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Count overlapping periods once in compute_total_samples_per_unit #4941

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Count overlapping periods once in compute_total_samples_per_unit #4941

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5 changes: 5 additions & 0 deletions src/spikeinterface/metrics/spiketrain/tests/test_metric_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,11 @@ def test_calculate_firing_rates(sorting_analyzer_simple):
firing_rates_periods = compute_firing_rates(sorting_analyzer, periods=periods)
assert firing_rates == firing_rates_periods

# Overlapping periods shouldn't double-count time:
# the same periods twice should give the same firing rates as the original periods
firing_rates_overlapping = compute_firing_rates(sorting_analyzer, periods=np.concatenate([periods, periods]))
assert firing_rates_overlapping == firing_rates

# calculate num spikes with empty periods
empty_periods = np.empty(0, dtype=unit_period_dtype)
firing_rates_empty_periods = compute_firing_rates(sorting_analyzer, periods=empty_periods)
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14 changes: 11 additions & 3 deletions src/spikeinterface/metrics/utils.py
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Expand Up @@ -83,7 +83,7 @@ def compute_total_samples_per_unit(sorting_analyzer, periods=None):
sorting_analyzer : SortingAnalyzer
The sorting analyzer object.
periods : array of unit_period_dtype, default: None
Periods to consider for each unit.
Periods to consider for each unit. Where a unit's periods overlap, the overlapping samples count once.

Returns
-------
Expand All @@ -93,9 +93,17 @@ def compute_total_samples_per_unit(sorting_analyzer, periods=None):
if periods is not None:
total_samples_array = np.zeros(len(sorting_analyzer.unit_ids), dtype="int64")
sorting = sorting_analyzer.sorting
for period in periods:
# count the union of each unit's periods
order = np.lexsort((periods["start_sample_index"], periods["segment_index"], periods["unit_index"]))
covered_until = {} # (unit_index, segment_index) -> end of that unit's periods so far
for period in periods[order]:
unit_index = period["unit_index"]
total_samples_array[unit_index] += period["end_sample_index"] - period["start_sample_index"]
key = (unit_index, period["segment_index"])
start = max(period["start_sample_index"], covered_until.get(key, period["start_sample_index"]))
end = period["end_sample_index"]
if end > start:
total_samples_array[unit_index] += end - start
covered_until[key] = end
total_samples = dict(zip(sorting.unit_ids, total_samples_array))
else:
total = sorting_analyzer.get_total_samples()
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