Switch calculate_pc_metrics to compute_pc_metrics for api consistency

src/spikeinterface/qualitymetrics/pca_metrics.py

@@ -57,8 +57,14 @@ def get_quality_pca_metric_list():
     return deepcopy(_possible_pc_metric_names)
 
 
-def calculate_pc_metrics(
-    sorting_analyzer, metric_names=None, qm_params=None, unit_ids=None, seed=None, n_jobs=1, progress_bar=False
+def compute_pc_metrics(
+    sorting_analyzer,
+    metric_names=None,
+    qm_params=None,
+    unit_ids=None,
+    seed=None,
+    n_jobs=1,
+    progress_bar=False,
 ):
     """Calculate principal component derived metrics.
 
@@ -180,6 +186,28 @@ def calculate_pc_metrics(
     return pc_metrics
 
 
+def calculate_pc_metrics(
+    sorting_analyzer, metric_names=None, qm_params=None, unit_ids=None, seed=None, n_jobs=1, progress_bar=False
+):
+    warnings.warn(
+        "The `calculate_pc_metrics` function is deprecated and will be removed in 0.103.0. Please use compute_pc_metrics instead",
+        category=DeprecationWarning,
+        stacklevel=2,
+    )
+
+    pc_metrics = compute_pc_metrics(
+        sorting_analyzer,
+        metric_names=metric_names,
+        qm_params=qm_params,
+        unit_ids=unit_ids,
+        seed=seed,
+        n_jobs=n_jobs,
+        progress_bar=progress_bar,
+    )
+
+    return pc_metrics
+
+
 #################################################################
 # Code from spikemetrics
 

src/spikeinterface/qualitymetrics/quality_metric_calculator.py

@@ -12,7 +12,7 @@
 from spikeinterface.core.sortinganalyzer import register_result_extension, AnalyzerExtension
 
 
-from .quality_metric_list import calculate_pc_metrics, _misc_metric_name_to_func, _possible_pc_metric_names
+from .quality_metric_list import compute_pc_metrics, _misc_metric_name_to_func, _possible_pc_metric_names
 from .misc_metrics import _default_params as misc_metrics_params
 from .pca_metrics import _default_params as pca_metrics_params
 
@@ -143,7 +143,7 @@ def _run(self, verbose=False, **job_kwargs):
         if len(pc_metric_names) > 0 and not self.params["skip_pc_metrics"]:
             if not self.sorting_analyzer.has_extension("principal_components"):
                 raise ValueError("waveform_principal_component must be provied")
-            pc_metrics = calculate_pc_metrics(
+            pc_metrics = compute_pc_metrics(
                 self.sorting_analyzer,
                 unit_ids=non_empty_unit_ids,
                 metric_names=pc_metric_names,

src/spikeinterface/qualitymetrics/quality_metric_list.py

@@ -21,7 +21,8 @@
 )
 
 from .pca_metrics import (
-    calculate_pc_metrics,
+    compute_pc_metrics,
+    calculate_pc_metrics,  # remove after 0.103.0
     mahalanobis_metrics,
     lda_metrics,
     nearest_neighbors_metrics,

src/spikeinterface/qualitymetrics/tests/test_pca_metrics.py

@@ -14,7 +14,7 @@
 from spikeinterface.qualitymetrics.utils import create_ground_truth_pc_distributions
 
 from spikeinterface.qualitymetrics import (
-    calculate_pc_metrics,
+    compute_pc_metrics,
     nearest_neighbors_isolation,
     nearest_neighbors_noise_overlap,
 )
@@ -55,10 +55,10 @@ def sorting_analyzer_simple():
 
 def test_calculate_pc_metrics(sorting_analyzer_simple):
     sorting_analyzer = sorting_analyzer_simple
-    res1 = calculate_pc_metrics(sorting_analyzer, n_jobs=1, progress_bar=True)
+    res1 = compute_pc_metrics(sorting_analyzer, n_jobs=1, progress_bar=True)
     res1 = pd.DataFrame(res1)
 
-    res2 = calculate_pc_metrics(sorting_analyzer, n_jobs=2, progress_bar=True)
+    res2 = compute_pc_metrics(sorting_analyzer, n_jobs=2, progress_bar=True)
     res2 = pd.DataFrame(res2)
 
     for k in res1.columns: