diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/README.md b/lib/node_modules/@stdlib/lapack/base/dlacn2/README.md
new file mode 100644
index 000000000000..3eaac8c2e4c1
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/README.md
@@ -0,0 +1,362 @@
+
+
+# dlacn2
+
+> LAPACK routine to estimate the one-norm of a square matrix `A`, using reverse communication for evaluating matrix-vector products.
+
+
+
+## Usage
+
+```javascript
+var dlacn2 = require( '@stdlib/lapack/base/dlacn2' );
+```
+
+#### dlacn2( N, V, X, ISGN, EST, KASE, ISAVE )
+
+Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+
+```javascript
+var Int32Array = require( '@stdlib/array/int32' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+var EST = new Float64Array( [ 10 ] );
+var KASE = new Int32Array( [ 1 ] );
+var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+
+dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+// X => [ 0.0, 0.0, 0.0, 1.0 ]
+// V => [ 5.0, 3.0, 1.0, 5.0 ]
+// EST => [ 10.0 ]
+// KASE => [ 1 ]
+```
+
+The function has the following parameters:
+
+- **N**: number of rows/columns in `A`.
+- **V**: workspace [`Float64Array`][mdn-float64array] having `N` indexed elements, used internally to store intermediate vectors.
+- **X**: input/output [`Float64Array`][mdn-float64array] having `N` indexed elements, contains the current or next matrix-vector product.
+- **ISGN**: [`Int32Array`][mdn-int32array] having `N` indexed elements, stores the sign of each element in `X` during iterations.
+- **EST**: single-element [`Float64Array`][mdn-float64array], on output, contains the estimated one-norm of the matrix `A`.
+- **KASE**: single-element [`Int32Array`][mdn-int32array] that controls the reverse communication.
+- **ISAVE**: [`Int32Array`][mdn-int32array] having 3 indexed elements, used internally to maintain state across multiple calls.
+
+The reverse communication takes place using `KASE`, it may have any of these values:
+
+- `0`: estimation is complete.
+- `1`: caller must compute `A * X` and store the result back in `X`.
+- `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`.
+
+`V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned).
+
+`ISAVE` has the following three elements:
+
+- the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+- the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`.
+- the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+
+
+```javascript
+var Int32Array = require( '@stdlib/array/int32' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+// Initial arrays...
+var V0 = new Float64Array( [ 0.0, 5.0, 3.0, 1.0, 5.0 ] );
+var X0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
+var ISGN0 = new Int32Array( [ 0, 1, 1, 1, 1 ] );
+var EST0 = new Float64Array( [ 0.0, 10.0 ] );
+var KASE0 = new Int32Array( [ 0, 1 ] );
+var ISAVE0 = new Int32Array( [ 0, 2, 3, 1 ] );
+
+// Create offset views...
+var V = new Float64Array( V0.buffer, V0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var X = new Float64Array( X0.buffer, X0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var ISGN = new Int32Array( ISGN0.buffer, ISGN0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var EST = new Float64Array( EST0.buffer, EST0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var KASE = new Int32Array( KASE0.buffer, KASE0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var ISAVE = new Int32Array( ISAVE0.buffer, ISAVE0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+// X0 => [ 0.0, 0.0, 0.0, 0.0, 1.0 ]
+// V0 => [ 0.0, 5.0, 3.0, 1.0, 5.0 ]
+// EST0 => [ 0.0, 10.0 ]
+// KASE0 => [ 0, 1 ]
+```
+
+
+
+#### dlacn2.ndarray( N, V, sv, ov, X, sx, ox, ISGN, sisgn, oisgn, EST, oe, KASE, ok, ISAVE, sisave, oisave )
+
+Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+
+```javascript
+var Int32Array = require( '@stdlib/array/int32' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+var EST = new Float64Array( [ 10 ] );
+var KASE = new Int32Array( [ 1 ] );
+var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+
+dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+// X => [ 0.0, 0.0, 0.0, 1.0 ]
+// V => [ 5.0, 3.0, 1.0, 5.0 ]
+// EST => [ 10.0 ]
+// KASE => [ 1 ]
+```
+
+The function has the following parameters:
+
+- **N**: number of rows/columns in `A`.
+- **V**: workspace [`Float64Array`][mdn-float64array] having `N` indexed elements, used internally to store intermediate vectors.
+- **sv**: stride length for `V`.
+- **ov**: starting index for `V`.
+- **X**: input/output [`Float64Array`][mdn-float64array] having `N` indexed elements, contains the current or next matrix-vector product.
+- **sx**: stride length for `X`.
+- **ox**: starting index for `X`.
+- **ISGN**: [`Int32Array`][mdn-int32array] having `N` indexed elements, stores the sign of each element in `X` during iterations.
+- **sisgn**: stride length for `ISGN`.
+- **oisgn**: starting index for `ISGN`.
+- **EST**: single-element [`Float64Array`][mdn-float64array], on output, contains the estimated one-norm of the matrix `A`.
+- **oe**: starting index for `EST`.
+- **KASE**: single-element [`Int32Array`][mdn-int32array] that controls the reverse communication.
+- **ok**: starting index for `KASE`.
+- **ISAVE**: [`Int32Array`][mdn-int32array] having 3 indexed elements, used internally to maintain state across multiple calls.
+- **sisave**: stride length for `ISAVE`.
+- **oisave**: starting index for `ISAVE`.
+
+The reverse communication takes place using `KASE`, it may have any of these values:
+
+- `0`: estimation is complete.
+- `1`: caller must compute `A * X` and store the result back in `X`.
+- `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`.
+
+`V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned).
+
+`ISAVE` has the following three elements:
+
+- the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+- the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`.
+- the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,
+
+
+
+```javascript
+var Int32Array = require( '@stdlib/array/int32' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+var V = new Float64Array( [ 0.0, 5.0, 3.0, 1.0, 5.0 ] );
+var X = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
+var ISGN = new Int32Array( [ 0, 1, 1, 1, 1 ] );
+var EST = new Float64Array( [ 0.0, 10.0 ] );
+var KASE = new Int32Array( [ 0, 1 ] );
+var ISAVE = new Int32Array( [ 0, 2, 3, 1 ] );
+
+dlacn2.ndarray( 4, V, 1, 1, X, 1, 1, ISGN, 1, 1, EST, 1, KASE, 1, ISAVE, 1, 1 );
+// X => [ 0.0, 0.0, 0.0, 0.0, 1.0 ]
+// V => [ 0.0, 5.0, 3.0, 1.0, 5.0 ]
+// EST => [ 0.0, 10.0 ]
+// KASE => [ 0, 1 ]
+```
+
+
+
+
+
+
+
+## Notes
+
+- `dlacn2()` corresponds to the [LAPACK][LAPACK] function [`dlacn2`][lapack-dlacn2].
+
+
+
+
+
+
+
+## Examples
+
+
+
+
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var Int32Array = require( '@stdlib/array/int32' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var dgemv = require( '@stdlib/blas/base/dgemv' );
+var dcopy = require( '@stdlib/blas/base/dcopy' );
+var dlacn2 = require( '@stdlib/lapack/base/dlacn2' );
+
+// Specify matrix meta data:
+var shape = [ 4, 4 ];
+var strides = [ 4, 1 ];
+var offset = 0;
+var order = 'row-major';
+
+// Create a matrix stored in linear memory:
+var A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+]);
+
+console.log( ndarray2array( A, shape, strides, offset, order ) );
+
+var KASE = new Int32Array( 1 );
+var EST = new Float64Array( 1 );
+var ISGN = new Int32Array( 4 );
+var ISAVE = new Int32Array( 3 );
+var X = new Float64Array( 4 );
+var V = new Float64Array( 4 );
+
+var work = new Float64Array( 4 );
+
+while ( true ) {
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'row-major', 'no-transpose', shape[ 0 ], shape[ 1 ], 1.0, A, strides[ 0 ], X, 1, 0, work, 1 );
+ dcopy( shape[ 0 ], work, 1, X, 1 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'row-major', 'transpose', shape[ 0 ], shape[ 1 ], 1.0, A, strides[ 0 ], X, 1, 0, work, 1 );
+ dcopy( shape[ 0 ], work, 1, X, 1 );
+ }
+}
+
+console.log( 'estimated norm: ', EST[ 0 ] );
+console.log( 'V: ', V );
+```
+
+
+
+
+
+
+
+* * *
+
+
+
+## C APIs
+
+
+
+
+
+
+
+
+
+
+
+### Usage
+
+```c
+TODO
+```
+
+#### TODO
+
+TODO.
