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feat: add lapack/base/dgebal
#6989
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191fc91
feat: add base implementation
aayush0325 08cc97d
feat: add main export
aayush0325 3a12298
test: add initial tests
aayush0325 080ed50
test: add P job test
aayush0325 02f5d2d
test: add test for S job
aayush0325 0b4af09
test: add test for job = B
aayush0325 aeaff94
test: add ndarray tests
aayush0325 03a6986
chore: cleanup
aayush0325 5f956b0
test: add tests for empty submatrix
aayush0325 4ab0380
test: add more tests
aayush0325 8192ae8
test: add test for norm = 0
aayush0325 f70eec0
test: add test for small values
aayush0325 c9ded98
refactor: update job names
aayush0325 2c45388
test: add tests with weird values
aayush0325 6d755ca
test: add ndarray tests
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285 changes: 285 additions & 0 deletions
285
lib/node_modules/@stdlib/lapack/base/dgebal/lib/base.js
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/** | ||
* @license Apache-2.0 | ||
* | ||
* Copyright (c) 2025 The Stdlib Authors. | ||
* | ||
* Licensed under the Apache License, Version 2.0 (the "License"); | ||
* you may not use this file except in compliance with the License. | ||
* You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, | ||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and | ||
* limitations under the License. | ||
*/ | ||
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/* eslint-disable max-len, max-params, max-statements */ | ||
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'use strict'; | ||
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// MODULES // | ||
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var dswap = require( '@stdlib/blas/base/dswap' ).ndarray; | ||
var dlamch = require( '@stdlib/lapack/base/dlamch' ); | ||
var dnrm2 = require( '@stdlib/blas/base/dnrm2' ).ndarray; | ||
var idamax = require( '@stdlib/blas/base/idamax' ).ndarray; | ||
var abs = require( '@stdlib/math/base/special/abs' ); | ||
var isnan = require( '@stdlib/assert/is-nan' ); | ||
var max = require( '@stdlib/math/base/special/maxn' ); | ||
var min = require( '@stdlib/math/base/special/minn' ); | ||
var dscal = require( '@stdlib/blas/base/dscal' ).ndarray; | ||
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// MAIN // | ||
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/** | ||
* Balances a general real matrix `A`. | ||
* | ||
* ## Notes | ||
* | ||
* The job parameter can be one of the following: | ||
* | ||
* - 'none': none, return immediately | ||
* - 'permutate': permute only | ||
* - 'scale': scale only | ||
* - 'both': both permute and scale | ||
* | ||
* The matrix `A` is overwritten by the balanced matrix. Scale factors are stored in the `scale` array. | ||
* | ||
* @private | ||
* @param {string} job - indicates the operations to be performed | ||
* @param {NonNegativeInteger} N - number of rows/columns in matrix `A` | ||
* @param {Float64Array} A - input matrix to be balanced | ||
* @param {integer} strideA1 - stride of the first dimension of `A` | ||
* @param {integer} strideA2 - stride of the second dimension of `A` | ||
* @param {NonNegativeInteger} offsetA - starting index for `A` | ||
* @param {Float64Array} out - stores the first and last row/column of the balanced submatrix | ||
* @param {integer} strideOut - stride of `out` | ||
* @param {NonNegativeInteger} offsetOut - starting index for `out` | ||
* @param {Float64Array} scale - array containing permutation and scaling information | ||
* @param {integer} strideScale - stride of `scale` | ||
* @param {NonNegativeInteger} offsetScale - starting index for `scale` | ||
* @returns {integer} status code | ||
* | ||
* @example | ||
* var Float64Array = require( '@stdlib/array/float64' ); | ||
* | ||
* var A = new Float64Array( [ 1.0, 100.0, 0.0, 2.0, 200.0, 0.0, 0.0, 0.0, 3.0 ] ); | ||
* var out = new Float64Array( 2 ); | ||
* var scale = new Float64Array( 3 ); | ||
* | ||
* dgebal( 'both', 3, A, 3, 1, 0, out, 1, 0, scale, 1, 0 ); | ||
* // A => <Float64Array>[ 1, 12.5, 0, 16, 200, 0, 0, 0, 3 ] | ||
* // out => <Float64Array>[ 0, 1 ] | ||
* // scale => <Float64Array>[ 8, 1, 2 ] | ||
*/ | ||
function dgebal( job, N, A, strideA1, strideA2, offsetA, out, strideOut, offsetOut, scale, strideScale, offsetScale ) { | ||
var canSwap; | ||
var noconv; | ||
var sfmin1; | ||
var sfmin2; | ||
var sfmax1; | ||
var sfmax2; | ||
var sclfac; | ||
var factor; | ||
var ica; | ||
var ira; | ||
var ca; | ||
var ra; | ||
var is; | ||
var c; | ||
var r; | ||
var k; | ||
var l; | ||
var i; | ||
var j; | ||
var g; | ||
var f; | ||
var s; | ||
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sclfac = 2.0; | ||
factor = 0.95; | ||
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// Quick return if possible | ||
if ( N === 0 ) { | ||
out[ offsetOut ] = 0.0; // ilo | ||
out[ offsetOut + strideOut ] = -1.0; // ihi (invalid) | ||
return 0; | ||
} | ||
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if ( job === 'none' ) { | ||
is = offsetScale; | ||
for ( i = 0; i < N; i++ ) { | ||
scale[ is ] = 1.0; | ||
is += strideScale; | ||
} | ||
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out[ offsetOut ] = 0.0; // ilo | ||
out[ offsetOut + strideOut ] = N - 1; // ihi | ||
return 0; | ||
} | ||
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// Permutation to isolate eigenvalues if possible | ||
k = 0; | ||
l = N - 1; | ||
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if ( job !== 'scale' ) { | ||
// Row and column exchange | ||
noconv = true; | ||
while ( noconv ) { | ||
// Search for rows isolating an eigenvalue and push them down | ||
noconv = false; | ||
for ( i = l; i >= 0; i-- ) { | ||
canSwap = true; | ||
for ( j = 0; j <= l; j++ ) { | ||
if ( i !== j && A[ offsetA + (i*strideA1) + (j*strideA2) ] !== 0.0 ) { | ||
canSwap = false; | ||
break; | ||
} | ||
} | ||
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if ( canSwap ) { | ||
scale[ offsetScale + (l*strideScale) ] = i; | ||
if ( i !== l ) { | ||
dswap( l+1, A, strideA1, offsetA + (i*strideA2), A, strideA1, offsetA + (l*strideA2) ); | ||
dswap( N - k, A, strideA2, offsetA + (i*strideA1) + (k*strideA2), A, strideA2, offsetA + (l*strideA1) + (k*strideA2) ); | ||
} | ||
noconv = true; | ||
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// Check if remaining submatrix is empty and return | ||
if ( l === 0.0 ) { | ||
out[ offsetOut ] = 0.0; // ilo | ||
out[ offsetOut + strideOut ] = 0.0; // ihi | ||
return 0; | ||
} | ||
l -= 1; | ||
} | ||
} | ||
} | ||
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noconv = true; | ||
while ( noconv ) { | ||
// Search for columns isolating an eigenvalue and push them left | ||
noconv = false; | ||
for ( j = k; j <= l; j++ ) { | ||
canSwap = true; | ||
for ( i = k; i <= l; i++ ) { | ||
if ( i !== j && A[ offsetA + (i*strideA1) + (j*strideA2) ] !== 0.0 ) { | ||
canSwap = false; | ||
break; | ||
} | ||
} | ||
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if ( canSwap ) { | ||
scale[ offsetScale + (k*strideScale) ] = j; | ||
if ( j !== k ) { | ||
dswap( l+1, A, strideA1, offsetA + (j*strideA2), A, strideA1, offsetA + (k*strideA2) ); | ||
dswap( N-k, A, strideA2, offsetA + (j*strideA1), A, strideA2, offsetA + (k*strideA1) ); | ||
} | ||
noconv = true; | ||
k += 1; | ||
} | ||
