numpy.MaskedArray.reshape()函数用于在不更改其数据的情况下为掩码数组赋予新的形状,它返回包含相同数据但具有新形状的掩码数组。结果是原始数组的视图;如果这不可能,则会引发ValueError。
用法: numpy.ma.reshape(shape, order)
参数:
shape:[int或int元组]新形状应与原始形状兼容。
order : [“ C”,“ F”,“ A”,“ K”,可选)默认情况下,使用“ C”索引顺序。
->使用此索引顺序读取a的元素。
->'C'表示以C-like顺序索引元素,最后一个轴索引更改最快,回到第一个轴索引更改最快。
->“ F”表示以Fortran-like索引顺序索引元素,第一个索引更改最快,最后一个索引更改最慢。
->'A'表示如果m在内存中是连续的,则以Fortran-like索引顺序读取元素,否则以C-like顺序读取元素。
->“ K”表示按顺序在内存中读取元素,但当步幅为负时反转数据。
返回:[reshaped_array]阵列上的新视图。
代码1:
# Python program explaining
# numpy.MaskedArray.reshape() method
# importing numpy as geek
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
# creating input array
in_arr = geek.array([1, 2, 3, -1])
print ("Input array : ", in_arr)
# Now we are creating a masked array.
# by making third entry as invalid.
mask_arr = ma.masked_array(in_arr, mask =[1, 0, 1, 0])
print ("Masked array : ", mask_arr)
# applying MaskedArray.reshape methods to make
# it a 2d masked array
out_arr = mask_arr.reshape(2, 2)
print ("Output 2D masked array : ", out_arr)
输出:
Input array : [ 1 2 3 -1] Masked array : [-- 2 -- -1] Output 2D masked array : [[-- 2] [-- -1]]
代码2:
# Python program explaining
# numpy.MaskedArray.reshape() method
# importing numpy as geek
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
# creating input array
in_arr = geek.array([[[ 2e8, 3e-5]], [[ -45.0, 2e5]]])
print ("Input array : ", in_arr)
# Now we are creating a masked array.
# by making one entry as invalid.
mask_arr = ma.masked_array(in_arr, mask =[[[ 1, 0]], [[ 0, 0]]])
print ("3D Masked array : ", mask_arr)
# applying MaskedArray.reshape methods to make
# it a 2d masked array
out_arr = mask_arr.reshape(1, 4)
print ("Output 2D masked array : ", out_arr)
print()
# applying MaskedArray.reshape methods to make
# it a 1d masked array
out_arr = mask_arr.reshape(4, )
print ("Output 1D masked array : ", out_arr)
输出:
Input array : [[[ 2.0e+08 3.0e-05]] [[-4.5e+01 2.0e+05]]] 3D Masked array : [[[-- 3e-05]] [[-45.0 200000.0]]] Output 2D masked array : [[-- 3e-05 -45.0 200000.0]] Output 1D masked array : [-- 3e-05 -45.0 200000.0]
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注:本文由纯净天空筛选整理自jana_sayantan大神的英文原创作品 Numpy MaskedArray.reshape() function | Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。