time-to-botec

Benchmark sampling in different programming languages
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repl.txt (1301B)


      1 
      2 {{alias}}( x, y[, options] )
      3     Two-dimensional kernel density estimation.
      4 
      5     Parameters
      6     ----------
      7     x: Array<number>
      8         Array of x values.
      9 
     10     y: Array<number>
     11         Array of y values.
     12 
     13     options: Object (optional)
     14         Function options.
     15 
     16     options.h: number (optional)
     17         Array of length two containing the bandwidth values for x and y.
     18 
     19     options.n: number (optional)
     20         Number of partitions on the x- and y-axes. Default: `25`.
     21 
     22     options.xMin: number (optional)
     23         Lower limit of x.
     24 
     25     options.xMax: number (optional)
     26         Upper limit of x.
     27 
     28     options.yMin: number (optional)
     29         Lower limit of y.
     30 
     31     options.yMax: number (optional)
     32         Upper limit of y.
     33 
     34     options.kernel: string|Function
     35         A string or function to specifying the used kernel function. Default:
     36         `'gaussian'`.
     37 
     38     Returns
     39     -------
     40     out: Object
     41         Object containing the density estimates (`z`) along grid points (`x` and
     42         `y` values).
     43 
     44     Examples
     45     --------
     46     > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];
     47     > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];
     48     > var out = {{alias}}( x, y )
     49     { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }
     50 
     51     See Also
     52     --------
     53