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random number generators perform unnecessary copy #1351
Description
Taking generate as an example:
Lines 265 to 271 in ee177aa
The result of ascontinguousarray can share memory with the input array yet the if array_1d.data != array.data: check can fail resulting in an unnecessary copy.
The issue can be illustrated in the following code:
import numpy as np
array = np.empty((10, 20, 30), dtype=float)
array_1d = np.ascontiguousarray(array.ravel(),dtype=float)
# data is not the same
assert array.data != array_1d.data
# because array_1d is a view of array
assert array.data == array_1d.base.data # note the use of base here
# arrays share memory
assert np.shares_memory(array, array_1d)
# double check
array_1d[:] = 2
assert np.all(array == 2)Replacing if array_1d.data != array.data: with if not np.shares_memory(array, array_1d): should fix the issue.
Activity
rmjarvis commentedon Mar 6, 2026
Sure. I'm not sure it's an "issue" exactly. But I'll admit the change would be marginally more efficient. Feel free to submit a PR.