+
+```c
+TODO
+```
+
+TODO
+
+```c
+TODO
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Examples
+
+```c
+TODO
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[lapack]: https://www.netlib.org/lapack/explore-html/
+
+[lapack-dlacn2]: https://netlib.org/lapack/explore-html/d6/d2d/group__lacn2_gabc1e7463e250c9e43596bfcbfa83c1de.html#gabc1e7463e250c9e43596bfcbfa83c1de
+
+[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array
+
+[mdn-int32array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Int32Array
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+
+
+
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.js
new file mode 100644
index 000000000000..34365003d68c
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.js
@@ -0,0 +1,116 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dlacn2 = require( './../lib/dlacn2.js' );
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - number of elements along each dimension
+* @returns {Function} benchmark function
+*/
+function createBenchmark( N ) {
+ var intOpts;
+ var ISAVE;
+ var KASE;
+ var opts;
+ var ISGN;
+ var EST;
+ var X;
+ var V;
+
+ opts = {
+ 'dtype': 'float64'
+ };
+ intOpts = {
+ 'dtype': 'int32'
+ };
+
+ X = uniform( N, 0.0, 100.0, opts );
+ V = uniform( N, 0.0, 100.0, opts );
+ ISAVE = discreteUniform( 3, 0, N, intOpts );
+ KASE = discreteUniform( 1, 0, 2, intOpts );
+ EST = uniform( 1, 0.0, 1000.0, opts );
+ ISGN = discreteUniform( N, 1, 1, intOpts );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dlacn2( N, V, X, ISGN, EST, KASE, ISAVE );
+ if ( isnan( EST[ 0 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( EST[ 0 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var min;
+ var max;
+ var N;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ N = pow( 10, i );
+ f = createBenchmark( N );
+ bench( pkg+':order=column-major,size='+(N*N), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..23904b9a77e9
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/benchmark/benchmark.ndarray.js
@@ -0,0 +1,116 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dlacn2 = require( './../lib/ndarray.js' );
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - number of elements along each dimension
+* @returns {Function} benchmark function
+*/
+function createBenchmark( N ) {
+ var intOpts;
+ var ISAVE;
+ var KASE;
+ var opts;
+ var ISGN;
+ var EST;
+ var X;
+ var V;
+
+ opts = {
+ 'dtype': 'float64'
+ };
+ intOpts = {
+ 'dtype': 'int32'
+ };
+
+ X = uniform( N, 0.0, 100.0, opts );
+ V = uniform( N, 0.0, 100.0, opts );
+ ISAVE = discreteUniform( 3, 0, N, intOpts );
+ KASE = discreteUniform( 1, 0, 2, intOpts );
+ EST = uniform( 1, 0.0, 1000.0, opts );
+ ISGN = discreteUniform( N, 1, 1, intOpts );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ dlacn2( N, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // eslint-disable-line max-len
+ if ( isnan( EST[ 0 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( EST[ 0 ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var min;
+ var max;
+ var N;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ N = pow( 10, i );
+ f = createBenchmark( N );
+ bench( pkg+':order=column-major,size='+(N*N), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/repl.txt
new file mode 100644
index 000000000000..ac457dc905c1
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/repl.txt
@@ -0,0 +1,151 @@
+
+{{alias}}( N, V, X, ISGN, EST, KASE, ISAVE )
+ Estimates the one-norm of a square matrix `A`, using reverse communication
+ for evaluating matrix-vector products.
+
+ Indexing is relative to the first index. To introduce an offset, use typed
+ array views.
+
+ Parameters
+ ----------
+ N: integer
+ Number of rows/columns in `A`.
+
+ V: Float64Array
+ Workspace array having `N` indexed elements, used internally to store
+ intermediate vectors.
+
+ X: Float64Array
+ Input/Output vector having `N` indexed elements, contains the current
+ or next matrix-vector product.
+
+ ISGN: Int32Array
+ Integer array having `N` indexed elements, stores the sign of each
+ element in `X` during iterations.
+
+ EST: Float64Array
+ Single-element array, on output, contains the estimated one-norm of the
+ matrix `A`.
+
+ KASE: Int32Array
+ Single-element array that controls the reverse communication.
+
+ ISAVE: Int32Array
+ Integer array having 3 indexed elements, used internally to maintain
+ state across multiple calls.
+
+ Returns
+ -------
+ out: undefined
+ Writes the arrays in place.
+
+ Examples
+ --------
+ > var V = new {{alias:@stdlib/array/float64}}( [ 5.0, 3.0, 1.0, 5.0 ] );
+ > var X = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
+ > var ISGN = new {{alias:@stdlib/array/int32}}( [ 1, 1, 1, 1 ] );
+ > var EST = new {{alias:@stdlib/array/float64}}( [ 10 ] );
+ > var KASE = new {{alias:@stdlib/array/int32}}( [ 1 ] );
+ > var ISAVE = new {{alias:@stdlib/array/int32}}( [ 2, 3, 1 ] );
+ > {{alias}}( 4, V, X, ISGN, EST, KASE, ISAVE );
+ > X
+ [ 0.0, 0.0, 0.0, 1.0 ]
+ > V
+ [ 5.0, 3.0, 1.0, 5.0 ]
+ > EST
+ [ 10.0 ]
+ > KASE
+ [ 1 ]
+
+
+{{alias}}.ndarray(N,V,sv,ov,X,sx,ox,ISGN,sis,ois,EST,oe,KASE,ok,ISAVE,sis1,ois1)
+ Estimates the one-norm of a square matrix `A`, using alternative indexing
+ semantics and reverse communication for evaluating matrix-vector products.
+
+ While typed array views mandate a view offset based on the underlying
+ buffer, the offset parameters support indexing semantics based on starting
+ indices.
+
+ Parameters
+ ----------
+ N: integer
+ Number of rows/columns in `A`.
+
+ V: Float64Array
+ Workspace array having `N` indexed elements, used internally to store
+ intermediate vectors.
+
+ sv: integer
+ Stride length for `V`.
+
+ ov: integer
+ Starting index for `V`.
+
+ X: Float64Array
+ Input/Output vector having `N` indexed elements, contains the current
+ or next matrix-vector product.
+
+ sx: integer
+ Stride length for `X`.
+
+ ox: integer
+ Starting index for `X`.
+
+ ISGN: Int32Array
+ Integer array having `N` indexed elements, stores the sign of each
+ element in `X` during iterations.
+
+ sis: integer
+ Stride length for `ISGN`.
+
+ ois: integer
+ Starting index for `ISGN`.
+
+ EST: Float64Array
+ Single-element array, on output, contains the estimated one-norm of the
+ matrix `A`.
+
+ oe: integer
+ Starting index for `EST`.
+
+ KASE: Int32Array
+ Single-element array that controls the reverse communication.
+
+ ok: integer
+ Starting index for `KASE`.
+
+ ISAVE: Int32Array
+ Integer array having 3 indexed elements, used internally to maintain
+ state across multiple calls.
+
+ sis1: integer
+ Stride length for `ISAVE`.
+
+ ois1: integer
+ Starting index for `ISAVE`.
+
+ Returns
+ -------
+ out: undefined
+ Writes the arrays in place.
