseQR.Create(CSparse.Storage.CompressedColumnStorage{System.Double},CSparse.ColumnOrdering,CSparse.IProgress)">
|
|
<summary>
|
|
Creates a sparse QR factorization.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix, symmetric positive definite.</param>
|
|
<param name="order">Ordering method to use (natural or A+A').</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseQR.Solve(System.Double[],System.Double[])">
|
|
<summary>
|
|
Solves a system of linear equations, <c>Ax = b</c>.
|
|
</summary>
|
|
<param name="input">The right hand side vector, <c>b</c>.</param>
|
|
<param name="result">The left hand side vector, <c>x</c>.</param>
|
|
<remarks>
|
|
Let A be a m-by-n matrix. If m >= n a least-squares problem (min |Ax-b|)
|
|
is solved. If m < n the underdetermined system is solved.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseQR.CreateHouseholder(System.Double[],System.Int32,System.Double@,System.Int32)">
|
|
<summary>
|
|
Create a Householder reflection [v,beta,s]=house(x), overwrite x with v,
|
|
where (I-beta*v*v')*x = s*e1 and e1 = [1 0 ... 0]'.
|
|
</summary>
|
|
<remarks>
|
|
Note that this CXSparse version is different than CSparse. See Higham,
|
|
Accuracy and Stability of Num Algorithms, 2nd ed, 2002, page 357.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Double.Factorization.SparseQR.ApplyHouseholder(CSparse.Storage.CompressedColumnStorage{System.Double},System.Int32,System.Double,System.Double[])">
|
|
<summary>
|
|
Apply the ith Householder vector to x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.SolverHelper.SolveLower(CSparse.Storage.CompressedColumnStorage{System.Double},System.Double[])">
|
|
<summary>
|
|
Solve a lower triangular system by forward elimination, Lx=b.
|
|
</summary>
|
|
<param name="L"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.SolverHelper.SolveLowerTranspose(CSparse.Storage.CompressedColumnStorage{System.Double},System.Double[])">
|
|
<summary>
|
|
Solve L'x=b where x and b are dense.
|
|
</summary>
|
|
<param name="L"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.SolverHelper.SolveUpper(CSparse.Storage.CompressedColumnStorage{System.Double},System.Double[])">
|
|
<summary>
|
|
Solve an upper triangular system by backward elimination, Ux=b.
|
|
</summary>
|
|
<param name="U"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Double.SolverHelper.SolveUpperTranspose(CSparse.Storage.CompressedColumnStorage{System.Double},System.Double[])">
|
|
<summary>
|
|
Solve U'x=b where x and b are dense.
|
|
</summary>
|
|
<param name="U"></param>
|
|
<param name="x"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="T:CSparse.Double.Vector">
|
|
<summary>
|
|
Vector helper methods.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Copy(System.Double[],System.Double[])">
|
|
<summary>
|
|
Copy one vector to another.
|
|
</summary>
|
|
<param name="src">The source array.</param>
|
|
<param name="dst">The destination array.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Copy(System.Double[],System.Double[],System.Int32)">
|
|
<summary>
|
|
Copy one vector to another.
|
|
</summary>
|
|
<param name="src">The source array.</param>
|
|
<param name="dst">The destination array.</param>
|
|
<param name="n">Number of values to copy.</param>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Create(System.Int32,System.Double)">
|
|
<summary>
|
|
Create a new vector.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Clone(System.Double[])">
|
|
<summary>
|
|
Clone the given vector.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Clear(System.Double[])">
|
|
<summary>
|
|
Set vector values to zero.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.DotProduct(System.Double[],System.Double[])">
|
|
<summary>
|
|
Computes the dot product of two vectors.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.PointwiseMultiply(System.Double[],System.Double[],System.Double[])">
|
|
<summary>
|
|
Computes the pointwise product of two vectors.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Norm(System.Double[])">
|
|
<summary>
|
|
Computes the norm of a vector, sqrt( x' * x ).
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.NormRobust(System.Double[])">
|
|
<summary>
|
|
Computes the norm of a vector avoiding overflow, sqrt( x' * x ).
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Scale(System.Double,System.Double[])">
|
|
<summary>
|
|
Scales a vector by a given factor, x = alpha * x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Axpy(System.Double,System.Double[],System.Double[])">
|
|
<summary>
|
|
Add a scaled vector to another vector, y = y + alpha * x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Double.Vector.Add(System.Double,System.Double[],System.Double,System.Double[],System.Double[])">
|
|
<summary>
|
|
Add two scaled vectors, z = alpha * x + beta * y.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Factorization.ISolver`1">
|
|
<summary>
|
|
Classes that solve a system of linear equations, <c>Ax = b</c>.
|
|
</summary>
|
|
<typeparam name="T">Supported data types are double and <see cref="N:CSparse.Complex"/>.</typeparam>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.ISolver`1.Solve(`0[],`0[])">
|
|
<summary>
|
|
Solves a system of linear equations, Ax = b.
|
|
</summary>
|
|
<param name="input">Right hand side b</param>
|
|
<param name="result">Solution vector x.</param>
|
|
</member>
|
|
<member name="T:CSparse.Factorization.ISparseFactorization`1">
|
|
<summary>
|
|
Interface for factorization methods.
|
|
</summary>
|
|
<typeparam name="T">Supported data types are <c>double</c> and <see cref="N:CSparse.Complex"/>.</typeparam>
|
|
</member>
|
|
<member name="P:CSparse.Factorization.ISparseFactorization`1.NonZerosCount">
|
|
<summary>
|
|
Gets the total number of non-zero entries (all factors).
