If x is an array, make a copy and shuffle the elements randomly. If x is an integer, randomly permute np.arange (x). It's correct because for the final b b = b] = iįor any i in. Randomly permute a sequence, or return a permuted range. You an check a = a]Ī function to compute the inverse is def inverse_permutation(a): If x is a multi-dimensional array, it is only shuffled along its first.
It's easy to see the composition of a and b is a in numpy notation. Randomly permute a sequence, or return a permuted range. Numpy library has a sub-module called random, which is used to generate random numbers for a given distribution. With output which maps 0 -> 2, 1->8, etc. axisint, optional Slices of x in this axis are shuffled. Returns outndarray Permuted sequence or array range. axisint, optional The axis which x is shuffled along. Parameters xint or arraylike If x is an integer, randomly permute np.arange (x).
Parameters xarraylike, at least one-dimensional Array to be shuffled. Randomly permute a sequence, or return a permuted range. Unlike shuffle, each slice along the given axis is shuffled independently of the others.
In numpy we can generate such permutation by shuffling (the identity map). method (x, axisNone, outNone) Randomly permute x along axis axis. Say the set contains n elements and labeled from 0 to n-1, we can denote a permutation by a length n array a with unique elements in such that a is the result of i. By permutation, we mean a one to one and onto map from a finite set to itself.
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