Numpy maskearray . STD()函数| Python
原文:https://www . geeksforgeeks . org/numpy-masked array-STD-function-python/
numpy.MaskedArray.std()
功能用于计算沿指定轴的标准偏差。这里屏蔽的条目被忽略。默认情况下,计算展平数组的标准偏差,否则计算指定轴的标准偏差。
语法:
numpy.ma.std(arr, axis=None, dtype=None, out=None, ddof=0, keepdims=False)
参数:
arr:【ndarray】输入屏蔽数组。 轴:【int,可选】计算标准差的轴。 数据类型:【数据类型,可选】返回数组的类型,以及元素相乘的累加器的类型。 out:【n 数组,可选】存储结果的位置。 - >如果提供,它必须具有输入广播到的形状。 - >如果未提供或无,则返回新分配的阵列。 ddof:【int,可选】“δ自由度”:计算中使用的除数为 N–ddof,其中 N 代表元素个数。默认情况下,ddof 为零。 保持尺寸:【布尔,可选】如果设置为真,减少的轴将作为尺寸为 1 的尺寸留在结果中。使用此选项,结果将根据输入数组正确广播。
Return:【standard _ variation _ long _ axis,ndarray】除非指定 out,否则将返回一个保存结果的新数组,在这种情况下,将返回对 out 的引用。
代码#1 :
# Python program explaining
# numpy.MaskedArray.std() 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], [ 5, -3]])
print ("Input array : ", in_arr)
# Now we are creating a masked array.
# by making entry as invalid.
mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]])
print ("Masked array : ", mask_arr)
# applying MaskedArray.std
# methods to masked array
out_arr = ma.std(mask_arr)
print ("standard deviation of masked array along default axis : ", out_arr)
Output:
Input array : [[ 1 2]
[ 3 -1]
[ 5 -3]]
Masked array : [[-- 2]
[-- -1]
[5 -3]]
standard deviation of masked array along default axis : 3.031088913245535
代码#2 :
# Python program explaining
# numpy.MaskedArray.std() 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, 0, 3], [ 4, 1, 6]])
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 =[[ 0, 0, 0], [ 0, 0, 1]])
print ("Masked array : ", mask_arr)
# applying MaskedArray.std methods
# to masked array
out_arr1 = ma.std(mask_arr, axis = 0)
print ("standard deviation of masked array along 0 axis : ", out_arr1)
out_arr2 = ma.std(mask_arr, axis = 1)
print ("standard deviation of masked array along 1 axis : ", out_arr2)
Output:
Input array : [[1 0 3]
[4 1 6]]
Masked array : [[1 0 3]
[4 1 --]]
standard deviation of masked array along 0 axis : [1.5 0.5 0.0]
standard deviation of masked array along 1 axis : [1.247219128924647 1.5]