Additional quality metrics #1981
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zm711
reviewed
Sep 12, 2023
|
Thank you for the improved implementation! |
Co-authored-by: Zach McKenzie <[email protected]>
Co-authored-by: Zach McKenzie <[email protected]>
Co-authored-by: Zach McKenzie <[email protected]>
Co-authored-by: Zach McKenzie <[email protected]>
alejoe91
commented
Sep 14, 2023
|
Ready for final revision! there was a bug with the percentile numbers (should be 0-100, not 0-1) which has now been fixed. |
zm711
reviewed
Sep 19, 2023
| @@ -522,37 +523,41 @@ def compute_synchrony_metrics(waveform_extractor, synchrony_sizes=(2, 4, 8), **k | |||
| Based on concepts described in [Gruen]_ | |||
| This code was adapted from `Elephant - Electrophysiology Analysis Toolkit <https://github.com/NeuralEnsemble/elephant/blob/master/elephant/spike_train_synchrony.py#L245>`_ | |||
| """ | |||
| assert np.all(s > 1 for s in synchrony_sizes), "Synchrony sizes must be greater than 1" | |||
| assert np.all([s > 1 for s in synchrony_sizes]), "Synchrony sizes must be greater than 1" | |||
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Super minor but couldn't you just do
assert min(synchrony_sizes) > 1.
5.2 µs ± 23.8 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each) # np.all with list comprehension
135 ns ± 1.18 ns per loop (mean ± std. dev. of 7 runs, 10,000,000 loops each) # min with tuple/list
795 ns ± 2.93 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each) # min with np.array
But maybe I'm missing something?
alejoe91
commented
Sep 19, 2023
samuelgarcia
approved these changes
Sep 27, 2023
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This PR adds the following new quality metrics, designed by @musall and slightly modified:
Firing range
A measure of the variation of firing rate across an experiment. Computed as the distance between the 5th-95th percentile of local firing rates computed on 10s intervals.
Amplitude CV
A measure of the amplitude distribution dispersion. The CV is computed over temporal bins estimated for each unit to contain an
average_num_spikes_per_binspikes. Both the medians and the range (percentile distance) are returned.