📜  numpy recarray.any()函数| Python

📅  最后修改于: 2022-05-13 01:54:48.214000             🧑  作者: Mango

numpy recarray.any()函数| Python

在 numpy 中,数组可能具有包含字段的数据类型,类似于电子表格中的列。一个例子是[(a, int), (b, float)] ,其中数组中的每个条目都是一对 (int, float)。通常,使用诸如arr['a'] and arr['b']类的字典查找来访问这些属性。
记录数组允许使用arr.a and arr.b作为数组成员访问字段。如果记录数组中的任何元素评估为 True, numpy.recarray.any()函数将返回 True。

代码#1:

# Python program explaining
# numpy.recarray.any() method 
  
# importing numpy as geek
import numpy as geek
  
# creating input array with 2 different field 
in_arr = geek.array([(5.0, 2), (3.0, 4)], 
       dtype =[('a', float), ('b', int)])
print ("Input array : ", in_arr)
   
# convert it to a record array, using arr.view(np.recarray)
rec_arr = in_arr.view(geek.recarray)
print("Record array of float: ", rec_arr.a)
  
# applying recarray.any methods to float record array
out_arr = geek.recarray.any(rec_arr.a)
print ("Output array: ", out_arr) 
  
print("\nRecord array of int: ", rec_arr.b)
# applying recarray.any methods
# to int record array
out_arr = geek.recarray.any(rec_arr.b)
print ("Output array: ", out_arr) 
输出:
Input array :  [(5.0, 2) (3.0, 4)]
Record array of float:  [ 5.  3.]
Output array:  True

Record array of int:  [2 4]
Output array:  True

代码#2:

如果我们将numpy.recarray.any()应用于整个记录数组,则会出现类型错误,因为数组是灵活或混合类型。

# Python program explaining
# numpy.recarray.any() method 
  
# importing numpy as geek
import numpy as geek
  
# creating input array with 2 different field 
in_arr = geek.array([(5.0, 2), (3.0, 4)],
         dtype =[('a', float), ('b', int)])
print ("Input array : ", in_arr) 
  
# convert it to a record array,
# using arr.view(np.recarray)
rec_arr = in_arr.view(geek.recarray)
print("Record array ", rec_arr)
  
# applying recarray.any methods to  record array
out_arr = geek.recarray.any(rec_arr)
print ("Output array: ", out_arr)  
输出:
TypeError: cannot perform reduce with flexible type