问题描述
所以我有一个数组，例如[-0.7, -3.7, -2.1, -5.8, -1.2 ]这些特定的数字对应于按顺序排列的标签:比如0.7对应于标签201，3.7对应于标签202，依此类推.
So I have an array for example [-0.7, -3.7, -2.1, -5.8, -1.2 ]and these particular numbers correspond to labels which are in order: say 0.7 corresponds to label 201, 3.7 to label 202 and so on.
在对它们进行正常排序时，我收到了[-5.8，-3.7，-2.1，-1.2，-0.7].我有兴趣从中挑选出前三个值，但在排序时，我会失去对标签的跟踪.现在要对它们进行排序，请使用 np.argsort .这给了我[1,2,0].这告诉我4的值具有较低的概率，而0的值具有较高的概率.
On sorting them normally, I receive [-5.8, -3.7, -2.1, -1.2, -0.7]. I am interested in picking out the top 3 values out of these but on sorting, I would lose track of the labels.Now to sort them in order I use np.argsort. This gives me [1,2,0]. This tells me the value with 4 has a low probability while the one with 0 has a high probability.
我的问题是关于argsort的，我该如何找回映射?我怎么知道我的标签现在在哪里?使用argsort时是否可以跟踪它们?
My question is with argsort, how can I get my mappings back? How can I tell where my labels are now? Is there a way I can keep a track of them while using argsort?
推荐答案
这会复制并使用内置的排序方法，但我认为它可以实现您想要的.
This makes a copy and uses the built-in sorted method, but I think it achieves what you want.
vals = [-0.7, -3.7, -2.1, -5.8, -1.2 ]
label_inds_vals = sorted([thing for thing in enumerate(vals)], key=lambda x: x[1])
排序后的值还带有索引，可用于在标签数组中为其对应的标签建立索引.
The sorted values also come with indices that you can use to index their corresponding label in the label array.
如果列表列表:
value_lists = [[-0.7，-3.2，-2.1，-5.8，-1.2]，[-1.2，-3.2，-3.4，-5.4，-6.4]]
value_lists = [[-0.7, -3.2, -2.1, -5.8, -1.2], [-1.2, -3.2, -3.4, -5.4, -6.4]]
for vals in value_lists:
#reverse depending if you want top 3 or bottom
label_inds_vals = sorted([thing for thing in enumerate(vals)], key=lambda x: x[1], reverse = True)
print label_inds_vals[:3]
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