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Factorization.SparseQR`1">
|
|
<summary>
|
|
Sparse QR decomposition abstract base class.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Factorization.SparseQR`1.NonZerosCount">
|
|
<summary>
|
|
Gets the number of nonzeros in both Q and R factors together.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.Solve(`0[],`0[])">
|
|
<summary>
|
|
Solves a linear system Ax=b.
|
|
</summary>
|
|
<param name="input">Right hand side b.</param>
|
|
<param name="result">Solution vector x.</param>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.CreateHouseholder(`0[],System.Int32,System.Double@,System.Int32)">
|
|
<summary>
|
|
Create a Householder reflection.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.ApplyHouseholder(CSparse.Storage.CompressedColumnStorage{`0},System.Int32,System.Double,`0[])">
|
|
<summary>
|
|
Apply the ith Householder vector to x.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.Factorize(CSparse.Storage.CompressedColumnStorage{`0},CSparse.IProgress)">
|
|
<summary>
|
|
Sparse QR factorization [V,beta,pinv,R] = qr(A)
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.SymbolicAnalysis(CSparse.Storage.CompressedColumnStorage{`0},System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Symbolic ordering and analysis for QR.
|
|
</summary>
|
|
<param name="A">Matrix to factorize.</param>
|
|
<param name="p">Permutation.</param>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.CountV(CSparse.Storage.SymbolicColumnStorage,CSparse.Factorization.SymbolicFactorization)">
|
|
<summary>
|
|
Compute nnz(V) = S.lnz, S.pinv, S.leftmost, S.m2 from A and S.parent
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Factorization.SparseQR`1.Permute(CSparse.Storage.CompressedColumnStorage{`0},System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Permutes a sparse matrix, C = PAQ.
|
|
</summary>
|
|
<param name="A">m-by-n, column-compressed matrix</param>
|
|
<param name="pinv">a permutation vector of length m</param>
|
|
<param name="q">a permutation vector of length n</param>
|
|
<returns>C = PAQ, null on error</returns>
|
|
</member>
|
|
<member name="T:CSparse.Factorization.SymbolicFactorization">
|
|
<summary>
|
|
Symbolic Cholesky, LU, or QR factorization storage.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.ILinearOperator`1">
|
|
<summary>
|
|
Linear operator interface.
|
|
</summary>
|
|
<typeparam name="T"></typeparam>
|
|
</member>
|
|
<member name="P:CSparse.ILinearOperator`1.RowCount">
|
|
<summary>
|
|
Gets the number of rows.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.ILinearOperator`1.ColumnCount">
|
|
<summary>
|
|
Gets the number of columns.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.ILinearOperator`1.Multiply(`0[],`0[])">
|
|
<summary>
|
|
Multiplies a (m-by-n) matrix by a vector, y = A*x.
|
|
</summary>
|
|
<param name="x">Vector of length n (column count).</param>
|
|
<param name="y">Vector of length m (row count), containing the result.</param>
|
|
</member>
|
|
<member name="M:CSparse.ILinearOperator`1.Multiply(`0,`0[],`0,`0[])">
|
|
<summary>
|
|
Multiplies a (m-by-n) matrix by a vector, y = alpha * A * x + beta * y.
|
|
</summary>
|
|
<param name="alpha">Scaling factor fo vertor x.</param>
|
|
<param name="x">Vector of length n (column count).</param>
|
|
<param name="beta">Scaling factor fo vertor y.</param>
|
|
<param name="y">Vector of length m (row count), containing the result.</param>
|
|
</member>
|
|
<member name="M:CSparse.ILinearOperator`1.TransposeMultiply(`0[],`0[])">
|
|
<summary>
|
|
Multiplies the transpose of a (m-by-n) matrix by a vector, y = A'*x.
|
|
</summary>
|
|
<param name="x">Vector of length m (column count of A').</param>
|
|
<param name="y">Vector of length n (row count of A'), containing the result.</param>
|
|
</member>
|
|
<member name="M:CSparse.ILinearOperator`1.TransposeMultiply(`0,`0[],`0,`0[])">
|
|
<summary>
|
|
Multiplies the transpose of a (m-by-n) matrix by a vector, y = alpha * A^t * x + beta * y.
|
|
</summary>
|
|
<param name="alpha">Scaling factor fo vertor x.</param>
|
|
<param name="x">Vector of length m (column count of A').</param>
|
|
<param name="beta">Scaling factor fo vertor y.</param>
|
|
<param name="y">Vector of length n (row count of A'), containing the result.</param>
|
|
</member>
|
|
<member name="T:CSparse.IO.MatrixMarketReader">
|
|
<summary>
|
|
Read files in Matrix Market format (only supports coordinate storage).
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.IO.MatrixMarketReader.ReadMatrix``1(System.String)">
|
|
<summary>
|
|
Read a matrix from file.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.IO.MatrixMarketReader.ReadMatrix``1(System.IO.Stream)">
|
|
<summary>
|
|
Read a matrix from stream.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.IO.MatrixMarketReader.ReadStorage``1(System.IO.TextReader,System.Boolean)">
|
|
<summary>
|
|
Read coordinate storage from a text reader.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.IProgress">
|
|
<summary>
|
|
Used to report progress of a factorization.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.IProgress.Report(System.Double)">
|
|
<summary>
|
|
Reports a progress update.
|
|
</summary>
|
|
<param name="value">The value of the updated progress (from 0.0 to 1.0).</param>
|
|
</member>
|
|
<member name="T:CSparse.Ordering.AMD">
|
|
<summary>
|
|
Approximate Minimum Degree ordering.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.AMD.Generate``1(CSparse.Storage.CompressedColumnStorage{``0},CSparse.ColumnOrdering)">
|
|
<summary>
|
|
Generate minimum degree ordering of A+A' (if A is symmetric) or A'A.
|
|
</summary>
|
|
<param name="A">Column-compressed matrix</param>
|
|
<param name="order">Column ordering method</param>
|
|
<returns>amd(A+A') if A is symmetric, or amd(A'A) otherwise, null on
|
|
error or for natural ordering</returns>
|
|
<remarks>
|
|
See Chapter 7.1 (Fill-reducing orderings: Minimum degree ordering) in
|
|
"Direct Methods for Sparse Linear Systems" by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="T:CSparse.Ordering.DulmageMendelsohn">
|
|
<summary>
|
|
Dulmage-Mendelsohn decomposition.
