Added test

src/aki_prj23_transparenzregister/utils/networkx/network_2d.py

@@ -45,11 +45,11 @@ def create_2d_graph(  # noqa PLR0913
         #     pos = nx.planar_layout(graph)
         case "Random":
             pos = nx.random_layout(graph)
-        case "Shell only 2D)":
+        case "(Shell only 2D)":
             pos = nx.shell_layout(graph)
         # case "Spectral":
         #     pos = nx.spectral_layout(graph)
-        case "Spiral only 2D)":
+        case "(Spiral only 2D)":
             pos = nx.spiral_layout(graph)
         # case "Multipartite":
         #     pos = nx.multipartite_layout(graph)

src/aki_prj23_transparenzregister/utils/networkx/network_base.py

@@ -22,20 +22,28 @@ def initialize_network(edges: list, nodes: dict) -> tuple[nx.Graph, pd.DataFrame
 
     # update node attributes from dataframe
     nx.set_node_attributes(graph, nodes)
-
+    # Create a DataFrame with all Metrics
     # Create a DataFrame with all Metrics
     metrics = pd.DataFrame(
-        {
-            "eigenvector": nx.eigenvector_centrality(graph).values(),
-            "degree": nx.degree_centrality(graph).values(),
-            "betweenness": nx.betweenness_centrality(graph).values(),
-            "closeness": nx.closeness_centrality(graph).values(),
-            "pagerank": nx.pagerank(graph).values(),
-            "category": nx.get_node_attributes(graph, "type").values(),
-            "designation": nx.get_node_attributes(graph, "name").values(),
-            "id": nx.get_node_attributes(graph, "id").values(),
-        }
-    ).T
+        columns=[
+            "eigenvector",
+            "degree",
+            "betweenness",
+            "closeness",
+            "pagerank",
+            "category",
+            "designation",
+            "id",
+        ]
+    )
+    metrics["eigenvector"] = nx.eigenvector_centrality(graph).values()
+    metrics["degree"] = nx.degree_centrality(graph).values()
+    metrics["betweenness"] = nx.betweenness_centrality(graph).values()
+    metrics["closeness"] = nx.closeness_centrality(graph).values()
+    metrics["pagerank"] = nx.pagerank(graph).values()
+    metrics["category"] = nx.get_node_attributes(graph, "type").values()
+    metrics["designation"] = nx.get_node_attributes(graph, "name").values()
+    metrics["id"] = nx.get_node_attributes(graph, "id").values()
 
     return graph, metrics
 
@@ -64,7 +72,7 @@ def initialize_network_with_reduced_metrics(
 
     # Create a DataFrame with all Metrics
     metrics = pd.DataFrame(
-        columns=["degree", "eigenvector", "betweenness", "closeness", "pagerank"]
+        columns=["degree", "betweenness", "closeness", "category", "designation", "id"]
     )
     # metrics["eigenvector"] = nx.eigenvector_centrality(graph).values()
     metrics["degree"] = nx.degree_centrality(graph).values()

src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py

@@ -63,24 +63,6 @@ def find_all_company_relations() -> pd.DataFrame:
     return companies_relations_df
 
 
-def find_top_companies() -> pd.DataFrame:
-    """_summary_.
-
-    Returns:
-        pd.DataFrame: _description_
-    """
-    session = SessionHandler.session
-    assert session  # noqa: S101
-    query_companies = session.query(entities.Company)  # .all()
-
-    companies_df: pd.DataFrame = pd.read_sql(str(query_companies), session.bind)  # type: ignore
-    companies_df = companies_df.head()
-    companies_df = companies_df[["company_name"]]
-    companies_df["Platzierung"] = [1, 2, 3, 4, 5]
-    companies_df["Umsatz M€"] = [1, 2, 3, 4, 5]
-    return companies_df[["Platzierung", "company_name", "Umsatz M€"]]
-
-
 def get_all_company_relations() -> pd.DataFrame:
     """This Methods makes a Database Request for all Companies and their relations, modifies the ID Column and returns the Result as an DataFrame.
 
@@ -380,7 +362,7 @@ def create_edge_and_node_list_for_company(
     return nodes, edges
 
 
-def get_all_metrics_from_id(company_id: int) -> pd.Series:
+def get_all_metrics_from_id(company_id: str) -> pd.Series:
     """Returns all Metric for the given ID.
 
