dlassq

Return an updated sum of squares represented in scaled form.

This routine returns the values $s_{textrm{out}}$ and $\textrm{ss}_{\textrm{out}}$ such that

where $x_i = X_{(i-1) \cdot \textrm{sx}}$ and $\textrm{sx}$ is the stride of X. The value of $\textrm{ss}_{\textrm{in}}$ is assumed to be nonnegative.

Usage

var dlassq = require( '@stdlib/lapack/base/dlassq' );

dlassq( N, X, strideX, scale, sumsq )

Returns an updated sum of squares represented in scaled form.

var Float64Array = require( '@stdlib/array/float64' );

var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

var out = dlassq( 4, X, 1, 1.0, 0.0 );
// returns <Float64Array>[ 1.0, 30.0 ]

The function has the following parameters:

• N: number of indexed elements.
• X: input Float64Array.
• strideX: stride length for X.
• scale: scaling factor.
• sumsq: basic sum of squares from which output is factored out.

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Float64Array = require( '@stdlib/array/float64' );

// Initial array:
var X0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );

// Create an offset view:
var X1 = new Float64Array( X0.buffer, X0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Compute the sum of squares:
var out = dlassq( X1.length, X1, 1, 1.0, 0.0 );
// returns <Float64Array>[ 1.0, 30.0 ]

The returned Float64Array contains an updated scale factor and an updated sum of squares, respectively.

dlassq.ndarray( N, X, sx, ox, scale, sumsq, out, so, oo )

Returns an updated sum of squares represented in scaled form using alternative indexing semantics.

var Float64Array = require( '@stdlib/array/float64' );

var X = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var out = new Float64Array( [ 0.0, 0.0 ] );

dlassq.ndarray( 4, X, 1, 0, 1.0, 0.0, out, 1, 0 );
// out => <Float64Array>[ 1.0, 30.0 ]

The function has the following additional parameters:

• ox: starting index for X.
• out: output Float64Array.
• so: stride length for out.
• oo: starting index for out.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,

var Float64Array = require( '@stdlib/array/float64' );

var X = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0 ] );
var out = new Float64Array( [ 0.0, 0.0, 999.9, 0.0, 999.9 ] );

dlassq.ndarray( 4, X, 2, 0, 1.0, 0.0, out, 2, 1 );
// out => <Float64Array>[ 0.0, 1.0, 999.9, 30.0, 999.9 ]

Notes

• dlassq() corresponds to the LAPACK function dlassq.

Examples

var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var dlassq = require( '@stdlib/lapack/base/dlassq' );

var X = discreteUniform( 10, -10, 10, {
    'dtype': 'float64'
});
console.log( X );

var out = dlassq( X.length, X, 1, 1.0, 0.0 );
console.log( out );

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C APIs

Usage

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Examples

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