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 7.4 (Fill-reducing orderings: Dulmage-Mendelsohn decomposition)
|
|
in "Direct Methods for Sparse Linear Systems" by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.DulmageMendelsohn.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Create a new Decomposition instance.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.DulmageMendelsohn.Generate``1(CSparse.Storage.CompressedColumnStorage{``0},System.Int32)">
|
|
<summary>
|
|
Compute coarse and then fine Dulmage-Mendelsohn decomposition. seed
|
|
optionally selects a randomized algorithm.
|
|
</summary>
|
|
<param name="matrix">column-compressed matrix</param>
|
|
<param name="seed">0: natural, -1: reverse, random order otherwise</param>
|
|
<returns>Dulmage-Mendelsohn analysis</returns>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.DulmageMendelsohn.FindScc(CSparse.Storage.SymbolicColumnStorage,System.Int32)">
|
|
<summary>
|
|
Finds the strongly connected components of a square matrix.
|
|
</summary>
|
|
<returns>strongly connected components, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.DulmageMendelsohn.RowPrune(CSparse.Storage.SymbolicColumnStorage,System.Int32,System.Int32[])">
|
|
<summary>
|
|
Drops entries from a sparse matrix
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Ordering.MaximumMatching">
|
|
<summary>
|
|
Maximum matching of any matrix A (also called maximum transveral).
|
|
</summary>
|
|
<remarks>
|
|
See Chapter 7.2 (Fill-reducing orderings: Maximum matching) in
|
|
"Direct Methods for Sparse Linear Systems" by Tim Davis.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.MaximumMatching.Generate(CSparse.Storage.SymbolicColumnStorage,System.Int32)">
|
|
<summary>
|
|
Find a maximum transveral (zero-free diagonal). Seed optionally selects a
|
|
randomized algorithm.
|
|
</summary>
|
|
<param name="A">column-compressed matrix</param>
|
|
<param name="seed">0: natural, -1: reverse, randomized otherwise</param>
|
|
<returns>row and column matching, size m+n</returns>
|
|
</member>
|
|
<member name="M:CSparse.Ordering.MaximumMatching.Augment(System.Int32,System.Int32[],System.Int32[],System.Int32[],System.Int32,System.Int32[],System.Int32[],System.Int32[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Find an augmenting path starting at column k and extend the match if found.
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.GraphHelper">
|
|
<summary>
|
|
Helper methods for sparse direct solvers.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.DepthFirstSearch(System.Int32,System.Int32[],System.Int32[],System.Int32,System.Int32[],System.Int32[],System.Int32,System.Int32[])">
|
|
<summary>
|
|
Depth-first-search of the graph of a matrix, starting at node j.
|
|
</summary>
|
|
<param name="j">starting node</param>
|
|
<param name="Gp">graph to search (modified, then restored)</param>
|
|
<param name="Gi">graph to search</param>
|
|
<param name="top">stack[top..n-1] is used on input</param>
|
|
<param name="xi">size n, stack containing nodes traversed</param>
|
|
<param name="pstack">size n, work array</param>
|
|
<param name="offset">the index of the first element in array pstack</param>
|
|
<param name="pinv">mapping of rows to columns of G, ignored if null</param>
|
|
<returns>new value of top, -1 on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.EliminationTree(System.Int32,System.Int32,System.Int32[],System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Compute the elimination tree of A or A'A (without forming A'A).
|
|
</summary>
|
|
<param name="m">Number of rows.</param>
|
|
<param name="n">Number of columns.</param>
|
|
<param name="colptr">Column pointers of column-compressed matrix.</param>
|
|
<param name="rowind">Row indices of column-compressed matrix.</param>
|
|
<param name="ata">analyze A if false, A'A oterwise</param>
|
|
<returns>elimination tree, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.TreePostorder(System.Int32[],System.Int32)">
|
|
<summary>
|
|
Postorders a tree of forest.
|
|
</summary>
|
|
<param name="parent">defines a tree of n nodes</param>
|
|
<param name="n">length of parent</param>
|
|
<returns>post[k]=i, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.ColumnCounts(CSparse.Storage.SymbolicColumnStorage,System.Int32[],System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Column counts for Cholesky (LL'=A or LL'=A'A) and QR, given parent and post ordering.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.IsLeaf(System.Int32,System.Int32,System.Int32[],System.Int32[],System.Int32[],System.Int32[],System.Int32@)">
|
|
<summary>
|
|
Determines if j is a leaf of the skeleton matrix and find lowest common
|
|
ancestor (lca).
|
|
</summary>
|
|
<returns>Least common ancestor (jprev,j)</returns>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.TreeDepthFirstSearch(System.Int32,System.Int32,System.Int32[],System.Int32[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Depth-first search and postorder of a tree rooted at node j
|
|
</summary>
|
|
<param name="j">postorder of a tree rooted at node j</param>
|
|
<param name="k">number of nodes ordered so far</param>
|
|
<param name="head">head[i] is first child of node i; -1 on output</param>
|
|
<param name="next">next[i] is next sibling of i or -1 if none</param>
|
|
<param name="post">postordering</param>
|
|
<param name="stack">size n, work array</param>
|
|
<returns>new value of k, -1 on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.GraphHelper.EtreeReach(CSparse.Storage.SymbolicColumnStorage,System.Int32,System.Int32[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Find nonzero pattern of Cholesky L(k,1:k-1) using etree and triu(A(:,k))
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Helper.CumulativeSum(System.Int32[],System.Int32[],System.Int32)">
|
|
<summary>
|
|
Cumulative sum of given array.