     Args:

tests/ui/networkx_dash_test.py

@@ -1,7 +0,0 @@
-"""Test for the NetworkX Component."""
-from aki_prj23_transparenzregister.ui.archive import networkx_dash
-
-
-def network_graph(edges: None) -> None:
-    """Checks if an import co company_stats_dash can be made."""
-    assert networkx_dash is not None

tests/utils/networkx/network_2d_test.py

@@ -2,15 +2,21 @@
 import datetime
 from collections.abc import Generator
 
-import networkx as nx
-import pandas as pd
+import plotly.graph_objects as go
 import pytest
 from sqlalchemy.orm import Session
 
 from aki_prj23_transparenzregister.ui.session_handler import SessionHandler
+from aki_prj23_transparenzregister.utils.networkx import network_2d
+from aki_prj23_transparenzregister.utils.networkx.network_2d import create_2d_graph
 from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
 
 
+def test_import() -> None:
+    """Checks if an import co company_stats_dash can be made."""
+    assert network_2d is not None
+
+
 @pytest.fixture(autouse=True)
 def _set_session(full_db: Session) -> Generator[None, None, None]:
     """Sets a session for the dash application to be used."""
@@ -19,32 +25,79 @@ def _set_session(full_db: Session) -> Generator[None, None, None]:
     SessionHandler.session = None
 
 
-def test_initialize_network() -> None:
+def test_create_2d_graph() -> None:
+    """Tests the creation of a 2D Graph."""
     edges: list = [
         {"from": "p_545", "to": "c_53", "type": "HAFTENDER_GESELLSCHAFTER"},
         {"from": "c_53", "to": "p_545", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_1", "to": "c_2", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_53", "to": "c_1", "type": "HAFTENDER_GESELLSCHAFTER"},
     ]
     nodes: dict = {
         "c_53": {
             "id": "c_53",
             "name": "1. Freiburger Solarfonds Beteiligungs-KG",
+            "type": "company",
             "color": "blue",
         },
         "p_545": {
             "id": "p_545",
-            "firstname": "Jürgen",
-            "lastname": "Wetzel",
+            "name": "Wetzel, Jürgen",
+            "type": "person",
             "date_of_birth": datetime.date(1962, 11, 15),
             "color": "red",
         },
+        "c_1": {
+            "id": "c_1",
+            "name": "Musterfirma",
+            "type": "company",
+            "color": "blue",
+        },
+        "c_2": {
+            "id": "c_2",
+            "name": "Firma 1",
+            "type": "company",
+            "color": "blue",
+        },
     }
     graph, metrics = initialize_network(edges=edges, nodes=nodes)
-    assert type(graph) is nx.Graph
-    assert type(metrics) is pd.DataFrame
-    # assert list(metrics.columns) == [
-    #     "degree",
-    #     "eigenvector",
-    #     "betweeness",
-    #     "closeness",
-    #     "pagerank",
-    # ]
+    metric = "None"
+    layout = "Spring"
+    edge_annotation = False
+    edge_thickness = 1
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    metric = "degree"
+    layout = "Circular"
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    edge_annotation = True
+    layout = "Kamada Kawai"
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    layout = "Random"
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    layout = "Shell (only 2D)"
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    layout = "Spiral (only 2D)"
+    figure = create_2d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure

tests/utils/networkx/network_3d_test.py

@@ -1,38 +1,79 @@
 """Test the initialize Network function."""
 import datetime
 
-import networkx as nx
-import pandas as pd
+import plotly.graph_objects as go
 
+from aki_prj23_transparenzregister.utils.networkx import network_3d
+from aki_prj23_transparenzregister.utils.networkx.network_3d import create_3d_graph
 from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
 
 
-def test_initialize_network() -> None:
+def test_import() -> None:
+    """Checks if an import co company_stats_dash can be made."""
+    assert network_3d is not None
+
+
+def test_create_3d_graph() -> None:
+    """Tests the creation of a 3D Graph."""
     edges: list = [
         {"from": "p_545", "to": "c_53", "type": "HAFTENDER_GESELLSCHAFTER"},
         {"from": "c_53", "to": "p_545", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_1", "to": "c_2", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_53", "to": "c_1", "type": "HAFTENDER_GESELLSCHAFTER"},
     ]
     nodes: dict = {
         "c_53": {
             "id": "c_53",
             "name": "1. Freiburger Solarfonds Beteiligungs-KG",
+            "type": "company",
             "color": "blue",
         },
         "p_545": {
             "id": "p_545",
-            "firstname": "Jürgen",
-            "lastname": "Wetzel",
+            "name": "Wetzel, Jürgen",
+            "type": "person",
             "date_of_birth": datetime.date(1962, 11, 15),
             "color": "red",
         },
+        "c_1": {
+            "id": "c_1",
+            "name": "Musterfirma",
+            "type": "company",
+            "color": "blue",
+        },
+        "c_2": {
+            "id": "c_2",
+            "name": "Firma 1",
+            "type": "company",
+            "color": "blue",
+        },
     }
     graph, metrics = initialize_network(edges=edges, nodes=nodes)
-    assert type(graph) is nx.Graph
-    assert type(metrics) is pd.DataFrame
-    # assert list(metrics.columns) == [
-    #     "degree",
-    #     "eigenvector",
-    #     "betweeness",
-    #     "closeness",
-    #     "pagerank",
-    # ]
+    metric = "None"
+    layout = "Spring"
+    edge_annotation = False
+    edge_thickness = 1
+    figure = create_3d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    metric = "degree"
+    layout = "Circular"
+    figure = create_3d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    edge_annotation = True
+    layout = "Kamada Kawai"
+    figure = create_3d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure
+
+    layout = "Random"
+    figure = create_3d_graph(
+        graph, nodes, edges, metrics, metric, layout, edge_annotation, edge_thickness
+    )
+    assert type(figure) is go.Figure

