time-to-botec

Benchmark sampling in different programming languages
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      1 
      2 {{alias}}( N, correction, x, stride )
      3     Computes the variance of a single-precision floating-point strided array
      4     ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and
      5     Cramer.
      6 
      7     The `N` and `stride` parameters determine which elements in `x` are accessed
      8     at runtime.
      9 
     10     Indexing is relative to the first index. To introduce an offset, use a typed
     11     array view.
     12 
     13     If `N <= 0`, the function returns `NaN`.
     14 
     15     If every indexed element is `NaN`, the function returns `NaN`.
     16 
     17     Parameters
     18     ----------
     19     N: integer
     20         Number of indexed elements.
     21 
     22     correction: number
     23         Degrees of freedom adjustment. Setting this parameter to a value other
     24         than `0` has the effect of adjusting the divisor during the calculation
     25         of the variance according to `n - c` where `c` corresponds to the
     26         provided degrees of freedom adjustment and `n` corresponds to the number
     27         of non-`NaN` indexed elements. When computing the variance of a
     28         population, setting this parameter to `0` is the standard choice (i.e.,
     29         the provided array contains data constituting an entire population).
     30         When computing the unbiased sample variance, setting this parameter to
     31         `1` is the standard choice (i.e., the provided array contains data
     32         sampled from a larger population; this is commonly referred to as
     33         Bessel's correction).
     34 
     35     x: Float32Array
     36         Input array.
     37 
     38     stride: integer
     39         Index increment.
     40 
     41     Returns
     42     -------
     43     out: number
     44         The variance.
     45 
     46     Examples
     47     --------
     48     // Standard Usage:
     49     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] );
     50     > {{alias}}( x.length, 1, x, 1 )
     51     ~4.3333
     52 
     53     // Using `N` and `stride` parameters:
     54     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
     55     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
     56     > {{alias}}( N, 1, x, 2 )
     57     ~4.3333
     58 
     59     // Using view offsets:
     60     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     61     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     62     > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
     63     > {{alias}}( N, 1, x1, 2 )
     64     ~4.3333
     65 
     66 {{alias}}.ndarray( N, correction, x, stride, offset )
     67     Computes the variance of a single-precision floating-point strided array
     68     ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and
     69     Cramer and alternative indexing semantics.
     70 
     71     While typed array views mandate a view offset based on the underlying
     72     buffer, the `offset` parameter supports indexing semantics based on a
     73     starting index.
     74 
     75     Parameters
     76     ----------
     77     N: integer
     78         Number of indexed elements.
     79 
     80     correction: number
     81         Degrees of freedom adjustment. Setting this parameter to a value other
     82         than `0` has the effect of adjusting the divisor during the calculation
     83         of the variance according to `n - c` where `c` corresponds to the
     84         provided degrees of freedom adjustment and `n` corresponds to the number
     85         of non-`NaN` indexed elements. When computing the variance of a
     86         population, setting this parameter to `0` is the standard choice (i.e.,
     87         the provided array contains data constituting an entire population).
     88         When computing the unbiased sample variance, setting this parameter to
     89         `1` is the standard choice (i.e., the provided array contains data
     90         sampled from a larger population; this is commonly referred to as
     91         Bessel's correction).
     92 
     93     x: Float32Array
     94         Input array.
     95 
     96     stride: integer
     97         Index increment.
     98 
     99     offset: integer
    100         Starting index.
    101 
    102     Returns
    103     -------
    104     out: number
    105         The variance.
    106 
    107     Examples
    108     --------
    109     // Standard Usage:
    110     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] );
    111     > {{alias}}.ndarray( x.length, 1, x, 1, 0 )
    112     ~4.3333
    113 
    114     // Using offset parameter:
    115     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
    116     > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
    117     > {{alias}}.ndarray( N, 1, x, 2, 1 )
    118     ~4.3333
    119 
    120     See Also
    121     --------
    122