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Remove tmp_data_to_save when loading old analyzers #4480

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Merged
alejoe91 merged 5 commits into from
Mar 30, 2026
+10 −5
Merged

Remove tmp_data_to_save when loading old analyzers #4480

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d4dabe1
set tmp_data_to_save = [] for old analyzers
chrishalcrow Mar 30, 2026
ea2f396
Merge branch 'main' into backwards-template-metrics-merge
chrishalcrow Mar 30, 2026
16597a7
set tmp_data_to_save = [] for old analyzers
chrishalcrow Mar 30, 2026
ca1bfac
Merge remote-tracking branch 'refs/remotes/origin/backwards-template-…
chrishalcrow Mar 30, 2026
efc7f57
oups
chrishalcrow Mar 30, 2026
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15 changes: 10 additions & 5 deletions src/spikeinterface/metrics/template/template_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -169,6 +169,11 @@ def _handle_backward_compatibility_on_load(self):
if "waveform_ratios" not in self.params["metric_names"]:
self.params["metric_names"].append("waveform_ratios")

# If original analyzer doesn't have "peaks_data" or "main_channel_templates",
# then we can't save this tmp data (important for merges/splits)
if "peaks_data" in self.tmp_data_to_save:
self.tmp_data_to_save = []

def _set_params(
self,
metric_names: list[str] | None = None,
Expand Down Expand Up @@ -234,12 +239,12 @@ def _prepare_data(self, sorting_analyzer, unit_ids):
unit_ids = sorting_analyzer.unit_ids
peak_sign = self.params["peak_sign"]
upsampling_factor = self.params["upsampling_factor"]
min_thresh_detect_peaks_troughs = self.params["min_thresh_detect_peaks_troughs"]
edge_exclusion_ms = self.params.get("edge_exclusion_ms", 0.1)
min_thresh_detect_peaks_troughs = self.params.get("min_thresh_detect_peaks_troughs", 0.3)
edge_exclusion_ms = self.params.get("edge_exclusion_ms", 0.09)
min_peak_trough_distance_ratio = self.params.get("min_peak_trough_distance_ratio", 0.2)
min_extremum_distance_samples = self.params.get("min_extremum_distance_samples", 3)
sampling_frequency = sorting_analyzer.sampling_frequency
if self.params["upsampling_factor"] > 1:
if upsampling_factor > 1:
sampling_frequency_up = upsampling_factor * sampling_frequency
else:
sampling_frequency_up = sampling_frequency
Expand All @@ -249,7 +254,7 @@ def _prepare_data(self, sorting_analyzer, unit_ids):
m in get_multi_channel_template_metric_names() for m in self.params["metrics_to_compute"]
)

operator = self.params["template_operator"]
operator = self.params.get("template_operator", "average")
extremum_channel_indices = get_template_extremum_channel(
sorting_analyzer, peak_sign=peak_sign, outputs="index", operator=operator
)
Expand Down Expand Up @@ -312,7 +317,7 @@ def _prepare_data(self, sorting_analyzer, unit_ids):
# multi_channel_templates is a list of 2D arrays of shape (n_times, n_channels)
tmp_data["multi_channel_templates"] = multi_channel_templates
tmp_data["channel_locations_multi"] = channel_locations_multi
tmp_data["depth_direction"] = self.params["depth_direction"]
tmp_data["depth_direction"] = self.params.get("depth_direction", "y")

# Add peaks_info and preprocessed templates to self.data for storage in extension
columns = []
Expand Down
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