+
+ Examples
+ --------
+ > var V = new {{alias:@stdlib/array/float64}}( [ 5.0, 3.0, 1.0, 5.0 ] );
+ > var X = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
+ > var ISGN = new {{alias:@stdlib/array/int32}}( [ 1, 1, 1, 1 ] );
+ > var EST = new {{alias:@stdlib/array/float64}}( [ 10 ] );
+ > var KASE = new {{alias:@stdlib/array/int32}}( [ 1 ] );
+ > var ISAVE = new {{alias:@stdlib/array/int32}}( [ 2, 3, 1 ] );
+ > {{alias}}.ndarray( 4, V,1,0, X,1,0, ISGN,1,0, EST,0, KASE,0, ISAVE,1,0 );
+ > X
+ [ 0.0, 0.0, 0.0, 1.0 ]
+ > V
+ [ 5.0, 3.0, 1.0, 5.0 ]
+ > EST
+ [ 10.0 ]
+ > KASE
+ [ 1 ]
+
+ See Also
+ --------
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/index.d.ts
new file mode 100644
index 000000000000..eddf520d7691
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/index.d.ts
@@ -0,0 +1,197 @@
+/*
+* @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.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Interface describing `dlacn2`.
+*/
+interface Routine {
+ /**
+ * Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+ *
+ * ## Notes
+ *
+ * the reverse communication takes place using `KASE`, it may have any of these values:
+ *
+ * - `0`: estimation is complete
+ * - `1`: caller must compute `A * X` and store the result back in `X`
+ * - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+ *
+ * `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+ *
+ * `ISAVE` has the following three elements:
+ *
+ * - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+ * - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+ * - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+ *
+ * @param N - number of rows/columns in `A`
+ * @param V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+ * @param X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+ * @param ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+ * @param EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+ * @param KASE - single-element array that controls the reverse communication.
+ * @param ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+ * @returns `B`
+ *
+ * @example
+ * var Int32Array = require( '@stdlib/array/int32' );
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+ * var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+ * var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+ * var EST = new Float64Array( [ 10 ] );
+ * var KASE = new Int32Array( [ 1 ] )
+ * var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+ *
+ * dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+ * // X => [ 0.0, 0.0, 0.0, 1.0 ]
+ * // V => [ 5.0, 3.0, 1.0, 5.0 ]
+ * // EST => [ 10.0 ]
+ * // KASE => [ 1 ]
+ */
+ ( N: number, V: Float64Array, X: Float64Array, ISGN: Int32Array, EST: Float64Array, KASE: Int32Array, ISAVE: Int32Array ): void;
+
+ /**
+ * Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+ *
+ * ## Notes
+ *
+ * the reverse communication takes place using `KASE`, it may have any of these values:
+ *
+ * - `0`: estimation is complete
+ * - `1`: caller must compute `A * X` and store the result back in `X`
+ * - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+ *
+ * `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+ *
+ * `ISAVE` has the following three elements:
+ *
+ * - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+ * - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+ * - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+ *
+ * @param N - number of rows/columns in `A`
+ * @param V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+ * @param strideV - stride length for `V`
+ * @param offsetV - starting index for `V`
+ * @param X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+ * @param strideX - stride length for `X`
+ * @param offsetX - starting index for `X`
+ * @param ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+ * @param strideISGN - stride length for `ISGN`
+ * @param offsetISGN - starting index for `ISGN`
+ * @param EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+ * @param offsetEST - starting index for `EST`
+ * @param KASE - single-element array that controls the reverse communication.
+ * @param offsetKASE - starting index for `KASE`
+ * @param ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+ * @param strideISAVE - stride length for `ISAVE`
+ * @param offsetISAVE - starting index for `ISAVE`
+ * @returns `B`
+ *
+ * @example
+ * var Int32Array = require( '@stdlib/array/int32' );
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+ * var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+ * var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+ * var EST = new Float64Array( [ 10 ] );
+ * var KASE = new Int32Array( [ 1 ] )
+ * var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+ *
+ * dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+ * // X => [ 0.0, 0.0, 0.0, 1.0 ]
+ * // V => [ 5.0, 3.0, 1.0, 5.0 ]
+ * // EST => [ 10.0 ]
+ * // KASE => [ 1 ]
+ */
+ ndarray( N: number, V: Float64Array, strideV: number, offsetV: number, X: Float64Array, strideX: number, offsetX: number, ISGN: Int32Array, strideISGN: number, offsetISGN: number, EST: Float64Array, offsetEST: number, KASE: Int32Array, offsetKASE: number, ISAVE: Int32Array, strideISAVE: number, offsetISAVE: number ): void;
+}
+
+/**
+* Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+*
+* ## Notes
+*
+* the reverse communication takes place using `KASE`, it may have any of these values:
+*
+* - `0`: estimation is complete
+* - `1`: caller must compute `A * X` and store the result back in `X`
+* - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+*
+* `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+*
+* `ISAVE` has the following three elements:
+*
+* - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+* - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+* - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+*
+* @param N - number of rows/columns in `A`
+* @param V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param KASE - single-element array that controls the reverse communication.
+* @param ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @returns `B`
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*/
+declare var dlacn2: Routine;
+
+
+// EXPORTS //
+
+export = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/test.ts
new file mode 100644
index 000000000000..94fcf446bd53
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/docs/types/test.ts
@@ -0,0 +1,536 @@
+/*
+* @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.
+*/
+
+import dlacn2 = require( './index' );
+
+
+// TESTS //
+
+// The function returns undefined...
+{
+ const KASE = new Int32Array( 1 );
+ const EST = new Float64Array( 1 );
+ const ISGN = new Int32Array( 4 );
+ const ISAVE = new Int32Array( 3 );
+ const X = new Float64Array( 4 );
+ const V = new Float64Array( 4 );
+
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectType void
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+ const X = new Float64Array( 4 );
+ const V = new Float64Array( 4 );
+
+ dlacn2( '5', V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( true, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( false, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( null, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( void 0, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( [], V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( {}, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( ( x: number ): number => x, V, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a Float64Array...
+{
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+ const X = new Float64Array( 4 );
+
+ dlacn2( 4, '5', X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, 5, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, true, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, false, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, null, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, void 0, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, [], X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, {}, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, ( x: number ): number => x, X, ISGN, EST, KASE, ISAVE ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a Float64Array...
+{
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+ const V = new Float64Array( 4 );
+
+ dlacn2( 4, V, '5', ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, 5, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, true, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, false, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, null, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, void 0, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, [], ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, {}, ISGN, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, ( x: number ): number => x, ISGN, EST, KASE, ISAVE ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2( 4, V, X, '5', EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, 5, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, true, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, false, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, null, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, void 0, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, [], EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, {}, EST, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ( x: number ): number => x, EST, KASE, ISAVE ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a Float64Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2( 4, V, X, ISGN, '5', KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, 5, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, true, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, false, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, null, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, void 0, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, [], KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, {}, KASE, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, ( x: number ): number => x, KASE, ISAVE ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a sixth argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2( 4, V, X, ISGN, EST, '5', ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, 5, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, true, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, false, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, null, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, void 0, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, [], ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, {}, ISAVE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, ( x: number ): number => x, ISAVE ); // $ExpectError
+}
+// The compiler throws an error if the function is provided a seventh argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+
+ dlacn2( 4, V, X, ISGN, EST, KASE, '5' ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, 5 ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, true ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, false ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, null ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, void 0 ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, [] ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, {} ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2(); // $ExpectError
+ dlacn2( 4 ); // $ExpectError
+ dlacn2( 4, V ); // $ExpectError
+ dlacn2( 4, V, X ); // $ExpectError
+ dlacn2( 4, V, X, ISGN ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE ); // $ExpectError
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE, 10 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a undefined...
