在numpy中,數組可能具有包含字段的數據類型,類似於電子表格中的列。一個例子是[(a, int), (b, float)]
,其中數組中的每個條目都是一對(int,float)。通常,這些屬性是使用字典查找(例如,arr['a'] and arr['b']
。
記錄數組允許使用以下方式將字段作為數組的成員進行訪問arr.a and arr.b
。 numpy.recarray.argpartition()函數返回將對該數組進行分區的索引。
用法: numpy.recarray.argpartition(kth, axis=-1, kind='introselect', order=None)
參數:
kth :[int或int序列]分區依據的元素索引。
axis :[int或None]要排序的軸。如果為None,則在排序之前將數組展平。默認值為-1,它沿著最後一個軸排序。
kind :選擇算法。默認值為“ introselect”。
order :[str或str的列表]當arr是定義了字段的數組時,此參數指定要比較第一個,第二個等的字段。
Return :[index_array,ndarray]沿指定軸劃分arr的索引數組。
代碼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)
輸出:
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]]
代碼2:
我們正在申請numpy.recarray.argpartition()
整個記錄數組。
# 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)
輸出:
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]]
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注:本文由純淨天空篩選整理自jana_sayantan大神的英文原創作品 Numpy recarray.argpartition() function | Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。