numpy.nanmax()
函数用于返回数组的最大值或沿数组的任何特定提到的轴,而忽略任何Nan值。
用法:numpy.nanmax(arr, axis=None, out=None, keepdims = no value)
参数:
arr :输入数组。
axis :我们想要最大值的轴。否则,它将认为arr是平坦的(在所有轴上均有效)axis = 0表示沿列
并且axis = 1表示沿行加工。
out :我们要在其中放置结果的另一个数组。数组必须具有与预期输出相同的尺寸。
keepdims :如果将其设置为True,则缩小的轴将保留为尺寸1的尺寸。使用此选项,结果将相对于原始a正确广播。
返回:最大数组值(如果轴为空则为标量值)或沿指定轴具有最大值的数组。
代码1:工作
# Python Program illustrating
# numpy.nanmax() method
import numpy as np
# 1D array
arr = [1, 2, 7, 0, np.nan]
print("arr : ", arr)
print("max of arr : ", np.amax(arr))
# nanmax ignores NaN values.
print("nanmax of arr : ", np.nanmax(arr))
输出:
arr : [1, 2, 7, 0, nan]
max of arr : nan
nanmax of arr : 7.0
代码2:
import numpy as np
# 2D array
arr = [[np.nan, 17, 12, 33, 44],
[15, 6, 27, 8, 19]]
print("\narr : \n", arr)
# maximum of the flattened array
print("\nmax of arr, axis = None : ", np.nanmax(arr))
# maximum along the first axis
# axis 0 means vertical
print("max of arr, axis = 0 : ", np.nanmax(arr, axis = 0))
# maximum along the second axis
# axis 1 means horizontal
print("max of arr, axis = 1 : ", np.nanmax(arr, axis = 1))
输出:
arr : [[nan, 17, 12, 33, 44], [15, 6, 27, 8, 19]] max of arr, axis = None : 44.0 max of arr, axis = 0 : [15. 17. 27. 33. 44.] max of arr, axis = 1 : [44. 27.]
代码3:
import numpy as np
arr1 = np.arange(5)
print("Initial arr1 : ", arr1)
# using out parameter
np.nanmax(arr, axis = 0, out = arr1)
print("Changed arr1(having results) : ", arr1)
输出:
Initial arr1 : [0 1 2 3 4] Changed arr1(having results) : [15 17 27 33 44]
相关用法
注:本文由纯净天空筛选整理自Mohit Gupta_OMG 大神的英文原创作品 np.nanmax() 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。