added test cases

tests/analysis/test_graphs.py

@@ -321,7 +321,7 @@ def test_pipe_add_graph_metrics():
 def test_pipe_rescale_graph_edge_weights(tk_graph):
     rescaled_tkg, rescaled_undir = graphs.pipe_rescale_graph_edge_weights(tk_graph)
     assert rescaled_tkg[2][1]['weight'] == pytest.approx(1.0)
-    assert rescaled_tkg[1][2]['weight'] == pytest.approx(0.0952)
+    assert rescaled_tkg[1][2]['weight'] == pytest.approx(0.095238)
     assert rescaled_undir[2][1]['weight'] == pytest.approx(1.0)
     assert rescaled_undir[1][2]['weight'] == pytest.approx(1.0)
 
@@ -331,7 +331,7 @@ def test_rescale_edge_weights(import_graph, request):
     test_graph = request.getfixturevalue(import_graph)
     rescaled_graph = graphs.rescale_edge_weights(test_graph)
     assert rescaled_graph[2][1]['weight'] == pytest.approx(1.0)
-    assert rescaled_graph[1][2]['weight'] == pytest.approx(0.0952)
+    assert rescaled_graph[1][2]['weight'] == pytest.approx(0.095238)
 
 
 @pytest.mark.parametrize('import_graph', ['graph', 'tk_graph'])

tests/analysis/test_timeline.py

@@ -72,7 +72,7 @@ def test_calc_delta_to_repair(data_pre_cleaned, convert_to_days):
 def test_non_relevant_obj_ids(data_pre_cleaned):
     feature_uniqueness = 'HObjektText'
     feature_obj_id = 'ObjektID'
-    threshold = 1
+    threshold = 2
     data = data_pre_cleaned.copy()
     data.at[0, feature_obj_id] = 1
     ids_to_ignore = tl._non_relevant_obj_ids(
@@ -88,7 +88,7 @@ def test_non_relevant_obj_ids(data_pre_cleaned):
 def test_remove_non_relevant_obj_ids(data_pre_cleaned):
     feature_uniqueness = 'HObjektText'
     feature_obj_id = 'ObjektID'
-    threshold = 1
+    threshold = 2
     data = data_pre_cleaned.copy()
     data.at[0, feature_obj_id] = 1
 

tests/test_model_loader.py

@@ -25,8 +25,6 @@ from lang_main.types import LanguageModels
 @pytest.mark.parametrize(
     'model_name',
     [
-        STFRModelTypes.ALL_DISTILROBERTA_V1,
-        STFRModelTypes.ALL_MINI_LM_L12_V2,
         STFRModelTypes.ALL_MINI_LM_L6_V2,
         STFRModelTypes.ALL_MPNET_BASE_V2,
     ],
@@ -47,6 +45,25 @@ def test_load_sentence_transformer(
     assert isinstance(model, SentenceTransformer)
 
 
+def test_preprocess_STFR_model_name() -> None:
+    model_name_not_exist = 'TestModel'
+    ret_model_name = model_loader._preprocess_STFR_model_name(
+        model_name=model_name_not_exist, backend=STFRBackends.TORCH, force_download=True
+    )
+    assert ret_model_name == model_name_not_exist
+    ret_model_name = model_loader._preprocess_STFR_model_name(
+        model_name=model_name_not_exist, backend=STFRBackends.TORCH, force_download=False
+    )
+    assert ret_model_name == model_name_not_exist
+
+    model_name_exist = STFRModelTypes.E5_BASE_STS_EN_DE
+    backend_exist = STFRBackends.ONNX
+    with pytest.raises(FileNotFoundError):
+        _ = model_loader._preprocess_STFR_model_name(
+            model_name=model_name_exist, backend=backend_exist, force_download=False
+        )
+
+
 @pytest.mark.parametrize(
     'similarity_func',
     [
@@ -57,8 +74,6 @@ def test_load_sentence_transformer(
 @pytest.mark.parametrize(
     'model_name',
     [
-        STFRModelTypes.ALL_DISTILROBERTA_V1,
-        STFRModelTypes.ALL_MINI_LM_L12_V2,
         STFRModelTypes.ALL_MINI_LM_L6_V2,
         STFRModelTypes.ALL_MPNET_BASE_V2,
     ],
@@ -108,6 +123,14 @@ def test_instantiate_spacy_model():
     assert isinstance(model, Language)
 
 
+def test_fail_instantiate_spacy_model():
+    with pytest.raises(KeyError):
+        _ = model_loader.instantiate_model(
+            model_load_map=model_loader.MODEL_LOADER_MAP,
+            model='test',  # type: ignore
+        )  # type: ignore
+
+
 @pytest.mark.mload
 def test_instantiate_stfr_model():
     model = model_loader.instantiate_model(