Refactor quality metrics tests to use fixture

src/spikeinterface/qualitymetrics/tests/conftest.py

@@ -5,8 +5,11 @@
     create_sorting_analyzer,
 )
 
+job_kwargs = dict(n_jobs=2, progress_bar=True, chunk_duration="1s")
 
-def _small_sorting_analyzer():
+
+@pytest.fixture(scope="module")
+def small_sorting_analyzer():
     recording, sorting = generate_ground_truth_recording(
         durations=[2.0],
         num_units=10,
@@ -33,5 +36,36 @@ def _small_sorting_analyzer():
 
 
 @pytest.fixture(scope="module")
-def small_sorting_analyzer():
-    return _small_sorting_analyzer()
+def sorting_analyzer_simple():
+    # we need high firing rate for amplitude_cutoff
+    recording, sorting = generate_ground_truth_recording(
+        durations=[
+            120.0,
+        ],
+        sampling_frequency=30_000.0,
+        num_channels=6,
+        num_units=10,
+        generate_sorting_kwargs=dict(firing_rates=10.0, refractory_period_ms=4.0),
+        generate_unit_locations_kwargs=dict(
+            margin_um=5.0,
+            minimum_z=5.0,
+            maximum_z=20.0,
+        ),
+        generate_templates_kwargs=dict(
+            unit_params=dict(
+                alpha=(200.0, 500.0),
+            )
+        ),
+        noise_kwargs=dict(noise_levels=5.0, strategy="tile_pregenerated"),
+        seed=1205,
+    )
+
+    sorting_analyzer = create_sorting_analyzer(sorting, recording, format="memory", sparse=True)
+
+    sorting_analyzer.compute("random_spikes", max_spikes_per_unit=300, seed=1205)
+    sorting_analyzer.compute("noise_levels")
+    sorting_analyzer.compute("waveforms", **job_kwargs)
+    sorting_analyzer.compute("templates")
+    sorting_analyzer.compute("spike_amplitudes", **job_kwargs)
+
+    return sorting_analyzer

src/spikeinterface/qualitymetrics/tests/test_metrics_functions.py

@@ -135,36 +135,6 @@ def test_unit_id_order_independence(small_sorting_analyzer):
         assert quality_metrics_2[metric][1] == metric_1_data["#4"]
 
 
-def _sorting_analyzer_simple():
-    recording, sorting = generate_ground_truth_recording(
-        durations=[
-            50.0,
-        ],
-        sampling_frequency=30_000.0,
-        num_channels=6,
-        num_units=10,
-        generate_sorting_kwargs=dict(firing_rates=6.0, refractory_period_ms=4.0),
-        noise_kwargs=dict(noise_levels=5.0, strategy="tile_pregenerated"),
-        seed=2205,
-    )
-
-    sorting_analyzer = create_sorting_analyzer(sorting, recording, format="memory", sparse=True)
-
-    sorting_analyzer.compute("random_spikes", max_spikes_per_unit=300, seed=2205)
-    sorting_analyzer.compute("noise_levels")
-    sorting_analyzer.compute("waveforms", **job_kwargs)
-    sorting_analyzer.compute("templates")
-    sorting_analyzer.compute("principal_components", n_components=5, mode="by_channel_local", **job_kwargs)
-    sorting_analyzer.compute("spike_amplitudes", **job_kwargs)
-
-    return sorting_analyzer
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_simple():
-    return _sorting_analyzer_simple()
-
-
 def _sorting_violation():
     max_time = 100.0
     sampling_frequency = 30000
@@ -576,6 +546,7 @@ def test_calculate_sd_ratio(sorting_analyzer_simple):
     test_unit_structure_in_output(_small_sorting_analyzer())
 
     # test_calculate_firing_rate_num_spikes(sorting_analyzer)
+
     # test_calculate_snrs(sorting_analyzer)
     # test_calculate_amplitude_cutoff(sorting_analyzer)
     # test_calculate_presence_ratio(sorting_analyzer)

src/spikeinterface/qualitymetrics/tests/test_quality_metric_calculator.py

@@ -2,7 +2,6 @@
 from pathlib import Path
 import numpy as np
 
-
 from spikeinterface.core import (
     generate_ground_truth_recording,
     create_sorting_analyzer,
@@ -15,54 +14,11 @@
     compute_quality_metrics,
 )
 
-
 job_kwargs = dict(n_jobs=2, progress_bar=True, chunk_duration="1s")
 
 
-def get_sorting_analyzer(seed=2205):
-    # we need high firing rate for amplitude_cutoff
-    recording, sorting = generate_ground_truth_recording(
-        durations=[
-            120.0,
-        ],
-        sampling_frequency=30_000.0,
-        num_channels=6,
-        num_units=10,
-        generate_sorting_kwargs=dict(firing_rates=10.0, refractory_period_ms=4.0),
-        generate_unit_locations_kwargs=dict(
-            margin_um=5.0,
-            minimum_z=5.0,
-            maximum_z=20.0,
-        ),
-        generate_templates_kwargs=dict(
-            unit_params=dict(
-                alpha=(200.0, 500.0),
-            )
-        ),
-        noise_kwargs=dict(noise_levels=5.0, strategy="tile_pregenerated"),
-        seed=seed,
-    )
-
-    sorting_analyzer = create_sorting_analyzer(sorting, recording, format="memory", sparse=True)
-
-    sorting_analyzer.compute("random_spikes", max_spikes_per_unit=300, seed=seed)
-    sorting_analyzer.compute("noise_levels")
-    sorting_analyzer.compute("waveforms", **job_kwargs)
-    sorting_analyzer.compute("templates")
-    sorting_analyzer.compute("spike_amplitudes", **job_kwargs)
-
-    return sorting_analyzer
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_simple():
-    sorting_analyzer = get_sorting_analyzer(seed=2205)
-    return sorting_analyzer
-
-
 def test_compute_quality_metrics(sorting_analyzer_simple):
     sorting_analyzer = sorting_analyzer_simple
-    print(sorting_analyzer)
 
     # without PCs
     metrics = compute_quality_metrics(