96 lines
2.5 KiB
Plaintext
96 lines
2.5 KiB
Plaintext
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{{alias}}( N, x, stride )
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Computes the arithmetic mean of a double-precision floating-point strided
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array using an improved Kahan–Babuška algorithm.
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The `N` and `stride` parameters determine which elements in `x` are accessed
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at runtime.
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Indexing is relative to the first index. To introduce an offset, use a typed
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array view.
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If `N <= 0`, the function returns `NaN`.
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Parameters
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----------
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N: integer
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Number of indexed elements.
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x: Float64Array
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Input array.
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stride: integer
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Index increment.
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Returns
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-------
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out: number
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The arithmetic mean.
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Examples
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--------
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// Standard Usage:
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> var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
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> {{alias}}( x.length, x, 1 )
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~0.3333
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// Using `N` and `stride` parameters:
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> x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> var stride = 2;
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> {{alias}}( N, x, stride )
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~0.3333
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// Using view offsets:
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> var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
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> var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
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> N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
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> stride = 2;
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> {{alias}}( N, x1, stride )
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~-0.3333
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{{alias}}.ndarray( N, x, stride, offset )
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Computes the arithmetic mean of a double-precision floating-point strided
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array using an improved Kahan–Babuška algorithm and alternative indexing
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semantics.
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While typed array views mandate a view offset based on the underlying
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buffer, the `offset` parameter supports indexing semantics based on a
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starting index.
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Parameters
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----------
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N: integer
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Number of indexed elements.
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x: Float64Array
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Input array.
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stride: integer
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Index increment.
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offset: integer
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Starting index.
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Returns
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-------
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out: number
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The arithmetic mean.
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Examples
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--------
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// Standard Usage:
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> var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
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> {{alias}}.ndarray( x.length, x, 1, 0 )
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~0.3333
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// Using offset parameter:
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> var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> {{alias}}.ndarray( N, x, 2, 1 )
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~-0.3333
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See Also
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--------
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