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本文小編為大家詳細(xì)介紹“如何獲取numpy的array中前N個(gè)最大值”,內(nèi)容詳細(xì),步驟清晰,細(xì)節(jié)處理妥當(dāng),希望這篇“如何獲取numpy的array中前N個(gè)最大值”文章能幫助大家解決疑惑,下面跟著小編的思路慢慢深入,一起來(lái)學(xué)習(xí)新知識(shí)吧。
numpy.argsort(a, axis=-1, kind='quicksort', order=None) ''' Returns the indices that would sort an array. Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order. ''' Parameters: a : array_like Array to sort. axis : int or None, optional Axis along which to sort. The default is -1 (the last axis). If None, the flattened array is used. kind : {‘quicksort', ‘mergesort', ‘heapsort', ‘stable'}, optional Sorting algorithm. order : str or list of str, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties. Returns: index_array : ndarray, int Array of indices that sort a along the specified axis. If a is one-dimensional, a[index_array] yields a sorted a. More generally, np.take_along_axis(a, index_array, axis=a) always yields the sorted a, irrespective of dimensionality.
import numpy as np top_k=3 arr = np.array([1, 3, 2, 4, 5]) top_k_idx=arr.argsort()[::-1][0:top_k] print(top_k_idx) #[4 3 1]
補(bǔ)充:python topN / topK 取 最大的N個(gè)數(shù) 或 最小的N個(gè)數(shù)
import numpy as np a = np.array([1,4,3,5,2]) b = np.argsort(a) print(b)
print結(jié)果[0 4 2 1 3]
說(shuō)明a[0]最小,a[3]最大
a[0]<a[4]<a[2]<a[1]<a[3]
補(bǔ)充:利用Python獲取數(shù)組或列表中最大的N個(gè)數(shù)及其索引
import heapq a=[43,5,65,4,5,8,87] re1 = heapq.nlargest(3, a) #求最大的三個(gè)元素,并排序 re2 = map(a.index, heapq.nlargest(3, a)) #求最大的三個(gè)索引 nsmallest與nlargest相反,求最小 print(re1) print(list(re2)) #因?yàn)閞e2由map()生成的不是list,直接print不出來(lái),添加list()就行了
結(jié)果:
re1:[87, 65, 43]
re2:[6, 2, 0]
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