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{{alias}}( ord, side, uplo, transa, diag, M, N, α, A, lda, B, ldb )
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Solves matrix equation `op(A) * X = α * B` or `X * op(A) = α * B` where `α`
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is a scalar, `X` and `B` are `M` by `N` matrices, `A` is a unit, or
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non-unit, upper or lower triangular matrix and `op(A)` is one of
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`op(A) = A` or `op(A) = A^T`. The matrix `X` is overwritten on `B`.
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Indexing is relative to the first index. To introduce an offset, use typed
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array views.
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If `M` or `N` is equal to `0`, the function returns `B` unchanged.
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If `α` equals `0`, returns `B` filled with zeros.
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Parameters
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----------
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ord: string
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Row-major (C-style) or column-major (Fortran-style) order. Must be
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either 'row-major' or 'column-major'.
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side: string
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Specifies whether `op( A )` multiplies `B` from the left or right.
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uplo: string
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Specifies whether `A` is an upper or lower triangular matrix.
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transa: string
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Specifies whether `A` should be transposed, conjugate-transposed, or
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not transposed.
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diag: string
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Specifies whether `A` has a unit diagonal.
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M: integer
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Number of rows of `B`.
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N: integer
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Number of columns of `B`.
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α: number
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Scalar constant.
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A: Float32Array
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Input matrix.
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lda: integer
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Stride of the first dimension of `A` (a.k.a., leading dimension of the
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matrix `A`).
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B: Float32Array
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Second matrix.
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ldb: integer
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Stride of the first dimension of `B` (a.k.a., leading dimension of the
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matrix `B`).
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Returns
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-------
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B: Float32Array
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Second matrix.
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Examples
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--------
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> var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 0.0, 2.0, 3.0 ] );
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> var B = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var ord = 'row-major';
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> var side = 'left';
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> var uplo = 'lower';
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> var transa = 'no-transpose';
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> var diag = 'unit';
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> {{alias}}( ord, side, uplo, transa, diag, 2, 2, 1.0, A, 2, B, 2 )
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<Float32Array>[ 1.0, 2.0, 1.0, 0.0 ]
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{{alias}}.ndarray(side,uplo,transa,diag,M,N,α,A,sa1,sa2,oa,B,sb1,sb2,ob)
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Solves matrix equation `op(A) * X = α * B` or `X * op(A) = α * B` where `α`
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is a scalar, `X` and `B` are `M` by `N` matrices, `A` is a unit, or
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non-unit, upper or lower triangular matrix and `op(A)` is one of
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`op(A) = A` or `op(A) = A^T`. The matrix `X` is overwritten on `B` using
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alternative indexing semantics.
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While typed array views mandate a view offset based on the underlying
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buffer, the offset parameters support indexing semantics based on starting
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indices.
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Parameters
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----------
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side: string
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Specifies whether `op( A )` multiplies `B` from the left or right.
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uplo: string
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Specifies whether `A` is an upper or lower triangular matrix.
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transa: string
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Specifies whether `A` should be transposed, conjugate-transposed, or
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not transposed.
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diag: string
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Specifies whether `A` has a unit diagonal.
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M: integer
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Number of rows of `B`.
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N: integer
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Number of columns of `B`.
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α: number
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Scalar constant.
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A: Float32Array
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Input matrix.
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sa1: integer
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Stride of the first dimension of `A`.
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sa2: integer
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Stride of the second dimension of `A`.
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oa: integer
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Starting index for `A`.
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B: Float32Array
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Second matrix.
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sb1: integer
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Stride of the first dimension of `B`.
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sb2: integer
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Stride of the second dimension of `B`.
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ob: integer
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Starting index for `B`.
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Returns
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-------
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B: Float32Array
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Second matrix.
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Examples
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--------
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> var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 0.0, 2.0, 3.0 ] );
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> var B = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var side = 'left';
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> var uplo = 'lower';
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> var transa = 'no-transpose';
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> var diag = 'unit';
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> {{alias}}.ndarray(side,uplo,transa,diag,2,2,1.0,A,2,1,0,B,2,1,0)
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<Float32Array>[ 1.0, 2.0, 1.0, 0.0 ]
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See Also
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--------

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