Python Numpy recarray.mean()函数

Python Numpy recarray.mean()函数

在numpy中,数组可以有一个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是一对(int, float)。通常情况下,这些属性使用字典查询,如arr[‘a’] 和 arr[‘b’] 。记录数组允许字段作为数组的成员被访问,使用arr.a和arr.b。

numpy.recarray.mean()函数返回沿给定轴的数组元素的平均值。

语法: numpy.recarray.mean(axis=None, dtype=None, out=None, keepdims=False)

参数:
axis : [None or int or tuple of ints, optional] 用于操作的一个或多个坐标轴。默认情况下,使用扁平化的输入。
dtype : [data-type, optional] 计算平均值时我们希望的类型。
out : [ndarray, optional] 一个储存结果的位置。
-> 如果提供,它必须有一个输入广播到的形状。
-> 如果没有提供或没有,将返回一个新分配的数组。
keepdims : [bool, optional] 如果设置为True,被缩小的轴将作为尺寸为1的尺寸留在结果中。

返回: [ndarray or scalar] 数组的算术平均数(如果没有轴,则为标量值)或沿指定轴的平均值的数组。

代码#1:

# Python program explaining
# numpy.recarray.mean() 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, 6), (6.0, 10)],
                     [(9.0, 1), (5.0, 4), (-12.0, 7)]],
                     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.mean methods
# to float record array along default axis 
# i, e along flattened array
out_arr1 = rec_arr.a.mean()
# Mean of the flattened array 
print("\nMean of float record array, axis = None : ", out_arr1) 
  
  
# applying recarray.mean methods
# to float record array along axis 0
# i, e along vertical
out_arr2 = rec_arr.a.mean(axis = 0)
# Mean along 0 axis
print("\nMean of float record array, axis = 0 : ", out_arr2)
  
  
# applying recarray.mean methods
# to float record array along axis 1
# i, e along horizontal
out_arr3 = rec_arr.a.mean(axis = 1)
# Mean along 0 axis
print("\nMean of float record array, axis = 1 : ", out_arr3)
  
  
# applying recarray.mean methods
# to int record array along default axis 
# i, e along flattened array
out_arr4 = rec_arr.b.mean(dtype ='int')
# Mean of the flattened array 
print("\nMean of int record array, axis = None : ", out_arr4) 
  
  
# applying recarray.mean methods
# to int record array along axis 0
# i, e along vertical
out_arr5 = rec_arr.b.mean(axis = 0)
# Mean along 0 axis
print("\nMean of int record array, axis = 0 : ", out_arr5)
  
  
# applying recarray.mean methods
# to int record array along axis 1
# i, e along horizontal
out_arr6 = rec_arr.b.mean(axis = 1)
# Mean along 0 axis
print("\nMean of int record array, axis = 1 : ", out_arr6)

输出:

Input array :  [[(  5.,  2) (  3.,  6) (  6., 10)]
 [(  9.,  1) (  5.,  4) (-12.,  7)]]
Record array of float:  [[  5.   3.   6.]
 [  9.   5. -12.]]
Record array of int:  [[ 2  6 10]
 [ 1  4  7]]

Mean of float record array, axis = None :  2.6666666666666665

Mean of float record array, axis = 0 :  [ 7.  4. -3.]

Mean of float record array, axis = 1 :  [4.66666667 0.66666667]

Mean of int record array, axis = None :  5

Mean of int record array, axis = 0 :  [1.5 5.  8.5]

Mean of int record array, axis = 1 :  [6. 4.]

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