[fix] edf.py: potential overflow with n_events=256 #12859
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since the n_events assigned with the UINT8 type of number "ne". So, the default type of n_events will also be UINT8. During the summation of all three byte of "ne" will potentially cause overflow. In my case, python raised overflow error when it reach 256 which exceed the upper limit of 255. Direct Bit-Wise operation can avoid this.
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larsoner
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Sep 19, 2024
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| ne = np.fromfile(fid, UINT8, 3) | ||
| n_events = ne[0] | ||
| for i in range(1, len(ne)): | ||
| n_events = n_events + ne[i] * 2 ** (i * 8) | ||
| n_events = ne[0] + (ne[1] << 8) + (ne[2] << 16) |
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I think this is a fix on NumPy < 2 but on 2.1 I get:
>>> np.uint8(255) + np.uint8(255)
<stdin>:1: RuntimeWarning: overflow encountered in scalar add
np.uint8(254)
So I think maybe doing this would be a clean way to fix it
ne = np.fromfile(fid, UINT8, 3).astype(np.int64)
or similar
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I think this was fixed by #12909 in the meantime, but happy to see other PRs in the future! |
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since the n_events assigned with the UINT8 type of number "ne". So, the default type of n_events will also be UINT8. During the summation of all three byte of "ne" will potentially cause overflow. In my case, python raised overflow error when it reach 256 which exceed the upper limit of 255. Direct Bit-Wise operation can avoid this.
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