say I have a sequence s and I'd like to select n random sub sequences from it each with length l and store in a matrix. Is there a more numpy way of doing that than
s = np.arange(0, 1000)
n = 5
l = 10
i = np.random.randint(0, len(s)-10, 5)
ss = np.array([s[x:x+l] for x in i])
We can leverage np.lib.stride_tricks.as_strided based scikit-image's view_as_windows for efficient patch extraction, like so -
from skimage.util.shape import view_as_windows
# Get sliding windows (these are simply views)
w = view_as_windows(s, l)
# Index with indices, i for desired output
out = w[i]
Related :
NumPy Fancy Indexing - Crop different ROIs from different channels
Take N first values from every row in NumPy matrix that fulfill condition
Selecting Random Windows from Multidimensional Numpy Array Rows