|
|
</summary>
|
|
<param name="sum">Output: cumulative sum of counts</param>
|
|
<param name="counts">input array, overwritten with sum</param>
|
|
<param name="size">length of counts</param>
|
|
<returns>sum[size] (non-zeros)</returns>
|
|
</member>
|
|
<member name="M:CSparse.Helper.OneOf``1">
|
|
<summary>
|
|
Sets the value of <c>1.0</c> for type T.
|
|
</summary>
|
|
<typeparam name="T">The type to return the value of 1.0 of.</typeparam>
|
|
<returns>The value of <c>1.0</c> for type T.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Helper.ZeroOf``1">
|
|
<summary>
|
|
Sets the value of <c>0.0</c> for type T.
|
|
</summary>
|
|
<typeparam name="T">The type to return the value of 0.0 of.</typeparam>
|
|
<returns>The value of <c>0.0</c> for type T.</returns>
|
|
</member>
|
|
<member name="T:CSparse.Permutation">
|
|
<summary>
|
|
Permutation helper methods.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Permutation.Apply``1(System.Int32[],``0[],``0[],System.Int32)">
|
|
<summary>
|
|
Permutes a vector, x=P*b.
|
|
</summary>
|
|
<param name="p">Permutation vector.</param>
|
|
<param name="b">Input vector.</param>
|
|
<param name="x">Output vector, x=P*b.</param>
|
|
<param name="n">Length of p, b and x.</param>
|
|
<remarks>
|
|
p = null denotes identity.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Permutation.ApplyInverse``1(System.Int32[],``0[],``0[],System.Int32)">
|
|
<summary>
|
|
Permutes a vector, x = P'b.
|
|
</summary>
|
|
<param name="p">Permutation vector.</param>
|
|
<param name="b">Input vector.</param>
|
|
<param name="x">Output vector, x = P'b.</param>
|
|
<param name="n">Length of p, b, and x.</param>
|
|
<remarks>
|
|
p = null denotes identity.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Permutation.Create(System.Int32,System.Int32)">
|
|
<summary>
|
|
Returns a permutation vector of length n.
|
|
</summary>
|
|
<param name="n">Length of the permutation.</param>
|
|
<param name="seed">0: identity, -1: reverse, seed > 0: random permutation</param>
|
|
<returns>Permutation vector.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Permutation.Invert(System.Int32[])">
|
|
<summary>
|
|
Inverts a permutation vector.
|
|
</summary>
|
|
<param name="p">A permutation vector.</param>
|
|
<returns>Returns pinv[i] = k if p[k] = i on input.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Permutation.IsValid(System.Int32[])">
|
|
<summary>
|
|
Checks whether the <paramref name="p"/> array represents a proper permutation.
|
|
</summary>
|
|
<param name="p">An array which represents where each integer is permuted too: indices[i]
|
|
represents that integer i is permuted to location indices[i].</param>
|
|
<returns>True if <paramref name="p"/> represents a proper permutation, <c>false</c> otherwise.</returns>
|
|
</member>
|
|
<member name="T:CSparse.Properties.Resources">
|
|
<summary>
|
|
A strongly-typed resource class, for looking up localized strings, etc.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.ResourceManager">
|
|
<summary>
|
|
Returns the cached ResourceManager instance used by this class.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.Culture">
|
|
<summary>
|
|
Overrides the current thread's CurrentUICulture property for all
|
|
resource lookups using this strongly typed resource class.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.InvalidColumnOrdering">
|
|
<summary>
|
|
Looks up a localized string similar to Invalid column ordering..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.InvalidDimensions">
|
|
<summary>
|
|
Looks up a localized string similar to Invalid matrix dimensions..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.InvalidPermutation">
|
|
<summary>
|
|
Looks up a localized string similar to Invalid permutation vector..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.MatrixDimensionNonNegative">
|
|
<summary>
|
|
Looks up a localized string similar to Matrix dimension must not be a negative number..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.MatrixDimensionPositive">
|
|
<summary>
|
|
Looks up a localized string similar to Matrix dimension must be a positive number..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.MatrixDimensions">
|
|
<summary>
|
|
Looks up a localized string similar to Matrix dimensions don't match..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.MatrixSquare">
|
|
<summary>
|
|
Looks up a localized string similar to Matrix must be square..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.MatrixSymmetricPositiveDefinite">
|
|
<summary>
|
|
Looks up a localized string similar to Matrix must be symmetric positive definite..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.ValueNotNaN">
|
|
<summary>
|
|
Looks up a localized string similar to Value must not be NaN..
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Properties.Resources.VectorsSameLength">
|
|
<summary>
|
|
Looks up a localized string similar to Vectors must have the same dimension..
|
|
</summary>
|
|
</member>
|
|
<member name="T:CSparse.Storage.CompressedColumnStorage`1">
|
|
<summary>
|
|
Compressed sparse column storage.
|
|
</summary>
|
|
<typeparam name="T"></typeparam>
|
|
</member>
|
|
<member name="F:CSparse.Storage.CompressedColumnStorage`1.ColumnPointers">
|
|
<summary>
|
|
Row pointers with last entry equal number of non-zeros (size = RowCount + 1)
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Storage.CompressedColumnStorage`1.RowIndices">
|
|
<summary>
|
|
Column indices (size >= NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Storage.CompressedColumnStorage`1.Values">
|
|
<summary>
|
|
Numerical values (size >= NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CompressedColumnStorage`1.NonZerosCount">
|
|
<summary>
|
|
Gets the number of non-zero entries.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the CompressedColumnStorage class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.#ctor(System.Int32,System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the CompressedColumnStorage class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.#ctor(System.Int32,System.Int32,`0[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Initializes a new instance of the CompressedColumnStorage class. Based on other CCS arrays
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.At(System.Int32,System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Clear">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Row(System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Row(System.Int32,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Column(System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Column(System.Int32,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Transpose">
|
|
<summary>
|
|
Returns the transpose of this matrix.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Transpose(CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Transpose this matrix and store the result in given matrix.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Add(CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Adds two matrices in CSC format, C = A + B, where A is current instance.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Add(`0,`0,CSparse.Storage.CompressedColumnStorage{`0},CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Adds two matrices, C = alpha*A + beta*B, where A is current instance.
|
|
</summary>
|
|
<param name="alpha">Scalar factor for A, current instance.</param>
|
|
<param name="beta">Scalar factor for B, other instance.</param>
|
|
<param name="other">The matrix added to this instance.</param>
|
|
<param name="result">Contains the sum.</param>
|
|
<remarks>
|
|
The (result) matrix has to be fully initialized and provide enough space for
|
|
the nonzero entries of the sum. An upper bound is the sum of the nonzeros count
|
|
of (this) and (other).
