极客教程使用Python中的NumPy，用大的有限数代替无穷大，并为复杂的输入值填充NaN
在这篇文章中，我们将介绍如何在Python中使用NumPy为复杂的输入值和大的有限数填充Nan。
示例:
输入: [complex(np.nan,np.inf)]
输出: [1000.+1.79769313e+308j]
解释：用复数值代替Nan，用大的有限值代替无限值。
numpy.nan_to_num 方法
numpy.nan_to_num方法用于用0替换Nan值，用用户定义的值或大正数填充正无穷和负无穷的值。 neginf是用于此目的的关键词。
语法: numpy.nan_to_num(arr, copy=True)
参数:
- arr: [array_like] 输入数据。
- copy: [bool, optional] 默认为True。
返回：新的数组，其形状与arr相同，并且Arr中元素的dtype精度最高。
示例 1:
在这个例子中，使用numpy.array()方法创建了一个数组，它由np.nan和正无穷组成。数组的形状、数据类型和尺寸可以通过.shape, .dtype , 和 .ndim属性找到。这里，使用nan参数将np.nan替换为1000，而n infinity则替换为一个大的有限数。
# import package
import numpy as np
# Creating an array of imaginary numbers
array = np.array([complex(np.nan,np.inf)])
print(array)
# shape of the array is
print("Shape of the array is : ",array.shape)
# dimension of the array
print("The dimension of the array is : ",array.ndim)
# Datatype of the array
print("Datatype of our Array is : ",array.dtype)
# np.nan is replaced with 1000 and
# infinity is replaced with a large positive number
print("After replacement the array is : ",
np.nan_to_num(array,nan= 1000))
输出:
[nan+infj]
Shape of the array is : (1,)
The dimension of the array is : 1
Datatype of our Array is : complex128
After replacement the array is : [1000.+1.79769313e+308j]
示例 2:
在这个例子中，正无穷被替换为一个用户定义的值。
# import package
import numpy as np
# Creating an array of imaginary numbers
array = np.array([complex(np.nan,np.inf)])
print(array)
# shape of the array is
print("Shape of the array is : ",array.shape)
# dimension of the array
print("The dimension of the array is : ",array.ndim)
# Datatype of the array
print("Datatype of our Array is : ",array.dtype)
# np.nan is replaced with 1000 and
# infinity is replaced with a large positive number
print("After replacement the array is : ",
np.nan_to_num(array,nan= 1000))
输出:
[nan+infj]
Shape of the array is : (1,)
The dimension of the array is : 1
Datatype of our Array is : complex128
After replacement the array is : [1000.+99999.j]