} | ||
} | ||
} | ||
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// Initialize `scale` for non-permuted submatrix | ||
is = offsetScale + (k*strideScale); | ||
for ( i = k; i <= l; i++ ) { | ||
scale[ is ] = 1.0; | ||
is += strideScale; | ||
} | ||
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if ( job === 'permutate' ) { | ||
out[ offsetOut ] = k; // ilo | ||
out[ offsetOut + strideOut ] = l; // ihi | ||
return 0; | ||
} | ||
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// Balance the submatrix in rows K to L, iterative loop for norm reduction (job = 'B') | ||
sfmin1 = dlamch( 'S' ) / dlamch( 'P' ); | ||
sfmax1 = 1.0 / sfmin1; | ||
sfmin2 = sfmin1 * sclfac; | ||
sfmax2 = 1.0 / sfmin2; | ||
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noconv = true; | ||
while ( noconv ) { | ||
noconv = false; | ||
for ( i = k; i <= l; i++ ) { | ||
c = dnrm2( l-k+1, A, strideA1, offsetA + (k*strideA1) + (i*strideA2) ); | ||
r = dnrm2( l-k+1, A, strideA2, offsetA + (i*strideA1) + (k*strideA2) ); | ||
ica = idamax( l+1, A, strideA1, offsetA + (i*strideA2) ); | ||
ca = abs( A[ offsetA + (ica*strideA1) + (i*strideA2) ] ); | ||
ira = idamax( N-k+1, A, strideA2, offsetA + (i*strideA1) + (k*strideA2) ); | ||
ra = abs( A[ offsetA + (i*strideA1) + ((ira+k)*strideA2) ] ); | ||
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if ( c === 0.0 || r === 0.0 ) { | ||
continue; | ||
} | ||
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if ( isnan( c ) || isnan( r ) || isnan( ca ) || isnan( ra ) ) { | ||
return -3; | ||
} | ||
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g = r / sclfac; | ||
f = 1.0; | ||
s = c + r; | ||
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while ( c < g && max( f, c, ca ) < sfmax2 && min( r, g, ra ) > sfmin2 ) { | ||
f *= sclfac; | ||
c *= sclfac; | ||
ca *= sclfac; | ||
r /= sclfac; | ||
g /= sclfac; | ||
ra /= sclfac; | ||
} | ||
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g = c / sclfac; | ||
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while ( g >= r && max( r, ra ) < sfmax2 && min( f, c, g, ca ) > sfmin2 ) { | ||
f /= sclfac; | ||
c /= sclfac; | ||
g /= sclfac; | ||
ca /= sclfac; | ||
r *= sclfac; | ||
ra *= sclfac; | ||
} | ||
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// Now balance | ||
if ( ( c + r ) >= factor * s ) { | ||
continue; | ||
} | ||
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if ( f < 1.0 && scale[ offsetScale + (i*strideScale) ] < 1.0 ) { | ||
if ( f * scale[ offsetScale + (i*strideScale) ] <= sfmin1 ) { | ||
continue; | ||
} | ||
} | ||
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if ( f > 1.0 && scale[ offsetScale + (i*strideScale) ] > 1.0 ) { | ||
if ( scale[ offsetScale + (i*strideScale) ] >= sfmax1 / f ) { | ||
continue; | ||
} | ||
} | ||
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g = 1.0 / f; | ||
scale[ offsetScale + (i*strideScale) ] *= f; | ||
noconv = true; | ||
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dscal( N-k, g, A, strideA2, offsetA + (i*strideA1) + (k*strideA2) ); | ||
dscal( l+1, f, A, strideA1, offsetA + (i*strideA2) ); | ||
} | ||
} | ||
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out[ offsetOut ] = k; // ilo | ||
out[ offsetOut + strideOut ] = l; // ihi | ||
return 0; | ||
} | ||
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// EXPORTS // | ||
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module.exports = dgebal; |
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/** | ||
* @license Apache-2.0 | ||
* | ||
* Copyright (c) 2025 The Stdlib Authors. | ||
* | ||
* Licensed under the Apache License, Version 2.0 (the "License"); | ||