+{
+ const KASE = new Int32Array( 1 );
+ const EST = new Float64Array( 1 );
+ const ISGN = new Int32Array( 4 );
+ const ISAVE = new Int32Array( 3 );
+ const X = new Float64Array( 4 );
+ const V = new Float64Array( 4 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectType void
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( '4', V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( true, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( false, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( null, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( void 0, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( [], V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( {}, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( ( x: number ): number => x, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a Float64Array...
+{
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, 'V', 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, 5, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, true, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, null, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, void 0, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, [], 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, {}, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, ( x: number ): number => x, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, '1', 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, true, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, false, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, null, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, void 0, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, [], 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, {}, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, ( x: number ): number => x, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, '0', X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, true, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, false, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, null, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, void 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, [], X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, {}, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, ( x: number ): number => x, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a Float64Array...
+{
+ const V = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, 'X', 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, 5, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, true, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, null, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, void 0, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, [], 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, {}, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, ( x: number ): number => x, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a sixth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, '1', 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, true, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, null, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, void 0, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, [], 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, {}, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, ( x: number ): number => x, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a seventh argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, '0', ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, true, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, null, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, void 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, [], ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, {}, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, ( x: number ): number => x, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an eighth argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, '0', 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, 5, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, true, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, null, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, void 0, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, [], 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, {}, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ( x: number ): number => x, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a ninth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, '1', 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, true, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, null, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, void 0, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, [], 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, {}, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, ( x: number ): number => x, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a tenth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, '0', EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, true, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, null, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, void 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, [], EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, {}, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, ( x: number ): number => x, EST, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an eleventh argument which is not a Float64Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, '0', 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, 5, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, true, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, null, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, void 0, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, [], 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, {}, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, ( x: number ): number => x, 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a twelfth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, '0', KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, true, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, null, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, void 0, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, [], KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, {}, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, ( x: number ): number => x, KASE, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a thirteenth argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, '0', 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, 5, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, true, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, null, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, void 0, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, [], 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, {}, 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, ( x: number ): number => x, 0, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourteenth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, '0', ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, true, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, null, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, void 0, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, [], ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, {}, ISAVE, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, ( x: number ): number => x, ISAVE, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifteenth argument which is not an Int32Array...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, '0', 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, 5, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, true, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, null, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, void 0, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, [], 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, {}, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a sixteenth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, '1', 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, true, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, null, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, void 0, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, [], 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, {}, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a seventeenth argument which is not a number...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, '0' ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, true ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, null ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, void 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, [] ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, {} ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
+{
+ const V = new Float64Array( 4 );
+ const X = new Float64Array( 4 );
+ const ISGN = new Int32Array( 4 );
+ const EST = new Float64Array( 1 );
+ const KASE = new Int32Array( 1 );
+ const ISAVE = new Int32Array( 3 );
+
+ dlacn2.ndarray(); // $ExpectError
+ dlacn2.ndarray( 4 ); // $ExpectError
+ dlacn2.ndarray( 4, V ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1 ); // $ExpectError
+ dlacn2.ndarray( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0, 0 ); // $ExpectError
+}
+
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/examples/index.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/examples/index.js
new file mode 100644
index 000000000000..34bd6c592c1c
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/examples/index.js
@@ -0,0 +1,71 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+/* eslint-disable array-element-newline */
+
+var Float64Array = require( '@stdlib/array/float64' );
