Reputation: 1467
I have a Python numpy N-dimensional array with shape M x N x ... x T
, but I do not know the number of dimensions (rank) of the array until runtime.
How can I create a view of a sub-array of that array, specified by two vectors with length rank: extent
and offset
?
import numpy as np
def select_subrange( orig_array, subrange_extent_vector, subrange_offset_vector ):
"""
returns a view of orig_array offset by the entries in subrange_offset_vector
and with extent specified by entries in subrange_extent_vector.
"""
# ???
return subarray
I'm stuck because the slicing examples I have found require [ start:end, ... ]
entries for each array dimension.
Upvotes: 1
Views: 862
Reputation: 251538
If I understand you right, use
orig_array[[slice(o, o+e) for o, e in zip(offset, extent)]]
Example:
>>> x = np.arange(4**4).reshape((4, 4, 4, 4))
>>> x[0:2, 1:2, 2:3, 1:3]
array([[[[25, 26]]],
[[[89, 90]]]])
>>> offset = (0, 1, 2, 1)
>>> extent = (2, 1, 1, 2)
>>> x[[slice(o, o+e) for o, e in zip(offset, extent)]]
array([[[[25, 26]]],
[[[89, 90]]]])
Upvotes: 3