Updated tests.

popv/visualization.py

@@ -202,6 +202,7 @@ def make_agreement_plots(
     prediction_keys: list,
     popv_prediction_key: str | None = "popv_prediction",
     save_folder: str | None = None,
+    show: bool = True,
 ):
     """
     Create plot of confusion matrix for different popv methods and consensus prediction.
@@ -216,6 +217,8 @@ def make_agreement_plots(
         Key in adata.obs for consensus prediction.
     save_folder
         Path to a folder for storing the plot. Defaults to None and plot is not stored.
+    show
+        If True, the plot will be shown in the console. If False, the plot will not be shown.
 
     Returns
     -------
@@ -237,6 +240,7 @@ def make_agreement_plots(
             x_label=method,
             y_label=popv_prediction_key,
             res_dir=save_folder,
+            show=show,
         )
 
 
@@ -247,6 +251,7 @@ def _prediction_eval(
     x_label="",
     y_label="",
     res_dir="./",
+    show=True,
 ):
     """Generate confusion matrix."""
     types, _ = np.unique(np.concatenate([labels, pred]), return_inverse=True)
@@ -266,4 +271,5 @@ def _prediction_eval(
         for fig in range(1, plt.gcf().number + 1):
             pdf.savefig(fig)
         pdf.close()
-    plt.show()
+    if show:
+        plt.show()

tests/core/test_models.py

@@ -10,7 +10,7 @@
 from popv.reproducibility import _accuracy
 
 
-def _get_test_anndata(cl_obo_folder="resources/ontology/"):
+def _get_test_anndata(cl_obo_folder="resources/ontology/", mode='retrain'):
     print("UUU", os.getcwd())
     save_folder = "tests/tmp_testing/popv_test_results/"
     fn = save_folder + "annotated_query.h5ad"
@@ -34,6 +34,8 @@ def _get_test_anndata(cl_obo_folder="resources/ontology/"):
     # Lesser used parameters
     query_labels_key = None
     unknown_celltype_label = "unknown"
+    hvg = 4000 if mode == "retrain" else None
+
     adata = Process_Query(
         query_adata,
         ref_adata,
@@ -44,13 +46,13 @@ def _get_test_anndata(cl_obo_folder="resources/ontology/"):
         unknown_celltype_label=unknown_celltype_label,
         save_path_trained_models=save_folder,
         cl_obo_folder=cl_obo_folder,
-        prediction_mode="retrain",
+        prediction_mode=mode,
         n_samples_per_label=n_samples_per_label,
         compute_embedding=True,
         return_probabilities=True,
         accelerator="cpu",
         devices="auto",
-        hvg=4000,
+        hvg=hvg,
     )
 
     return adata
@@ -183,7 +185,7 @@ def test_annotation():
         save_path="tests/tmp_testing/popv_test_results/")
     popv.visualization.agreement_score_bar_plot(adata)
     popv.visualization.prediction_score_bar_plot(adata)
-    popv.visualization.make_agreement_plots(adata, prediction_keys=adata.uns["prediction_keys"])
+    popv.visualization.make_agreement_plots(adata, prediction_keys=adata.uns["prediction_keys"], show=False)
     popv.visualization.celltype_ratio_bar_plot(adata)
     obo_fn = "resources/ontology/cl.obo"
     _accuracy._ontology_accuracy(adata[adata.obs['_dataset']=='ref'], obofile=obo_fn, gt_key='cell_ontology_class', pred_key='popv_prediction')
@@ -192,6 +194,15 @@ def test_annotation():
     assert "popv_majority_vote_prediction" in adata.obs.columns
     assert not adata.obs["popv_majority_vote_prediction"].isnull().any()
 
+    adata = _get_test_anndata(mode='inference').adata
+    popv.annotation.annotate_data(
+        adata, save_path="tests/tmp_testing/popv_test_results/")
+
+    adata = _get_test_anndata(mode='fast').adata
+    popv.annotation.annotate_data(
+        adata, methods=["svm", "rf"],
+        save_path="tests/tmp_testing/popv_test_results/")
+
 
 def test_annotation_no_ontology():
     """Test Annotation and Plotting pipeline without ontology."""