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Multiply(CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Sparse matrix multiplication, C = A*B
|
|
</summary>
|
|
<param name="other">column-compressed matrix</param>
|
|
<returns>C = A*B, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Keep(System.Func{System.Int32,System.Int32,`0,System.Boolean})">
|
|
<summary>
|
|
Filter matrix values.
|
|
</summary>
|
|
<param name="func">Filter function returning true if value should be kept,
|
|
false if value should be discarded.</param>
|
|
<returns>New number of non-zeros.</returns>
|
|
<remarks>
|
|
Filter function arguments:
|
|
|
|
1 = Row index i
|
|
2 = Column index j
|
|
3 = Value of entry (i,j)
|
|
|
|
Element a_{i,j} is dropped, if func(i, j, aij) returns false.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.DropZeros(System.Double)">
|
|
<summary>
|
|
Removes numerically zero entries from a matrix.
|
|
</summary>
|
|
<param name="tolerance">Drop tolerance (default is 0.0)</param>
|
|
<returns>The new number of nonzero entries.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Clone(System.Boolean)">
|
|
<summary>
|
|
Returns a clone of this matrix.
|
|
</summary>
|
|
<param name="values">If true (default), the values are copied.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.EnumerateIndexed">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.IsSymmetric">
|
|
<summary>
|
|
Evaluates whether this matrix is symmetric.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteRows(System.Int32[],CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Permute the rows of the matrix.
|
|
</summary>
|
|
<param name="perm">Permutation matrix P.</param>
|
|
<param name="target">The target storage (must be fully initialized to match the source storage).</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteRows(System.Int32[])">
|
|
<summary>
|
|
Permute the rows of the matrix.
|
|
</summary>
|
|
<param name="perm">Permutation matrix P.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteColumns(System.Int32[],CSparse.Storage.CompressedColumnStorage{`0})">
|
|
<summary>
|
|
Permute the columns of the matrix.
|
|
</summary>
|
|
<param name="perm">Permutation matrix P.</param>
|
|
<param name="target">The target storage (must be fully initialized to match the source storage).</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteColumns(System.Int32[])">
|
|
<summary>
|
|
Permute the columns of the matrix.
|
|
</summary>
|
|
<param name="perm">Permutation matrix P.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.FindDiagonalIndices(System.Boolean)">
|
|
<summary>
|
|
Returns the positions of the diagonal elements of a sparse matrix.
|
|
</summary>
|
|
<param name="throwOnMissingDiag"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteColumns(`0[],System.Int32[],System.Int32[],`0[],System.Int32[],System.Int32[],System.Int32[])">
|
|
<summary>
|
|
Permutes the columns of a matrix in CSC format, B = A * P, where P represents
|
|
a permutation matrix.
|
|
</summary>
|
|
<param name="ax">Input matrix values.</param>
|
|
<param name="ai">Input matrix row pointers.</param>
|
|
<param name="aj">Input matrix column indices.</param>
|
|
<param name="bx">Output matrix values.</param>
|
|
<param name="bi">Output matrix row pointers.</param>
|
|
<param name="bj">Output matrix column indices.</param>
|
|
<param name="perm">Permutation array of length ColumnCount.</param>
|
|
<remarks>
|
|
The permutation P is defined through the array perm: for each j,
|
|
perm(j) represents the destination row number of row number j:
|
|
|
|
a(i,j) in the original matrix becomes a(perm(i),j) in the output matrix.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.PermuteRows(`0[],System.Int32[],System.Int32[],`0[],System.Int32[],System.Int32[],System.Int32[],System.Boolean)">
|
|
<summary>
|
|
Permute the rows of a matrix in CSC format, B = P * A, where P represents
|
|
a permutation matrix.
|
|
</summary>
|
|
<param name="ax">Input matrix values.</param>
|
|
<param name="ai">Input matrix row pointers.</param>
|
|
<param name="aj">Input matrix column indices.</param>
|
|
<param name="bx">Output matrix values.</param>
|
|
<param name="bi">Output matrix row pointers.</param>
|
|
<param name="bj">Output matrix column indices.</param>
|
|
<param name="perm">Permutation array of length RowCount.</param>
|
|
<param name="copy">Copy matrix values (not needed if used 'in place').</param>
|
|
<remarks>
|
|
The permutation matrix P maps column j into column perm(j), i.e.,
|
|
on return a(i,j) in the original matrix becomes a(i,perm(j)) in the
|
|
output matrix.
|
|
|
|
Notes:
|
|
|
|
1. This routine is in place: aj, bj can be the same.
|
|
2. If the matrix is initially sorted (by increasing column number)
|
|
then bx, bi, bj may not be on return.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.Resize(System.Int32)">
|
|
<summary>
|
|
Change the max # of entries sparse matrix
|
|
</summary>
|
|
<param name="size"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CompressedColumnStorage`1.GetHashCode">
|
|
<summary>
|
|
Serves as a hash function for a particular type.
|
|
</summary>
|
|
<returns>
|
|
A hash code for the current <see cref="T:System.Object"/>.