+var Int32Array = require( '@stdlib/array/int32' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var dgemv = require( '@stdlib/blas/base/dgemv' );
+var dcopy = require( '@stdlib/blas/base/dcopy' );
+var dlacn2 = require( './../lib' );
+
+// Specify matrix meta data:
+var shape = [ 4, 4 ];
+var strides = [ 4, 1 ];
+var offset = 0;
+var order = 'row-major';
+
+// Create a matrix stored in linear memory:
+var A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+]);
+
+console.log( ndarray2array( A, shape, strides, offset, order ) );
+
+var KASE = new Int32Array( 1 );
+var EST = new Float64Array( 1 );
+var ISGN = new Int32Array( 4 );
+var ISAVE = new Int32Array( 3 );
+var X = new Float64Array( 4 );
+var V = new Float64Array( 4 );
+
+var work = new Float64Array( 4 );
+
+while ( true ) {
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'row-major', 'no-transpose', shape[ 0 ], shape[ 1 ], 1.0, A, strides[ 0 ], X, 1, 0, work, 1 );
+ dcopy( shape[ 0 ], work, 1, X, 1 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'row-major', 'transpose', shape[ 0 ], shape[ 1 ], 1.0, A, strides[ 0 ], X, 1, 0, work, 1 );
+ dcopy( shape[ 0 ], work, 1, X, 1 );
+ }
+}
+
+console.log( 'estimated norm: ', EST[ 0 ] );
+console.log( 'V: ', V );
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/base.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/base.js
new file mode 100644
index 000000000000..c408a7489eec
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/base.js
@@ -0,0 +1,487 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+/* eslint-disable max-len, max-params */
+
+// MODULES //
+
+var abs = require( '@stdlib/math/base/special/abs' );
+var idamax = require( '@stdlib/blas/base/idamax' ).ndarray;
+var dcopy = require( '@stdlib/blas/base/dcopy' ).ndarray;
+var dasum = require( '@stdlib/blas/base/dasum' ).ndarray;
+var nint = require( './nint.js' );
+
+
+// MAIN //
+
+/**
+* Applies a deterministic fallback vector for final evaluation.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var X = new Float64Array( 4 );
+* var KASE = new Int32Array( [ 0 ] );
+* var ISAVE = new Int32Array( [ 0 ] );
+*
+* finalStep( 4, X, 1, 0, KASE, 0, ISAVE, 0 );
+*
+* // X => [ 1.0, ~-1.33, ~1.67, -2.0 ]
+* // KASE => [ 1 ]
+* // ISAVE => [ 5 ]
+*/
+function finalStep( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, offsetISAVE ) {
+ var altsgn;
+ var ix;
+ var i;
+
+ ix = offsetX;
+ altsgn = 1.0;
+ for ( i = 0; i < N; i++ ) {
+ X[ ix ] = altsgn * ( 1.0 + ( i / ( N - 1 ) ) );
+ altsgn *= -1;
+
+ ix += strideX;
+ }
+
+ KASE[ offsetKASE ] = 1;
+ ISAVE[ offsetISAVE ] = 5;
+}
+
+/**
+* Initializes the estimation of the one-norm of a square matrix `A`.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {NonNegativeInteger} offsetV - starting index for `V`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param {integer} strideISGN - stride length for `ISGN`
+* @param {NonNegativeInteger} offsetISGN - starting index for `ISGN`
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {NonNegativeInteger} offsetEST - starting index for `EST`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var X = new Float64Array( [ -2.0, 3.0, 0.0, -4.0 ] );
+* var V = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var ISGN = new Int32Array( [ 0, 0, 0, 0 ] );
+* var EST = new Float64Array( [ 0.0 ] );
+* var KASE = new Int32Array( [ -1 ] );
+* var ISAVE = new Int32Array( [ 0 ] );
+*
+* isaveIsOne( 4, V, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 0 );
+*
+* // EST => [ 9.0 ]
+* // X => [ -1.0, 1.0, 1.0, -1.0 ]
+* // ISGN => [ -1, 1, 1, -1 ]
+* // KASE => [ 2 ]
+* // ISAVE => [ 2 ]
+*/
+function isaveIsOne( N, V, offsetV, X, strideX, offsetX, ISGN, strideISGN, offsetISGN, EST, offsetEST, KASE, offsetKASE, ISAVE, offsetISAVE ) {
+ var is;
+ var ix;
+ var i;
+
+ if ( N === 1 ) {
+ V[ offsetV ] = X[ offsetX ];
+ EST[ offsetEST ] = abs( V[ offsetV ] );
+ KASE[ offsetKASE ] = 0;
+ return;
+ }
+
+ EST[ offsetEST ] = dasum( N, X, strideX, offsetX );
+
+ ix = offsetX;
+ is = offsetISGN;
+ for ( i = 0; i < N; i++ ) {
+ if ( X[ ix ] >= 0.0 ) {
+ X[ ix ] = 1.0;
+ } else {
+ X[ ix ] = -1.0;
+ }
+ ISGN[ is ] = nint( X[ ix ] );
+
+ ix += strideX;
+ is += strideISGN;
+ }
+ KASE[ offsetKASE ] = 2;
+ ISAVE[ offsetISAVE ] = 2;
+}
+
+/**
+* Performs an initial pivot based on the largest magnitude element of `X`.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {integer} strideISAVE - stride length for `ISAVE`
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var X = new Float64Array( [ 1.0, -5.0, 2.0, 0.5 ] );
+* var KASE = new Int32Array( [ 0 ] );
+* var ISAVE = new Int32Array( [ 0, 0, 0 ] );
+*
+* isaveIsTwo( 4, X, 1, 0, KASE, 0, ISAVE, 1, 0 );
+*
+* // X => [ 0.0, 1.0, 0.0, 0.0 ]
+* // ISAVE => [ 3, 1, 2 ]
+* // KASE => [ 1 ]
+*/
+function isaveIsTwo( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, strideISAVE, offsetISAVE ) {
+ var ix;
+ var i;
+
+ ISAVE[ offsetISAVE + strideISAVE ] = idamax( N, X, strideX, offsetX );
+ ISAVE[ offsetISAVE + ( 2 * strideISAVE ) ] = 2;
+
+ ix = offsetX;
+ for ( i = 0; i < N; i++ ) {
+ X[ ix ] = 0.0;
+ ix += strideX;
+ }
+
+ X[ offsetX + ( ISAVE[ offsetISAVE + strideISAVE ] * strideX ) ] = 1.0;
+ KASE[ offsetKASE ] = 1;
+ ISAVE[ offsetISAVE ] = 3;
+}
+
+/**
+* Updates estimates and checks whether convergence has occurred.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {integer} strideV - stride length for `V`
+* @param {NonNegativeInteger} offsetV - starting index for `V`
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {NonNegativeInteger} offsetEST - starting index for `EST`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param {integer} strideISGN - stride length for `ISGN`
+* @param {NonNegativeInteger} offsetISGN - starting index for `ISGN`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var X = new Float64Array( [ -2.0, 0.0, 3.0, -4.0 ] );
+* var V = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] ); // Deliberate mismatch
+* var EST = new Float64Array( [ 6.0 ] ); // estold
+* var KASE = new Int32Array( [ -1 ] );
+* var ISAVE = new Int32Array( [ 3 ] );
+*
+* isaveIsThree( 4, X, 1, 0, V, 1, 0, EST, 0, KASE, 0, ISGN, 1, 0, ISAVE, 0 );
+*
+* // EST => [ 9.0 ]
+* // X => [ -1.0, 1.0, -1.0, -1.0 ]
+* // ISGN => [ -1, 1, -1, -1 ]
+* // KASE => [ 2 ]
+* // ISAVE => [ 4 ]
+* // V => [ -2.0, 0.0, 3.0, -4.0 ]
+*/
+function isaveIsThree( N, X, strideX, offsetX, V, strideV, offsetV, EST, offsetEST, KASE, offsetKASE, ISGN, strideISGN, offsetISGN, ISAVE, offsetISAVE ) {
+ var estold;
+ var ix1;
+ var is1;
+ var ix;
+ var is;
+ var xs;
+ var i;
+ var j;
+
+ dcopy( N, X, strideX, offsetX, V, strideV, offsetV );
+ estold = EST[ offsetEST ];
+ EST[ offsetEST ] = dasum( N, V, strideV, offsetV );
+
+ ix = offsetX;
+ is = offsetISGN;
+ for ( i = 0; i < N; i++ ) {
+ if ( X[ ix ] >= 0.0 ) {
+ xs = 1.0;
+ } else {
+ xs = -1.0;
+ }
+
+ if ( nint( xs ) !== ISGN[ is ] ) {
+ if ( EST[ offsetEST ] <= estold ) {
+ finalStep( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, offsetISAVE );
+ return;
+ }
+
+ ix1 = offsetX;
+ is1 = offsetISGN;
+ for ( j = 0; j < N; j++ ) {
+ if ( X[ ix1 ] >= 0.0 ) {
+ X[ ix1 ] = 1.0;
+ } else {
+ X[ ix1 ] = -1.0;
+ }
+ ISGN[ is1 ] = nint( X[ ix1 ] );
+
+ ix1 += strideX;
+ is1 += strideISGN;
+ }
+ KASE[ offsetKASE ] = 2;
+ ISAVE[ offsetISAVE ] = 4;
+ return;
+ }
+
+ ix += strideX;
+ is += strideISGN;
+ }
+
+ finalStep( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, offsetISAVE );
+}
+
+/**
+* Attempts to refine the estimate by cycling through multiple basis vectors.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {integer} strideISAVE - stride length for `ISAVE`
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @returns {void}
+*
+* @example
+* var X = new Float64Array( [ 2.0, 0.5, -3.0, 4.0 ] );
+* var ISAVE = new Int32Array( [ 2, 1, 3 ] );
+* var KASE = new Int32Array( [ -1 ] );
+*
+* isaveIsFour( 4, X, 1, 0, ISAVE, 1, 0, KASE, 0 );
+*
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // ISAVE => [ 3, 3, 4 ]
+* // KASE => [ 1 ]
+*/
+function isaveIsFour( N, X, strideX, offsetX, ISAVE, strideISAVE, offsetISAVE, KASE, offsetKASE ) {
+ var jlast;
+ var ix;
+ var i;
+
+ jlast = ISAVE[ offsetISAVE + strideISAVE ];
+ ISAVE[ offsetISAVE + strideISAVE ] = idamax( N, X, strideX, offsetX );
+
+ if ( X[ offsetX + ( jlast * strideX ) ] !== abs( X[ offsetX + ( ISAVE[ offsetISAVE + strideISAVE ] * strideX ) ] ) && ISAVE[ offsetISAVE + ( 2 * strideISAVE ) ] < 5 ) {
+ ISAVE[ offsetISAVE + ( 2 * strideISAVE ) ] += 1;
+ ix = offsetX;
+ for ( i = 0; i < N; i++ ) {
+ X[ ix ] = 0.0;
+ ix += strideX;
+ }
+ X[ offsetX + ( ISAVE[ offsetISAVE + strideISAVE ] * strideX ) ] = 1.0;
+ KASE[ offsetKASE ] = 1;
+ ISAVE[ offsetISAVE ] = 3;
+ return;
+ }
+
+ finalStep( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, offsetISAVE );
+}
+
+/**
+* Final test to refine the current estimate.
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {integer} strideV - stride length for `V`
+* @param {NonNegativeInteger} offsetV - starting index for `V`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {NonNegativeInteger} offsetEST - starting index for `EST`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {integer} strideISAVE - stride length for `ISAVE`
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var X = new Float64Array( [ 3.0, 1.0, -2.0, 4.0 ] );
+* var EST = new Float64Array( [ 1.0 ] );
+* var KASE = new Int32Array( [ 1 ] );
+*
+* isaveIsFive( 4, V, 1, 0, X, 1, 0, EST, 0, KASE, 0 );
+*
+* // EST => [ 2.5 ]
+* // V => [ 3.0, 1.0, -2.0, 4.0 ]
+* // KASE => [ 0 ]
+*/
+function isaveIsFive( N, V, strideV, offsetV, X, strideX, offsetX, EST, offsetEST, KASE, offsetKASE ) {
+ var temp;
+
+ temp = 2.0 * dasum( N, X, strideX, offsetX ) / ( 3 * N );
+ if ( temp > EST[ offsetEST ] ) {
+ dcopy( N, X, strideX, offsetX, V, strideV, offsetV );
+ EST[ offsetEST ] = temp;
+ }
+
+ KASE[ offsetKASE ] = 0;
+}
+
+/**
+* Estimates the one-norm of a square matrix `A`, using reverse communication for evaluating matrix-vector products.
