A.两个参数解决方案（两列输出）
您可以使用生成这些索引，
np.indices然后通过转置和重塑来完成工作-
np.indices((32,30)).T.reshape(-1,2)
样本输出-
In [36]: np.indices((32,30)).T.reshape(-1,2)Out[36]: array([[ 0, 0], [ 1, 0], [ 2, 0], ..., [29, 29], [30, 29], [31, 29]])
运行时测试-
In [74]: points = [32,30]# @218's solnIn [75]: %timeit np.transpose(np.nonzero(np.ones(points[::-1])))[:,::-1]100000 loops, best of 3: 18.6 µs per loopIn [76]: %timeit np.indices((points)).T.reshape(-1,2)100000 loops, best of 3: 16.1 µs per loopIn [77]: points = [320,300]# @218's solnIn [78]: %timeit np.transpose(np.nonzero(np.ones(points[::-1])))[:,::-1]100 loops, best of 3: 2.14 ms per loopIn [79]: %timeit np.indices((points)).T.reshape(-1,2)1000 loops, best of 3: 1.26 ms per loop
进一步提升性能
我们可以通过使用
pointswith翻转，
np.indices然后使用
np.column_stack来创建最终的
2column数组来进一步优化它。让我们花些时间并对照已经提出的方案进行验证。在下面列出这两种方法-
def app1(points): return np.indices((points)).T.reshape(-1,2)def app2(points): R,C = np.indices((points[::-1])) return np.column_stack((C.ravel(), R.ravel()))
时间-
In [146]: points = [32,30]In [147]: np.allclose(app1(points), app2(points))Out[147]: TrueIn [148]: %timeit app1(points)100000 loops, best of 3: 14.8 µs per loopIn [149]: %timeit app2(points)100000 loops, best of 3: 17.4 µs per loopIn [150]: points = [320,300]In [151]: %timeit app1(points)1000 loops, best of 3: 1.1 ms per loopIn [152]: %timeit app2(points)1000 loops, best of 3: 822 µs per loop
因此，在较大的形状上效果更好。
B.通用解决方案（通用列输出）
我们将使其通用，以便我们可以使用给定的尽可能多的参数，如下所示：
def get_combinations(params, order='right'): # params : tuple of input scalars that denotes sizes # The order arg is used for the LSB position. So, with order='right', the # rightmost column is the least significant, hence it will change the most # when going through the rows. For order='left', the leftmost column # would change the most. all_indices = np.indices(params) if order=='right': return np.moveaxis(all_indices,0,-1).reshape(-1,len(params)) elif order=='left': return all_indices.T.reshape(-1,len(params)) else: raise Exception('Wrong side value!')样本案例运行-
In [189]: get_combinations((2,3), order='left')Out[189]: array([[0, 0], [1, 0], [0, 1], [1, 1], [0, 2], [1, 2]])In [191]: get_combinations((2,3,2), order='right')Out[191]: array([[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [0, 2, 0], [0, 2, 1], [1, 0, 0], [1, 0, 1], [1, 1, 0], [1, 1, 1], [1, 2, 0], [1, 2, 1]])