|
|
</returns>
|
|
</member>
|
|
<member name="T:CSparse.Storage.CoordinateStorage`1">
|
|
<summary>
|
|
Coordinate storage sparse matrix format.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.RowIndices">
|
|
<summary>
|
|
Row indices (size = NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.ColumnIndices">
|
|
<summary>
|
|
Column indices (size = NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.Values">
|
|
<summary>
|
|
Numerical values (size = NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.RowCount">
|
|
<summary>
|
|
Gets the number of rows.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.ColumnCount">
|
|
<summary>
|
|
Gets the number of columns.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.CoordinateStorage`1.NonZerosCount">
|
|
<summary>
|
|
Gets the number of non-zero entries.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CoordinateStorage`1.#ctor(System.Int32,System.Int32,System.Int32,System.Boolean)">
|
|
<summary>
|
|
Initializes a new instance of the CoordinateStorage class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CoordinateStorage`1.At(System.Int32,System.Int32,`0)">
|
|
<summary>
|
|
Adds an entry to the storage.
|
|
</summary>
|
|
<param name="i">Row index of new entry</param>
|
|
<param name="j">Column index of new entry</param>
|
|
<param name="value">Numerical value of new entry</param>
|
|
<remarks>
|
|
Duplicate entries will be added up, i.e. calling
|
|
<code>
|
|
storage.At(0, 0, 1.0);
|
|
storage.At(0, 0, 2.0);
|
|
</code>
|
|
will result in an entry with value 3.0 at index (0, 0) of the
|
|
resulting matrix.
|
|
|
|
Memory will be increased as necessary.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CoordinateStorage`1.Transpose(System.Boolean)">
|
|
<summary>
|
|
Returns the transposed coordinate storage.
|
|
</summary>
|
|
<param name="alloc">If true, clone storage arrays, otherwise just swap the references and re-use the arrays.</param>
|
|
<returns>The transposed storage.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.CoordinateStorage`1.Resize(System.Int32)">
|
|
<summary>
|
|
Resize the storage arrays of the sparse matrix.
|
|
</summary>
|
|
<param name="size">The new size of Values and ColumnIndices arrays.</param>
|
|
<remarks>
|
|
Use size = 0 to automatically resize to non-zeros count.
|
|
</remarks>
|
|
</member>
|
|
<member name="T:CSparse.Storage.DenseColumnMajorStorage`1">
|
|
<summary>
|
|
Dense column-major matrix storage.
|
|
</summary>
|
|
<typeparam name="T"></typeparam>
|
|
</member>
|
|
<member name="F:CSparse.Storage.DenseColumnMajorStorage`1.Values">
|
|
<summary>
|
|
Gets the numerical values in column-major order.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.DenseColumnMajorStorage`1.Item(System.Int32,System.Int32)">
|
|
<summary>
|
|
Return the matrix value at position (i, j).
|
|
</summary>
|
|
<param name="i">The row index.</param>
|
|
<param name="j">The column index.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the DenseColumnMajorStorage class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.#ctor(System.Int32,System.Int32,`0[])">
|
|
<summary>
|
|
Initializes a new instance of the DenseColumnMajorStorage class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.At(System.Int32,System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.At(System.Int32,System.Int32,`0)">
|
|
<summary>
|
|
Sets the element without range checking.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Row(System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Column(System.Int32)">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Row(System.Int32,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Column(System.Int32,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.SetRow(System.Int32,`0[])">
|
|
<summary>
|
|
Copy values from array to matrix row.
|
|
</summary>
|
|
<param name="row">The row index.</param>
|
|
<param name="values">The new values.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.SetColumn(System.Int32,`0[])">
|
|
<summary>
|
|
Copy values from array to matrix column.
|
|
</summary>
|
|
<param name="column">The column index.</param>
|
|
<param name="values">The new values.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Transpose">
|
|
<summary>
|
|
Returns the transpose of this matrix.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Transpose(CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Transpose this matrix and store the result in given matrix.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Add(CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Adds two matrices in CSC format, C = A + B, where A is current instance.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Add(CSparse.Storage.DenseColumnMajorStorage{`0},CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Adds two matrices, C = A + B, where A is current instance.
|
|
</summary>
|
|
<param name="other">The matrix added to this instance.</param>
|
|
<param name="result">Contains the sum.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Multiply(CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Dense matrix multiplication, C = A*B
|
|
</summary>
|
|
<param name="other">Dense matrix</param>
|
|
<returns>C = A*B, null on error</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Multiply(CSparse.Storage.DenseColumnMajorStorage{`0},CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Dense matrix multiplication, C = A*B
|
|
</summary>
|
|
<param name="other">The matrix multiplied to this instance.</param>
|
|
<param name="result">The product matrix.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.PointwiseMultiply(CSparse.Storage.DenseColumnMajorStorage{`0},CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Pointwise multiplies this matrix with another matrix and stores the result into the result matrix.
|
|
</summary>
|
|
<param name="other">The matrix to pointwise multiply with this one.</param>
|
|
<param name="result">The matrix to store the result of the pointwise multiplication.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Clone">
|
|
<summary>
|
|
Returns a clone of this matrix.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.UpperTriangle">
|
|
<summary>
|
|
Returns a new matrix containing the upper triangle of this matrix.
|
|
</summary>
|
|
<returns>The upper triangle of this matrix.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.LowerTriangle">
|
|
<summary>
|
|
Returns a new matrix containing the lower triangle of this matrix.
|
|
</summary>
|
|
<returns>The lower triangle of this matrix.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.LowerTriangle(CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Puts the lower triangle of this matrix into the result matrix.
|
|
</summary>
|
|
<param name="result">Where to store the lower triangle.</param>
|
|
<exception cref="T:System.ArgumentNullException">If <paramref name="result"/> is <see langword="null" />.</exception>
|
|
<exception cref="T:System.ArgumentException">If the result matrix's dimensions are not the same as this matrix.</exception>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.UpperTriangle(CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Puts the upper triangle of this matrix into the result matrix.
