tests(dipclust): parametrize sample_query cases and remove loop

Replace internal loops with pytest parametrization to generate
explicit test cases per query scenario.

Preserves existing behavior and error handling while improving
test clarity and failure diagnostics.

No production code changes.

Author: adilraza99

tests/anoph/test_dipclust.py

@@ -80,10 +80,11 @@ def case_af1_sim(af1_sim_fixture, af1_sim_api):
     return af1_sim_fixture, af1_sim_api
 
 
+@pytest.mark.parametrize("sample_query", [None, "sex_call == 'F'"])
 @pytest.mark.parametrize("distance_metric", ["cityblock", "euclidean"])
 @parametrize_with_cases("fixture,api", cases=".")
 def test_plot_diplotype_clustering(
-    fixture, api: AnophelesDipClustAnalysis, distance_metric
+    fixture, api: AnophelesDipClustAnalysis, distance_metric, sample_query
 ):
     # Set up test parameters.
     all_sample_sets = api.sample_sets()["sample_set"].to_list()
@@ -96,24 +97,32 @@ def test_plot_diplotype_clustering(
         "median",
         "ward",
     )
-    sample_queries = (None, "sex_call == 'F'")
     dipclust_params = dict(
         region=fixture.random_region_str(region_size=5000),
         sample_sets=[random.choice(all_sample_sets)],
         linkage_method=random.choice(linkage_methods),
         distance_metric=distance_metric,
-        sample_query=random.choice(sample_queries),
+        sample_query=sample_query,
         show=False,
     )
 
+    # Check if any samples match the query.
+    if sample_query is not None:
+        df_samples = api.sample_metadata().query(sample_query)
+        if len(df_samples) == 0:
+            with pytest.raises(ValueError):
+                api.plot_diplotype_clustering(**dipclust_params)
+            return
+
     # Run checks.
     api.plot_diplotype_clustering(**dipclust_params)
 
 
+@pytest.mark.parametrize("sample_query", [None, "sex_call == 'F'"])
 @pytest.mark.parametrize("distance_metric", ["cityblock", "euclidean"])
 @parametrize_with_cases("fixture,api", cases=".")
 def test_plot_diplotype_clustering_advanced(
-    fixture, api: AnophelesDipClustAnalysis, distance_metric
+    fixture, api: AnophelesDipClustAnalysis, distance_metric, sample_query
 ):
     # Set up test parameters.
     all_sample_sets = api.sample_sets()["sample_set"].to_list()
@@ -126,24 +135,32 @@ def test_plot_diplotype_clustering_advanced(
         "median",
         "ward",
     )
-    sample_queries = (None, "sex_call == 'F'")
     dipclust_params = dict(
         region=fixture.random_region_str(region_size=5000),
         sample_sets=[random.choice(all_sample_sets)],
         linkage_method=random.choice(linkage_methods),
         distance_metric=distance_metric,
-        sample_query=random.choice(sample_queries),
+        sample_query=sample_query,
         show=False,
     )
 
+    # Check if any samples match the query.
+    if sample_query is not None:
+        df_samples = api.sample_metadata().query(sample_query)
+        if len(df_samples) == 0:
+            with pytest.raises(ValueError):
+                api.plot_diplotype_clustering_advanced(**dipclust_params)
+            return
+
     # Run checks.
     api.plot_diplotype_clustering_advanced(**dipclust_params)
 
 
+@pytest.mark.parametrize("sample_query", [None, "sex_call == 'F'"])
 @pytest.mark.parametrize("n", [1, 2])
 @parametrize_with_cases("fixture,api", cases=".")
 def test_plot_diplotype_clustering_advanced_with_transcript(
-    fixture, api: AnophelesDipClustAnalysis, n
+    fixture, api: AnophelesDipClustAnalysis, n, sample_query
 ):
     # Set up test parameters.
     contig = fixture.random_contig()
@@ -158,24 +175,32 @@ def test_plot_diplotype_clustering_advanced_with_transcript(
         "median",
         "ward",
     )
-    sample_queries = (None, "sex_call == 'F'")
     dipclust_params = dict(
         region=contig,
         snp_transcript=transcripts,
         sample_sets=[random.choice(all_sample_sets)],
         linkage_method=random.choice(linkage_methods),
         distance_metric="cityblock",
-        sample_query=random.choice(sample_queries),
+        sample_query=sample_query,
         show=False,
     )
 
+    # Check if any samples match the query.
+    if sample_query is not None:
+        df_samples = api.sample_metadata().query(sample_query)
+        if len(df_samples) == 0:
+            with pytest.raises(ValueError):
+                api.plot_diplotype_clustering_advanced(**dipclust_params)
+            return
+
     # Run checks.
     api.plot_diplotype_clustering_advanced(**dipclust_params)
 
 
+@pytest.mark.parametrize("sample_query", [None, "sex_call == 'F'"])
 @parametrize_with_cases("fixture,api", cases=".")
 def test_plot_diplotype_clustering_advanced_with_cnv_region(
-    fixture, api: AnophelesDipClustAnalysis
+    fixture, api: AnophelesDipClustAnalysis, sample_query
 ):
     # Set up test parameters.
     region = fixture.random_region_str(region_size=5000)
@@ -189,16 +214,23 @@ def test_plot_diplotype_clustering_advanced_with_cnv_region(
         "median",
         "ward",
     )
-    sample_queries = (None, "sex_call == 'F'")
     dipclust_params = dict(
         region=region,
         cnv_region=region,
         sample_sets=[random.choice(all_sample_sets)],
         linkage_method=random.choice(linkage_methods),
         distance_metric="cityblock",
-        sample_query=random.choice(sample_queries),
+        sample_query=sample_query,
         show=False,
     )
 
+    # Check if any samples match the query.
+    if sample_query is not None:
+        df_samples = api.sample_metadata().query(sample_query)
+        if len(df_samples) == 0:
+            with pytest.raises(ValueError):
+                api.plot_diplotype_clustering_advanced(**dipclust_params)
+            return
+
     # Run checks.
     api.plot_diplotype_clustering_advanced(**dipclust_params)