+*
+* ## Notes
+*
+* the reverse communication takes place using `KASE`, it may have any of these values:
+*
+* - `0`: estimation is complete
+* - `1`: caller must compute `A * X` and store the result back in `X`
+* - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+*
+* `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+*
+* `ISAVE` has the following three elements:
+*
+* - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm
+* - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+* - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm
+*
+* @private
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {integer} strideV - stride length for `V`
+* @param {NonNegativeInteger} offsetV - starting index for `V`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param {integer} strideISGN - stride length for `ISGN`
+* @param {NonNegativeInteger} offsetISGN - starting index for `ISGN`
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {NonNegativeInteger} offsetEST - starting index for `EST`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {integer} strideISAVE - stride length for `ISAVE`
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*/
+function dlacn2( N, V, strideV, offsetV, X, strideX, offsetX, ISGN, strideISGN, offsetISGN, EST, offsetEST, KASE, offsetKASE, ISAVE, strideISAVE, offsetISAVE ) {
+ var ix;
+ var i;
+
+ if ( KASE[ offsetKASE ] === 0 ) {
+ ix = offsetX;
+ for ( i = 0; i < N; i++ ) {
+ X[ ix ] = 1 / N;
+ ix += strideX;
+ }
+ KASE[ offsetKASE ] = 1;
+ ISAVE[ offsetISAVE ] = 1;
+ return;
+ }
+
+ if ( ISAVE[ offsetISAVE ] === 1 ) {
+ isaveIsOne( N, V, offsetV, X, strideX, offsetX, ISGN, strideISGN, offsetISGN, EST, offsetEST, KASE, offsetKASE, ISAVE, offsetISAVE );
+ return;
+ }
+
+ if ( ISAVE[ offsetISAVE ] === 2 ) {
+ isaveIsTwo( N, X, strideX, offsetX, KASE, offsetKASE, ISAVE, strideISAVE, offsetISAVE );
+ return;
+ }
+
+ if ( ISAVE[ offsetISAVE ] === 3 ) {
+ isaveIsThree( N, X, strideX, offsetX, V, strideV, offsetV, EST, offsetEST, KASE, offsetKASE, ISGN, strideISGN, offsetISGN, ISAVE, offsetISAVE );
+ return;
+ }
+
+ if ( ISAVE[ offsetISAVE ] === 4 ) {
+ isaveIsFour( N, X, strideX, offsetX, ISAVE, strideISAVE, offsetISAVE, KASE, offsetKASE );
+ return;
+ }
+
+ if ( ISAVE[ offsetISAVE ] === 5 ) {
+ isaveIsFive( N, V, strideV, offsetV, X, strideX, offsetX, EST, offsetEST, KASE, offsetKASE );
+ }
+}
+
+
+// EXPORTS //
+
+module.exports = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/dlacn2.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/dlacn2.js
new file mode 100644
index 000000000000..3d8df2a26706
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/dlacn2.js
@@ -0,0 +1,80 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var base = require( './base.js' );
+
+
+// MAIN //
+
+/**
+* Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+*
+* ## Notes
+*
+* the reverse communication takes place using `KASE`, it may have any of these values:
+*
+* - `0`: estimation is complete
+* - `1`: caller must compute `A * X` and store the result back in `X`
+* - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+*
+* `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+*
+* `ISAVE` has the following three elements:
+*
+* - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm
+* - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+* - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm
+*
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {Int32Array} ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*/
+function dlacn2( N, V, X, ISGN, EST, KASE, ISAVE ) {
+ return base( N, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/index.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/index.js
new file mode 100644
index 000000000000..a819f3650790
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/index.js
@@ -0,0 +1,66 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+/**
+* LAPACK routine to estimate the one-norm of a square matrix `A`, using reverse communication for evaluating matrix-vector products.
+*
+* @module @stdlib/lapack/base/dlacn2
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dlacn2 = require( '@stdlib/lapack/base/dlacn2' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*/
+
+// MODULES //
+
+var join = require( 'path' ).join;
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isError = require( '@stdlib/assert/is-error' );
+var main = require( './main.js' );
+
+
+// MAIN //
+
+var dlacn2;
+var tmp = tryRequire( join( __dirname, './native.js' ) );
+if ( isError( tmp ) ) {
+ dlacn2 = main;
+} else {
+ dlacn2 = tmp;
+}
+
+
+// EXPORTS //
+
+module.exports = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/main.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/main.js
new file mode 100644
index 000000000000..95209612ef75
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/main.js
@@ -0,0 +1,35 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var dlacn2 = require( './dlacn2.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( dlacn2, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/ndarray.js
new file mode 100644
index 000000000000..3506e7f466ab
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/ndarray.js
@@ -0,0 +1,90 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var base = require( './base.js' );
+
+
+// MAIN //
+
+/**
+* Estimates the one-norm of a square matrix `A`, using alternative indexing semantics and reverse communication for evaluating matrix-vector products.
+*
+* ## Notes
+*
+* the reverse communication takes place using `KASE`, it may have any of these values:
+*
+* - `0`: estimation is complete
+* - `1`: caller must compute `A * X` and store the result back in `X`
+* - `2`: caller must compute `A^T * X` (transpose) and store the result back in `X`
+*
+* `V` is over written by `A * W` where `EST` contains `norm( A ) / norm( W )`. (W is not returned)
+*
+* `ISAVE` has the following three elements:
+*
+* - the first indexed element of `ISAVE` is used to determine the control flow for the algorithm.
+* - the second indexed element of `ISAVE` holds the index of the largest absolute value in `X`
+* - the third indexed element of `ISAVE` counts the number of refinement iterations in the algorithm.
+*
+* @param {PositiveInteger} N - number of rows/columns in `A`
+* @param {Float64Array} V - workspace array having `N` indexed elements, used internally to store intermediate vectors
+* @param {integer} strideV - stride length for `V`
+* @param {NonNegativeInteger} offsetV - starting index for `V`
+* @param {Float64Array} X - input/output vector having `N` indexed elements, contains the current or next matrix-vector product
+* @param {integer} strideX - stride length for `X`
+* @param {NonNegativeInteger} offsetX - starting index for `X`
+* @param {Int32Array} ISGN - integer array having `N` indexed elements, stores the sign of each element in `X` during iterations
+* @param {integer} strideISGN - stride length for `ISGN`
+* @param {NonNegativeInteger} offsetISGN - starting index for `ISGN`
+* @param {Float64Array} EST - single-element array, on output, contains the estimated one-norm of the matrix `A`
+* @param {NonNegativeInteger} offsetEST - starting index for `EST`
+* @param {Int32Array} KASE - single-element array that controls the reverse communication.
+* @param {NonNegativeInteger} offsetKASE - starting index for `KASE`
+* @param {Int32Array} ISAVE - integer array having 3 indexed elements, used internally to maintain state across multiple calls
+* @param {integer} strideISAVE - stride length for `ISAVE`
+* @param {NonNegativeInteger} offsetISAVE - starting index for `ISAVE`
+* @returns {void}
+*
+* @example
+* var Int32Array = require( '@stdlib/array/int32' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var V = new Float64Array( [ 5.0, 3.0, 1.0, 5.0 ] );
+* var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ISGN = new Int32Array( [ 1, 1, 1, 1 ] );
+* var EST = new Float64Array( [ 10 ] );
+* var KASE = new Int32Array( [ 1 ] )
+* var ISAVE = new Int32Array( [ 2, 3, 1 ] );
+*
+* dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+* // X => [ 0.0, 0.0, 0.0, 1.0 ]
+* // V => [ 5.0, 3.0, 1.0, 5.0 ]
+* // EST => [ 10.0 ]
+* // KASE => [ 1 ]
+*/
+function dlacn2( N, V, strideV, offsetV, X, strideX, offsetX, ISGN, strideISGN, offsetISGN, EST, offsetEST, KASE, offsetKASE, ISAVE, strideISAVE, offsetISAVE ) { // eslint-disable-line max-len, max-params
+ return base( N, V, strideV, offsetV, X, strideX, offsetX, ISGN, strideISGN, offsetISGN, EST, offsetEST, KASE, offsetKASE, ISAVE, strideISAVE, offsetISAVE ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = dlacn2;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/nint.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/nint.js
new file mode 100644
index 000000000000..2fc213aac233
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/lib/nint.js
@@ -0,0 +1,65 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var floor = require( '@stdlib/math/base/special/floor' );
+var isEven = require( '@stdlib/math/base/assert/is-even' );
+
+
+// MAIN //
+
+/**
+* Rounds X to the nearest integer following Baker's rounding.