|
|
</summary>
|
|
<param name="result">Where to store the lower triangle.</param>
|
|
<exception cref="T:System.ArgumentNullException">If <paramref name="result"/> is <see langword="null" />.</exception>
|
|
<exception cref="T:System.ArgumentException">If the result matrix's dimensions are not the same as this matrix.</exception>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.SubMatrix(System.Int32,System.Int32,System.Int32,System.Int32)">
|
|
<summary>
|
|
Returns a sub-matrix with values in given range.
|
|
</summary>
|
|
<param name="rowIndex">The row to start copying to.</param>
|
|
<param name="rowCount">The number of rows to copy. Must be positive.</param>
|
|
<param name="columnIndex">The column to start copying to.</param>
|
|
<param name="columnCount">The number of columns to copy. Must be positive.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.SetSubMatrix(System.Int32,System.Int32,CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Copies the values of a given matrix into a region in this matrix.
|
|
</summary>
|
|
<param name="rowIndex">The row to start copying to.</param>
|
|
<param name="columnIndex">The column to start copying to.</param>
|
|
<param name="subMatrix">The sub-matrix to copy from.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.SetSubMatrix(System.Int32,System.Int32,System.Int32,System.Int32,CSparse.Storage.DenseColumnMajorStorage{`0})">
|
|
<summary>
|
|
Copies the values of a given matrix into a region in this matrix.
|
|
</summary>
|
|
<param name="rowIndex">The row to start copying to.</param>
|
|
<param name="rowCount">The number of rows to copy. Must be positive.</param>
|
|
<param name="columnIndex">The column to start copying to.</param>
|
|
<param name="columnCount">The number of columns to copy. Must be positive.</param>
|
|
<param name="subMatrix">The sub-matrix to copy from.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.Clear">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Storage.DenseColumnMajorStorage`1.EnumerateIndexed">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="T:CSparse.Storage.SymbolicColumnStorage">
|
|
<summary>
|
|
Represents the nonzero pattern of a column-compressed matrix.
|
|
</summary>
|
|
<remarks>
|
|
Used for ordering and symbolic factorization.
|
|
</remarks>
|
|
</member>
|
|
<member name="F:CSparse.Storage.SymbolicColumnStorage.ColumnPointers">
|
|
<summary>
|
|
Column pointers with last entry equal number of non-zeros (size = ColumnCount + 1)
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Storage.SymbolicColumnStorage.RowIndices">
|
|
<summary>
|
|
Row indices (size = NonZerosCount)
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.SymbolicColumnStorage.RowCount">
|
|
<summary>
|
|
Gets the number of rows.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.SymbolicColumnStorage.ColumnCount">
|
|
<summary>
|
|
Gets the number of columns.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Storage.SymbolicColumnStorage.NonZerosCount">
|
|
<summary>
|
|
Gets the number of non-zero entries.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Reshape(System.Int32,System.Int32)">
|
|
<summary>
|
|
Change the shape of the matrix (only used by Dulmage-Mendelsohn decomposition).
|
|
</summary>
|
|
<param name="rowCount"></param>
|
|
<param name="columnCount"></param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Resize(System.Int32)">
|
|
<summary>
|
|
Change the max # of entries sparse matrix
|
|
</summary>
|
|
<param name="size"></param>
|
|
<returns></returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Sort">
|
|
<summary>
|
|
Sort column indices using insertion sort.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Transpose">
|
|
<summary>
|
|
Computes the transpose of a sparse matrix, C = A';
|
|
</summary>
|
|
<returns>Transposed matrix, C = A'</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Add(CSparse.Storage.SymbolicColumnStorage)">
|
|
<summary>
|
|
Symbolic sum C = A + B
|
|
</summary>
|
|
<param name="other">column-compressed matrix</param>
|
|
<returns>Sum C = A + B</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Multiply(CSparse.Storage.SymbolicColumnStorage)">
|
|
<summary>
|
|
Sparse matrix multiplication, C = A*B
|
|
</summary>
|
|
<param name="other">column-compressed matrix</param>
|
|
<returns>C = A*B</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Permute(System.Int32[],System.Int32[],CSparse.Storage.SymbolicColumnStorage)">
|
|
<summary>
|
|
Permutes a sparse matrix, C = PAQ.
|
|
</summary>
|
|
<param name="pinv">Permutation vector of length m.</param>
|
|
<param name="q">Permutation vector of length n.</param>
|
|
<param name="result">Permuted matrix, C = PAQ.</param>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Keep(System.Func{System.Int32,System.Int32,System.Boolean})">
|
|
<summary>
|
|
Drops entries from a sparse matrix
|
|
</summary>
|
|
<param name="func">Drop element a_{i,j} if func(i, j) is false.</param>
|
|
<returns>New number of entries in A.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Storage.SymbolicColumnStorage.Scatter(System.Int32,System.Int32[],System.Int32,System.Int32[],System.Int32)">
|
|
<summary>
|
|
Scatters and sums a sparse vector A(:,j) into a dense vector, x = x + beta * A(:,j).
|
|
</summary>
|
|
<param name="j">the column of A to use</param>
|
|
<param name="work">size m, node i is marked if w[i] = mark</param>
|
|
<param name="mark">mark value of w</param>
|
|
<param name="ci">pattern of x accumulated in ci</param>
|
|
<param name="nz">pattern of x placed in C starting at C.i[nz]</param>
|
|
<returns>new value of nz</returns>
|
|
</member>
|
|
<member name="T:CSparse.Converter">
|
|
<summary>
|
|
Converter for different types of storages.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Converter.ToCompressedColumnStorage``1(CSparse.Storage.CoordinateStorage{``0},System.Boolean)">
|
|
<summary>
|
|
Convert a coordinate storage to compressed sparse column (CSC) format.
|
|
</summary>
|
|
<param name="storage">Coordinate storage.</param>
|
|
<param name="cleanup">Remove and sum duplicate entries.</param>
|
|
<returns>Compressed sparse column storage.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Converter.FromDenseArray``1(``0[0:,0:])">
|
|
<summary>
|
|
Convert a 2D array to coordinate storage.
