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Hi,
I'm having issues with storing the recording object after applying deepinterpolation.
When saving an interpolated recording, I get error messages like:
ValueError: could not broadcast input array from shape (29886,768) into shape (30000,768)
I assume that is because the convolutional network removes samples at the edges of the signal.
What is the recommended way of dealing with this? Should I pad the traces before applying deepinterpolation? If so, is there a function for this? Or would it be better to create a new object for storing the interpolated recording?
Below is a code example. I'm using spikeinterface version 0.100.6 because deepinterpolation requires python <= 3.8
from pathlib import Path
import numpy as np
import spikeinterface.extractors as se
from spikeinterface.preprocessing import common_reference, deepinterpolate, zero_channel_pad
root = Path(__file__).parent.parent.absolute()
model_path = list((root/"model").glob("*"))[0]
recording = se.read_spikeglx( folder_path=root/"data"/"neuropixels")
# pad so dimensions are compatible with model
recording = zero_channel_pad(recording, num_channels=384*2)
# create preprocessing pipeline
recording_cmr = common_reference(recording=recording, operator="median")
recording_deepint = deepinterpolate(recording=recording_cmr, model_path=str(model_path), use_gpu=False)
# process and save
recording_deepint.save()Thanks in advance!