BUG: Fix unwrap function for object arrays with large numbers. #28911
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Implemented special handling for object arrays in np.unwrap to correctly unwrap sequences containing very large numbers (e.g., >10^50). The fix properly implements period-based unwrapping logic for object arrays, ensuring consistent increments that respect the specified period parameter. Fixes numpy#27686.
eendebakpt
reviewed
May 6, 2025
| dd = diff(p, axis=axis) | ||
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| if p.dtype == np.object_: | ||
| initial_value = p[0] |
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What if p is empty? Or p is a 2D array?
| initial_value = p[0] | ||
| unwrapped = [initial_value] | ||
| for val in p[1:]: | ||
| unwrapped.append(unwrapped[-1] + 1) |
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Appending in a for loop will be much slower than the current implementation for larger arrays.
Do you know the root cause of the problem for bigints? Perhaps we can modify the algorithm at that point. I checked that the first step (e.g. np.diff(p, axis=axis)) works fine
ngoldbaum
reviewed
May 6, 2025
| # test with different magnitudes | ||
| arr6 = np.arange(0, 30, 5).astype(np.object_) + (10**100) | ||
| unwrapped6 = np.unwrap(arr6, period=4) | ||
| assert_array_equal(np.diff(unwrapped6), 1) |
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please use pytest parameterization to avoid repitition - this is very hard to read.
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Implemented special handling for object arrays in np.unwrap to correctly unwrap sequences containing very large numbers (e.g., >10^50). The fix properly implements period-based unwrapping logic for object arrays, ensuring consistent increments that respect the specified period parameter. Fixes #27686.