|
|
</summary>
|
|
<param name="array">2D array storage.</param>
|
|
<returns>Coordinate storage.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Converter.ToCompressedColumnStorage``1(``0[][])">
|
|
<summary>
|
|
Convert a jagged array to compressed sparse column (CSC) format.
|
|
</summary>
|
|
<param name="array">Jagged array storage.</param>
|
|
<returns>Compressed sparse column storage.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Converter.FromColumnMajorArray``1(``0[],System.Int32,System.Int32)">
|
|
<summary>
|
|
Convert a column major array to coordinate storage.
|
|
</summary>
|
|
<param name="array">Column major array storage.</param>
|
|
<param name="rowCount">Number of rows.</param>
|
|
<param name="columnCount">Number of columns.</param>
|
|
<returns>Coordinate storage.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Converter.FromDenseArray``1(``0[][])">
|
|
<summary>
|
|
Convert a 2D jagged array to coordinate storage.
|
|
</summary>
|
|
<param name="array">jagged array storage.</param>
|
|
<returns>Coordinate storage.</returns>
|
|
<remarks>All rows of the array are assumed to be equal in length</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Converter.FromRowMajorArray``1(``0[],System.Int32,System.Int32)">
|
|
<summary>
|
|
Convert a row major array to coordinate storage.
|
|
</summary>
|
|
<param name="array">Row major array storage.</param>
|
|
<param name="rowCount">Number of rows.</param>
|
|
<param name="columnCount">Number of columns.</param>
|
|
<returns>Coordinate storage.</returns>
|
|
</member>
|
|
<member name="T:CSparse.Matrix`1">
|
|
<summary>
|
|
Abstract base class for matrix implementations.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Matrix`1.Zero">
|
|
<summary>
|
|
Zero value for T.
|
|
</summary>
|
|
</member>
|
|
<member name="F:CSparse.Matrix`1.One">
|
|
<summary>
|
|
One value for T.
|
|
</summary>
|
|
</member>
|
|
<member name="P:CSparse.Matrix`1.RowCount">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="P:CSparse.Matrix`1.ColumnCount">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.#ctor(System.Int32,System.Int32)">
|
|
<summary>
|
|
Initializes a new instance of the Matrix class.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.At(System.Int32,System.Int32)">
|
|
<summary>
|
|
Return the matrix value at position (row, column).
|
|
</summary>
|
|
<param name="row">The row index.</param>
|
|
<param name="column">The column index.</param>
|
|
<returns>Matrix value</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Clear">
|
|
<summary>
|
|
Clears all values form the matrix.
|
|
</summary>
|
|
<remarks>
|
|
The method does not release memory.
|
|
</remarks>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Row(System.Int32)">
|
|
<summary>
|
|
Extract row from matrix.
|
|
</summary>
|
|
<param name="rowIndex">The column index to extract.</param>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Row(System.Int32,`0[])">
|
|
<summary>
|
|
Extract row from matrix.
|
|
</summary>
|
|
<param name="rowIndex">The column index to extract.</param>
|
|
<param name="target">Dense array.</param>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Column(System.Int32)">
|
|
<summary>
|
|
Extract column from matrix.
|
|
</summary>
|
|
<param name="columnIndex">The column index to extract.</param>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Column(System.Int32,`0[])">
|
|
<summary>
|
|
Extract column from matrix.
|
|
</summary>
|
|
<param name="columnIndex">The column index to extract.</param>
|
|
<param name="target">Dense array.</param>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.L1Norm">
|
|
<summary>
|
|
Calculates the induced L1 norm of this matrix.
|
|
</summary>
|
|
<returns>The maximum absolute column sum of the matrix.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.InfinityNorm">
|
|
<summary>
|
|
Calculates the induced infinity norm of this matrix.
|
|
</summary>
|
|
<returns>The maximum absolute row sum of the matrix.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.FrobeniusNorm">
|
|
<summary>
|
|
Calculates the entry-wise Frobenius norm of this matrix.
|
|
</summary>
|
|
<returns>The square root of the sum of the squared values.</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.EnumerateIndexed">
|
|
<summary>
|
|
Enumerates all values of the matrix.
|
|
</summary>
|
|
<returns>Enumeration of tuples (i, j, a[i, j]).</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Multiply(`0[],`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Multiply(`0,`0[],`0,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.TransposeMultiply(`0[],`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.TransposeMultiply(`0,`0[],`0,`0[])">
|
|
<inheritdoc />
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Equals(CSparse.Matrix{`0})">
|
|
<summary>
|
|
Indicates whether the current object is equal to another object of the same type.
|
|
</summary>
|
|
<param name="other">
|
|
An object to compare with this object.
|
|
</param>
|
|
<returns>
|
|
<c>true</c> if the current object is equal to the <paramref name="other"/> parameter; otherwise, <c>false</c>.
|
|
</returns>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Equals(CSparse.Matrix{`0},System.Double)">
|
|
<summary>
|
|
Check two matrices for equality.
|
|
</summary>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.Equals(System.Object)">
|
|
<summary>
|
|
Determines whether the specified <see cref="T:System.Object"/> is equal to the current <see cref="T:System.Object"/>.
|
|
</summary>
|
|
<returns>
|
|
true if the specified <see cref="T:System.Object"/> is equal to the current <see cref="T:System.Object"/>; otherwise, false.
|
|
</returns>
|
|
<param name="obj">The <see cref="T:System.Object"/> to compare with the current <see cref="T:System.Object"/>. </param>
|
|
</member>
|
|
<member name="M:CSparse.Matrix`1.GetHashCode">
|
|
<summary>
|
|
Serves as a hash function for a particular type.
|
|
</summary>
|
|
<returns>
|
|
A hash code for the current <see cref="T:System.Object"/>.
|
|
</returns>
|
|
</member>
|
|
</members>
|
|
</doc>
|