通过x步骤在numpy数组中滚动每列的最有效方法

Question

我有一个2D数组，可以保存数据，如下图所示。 每列需要与列的索引卷起相同的步骤数。我怎么能最理想地做到这一点？我正在考虑一个for循环，我迭代列，由i滚动它们，然后将数组的列应用于此滚动结果。

有更有效的方法吗？

Answer 1

您可以像这样使用重塑：

>>> a = np.r_[np.tril(np.random.randint(1, 10, (10, 10))), np.random.randint(1, 10, (5, 10))]
>>> a
array([[7, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [9, 4, 0, 0, 0, 0, 0, 0, 0, 0],
       [5, 3, 6, 0, 0, 0, 0, 0, 0, 0],
       [7, 2, 8, 2, 0, 0, 0, 0, 0, 0],
       [6, 1, 3, 6, 5, 0, 0, 0, 0, 0],
       [7, 4, 1, 2, 9, 8, 0, 0, 0, 0],
       [2, 9, 7, 3, 7, 7, 4, 0, 0, 0],
       [2, 4, 2, 9, 1, 6, 8, 8, 0, 0],
       [8, 5, 4, 5, 2, 6, 5, 5, 8, 0],
       [9, 3, 4, 6, 1, 4, 8, 3, 9, 1],
       [3, 7, 7, 7, 3, 7, 9, 8, 2, 1],
       [8, 1, 2, 6, 3, 1, 4, 8, 7, 8],
       [5, 8, 4, 6, 1, 1, 9, 7, 5, 6],
       [7, 3, 9, 9, 1, 1, 3, 4, 8, 1],
       [4, 7, 7, 5, 7, 9, 4, 8, 2, 7]])
>>> 
>>> m, n = a.shape
>>> buffer = np.zeros((m+1, n), dtype=a.dtype, order='F')
>>> buffer.ravel(order='F')[:m*n].reshape(m, n, order='F')[...] = a
>>> result = buffer[:-1]
>>> result
array([[7, 4, 6, 2, 5, 8, 4, 8, 8, 1],
       [9, 3, 8, 6, 9, 7, 8, 5, 9, 1],
       [5, 2, 3, 2, 7, 6, 5, 3, 2, 8],
       [7, 1, 1, 3, 1, 6, 8, 8, 7, 6],
       [6, 4, 7, 9, 2, 4, 9, 8, 5, 1],
       [7, 9, 2, 5, 1, 7, 4, 7, 8, 7],
       [2, 4, 4, 6, 3, 1, 9, 4, 2, 0],
       [2, 5, 4, 7, 3, 1, 3, 8, 0, 0],
       [8, 3, 7, 6, 1, 1, 4, 0, 0, 0],
       [9, 7, 2, 6, 1, 9, 0, 0, 0, 0],
       [3, 1, 4, 9, 7, 0, 0, 0, 0, 0],
       [8, 8, 9, 5, 0, 0, 0, 0, 0, 0],
       [5, 3, 7, 0, 0, 0, 0, 0, 0, 0],
       [7, 7, 0, 0, 0, 0, 0, 0, 0, 0],
       [4, 0, 0, 0, 0, 0, 0, 0, 0, 0]])