Python Numpy recarray.argpartition()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.argpartition()函数返回将分割该数组的索引。
语法: numpy.recarray.argpartition(kth, axis=-1, kind='introselect', order=None)
参数:
kth : [int or sequence of ints ] 要分区的元素索引。
axis : [int or None] 用于排序的轴。如果没有,数组在排序前会被压扁。默认为-1,沿最后一个轴进行排序。
kind:选择算法。默认为’introselect’。
order : [str or list of str] 当arr是一个定义了字段的数组时,这个参数指定了哪些字段要首先比较,其次,等等。
返回 : [index_array, ndarray] 沿指定轴线分割Arr的索引数组。
代码#1:
# Python program explaining
# numpy.recarray.argpartition() 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), (6.0, 9)],
[(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.argpartition methods
# to float record array along axis 1
out_arr = geek.recarray.argpartition(rec_arr.a, kth = 1, axis = 1)
print ("Output partitioned array indices along axis 1: ", out_arr)
# applying recarray.argpartition methods
# to int record array along axis 0
out_arr = geek.recarray.argpartition(rec_arr.b, kth = 1, axis = 0)
print ("Output partitioned array indices array along axis 0: ", out_arr)
输出:
Input array : [[(5.0, 2) (3.0, -4) (6.0, 9)]
[(9.0, 1) (5.0, 4) (-12.0, -7)]]
Record array of float: [[ 5. 3. 6.]
[ 9. 5. -12.]]
Record array of int: [[ 2 -4 9]
[ 1 4 -7]]
Output partitioned array indices along axis 1: [[1 0 2]
[2 1 0]]
Output partitioned array indices array along axis 0: [[1 0 1]
[0 1 0]]
代码#2:
我们正在将numpy.recarray.argpartition()应用于整个记录数组。
# Python program explaining
# numpy.recarray.argpartition() 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), (6.0, -7)],
[(9.0, 1), (6.0, 4), (-2.0, -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)
# applying recarray.argpartition methods to record array
out_arr = geek.recarray.argpartition(rec_arr, kth = 2)
print ("Output array : ", out_arr)
输出:
Input array : [[(5.0, 2) (3.0, 4) (6.0, -7)]
[(9.0, 1) (6.0, 4) (-2.0, -7)]]
Output array : [[1 0 2]
[2 1 0]]