[FIX] remove AnalogSignalGap#12417
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larsoner merged 2 commits intomne-tools:mainfrom Feb 2, 2024
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mne/io/neuralynx/neuralynx.py
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| signal.load(channel_indexes=idx).magnitude[ | ||
| samples[0] : samples[-1] + 1, : | ||
| ] | ||
| if type(signal) is not AnalogSignal # then it's AnalogSignalProxy |
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| if type(signal) is not AnalogSignal # then it's AnalogSignalProxy | |
| if not isinstance(signal, AnalogSignal) # then it's AnalogSignalProxy |
or better, actually check if it's AnalogSignalProxy rather than AnalogSignal?
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Yeah, was just editing this. Can also check for AnalogSignalProxy. Wasn't sure if it's worth doing an import for that (from neo.io.proxyobjects import AnalogSignalProxy).
Commit coming + sorting the neo import at the correct location.
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@larsoner See if it looks good? If yes, needs update from main and good on my end. |
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Thanks for the quick fix @KristijanArmeni ! |
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Reference issue
Fixes #12413.
What does this implement/fix
So far, to insert gap data (0's representing missing samples), the
AnalogSignalGapclass with a dummyload()method was defined and used to mirror theneo.AnalogSignalProxyobject which loads recorded samples from disk.As of v13,
neoallows onlyAnalogSignal/AnalogSignalProxytypes to be appended toSegment.analogsignalsattribute. To fix this, we drop the over-engineeredAnalogSignalGapclass. Instead, we create zero-arrays directly withAnalogSignaland use a simple control statement to distinguish loading real data (viaAnalogSignalProxy.load().magnitude) and padding 0's (viaAnalogSignal.magnitude) when looping over segments and creating the output data array.