使用 numpy 对数组进行排序

Question

我想更改

中列元素的顺序

a = np.asarray(
[[0,1,1,2,2,2,2,3,3,3,4,4,4,4,4,4],
 [4,0,3,0,1,2,5,1,2,5,3,4,6,6,7,7],
 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
 [0,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1]]
)

基于第 1-3 行的值（从 0 开始）。我的解决方案目前如下所示：

a[:, a.transpose()[:, 1].argsort(axis=0)]

array([[1, 2, 2, 3, 2, 3, 1, 4, 0, 4, 2, 3, 4, 4, 4, 4],
       [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1]])

很好，除了我还想在搜索中包括第 2-3 行（按字典顺序）。理想情况下，我希望最后一行是 [0, 1, 0, 1, ..., 0, 1] 的结果（也应考虑充满零的第二行，但在本例中它包含相同的值）。

Answer 1

你需要numpy.lexsort，相当于argsort但是基于多个排序键；给定多个数组，它 returns 对数组进行排序的索引：

Given multiple sorting keys, which can be interpreted as columns in a spreadsheet, lexsort returns an array of integer indices that describes the sort order by multiple columns. The last key in the sequence is used for the primary sort order, the second-to-last key for the secondary sort order, and so on. The keys argument must be a sequence of objects that can be converted to arrays of the same shape. If a 2D array is provided for the keys argument, it’s rows are interpreted as the sorting keys and sorting is according to the last row, second last row etc.

a[:, np.lexsort(a[:0:-1])]
#array([[2, 1, 3, 2, 3, 2, 1, 4, 0, 4, 3, 2, 4, 4, 4, 4],
#       [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7],
#       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
#       [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1]])

使用 numpy 对数组进行排序

Sorting array with numpy

python

sorting

numpy

lexicographic