+*
+* @private
+* @param {PositiveInteger} X - input number
+* @returns {number} nearest integer
+*
+* @example
+* var out = nint( 4.5 );
+* // returns 4.0
+*/
+function nint( X ) {
+ var frac;
+ var flo;
+
+ flo = floor( X );
+ frac = X - flo;
+
+ if ( frac < 0.5 ) {
+ return flo;
+ }
+
+ if ( frac > 0.5 ) {
+ return flo + 1;
+ }
+
+ if ( isEven( flo ) ) {
+ return flo;
+ }
+
+ return flo + 1;
+}
+
+
+// EXPORTS //
+
+module.exports = nint;
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/package.json b/lib/node_modules/@stdlib/lapack/base/dlacn2/package.json
new file mode 100644
index 000000000000..f56f48336fb9
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/lapack/base/dlacn2",
+ "version": "0.0.0",
+ "description": "LAPACK routine to estimate the one-norm of a square matrix `A`, using reverse communication for evaluating matrix-vector products.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "mathematics",
+ "math",
+ "lapack",
+ "dlacn2",
+ "norm",
+ "linear",
+ "algebra",
+ "subroutines",
+ "array",
+ "ndarray",
+ "matrix",
+ "float64",
+ "double",
+ "float64array"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.dlacn2.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.dlacn2.js
new file mode 100644
index 000000000000..dc7403f190b1
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.dlacn2.js
@@ -0,0 +1,222 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+/* eslint-disable array-element-newline */
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Int32Array = require( '@stdlib/array/int32' );
+var dgemv = require( '@stdlib/blas/base/dgemv' );
+var dcopy = require( '@stdlib/blas/base/dcopy' );
+var dlacn2 = require( './../lib/dlacn2.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dlacn2, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 7', function test( t ) {
+ t.strictEqual( dlacn2.length, 7, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix for N = 1', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array( [ -25.0 ] );
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 1 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 1 );
+ V = new Float64Array( 1 );
+
+ work = new Float64Array( 1 );
+
+ while ( true ) {
+ dlacn2( 1, V, X, ISGN, EST, KASE, ISAVE );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'row-major', 'no-transpose', 1, 1, 1.0, A, 1, X, 1, 0, work, 1 );
+ dcopy( 1, work, 1, X, 1 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'row-major', 'transpose', 1, 1, 1.0, A, 1, X, 1, 0, work, 1 );
+ dcopy( 1, work, 1, X, 1 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 25.0 ] );
+ expectedV = new Float64Array( [ -25.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ 0 ] );
+ expectedISAVE = new Int32Array( [ 1, 0, 0 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'row-major', 'no-transpose', 4, 4, 1.0, A, 4, X, 1, 0, work, 1 );
+ dcopy( 4, work, 1, X, 1 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'row-major', 'transpose', 4, 4, 1.0, A, 4, X, 1, 0, work, 1 );
+ dcopy( 4, work, 1, X, 1 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 12.0 ] );
+ expectedV = new Float64Array( [ -2.0, 4.0, 6.0, 0.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ -1, 1, 1, 1 ] );
+ expectedISAVE = new Int32Array( [ 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, -1.0, 1.0, 1.0,
+ 1.0, -1.0, 1.0, 1.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, X, ISGN, EST, KASE, ISAVE );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'row-major', 'no-transpose', 4, 4, 1.0, A, 4, X, 1, 0, work, 1 );
+ dcopy( 4, work, 1, X, 1 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'row-major', 'transpose', 4, 4, 1.0, A, 4, X, 1, 0, work, 1 );
+ dcopy( 4, work, 1, X, 1 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 22.0 ] );
+ expectedV = new Float64Array( [ 10.0, 10.0, -1.0, -1.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ 1, 1, -1, -1 ] );
+ expectedISAVE = new Int32Array( [ 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.js
new file mode 100644
index 000000000000..112dac9c75b9
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.js
@@ -0,0 +1,82 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var proxyquire = require( 'proxyquire' );
+var IS_BROWSER = require( '@stdlib/assert/is-browser' );
+var dlacn2 = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+ 'skip': IS_BROWSER
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dlacn2, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) {
+ t.strictEqual( typeof dlacn2.ndarray, 'function', 'method is a function' );
+ t.end();
+});
+
+tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) {
+ var dlacn2 = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dlacn2, mock, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return mock;
+ }
+
+ function mock() {
+ // Mock...
+ }
+});
+
+tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) {
+ var dlacn2;
+ var main;
+
+ main = require( './../lib/dlacn2.js' );
+
+ dlacn2 = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dlacn2, main, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return new Error( 'Cannot find module' );
+ }
+});
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.ndarray.js
new file mode 100644
index 000000000000..eba56b468c81
--- /dev/null
+++ b/lib/node_modules/@stdlib/lapack/base/dlacn2/test/test.ndarray.js
@@ -0,0 +1,588 @@
+/**
+* @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.
