Fix overflow of Plexon in numpy 2.0 #1613
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@h-mayorquin merge conflict from #1612. |
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Solved. |
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Cool. I'll double check this weekend :) |
| @@ -209,6 +209,10 @@ def _parse_header(self): | |||
| for index, pos in enumerate(positions): | |||
| bl_header = data[pos : pos + 16].view(DataBlockHeader)[0] | |||
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| # To avoid overflow errors when doing arithmetic operations on numpy scalars | |||
| np_scalar_to_python_scalar = lambda x: x.item() if isinstance(x, np.generic) else x | |||
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Is there a reason not to make this lambda function near the top so it is reusable. Or even define this as a true private function. How are you thinking about using the same lambda function twice being generated in the for loop. It should be relatively low cost although seems a bit of a waste no? We could define the function once and reuse in both the for loops, no?
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Keeping the definition close to the use so people can quickly see what it is for. This takes nanoseconds:
Extracting the data from plexon takes minutes. It does not factor.
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I figured you'd have checked. Fair enough. :)
neo/rawio/plexonrawio.py
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| channel_headers = slowChannelHeaders[chan_index] | ||
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| # To avoid overflow errors when doing arithmetic operations on numpy scalars | ||
| np_scalar_to_python_scalar = lambda x: x.item() if isinstance(x, np.generic) else x | ||
| channel_headers = {key: np_scalar_to_python_scalar(channel_headers[key]) for key in channel_headers.dtype.names} | ||
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| name = channel_headers["Name"].decode("utf8") | ||
| chan_id = channel_headers["Channel"] |
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Last question.
so below you called it dsp_channel_headers which was really nice. Any interest in changing this to slow_channel_headers, just so we make sure we never accidentally overwrite any variable. I think the explicit makes it cleaner and since we are already fixing up the variable naming might be worth the push?
| @@ -209,6 +209,10 @@ def _parse_header(self): | |||
| for index, pos in enumerate(positions): | |||
| bl_header = data[pos : pos + 16].view(DataBlockHeader)[0] | |||
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| # To avoid overflow errors when doing arithmetic operations on numpy scalars | |||
| np_scalar_to_python_scalar = lambda x: x.item() if isinstance(x, np.generic) else x | |||
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I figured you'd have checked. Fair enough. :)
This should fix the errors in #1612.
At least for Plexon.