* you may not use this file except in compliance with the License. | ||
* You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, | ||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and | ||
* limitations under the License. | ||
*/ | ||
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'use strict'; | ||
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// MODULES // | ||
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var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); | ||
var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); | ||
var format = require( '@stdlib/string/format' ); | ||
var base = require( './base.js' ); | ||
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// MAIN // | ||
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/** | ||
* Balances a general real matrix `A`. | ||
* | ||
* ## Notes | ||
* | ||
* The job parameter can be one of the following: | ||
* | ||
* - 'none': none, return immediately | ||
* - 'permutate': permute only | ||
* - 'scale': scale only | ||
* - 'both': both permute and scale | ||
* - The matrix `A` is overwritten by the balanced matrix. | ||
* | ||
* @private | ||
* @param {string} order - storage layout of `A` | ||
* @param {string} job - indicates the operations to be performed | ||
* @param {NonNegativeInteger} N - number of rows/columns in matrix `A` | ||
* @param {Float64Array} A - input matrix to be balanced | ||
* @param {NonNegativeInteger} LDA - leading dimension of `A` | ||
* @param {Float64Array} out - stores the first and last row/column of the balanced submatrix | ||
* @param {Float64Array} scale - array containing permutation and scaling information | ||
* @throws {TypeError} first argument must be a valid order | ||
* @throws {TypeError} second argument must be a valid job | ||
* @throws {RangeError} fifth argument must be greater than or equal to `N` | ||
* @returns {integer} status code | ||
* | ||
* @example | ||
* var Float64Array = require( '@stdlib/array/float64' ); | ||
* | ||
* var A = new Float64Array( [ 1.0, 100.0, 0.0, 2.0, 200.0, 0.0, 0.0, 0.0, 3.0 ] ); | ||
* var out = new Float64Array( 2 ); | ||
* var scale = new Float64Array( 3 ); | ||
* | ||
* dgebal( 'row-major', 'both', 3, A, 3, out, scale ); | ||
* // A => <Float64Array>[ 1, 12.5, 0, 16, 200, 0, 0, 0, 3 ] | ||
* // out => <Float64Array>[ 0, 1 ] | ||
* // scale => <Float64Array>[ 8, 1, 2 ] | ||
*/ | ||
function dgebal( order, job, N, A, LDA, out, scale ) { | ||
var sa1; | ||
var sa2; | ||
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if ( !isLayout( order ) ) { | ||
throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); | ||
} | ||
if ( job !== 'both' && job !== 'scale' && job !== 'permutate' && job !== 'none' ) { | ||
throw new TypeError( format( 'invalid argument. Second argument must be one of the following: `both`, `scale`, `permutate`, or `none`. Value: `%s`.', job ) ); | ||
} | ||
if ( isColumnMajor( order ) ) { | ||
sa1 = 1; | ||
sa2 = LDA; | ||
} else { // order === 'row-major' | ||
if ( LDA < N ) { | ||
throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.', N, LDA ) ); | ||
} | ||
sa1 = LDA; | ||
sa2 = 1; | ||
} | ||
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return base( job, N, A, sa1, sa2, 0, out, 1, 0, scale, 1, 0 ); | ||
} | ||
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// EXPORTS // | ||
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module.exports = dgebal; |
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we don't normally return negative status codes, but in this case i needed the program to exit so i've used a negative status code (-3 from LAPACK). is there a better/more preferred way to handle this?