Numpy MaskedArray.atleast_2d()函数| Python
numpy.MaskedArray.atleast_2d()
函数用于将输入转换为具有至少二维的掩码数组。标量和一维数组转换为二维数组,同时保留高维输入。
Syntax : numpy.ma.atleast_2d(*arys)
Parameters:
arys:[ array_like] One or more input arrays.
Return : [ ndarray] An array, or list of arrays, each with arr.ndim >= 2
代码#1:
# Python program explaining
# numpy.MaskedArray.atleast_2d() method
# importing numpy as geek
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
# creating input arrays
in_arr1 = geek.array([ 3, -1, 5, -3])
print ("1st Input array : ", in_arr1)
in_arr2 = geek.array(2)
print ("2nd Input array : ", in_arr2)
# Now we are creating masked array.
# by making entry as invalid.
mask_arr1 = ma.masked_array(in_arr1, mask =[ 1, 0, 1, 0])
print ("1st Masked array : ", mask_arr1)
mask_arr2 = ma.masked_array(in_arr2, mask = 0)
print ("2nd Masked array : ", mask_arr2)
# applying MaskedArray.atleast_2d methods
# to masked array
out_arr = ma.atleast_2d(mask_arr1, mask_arr2)
print ("Output masked array : ", out_arr)
输出:
1st Input array : [ 3 -1 5 -3]
2nd Input array : 2
1st Masked array : [-- -1 -- -3]
2nd Masked array : 2
Output masked array : [masked_array(data=[[--, -1, --, -3]],
mask=[[ True, False, True, False]],
fill_value=999999), masked_array(data=[[2]],
mask=[[False]],
fill_value=999999)]
代码#2:
# Python program explaining
# numpy.MaskedArray.atleast_2d() 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.atleast_2d methods
# to masked array
out_arr = ma.atleast_2d(mask_arr)
print ("Output 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 masked array : [[[-- 3e-05]]
[[-45.0 200000.0]]]