implement data compression using mtscomp for openephys and spikeglx for neuropixels data
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… neuropixels data
| # explicitly garbage collect "loaded_oe" | ||
| # as these may have large memory footprint and may not be cleared fast enough | ||
| del loaded_oe | ||
| gc.collect() |
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has been this shown to improve performance compared to normal garbage collection?
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| self.EphysFile.insert([{**key, | ||
| 'file_path': fp.relative_to(root_dir).as_posix()} | ||
| for fp in probe_data.recording_info['recording_files']]) |
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The generator is even more efficient that then the list
self.EphysFile.insert({**key,
'file_path': fp.relative_to(root_dir).as_posix()}
for fp in probe_data.recording_info['recording_files'])| @@ -325,6 +326,10 @@ def make(self, key): | |||
| self.EphysFile.insert([{**key, | |||
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also, replace list comprehension with generator.
| lfp_file = self.root_dir / (self.root_name + '.lf.bin') | ||
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| decompressed_files = [] | ||
| for bin_fp, band_type in zip([ap_file, lfp_file], ['ap', 'lfp']): |
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for bin_fp, band_type in ((ap_file, 'ap'), (lfp_file, 'lfp')):
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Jun 26, 2023
Revise pytests/docker, markdown lint, pre-commit, spell check cleanup, NWB test update
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mtscompfor openephys and spikeglx for neuropixels datagc.collect()