apply-parallel

apply_parallel

skimage.util.apply_parallel(function, array, chunks=None, depth=0, mode=None, extra_arguments=(), extra_keywords={}) [source]

Map a function in parallel across an array.

Split an array into possibly overlapping chunks of a given depth and boundary type, call the given function in parallel on the chunks, combine the chunks and return the resulting array.

Parameters:

function : function Function to be mapped which takes an array as an argument. array : numpy array Array which the function will be applied to. chunks : int, tuple, or tuple of tuples, optional A single integer is interpreted as the length of one side of a square chunk that should be tiled across the array. One tuple of length array.ndim represents the shape of a chunk, and it is tiled across the array. A list of tuples of length ndim, where each sub-tuple is a sequence of chunk sizes along the corresponding dimension. If None, the array is broken up into chunks based on the number of available cpus. More information about chunks is in the documentation here. depth : int, optional Integer equal to the depth of the added boundary cells. Defaults to zero. mode : {‘reflect’, ‘symmetric’, ‘periodic’, ‘wrap’, ‘nearest’, ‘edge’}, optional type of external boundary padding. extra_arguments : tuple, optional Tuple of arguments to be passed to the function. extra_keywords : dictionary, optional Dictionary of keyword arguments to be passed to the function.

Notes

Numpy edge modes ‘symmetric’, ‘wrap’, and ‘edge’ are converted to the equivalent dask boundary modes ‘reflect’, ‘periodic’ and ‘nearest’, respectively.