cunumeric.percentile#

Compute the q-th percentile of the data along the specified axis.

Parameters:

a (array_like) – Input array or object that can be converted to an array.
q (array_like of float) – Percentile or sequence of percentiles to compute, which must be between 0 and 100 inclusive.
axis ({int, tuple of int, None}, optional) – Axis or axes along which the percentiles are computed. The default is to compute the percentile(s) along a flattened version of the array.
out (ndarray, optional) – Alternative output array in which to place the result. It must have the same shape as the expected output.
overwrite_input (bool, optional) – If True, then allow the input array a to be modified by intermediate calculations, to save memory. In this case, the contents of the input a after this function completes is undefined.
method (str, optional) – This parameter specifies the method to use for estimating the percentile. The options sorted by their R type as summarized in the H&F paper [1] are: 1. ‘inverted_cdf’ 2. ‘averaged_inverted_cdf’ 3. ‘closest_observation’ 4. ‘interpolated_inverted_cdf’ 5. ‘hazen’ 6. ‘weibull’ 7. ‘linear’ (default) 8. ‘median_unbiased’ 9. ‘normal_unbiased’ The first three methods are discontinuous. NumPy further defines the following discontinuous variations of the default ‘linear’ (7.) option: * ‘lower’ * ‘higher’, * ‘midpoint’ * ‘nearest’
keepdims (bool, optional) – If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original array a.

Returns:

percentile – If q is a single percentile and axis=None, then the result is a scalar. If multiple percentiles are given, first axis of the result corresponds to the percentiles. The other axes are the axes that remain after the reduction of a. If the input contains integers or floats smaller than float64, the output data-type is float64. Otherwise, the output data-type is the same as that of the input. If out is specified, that array is returned instead.

Return type:

scalar or ndarray

Raises:

TypeError – If the type of the input is complex.