+*/
+
+'use strict';
+
+/* eslint-disable array-element-newline, max-len */
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Int32Array = require( '@stdlib/array/int32' );
+var dgemv = require( '@stdlib/blas/base/dgemv' ).ndarray;
+var dcopy = require( '@stdlib/blas/base/dcopy' ).ndarray;
+var dlacn2 = require( './../lib/ndarray.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dlacn2, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 17', function test( t ) {
+ t.strictEqual( dlacn2.length, 17, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix for N = 1', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array( [ -25.0 ] );
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 1 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 1 );
+ V = new Float64Array( 1 );
+
+ work = new Float64Array( 1 );
+
+ while ( true ) {
+ dlacn2( 1, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 1, 1, 1.0, A, 1, 1, 0, X, 1, 0, 0, work, 1, 0 );
+ dcopy( 1, work, 1, 0, X, 1, 0 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 1, 1, 1.0, A, 1, 1, 0, X, 1, 0, work, 1 );
+ dcopy( 1, work, 1, X, 0 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 25.0 ] );
+ expectedV = new Float64Array( [ -25.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ 0 ] );
+ expectedISAVE = new Int32Array( [ 1, 0, 0 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 0, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, 1, 0 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 0, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, 1, 0 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 12.0 ] );
+ expectedV = new Float64Array( [ -2.0, 4.0, 6.0, 0.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ -1, 1, 1, 1 ] );
+ expectedISAVE = new Int32Array( [ 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, -1.0, 1.0, 1.0,
+ 1.0, -1.0, 1.0, 1.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, 1, 0, X, 1, 0, ISGN, 1, 0, EST, 0, KASE, 0, ISAVE, 1, 0 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 0, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, 1, 0 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 0, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, 1, 0 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 22.0 ] );
+ expectedV = new Float64Array( [ 10.0, 10.0, -1.0, -1.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ 1, 1, -1, -1 ] );
+ expectedISAVE = new Int32Array( [ 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (offsets)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+ ]);
+
+ KASE = new Int32Array( 2 );
+ EST = new Float64Array( 2 );
+ ISGN = new Int32Array( 5 );
+ ISAVE = new Int32Array( 4 );
+ X = new Float64Array( 5 );
+ V = new Float64Array( 5 );
+
+ work = new Float64Array( 5 );
+
+ while ( true ) {
+ dlacn2( 4, V, 1, 1, X, 1, 1, ISGN, 1, 1, EST, 1, KASE, 1, ISAVE, 1, 1 );
+
+ if ( KASE[ 1 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 1 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 1, 0, work, 1, 1 );
+ dcopy( 4, work, 1, 1, X, 1, 1 );
+ } else if ( KASE[ 1 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 1, 0, work, 1, 1 );
+ dcopy( 4, work, 1, 1, X, 1, 1 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 0.0, 12.0 ] );
+ expectedV = new Float64Array( [ 0.0, -2.0, 4.0, 6.0, 0.0 ] );
+ expectedKASE = new Int32Array( [ 0, 0 ] );
+ expectedISGN = new Int32Array( [ 0, -1, 1, 1, 1 ] );
+ expectedISAVE = new Int32Array( [ 0.0, 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (offsets)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, -1.0, 1.0, 1.0,
+ 1.0, -1.0, 1.0, 1.0
+ ]);
+
+ KASE = new Int32Array( 2 );
+ EST = new Float64Array( 2 );
+ ISGN = new Int32Array( 5 );
+ ISAVE = new Int32Array( 4 );
+ X = new Float64Array( 5 );
+ V = new Float64Array( 5 );
+
+ work = new Float64Array( 5 );
+
+ while ( true ) {
+ dlacn2( 4, V, 1, 1, X, 1, 1, ISGN, 1, 1, EST, 1, KASE, 1, ISAVE, 1, 1 );
+
+ if ( KASE[ 1 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 1 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 1, 0, work, 1, 1 );
+ dcopy( 4, work, 1, 1, X, 1, 1 );
+ } else if ( KASE[ 1 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 1, 1, 0, work, 1, 1 );
+ dcopy( 4, work, 1, 1, X, 1, 1 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 0.0, 22.0 ] );
+ expectedV = new Float64Array( [ 0.0, 10.0, 10.0, -1.0, -1.0 ] );
+ expectedKASE = new Int32Array( [ 0, 0 ] );
+ expectedISGN = new Int32Array( [ 0, 1, 1, -1, -1 ] );
+ expectedISAVE = new Int32Array( [ 0.0, 5, 1, 2 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (negative strides)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, -1, 3, X, -1, 3, ISGN, -1, 3, EST, 0, KASE, 0, ISAVE, -1, 2 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, -1, 3, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, -1, 3 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, -1, 3, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, -1, 3 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 12.0 ] );
+ expectedV = new Float64Array( [ 0, 6, 4, -2 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ 1, 1, 1, -1 ] );
+ expectedISAVE = new Int32Array( [ 2, 1, 5 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (negative strides)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, -1.0, 1.0, 1.0,
+ 1.0, -1.0, 1.0, 1.0
+ ]);
+
+ KASE = new Int32Array( 1 );
+ EST = new Float64Array( 1 );
+ ISGN = new Int32Array( 4 );
+ ISAVE = new Int32Array( 3 );
+ X = new Float64Array( 4 );
+ V = new Float64Array( 4 );
+
+ work = new Float64Array( 4 );
+
+ while ( true ) {
+ dlacn2( 4, V, -1, 3, X, -1, 3, ISGN, -1, 3, EST, 0, KASE, 0, ISAVE, -1, 2 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, -1, 3, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, -1, 3 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, -1, 3, 0, work, 1, 0 );
+ dcopy( 4, work, 1, 0, X, -1, 3 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 22.0 ] );
+ expectedV = new Float64Array( [ -1.0, -1.0, 10.0, 10.0 ] );
+ expectedKASE = new Int32Array( [ 0 ] );
+ expectedISGN = new Int32Array( [ -1, -1, 1, 1 ] );
+ expectedISAVE = new Int32Array( [ 2, 1, 5 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (large strides)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, -2.0, 0.0, 0.0,
+ 3.0, 4.0, -5.0, 0.0,
+ 0.0, 6.0, 7.0, -8.0,
+ 0.0, 0.0, 9.0, 10.0
+ ]);
+
+ KASE = new Int32Array( 2 );
+ EST = new Float64Array( 2 );
+ ISGN = new Int32Array( 8 );
+ ISAVE = new Int32Array( 6 );
+ X = new Float64Array( 8 );
+ V = new Float64Array( 8 );
+
+ work = new Float64Array( 8 );
+
+ while ( true ) {
+ dlacn2( 4, V, 2, 0, X, 2, 0, ISGN, 2, 0, EST, 0, KASE, 0, ISAVE, 2, 0 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 2, 0, 0, work, 2, 0 );
+ dcopy( 4, work, 2, 0, X, 2, 0 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 2, 0, 0, work, 2, 0 );
+ dcopy( 4, work, 2, 0, X, 2, 0 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 12.0, 0.0 ] );
+ expectedV = new Float64Array( [ -2.0, 0.0, 4.0, 0.0, 6.0, 0.0, 0.0, 0.0 ] );
+ expectedKASE = new Int32Array( [ 0, 0 ] );
+ expectedISGN = new Int32Array( [ -1, 0, 1, 0, 1, 0, 1, 0 ] );
+ expectedISAVE = new Int32Array( [ 5, 0, 1, 0, 2, 0 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns expected values when calculating the one-norm of a square matrix (large strides)', function test( t ) {
+ var expectedISAVE;
+ var expectedKASE;
+ var expectedISGN;
+ var expectedEST;
+ var expectedV;
+ var ISAVE;
+ var KASE;
+ var ISGN;
+ var work;
+ var EST;
+ var X;
+ var V;
+ var A;
+
+ A = new Float64Array([
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, 10.0, 0.0, 0.0,
+ 1.0, -1.0, 1.0, 1.0,
+ 1.0, -1.0, 1.0, 1.0
+ ]);
+
+ KASE = new Int32Array( 2 );
+ EST = new Float64Array( 2 );
+ ISGN = new Int32Array( 8 );
+ ISAVE = new Int32Array( 6 );
+ X = new Float64Array( 8 );
+ V = new Float64Array( 8 );
+
+ work = new Float64Array( 8 );
+
+ while ( true ) {
+ dlacn2( 4, V, 2, 0, X, 2, 0, ISGN, 2, 0, EST, 0, KASE, 0, ISAVE, 2, 0 );
+
+ if ( KASE[ 0 ] === 0 ) {
+ break;
+ }
+ else if ( KASE[ 0 ] === 1 ) {
+ dgemv( 'no-transpose', 4, 4, 1.0, A, 4, 1, 0, X, 2, 0, 0, work, 2, 0 );
+ dcopy( 4, work, 2, 0, X, 2, 0 );
+ } else if ( KASE[ 0 ] === 2 ) {
+ dgemv( 'transpose', 4, 4, 1.0, A, 4, 1, 0, X, 2, 0, 0, work, 2, 0 );
+ dcopy( 4, work, 2, 0, X, 2, 0 );
+ }
+ }
+
+ expectedEST = new Float64Array( [ 22.0, 0.0 ] );
+ expectedV = new Float64Array( [ 10.0, 0.0, 10.0, 0.0, -1.0, 0.0, -1.0, 0.0 ] );
+ expectedKASE = new Int32Array( [ 0, 0 ] );
+ expectedISGN = new Int32Array( [ 1, 0, 1, 0, -1, 0, -1, 0 ] );
+ expectedISAVE = new Int32Array( [ 5, 0, 1, 0, 2, 0 ] );
+
+ t.deepEqual( KASE, expectedKASE, 'returns expected value' );
+ t.deepEqual( ISGN, expectedISGN, 'returns expected value' );
+ t.deepEqual( EST, expectedEST, 'returns expected value' );
+ t.deepEqual( V, expectedV, 'returns expected value' );
+ t.deepEqual( ISAVE, expectedISAVE, 'returns expected value' );
+
+ t.end();
+});