time-to-botec

Benchmark sampling in different programming languages
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      1 
      2 {{alias}}( N, sum, x, strideX, y, strideY )
      3     Computes the cumulative sum of strided array elements.
      4 
      5     The `N` and `stride` parameters determine which elements in `x` and `y` are
      6     accessed at runtime.
      7 
      8     Indexing is relative to the first index. To introduce an offset, use a typed
      9     array view.
     10 
     11     If `N <= 0`, the function returns `y` unchanged.
     12 
     13     Parameters
     14     ----------
     15     N: integer
     16         Number of indexed elements.
     17 
     18     sum: number
     19         Initial sum.
     20 
     21     x: Array<number>|TypedArray
     22         Input array.
     23 
     24     strideX: integer
     25         Index increment for `x`.
     26 
     27     y: Array<number>|TypedArray
     28         Output array.
     29 
     30     strideY: integer
     31         Index increment for `y`.
     32 
     33     Returns
     34     -------
     35     out: Array<number>|TypedArray
     36         Output array.
     37 
     38     Examples
     39     --------
     40     // Standard Usage:
     41     > var x = [ 1.0, -2.0, 2.0 ];
     42     > var y = [ 0.0, 0.0, 0.0 ];
     43     > {{alias}}( x.length, 0.0, x, 1, y, 1 )
     44     [ 1.0, -1.0, 1.0 ]
     45 
     46     // Using `N` and `stride` parameters:
     47     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
     48     > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
     49     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
     50     > {{alias}}( N, 0.0, x, 2, y, 2 )
     51     [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]
     52 
     53     // Using view offsets:
     54     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     55     > var y0 = new {{alias:@stdlib/array/float64}}( x0.length );
     56     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     57     > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );
     58     > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
     59     > {{alias}}( N, 0.0, x1, 2, y1, 1 )
     60     <Float64Array>[ -2.0, 0.0, -1.0 ]
     61     > y0
     62     <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]
     63 
     64 {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )
     65     Computes the cumulative sum of strided array elements using alternative
     66     indexing semantics.
     67 
     68     While typed array views mandate a view offset based on the underlying
     69     buffer, the `offset` parameter supports indexing semantics based on a
     70     starting index.
     71 
     72     Parameters
     73     ----------
     74     N: integer
     75         Number of indexed elements.
     76 
     77     sum: number
     78         Initial sum.
     79 
     80     x: Array<number>|TypedArray
     81         Input array.
     82 
     83     strideX: integer
     84         Index increment for `x`.
     85 
     86     offsetX: integer
     87         Starting index for `x`.
     88 
     89     y: Array<number>|TypedArray
     90         Output array.
     91 
     92     strideY: integer
     93         Index increment for `y`.
     94 
     95     offsetY: integer
     96         Starting index for `y`.
     97 
     98     Returns
     99     -------
    100     out: Array<number>|TypedArray
    101         Output array.
    102 
    103     Examples
    104     --------
    105     // Standard Usage:
    106     > var x = [ 1.0, -2.0, 2.0 ];
    107     > var y = [ 0.0, 0.0, 0.0 ];
    108     > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )
    109     <Float64Array>[ 1.0, -1.0, 1.0 ]
    110 
    111     // Advanced indexing:
    112     > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];
    113     > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
    114     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
    115     > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )
    116     <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]
    117 
    118     See Also
    119     --------
    120