numpy.nanargmin(array，axis = None)：返回忽略NaN的特定轴上数组的min元素的索引。
如果切片仅包含NaN和Inf，则结果将不可信任。
参数：
array : Input array to work on axis : [int, optional]Along a specified axis like 0 or 1
返回：
Array of indices into the array with same shape as array.shape. with the dimension along axis removed.
代码1：
# Python Program illustrating
# working of nanargmin()
import numpy as geek
# Working on 1D array
array = [geek.nan, 4, 2, 3, 1]
print("INPUT ARRAY 1 : \n", array)
array2 = geek.array([[geek.nan, 4], [1, 3]])
# returning Indices of the min element
# as per the indices ingnoring NaN
print("\nIndices of min in array1 : ", geek.nanargmin(array))
# Working on 2D array
print("\nINPUT ARRAY 2 : \n", array2)
print("\nIndices of min in array2 : ", geek.nanargmin(array2))
print("\nIndices at axis 1 of array2 : ", geek.nanargmin(array2, axis = 1))输出：
INPUT ARRAY 1 : [nan, 4, 2, 3, 1] Indices of min in array1 : 4 INPUT ARRAY 2 : [[ nan 4.] [ 1. 3.]] Indices of min in array2 : 2 Indices at axis 1 of array2 : [1 0]
代码2：比较argmin和nanargmin的工作
# Python Program illustarting
# working of nanargmin()
import numpy as geek
# Working on 2D array
array = ( [[ 8, 13, 5, 0],
[ geek.nan, geek.nan, 5, 3],
[10, 7, 15, 15],
[3, 11, 4, 12]])
print("INPUT ARRAY : \n", array)
# returning Indices of the min element
# as per the indices
'''
[[ 8 13 5 0]
[ 0 2 5 3]
[10 7 15 15]
[ 3 11 4 12]]
^ ^ ^ ^
0 2 4 0 - element
1 1 3 0 - indices
'''
print("\nIndices of min using argmin : ", geek.argmin(array, axis = 0))
print("\nIndices of min using nanargmin : : ", geek.nanargmin(array, axis = 0))输出：
INPUT ARRAY : [[ 8 13 5 0] [ 0 2 5 3] [10 7 15 15] [ 3 11 4 12]] Indices of min element : [1 1 3 0]
参考文献：
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.nanargmin.html
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注：本文由纯净天空筛选整理自 numpy.nanargmin() in 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。