Fix curated dataset reload without templates

Author: rossant

CHANGELOG.md

@@ -12,6 +12,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 - Development checkouts now report a development version with a Git commit suffix.
+- Template datasets without waveform templates can be reloaded after cluster assignments change.
 
 ## [2.7.0] 2025-12-10
 

phylib/io/model.py

@@ -414,16 +414,16 @@ def _load_data(self):
             self.n_channels_loc = 0
 
         # Clusters waveforms
-        if not np.all(self.spike_clusters == self.spike_templates) and \
+        clusters_changed = not np.array_equal(self.spike_clusters, self.spike_templates)
+        if clusters_changed and self.sparse_templates is not None and \
                 self.sparse_templates.cols is None:
             self.merge_map, self.nan_idx = self.get_merge_map()
             self.sparse_clusters = self.cluster_waveforms()
-            self.n_clusters = self.spike_clusters.max() + 1
         else:
             self.merge_map = {}
             self.nan_idx = []
             self.sparse_clusters = self.sparse_templates
-            self.n_clusters = self.spike_templates.max() + 1
+        self.n_clusters = self.spike_clusters.max() + 1
 
         # Spike waveforms (optional, otherwise fetched from raw data as needed).
         self.spike_waveforms = self._load_spike_waveforms()

phylib/io/tests/test_model.py

@@ -135,6 +135,26 @@ def test_model_save(template_model_full):
     m.save_spike_clusters(m.spike_clusters)
 
 
+def test_model_reload_curated_dataset_without_templates(template_path):
+    (template_path.parent / 'templates.npy').unlink()
+
+    model = load_model(template_path)
+    assert model.sparse_templates is None
+    spike_clusters = model.spike_clusters.copy()
+    spike_clusters[spike_clusters == spike_clusters[0]] = spike_clusters.max() + 1
+    model.save_spike_clusters(spike_clusters)
+    model.close()
+
+    model = load_model(template_path)
+    try:
+        ae(model.spike_clusters, spike_clusters)
+        assert model.sparse_templates is None
+        assert model.sparse_clusters is None
+        assert model.n_clusters == spike_clusters.max() + 1
+    finally:
+        model.close()
+
+
 def test_model_spike_waveforms(template_path_full):
     model = load_model(template_path_full)