numpy.MaskedArray.reshape()函數用於在不更改其數據的情況下為掩碼數組賦予新的形狀,它返回包含相同數據但具有新形狀的掩碼數組。結果是原始數組的視圖;如果這不可能,則會引發ValueError。
用法: numpy.ma.reshape(shape, order)
參數:
shape:[int或int元組]新形狀應與原始形狀兼容。
order : [“ C”,“ F”,“ A”,“ K”,可選)默認情況下,使用“ C”索引順序。
->使用此索引順序讀取a的元素。
->'C'表示以C-like順序索引元素,最後一個軸索引更改最快,回到第一個軸索引更改最快。
->“ F”表示以Fortran-like索引順序索引元素,第一個索引更改最快,最後一個索引更改最慢。
->'A'表示如果m在內存中是連續的,則以Fortran-like索引順序讀取元素,否則以C-like順序讀取元素。
->“ K”表示按順序在內存中讀取元素,但當步幅為負時反轉數據。
返回:[reshaped_array]陣列上的新視圖。
代碼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)
輸出:
Input array : [ 1 2 3 -1] Masked array : [-- 2 -- -1] Output 2D masked array : [[-- 2] [-- -1]]
代碼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)
輸出:
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:本文由純淨天空篩選整理自jana_sayantan大神的英文原創作品 Numpy MaskedArray.reshape() function | Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。