这是一种杠杆作用
np.lib.stride_tricks.as_strided-
def random_windows_per_row_strided(arr, W=3): idx = np.random.randint(0,arr.shape[1]-W+1, arr.shape[0]) strided = np.lib.stride_tricks.as_strided m,n = arr.shape s0,s1 = arr.strides windows = strided(arr, shape=(m,n-W+1,W), strides=(s0,s1,s1)) return windows[np.arange(len(idx)), idx]
在具有
10,000行的更大数组上进行运行时测试-
In [469]: arr = np.random.rand(100000,100)# @Psidom's solnIn [470]: %timeit select_random_windows(arr, window_size=3)100 loops, best of 3: 7.41 ms per loopIn [471]: %timeit random_windows_per_row_strided(arr, W=3)100 loops, best of 3: 6.84 ms per loop# @Psidom's solnIn [472]: %timeit select_random_windows(arr, window_size=30)10 loops, best of 3: 26.8 ms per loopIn [473]: %timeit random_windows_per_row_strided(arr, W=30)100 loops, best of 3: 9.65 ms per loop# @Psidom's solnIn [474]: %timeit select_random_windows(arr, window_size=50)10 loops, best of 3: 41.8 ms per loopIn [475]: %timeit random_windows_per_row_strided(arr, W=50)100 loops, best of 3: 10 ms per loop
