numpy recarray.all()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。如果记录数组中的所有元素评估为 True， numpy.recarray.all()函数将返回 True。

Syntax : numpy.recarray.all(axis=None, out=None, keepdims=False)

Parameters:
axis : [ None or int or tuple of ints, optional] Axis or axes along which a logical AND reduction is performed.
out : [ndarray, optional] A location into which the result is stored.
  -> If provided, it must have a shape that the inputs broadcast to.
  -> If not provided or None, a freshly-allocated array is returned.
keepdims : [ bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
If the default value is passed, then keepdims will not be passed through to all method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method does not implement keepdims any exceptions will be raised.

Returns : [ndarray, bool] It returns True if all elements evaluate to True.

代码#1：

# Python program explaining
# numpy.recarray.all() 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)
print("Record array of int: ", rec_arr.b)
  
# applying recarray.all methods to float record array
out_arr = geek.recarray.all(rec_arr.a)
print ("Output array: ", out_arr) 
  
# applying recarray.all methods to int record array
out_arr = geek.recarray.all(rec_arr.b)
print ("Output array: ", out_arr) 

输出：

Input array :  [(5.0, 2) (3.0, 4)]
Record array of float:  [ 5.  3.]
Record array of int:  [2 4]
Output array:  True
Output array:  True

代码#2：

如果我们将numpy.recarray.all()应用于整个记录数组，则会Type error ，因为数组是灵活或混合类型。

# Python program explaining
# numpy.recarray.all() 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.all methods to  record array
out_arr = geek.recarray.all(rec_arr)
print ("Output array: ", out_arr)  

输出：

TypeError: cannot perform reduce with flexible type