格式化多维数组 Python

2022-01-15 00:00:00 python numpy indexing arrays format

问题描述

如何编写代码，在出现负值后立即将多维数组 a 中每个单独数组的值更改为零.因此，a 中的第二个数组的负值 [12,34,5,6,88,-10,30,75] 为 -10，它会将所有该值和紧随其后的值为零.将数组转换为 [12,34,5,6,88,0,0,0].我怎样才能获得预期的输出?

How can I write a code that changes the values of each individual arrays within the multidimensional array a to zeroes right after there was a negative value. So the second array within a has a negative value [12,34,5,6,88,-10,30,75] of -10 that would turn all the values of that and the values right after it to zeroes. Turning the array into [12,34,5,6,88,0,0,0]. How would I be able to get my Expected Output?

import numpy as np 

a = np.array([[12,45,50,60,30],
             [12,34,5,6,88,-10,30,75],
             [3,45,332,45,-12,-4,-64,12],
             [12,45,3,22,323]])

预期输出:

[[12,45,50,60,30],
 [12,34,5,6,88,0,0,0],
 [3,45,332,45,0,0,0,0],
 [12,45,3,22,323]]

解决方案

试试这个:

import numpy as np 

a = np.array([[12,45,50,60,30],
             [12,34,5,6,88,-10,30,75],
             [3,45,332,45,-12,-4,-64,12],
             [12,45,3,22,323]], dtype='object')


for l in a:
    for i in l:
        if i<0:
            l[l.index(i):] = [0] * len(l[l.index(i):])
            
a

输出:

array([list([12, 45, 50, 60, 30]), list([12, 34, 5, 6, 88, 0, 0, 0]),
       list([3, 45, 332, 45, 0, 0, 0, 0]), list([12, 45, 3, 22, 323])],
      dtype=object)

第二种解决方案:

import numpy as np 

def neg_to_zero(l):
    for i in l:
        if i<0:
            l[l.index(i):] = [0] * len(l[l.index(i):])

a = np.array([[12,45,50,60,30],
             [12,34,5,6,88,-10,30,75],
             [3,45,332,45,-12,-4,-64,12],
             [12,45,3,22,323]], dtype='object')

list(map(neg_to_zero, a))

a

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