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docs: add repl.txt
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lib/node_modules/@stdlib/lapack/base/dlange/README.md

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2020

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# dlange
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> Compute an `LU` factorization of a real tridiagonal matrix `A` using elimination with partial pivoting and row interchanges.
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> LAPACK routine to compute the value of the one norm, or the frobenius norm, or the infinity norm, or the element with the largest absolute value of a real matrix `A`.
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<section class="intro">
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var dlange = require( '@stdlib/lapack/base/dlange' );
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```
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#### dlange( N, DL, D, DU, DU2, IPIV )
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#### dlange( norm, M, N, A, LDA, work )
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Computes the value of the one norm, or the frobenius norm, or the infinity norm, or the element with the largest absolute value of a real matrix `A`.
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{{alias}}( order, norm, M, N, A, LDA, work )
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Computes the value of the one norm, or the frobenius norm, or the infinity
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norm, or the element with the largest absolute value of a real matrix `A`.
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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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Parameters
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----------
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order: 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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norm: string
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Specifies the type of norm to be calculated, should be one of the
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following: `max`, `one`, `frobenius` or `infinity`.
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M: integer
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Number of rows in `A`.
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N: integer
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Number of columns in `A`.
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A: Float64Array
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Input matrix `A`.
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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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work: Float64Array
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Work array used to compute the infinity norm, should have `M` indexed
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elements if computing the infinity norm otherwise pass a dummy array.
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Returns
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-------
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Required norm: number
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Value of the required norm.
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Examples
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--------
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> var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var work = new {{alias:@stdlib/array/float64}}( 1 );
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> var order = 'row-major';
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> var norm = 'max';
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> {{alias}}( order, norm, 2, 2, A, 2, work )
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4.0
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{{alias}}.ndarray( norm, M, N, A, sa1, sa2, oa, work, sw, ow )
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Computes the value of the one norm, or the frobenius norm, or the infinity
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norm, or the element with the largest absolute value of a real matrix `A`
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using 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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norm: string
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Specifies the type of norm to be calculated, should be one of the
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following: `max`, `one`, `frobenius` or `infinity`.
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M: integer
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Number of rows in `A`.
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N: integer
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Number of columns in `A`.
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A: Float64Array
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Input matrix `A`.
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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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work: Float64Array
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Work array used to compute the infinity norm, should have `M` indexed
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elements if computing the infinity norm otherwise pass a dummy array.
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sw: integer
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Stride length for `work`.
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ow: integer
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Starting index for `work`.
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Returns
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-------
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Required norm: number
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Value of the required norm.
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Examples
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--------
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> var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var work = new {{alias:@stdlib/array/float64}}( 1 );
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> var norm = 'max';
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> {{alias}}.ndarray( norm, 2, 2, A, 2, 1, 0, work, 1, 0 )
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4.0
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See Also
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--------

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