time-to-botec/js/node_modules/@stdlib/blas/base/dasum/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, stride )
Computes the sum of the absolute values.
The sum of absolute values corresponds to the *L1* norm.
The `N` and `stride` parameters determine which elements in `x` are used to
compute the sum.
Indexing is relative to the first index. To introduce an offset, use typed
array views.
If `N` or `stride` is less than or equal to `0`, the function returns `0`.
Parameters
----------
N: integer
Number of elements to sum.
x: Float64Array
Input array.
stride: integer
Index increment.
Returns
-------
sum: number
Sum of absolute values.
Examples
--------
// Standard usage:
> var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );
> var sum = {{alias}}( x.length, x, 1 )
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// Sum every other value:
> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
> var stride = 2;
> sum = {{alias}}( N, x, stride )
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// Use view offset; e.g., starting at 2nd element:
> var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
> var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
> N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
> sum = {{alias}}( N, x1, stride )
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{{alias}}.ndarray( N, x, stride, offset )
Computes the sum of absolute values using alternative indexing semantics.
While typed array views mandate a view offset based on the underlying
buffer, the `offset` parameter supports indexing semantics based on a
starting index.
Parameters
----------
N: integer
Number of elements to sum.
x: Float64Array
Input array.
stride: integer
Index increment.
offset: integer
Starting index.
Returns
-------
sum: number
Sum of absolute values.
Examples
--------
// Standard usage:
> var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );
> var sum = {{alias}}.ndarray( x.length, x, 1, 0 )
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// Sum the last three elements:
> x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
> sum = {{alias}}.ndarray( 3, x, -1, x.length-1 )
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See Also
--------