计算给定 NumPy 数组沿第二个轴的最大值和最小值之间的差
让我们看看如何计算给定 NumPy 数组沿第二个轴的最大值和最小值之间的差。在这里,第二个轴表示逐行。
因此,首先要在 NumPy 数组中查找逐行的最大和最小元素,我们分别使用 NumPy 库的numpy.amax()和numpy.amin()函数。然后之后我们简单地对其进行减法运算。
numpy.amax():此函数返回数组的最大值或沿轴的最大值(如果提到)。
Syntax: numpy.amax(arr, axis = None, out = None, keepdims = )
numpy.amin():此函数返回数组的最小值或沿轴的最小值(如果提到)。
Syntax: numpy.amin(arr, axis = None, out = None, keepdims = )
现在,让我们看一个例子:
示例 1:
Python3
# import library
import numpy as np
# create a numpy 2d-array
x = np.array([[100, 20, 305],
[ 200, 40, 300]])
print("given array:\n", x)
# get maximum element row
# wise from numpy array
max1 = np.amax(x ,1)
# get minimum element row
# wise from numpy array
min1 = np.amin(x, 1)
# print the row-wise max
# and min difference
print("difference:\n", max1 - min1)
Python3
# import library
import numpy as np
# list
x = [12, 13, 14, 15, 16]
y = [17, 18, 19, 20, 21]
# create a numpy 2d-array
array = np.array([x, y]).reshape((2, 5))
print("original array:\n", array)
# find max and min elements
# row-wise
max1, min1 = np.amax(array, 1), np.amin(array,1)
# print the row-wise max
# and min difference
print("Difference:\n", max1 - min1)
输出:
given array:
[[100 20 305]
[200 40 300]]
difference:
[285 260]
示例 2:
Python3
# import library
import numpy as np
# list
x = [12, 13, 14, 15, 16]
y = [17, 18, 19, 20, 21]
# create a numpy 2d-array
array = np.array([x, y]).reshape((2, 5))
print("original array:\n", array)
# find max and min elements
# row-wise
max1, min1 = np.amax(array, 1), np.amin(array,1)
# print the row-wise max
# and min difference
print("Difference:\n", max1 - min1)
输出:
original array:
[[12 13 14 15 16]
[17 18 19 20 21]]
Difference:
[4 4]