time-to-botec

Benchmark sampling in different programming languages
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      1 
      2 {{alias}}( N, correction, x, stride )
      3     Computes the standard deviation of a strided array ignoring `NaN` values and
      4     using a one-pass algorithm proposed by Youngs and Cramer.
      5 
      6     The `N` and `stride` parameters determine which elements in `x` are accessed
      7     at runtime.
      8 
      9     Indexing is relative to the first index. To introduce an offset, use a typed
     10     array view.
     11 
     12     If `N <= 0`, the function returns `NaN`.
     13 
     14     If every indexed element is `NaN`, the function returns `NaN`.
     15 
     16     Parameters
     17     ----------
     18     N: integer
     19         Number of indexed elements.
     20 
     21     correction: number
     22         Degrees of freedom adjustment. Setting this parameter to a value other
     23         than `0` has the effect of adjusting the divisor during the calculation
     24         of the standard deviation according to `N - c` where `c` corresponds to
     25         the provided degrees of freedom adjustment. When computing the standard
     26         deviation of a population, setting this parameter to `0` is the standard
     27         choice (i.e., the provided array contains data constituting an entire
     28         population). When computing the corrected sample standard deviation,
     29         setting this parameter to `1` is the standard choice (i.e., the provided
     30         array contains data sampled from a larger population; this is commonly
     31         referred to as Bessel's correction).
     32 
     33     x: Array<number>|TypedArray
     34         Input array.
     35 
     36     stride: integer
     37         Index increment.
     38 
     39     Returns
     40     -------
     41     out: number
     42         The standard deviation.
     43 
     44     Examples
     45     --------
     46     // Standard Usage:
     47     > var x = [ 1.0, -2.0, NaN, 2.0 ];
     48     > {{alias}}( x.length, 1, x, 1 )
     49     ~2.0817
     50 
     51     // Using `N` and `stride` parameters:
     52     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
     53     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
     54     > {{alias}}( N, 1, x, 2 )
     55     ~2.0817
     56 
     57     // Using view offsets:
     58     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     59     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     60     > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
     61     > {{alias}}( N, 1, x1, 2 )
     62     ~2.0817
     63 
     64 {{alias}}.ndarray( N, correction, x, stride, offset )
     65     Computes the standard deviation of a strided array ignoring `NaN` values and
     66     using a one-pass algorithm proposed by Youngs and Cramer and alternative
     67     indexing semantics.
     68 
     69     While typed array views mandate a view offset based on the underlying
     70     buffer, the `offset` parameter supports indexing semantics based on a
     71     starting index.
     72 
     73     Parameters
     74     ----------
     75     N: integer
     76         Number of indexed elements.
     77 
     78     correction: number
     79         Degrees of freedom adjustment. Setting this parameter to a value other
     80         than `0` has the effect of adjusting the divisor during the calculation
     81         of the standard deviation according to `N - c` where `c` corresponds to
     82         the provided degrees of freedom adjustment. When computing the standard
     83         deviation of a population, setting this parameter to `0` is the standard
     84         choice (i.e., the provided array contains data constituting an entire
     85         population). When computing the corrected sample standard deviation,
     86         setting this parameter to `1` is the standard choice (i.e., the provided
     87         array contains data sampled from a larger population; this is commonly
     88         referred to as Bessel's correction).
     89 
     90     x: Array<number>|TypedArray
     91         Input array.
     92 
     93     stride: integer
     94         Index increment.
     95 
     96     offset: integer
     97         Starting index.
     98 
     99     Returns
    100     -------
    101     out: number
    102         The standard deviation.
    103 
    104     Examples
    105     --------
    106     // Standard Usage:
    107     > var x = [ 1.0, -2.0, NaN, 2.0 ];
    108     > {{alias}}.ndarray( x.length, 1, x, 1, 0 )
    109     ~2.0817
    110 
    111     // Using offset parameter:
    112     > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];
    113     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
    114     > {{alias}}.ndarray( N, 1, x, 2, 1 )
    115     ~2.0817
    116 
    117     See Also
    118     --------
    119