Numpy usage tips: array filtering instance code, numpy usage tips

Numpy usage tips: array filtering instance code, numpy usage tips

This article focuses on the array filtering related to numpy usage techniques, as detailed below.

When Boolean array B is used as the subscript to access elements in array x, all elements in array x corresponding to the subscript True in array B are collected. The array obtained using a Boolean array as the subscript does not share data space with the original array. Note that this method only corresponds to a Boolean array (array) and does not support a Boolean list (list ).

>>> X = np. arange (5, 0,-1) >>> xarray ([5, 4, 3, 2, 1]) >>> x [np. array ([True, False, True, False, False])] >>> # obtain the subscript True. The element 0, 2 in the Boolean array is True, therefore, we can obtain the array ([5, 3])> x [[True, False, True, False, False] element with the lower mark 0, 2 in x. # Error, this is not the expected result >>> # if it is a Boolean list, True is treated as 1, False is treated as 0, and the element array ([4, 5, 5, 4, 5, 5]) >>> x [np. array ([True, False, True, True])] >>> # When the length of a Boolean array is insufficient, all the insufficient parts are treated as Falsearray ([5, 3, 2]) >>> x [np. array ([True, False, True, True])] =-1,-2, -3 # modify only the elements whose subscript is True >># the Boolean array subscript can also be used to modify the element >>> xarray ([-1, 4,-2,-3, 1])

Note: Boolean arrays are generally not produced manually. We usually use a Boolean expression, for example:

>>> X = np. random. rand (10) # generate an array of random numbers with a length of 10 and an element value of 0-1> xarray ([0.72223939, 0.921226, 0.7770805, 0.2055047, 0.17567449, 0.95799412, 0.12015178, 0.7627083, 0.43260184, 0.91379859]) >>>> x> 0.5 >>># compare the size of each element in array x with 0.5 to obtain a Boolean array, true indicates that the value of x is greater than 0.5 array ([True, False, False, True, False], dtype = bool) >>> x [x> 0.5] # x> 0.5 is a Boolean array >>## use the Boolean array returned by x> 0.5 to collect elements in x, the result is an array of all elements greater than 0.5 in array x ([0.72223939, 0.921226, 0.7770805, 0.95799412, 0.7627083, 0.91379859]).

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