time-to-botec/js/node_modules/@stdlib/math/strided/special/dmskabs/docs/repl.txt
NunoSempere b6addc7f05 feat: add the node modules
Necessary in order to clearly see the squiggle hotwiring.
2022-12-03 12:44:49 +00:00

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{{alias}}( N, x, sx, m, sm, y, sy )
Computes the absolute value for each element in a double-precision floating-
point strided array `x` according to a strided mask array and assigns the
results to elements in a double-precision floating-point strided array `y`.
The `N` and stride parameters determine which strided array elements are
accessed at runtime.
Indexing is relative to the first index. To introduce an offset, use typed
array views.
Parameters
----------
N: integer
Number of indexed elements.
x: Float64Array
Input array.
sx: integer
Index increment for `x`.
m: Uint8Array
Mask array.
sm: integer
Index increment for `m`.
y: Float64Array
Destination array.
sy: integer
Index increment for `y`.
Returns
-------
y: Float64Array
Input array `y`.
Examples
--------
// Standard usage:
> var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, -3.0, -5.0 ] );
> var m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] );
> var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] );
> {{alias}}( x.length, x, 1, m, 1, y, 1 )
<Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]
// Using `N` and stride parameters:
> y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] );
> {{alias}}( 2, x, 2, m, 2, y, -1 )
<Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]
// Using view offsets:
> var x0 = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, -3.0, -5.0 ] );
> var m0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] );
> var y0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] );
> var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
> var m1 = new {{alias:@stdlib/array/uint8}}( m0.buffer, m0.BYTES_PER_ELEMENT*1 );
> var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 );
> {{alias}}( 2, x1, -2, m1, -2, y1, 1 )
<Float64Array>[ 5.0, 1.0 ]
> y0
<Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]
{{alias}}.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )
Computes the absolute value for each element in a double-precision floating-
point strided array `x` according to a strided mask array and assigns the
results to elements in a double-precision floating-point strided array `y`
using alternative indexing semantics.
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 indexed elements.
x: Float64Array
Input array.
sx: integer
Index increment for `x`.
ox: integer
Starting index for `x`.
m: Float64Array
Mask array.
sm: integer
Index increment for `m`.
om: integer
Starting index for `m`.
y: Float64Array
Destination array.
sy: integer
Index increment for `y`.
oy: integer
Starting index for `y`.
Returns
-------
y: Float64Array
Input array `y`.
Examples
--------
// Standard usage:
> var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, -3.0, -5.0 ] );
> var m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] );
> var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] );
> {{alias}}.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )
<Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]
// Advanced indexing:
> x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, -3.0, -5.0 ] );
> m = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 1, 0 ] );
> y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] );
> {{alias}}.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )
<Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]
See Also
--------