tests/utils/networkx/network_base_test.py

@@ -3,38 +3,83 @@ import datetime
 
 import networkx as nx
 import pandas as pd
-import pytest
 
-from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
+from aki_prj23_transparenzregister.utils.networkx import network_base
+from aki_prj23_transparenzregister.utils.networkx.network_base import (
+    initialize_network,
+    initialize_network_with_reduced_metrics,
+    initialize_network_without_metrics,
+)
+
+
+def test_import() -> None:
+    """Checks if an import co company_stats_dash can be made."""
+    assert network_base is not None
 
 
-@pytest.mark.tim()
 def test_initialize_network() -> None:
     edges: list = [
         {"from": "p_545", "to": "c_53", "type": "HAFTENDER_GESELLSCHAFTER"},
         {"from": "c_53", "to": "p_545", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_1", "to": "c_2", "type": "HAFTENDER_GESELLSCHAFTER"},
+        {"from": "c_53", "to": "c_1", "type": "HAFTENDER_GESELLSCHAFTER"},
     ]
     nodes: dict = {
         "c_53": {
             "id": "c_53",
             "name": "1. Freiburger Solarfonds Beteiligungs-KG",
+            "type": "company",
             "color": "blue",
         },
         "p_545": {
             "id": "p_545",
-            "firstname": "Jürgen",
-            "lastname": "Wetzel",
+            "name": "Wetzel, Jürgen",
+            "type": "person",
             "date_of_birth": datetime.date(1962, 11, 15),
             "color": "red",
         },
+        "c_1": {
+            "id": "c_1",
+            "name": "Musterfirma",
+            "type": "company",
+            "color": "blue",
+        },
+        "c_2": {
+            "id": "c_2",
+            "name": "Firma 1",
+            "type": "company",
+            "color": "blur",
+        },
     }
+    # print(len(edges))
+    # print(len(nodes))
     graph, metrics = initialize_network(edges=edges, nodes=nodes)
     assert isinstance(graph, nx.Graph)
     assert isinstance(metrics, pd.DataFrame)
-    # assert list(metrics.columns) == [
-    #     "degree",
-    #     "eigenvector",
-    #     "betweeness",
-    #     "closeness",
-    #     "pagerank",
-    # ]
+    assert list(metrics.columns) == [
+        "eigenvector",
+        "degree",
+        "betweenness",
+        "closeness",
+        "pagerank",
+        "category",
+        "designation",
+        "id",
+    ]
+
+    graph_reduced, metrics_reduced = initialize_network_with_reduced_metrics(
+        edges=edges, nodes=nodes
+    )
+    assert isinstance(graph_reduced, nx.Graph)
+    assert isinstance(metrics_reduced, pd.DataFrame)
+    assert list(metrics_reduced.columns) == [
+        "degree",
+        "betweenness",
+        "closeness",
+        "category",
+        "designation",
+        "id",
+    ]
+
+    graph = initialize_network_without_metrics(edges=edges, nodes=nodes)
+    assert isinstance(graph_reduced, nx.Graph)

tests/utils/networkx/networkx_data_test.py

@@ -1,37 +1,150 @@
 """Test the initialize Network function."""
-import datetime
+from collections.abc import Generator
 
-import networkx as nx
 import pandas as pd
+import pytest
+from sqlalchemy.orm import Session
 
-from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
+from aki_prj23_transparenzregister.ui.session_handler import SessionHandler
+from aki_prj23_transparenzregister.utils.networkx import networkx_data
+from aki_prj23_transparenzregister.utils.networkx.networkx_data import (
+    create_edge_and_node_list,
+    create_edge_and_node_list_for_company,
+    filter_relation_type,
+    filter_relation_with_more_than_one_connection,
+    find_all_company_relations,
+    find_company_relations,
+    get_all_company_relations,
+    get_all_person_relations,
+)
 
 
-def test_initialize_network() -> None:
-    edges: list = [
-        {"from": "p_545", "to": "c_53", "type": "HAFTENDER_GESELLSCHAFTER"},
-        {"from": "c_53", "to": "p_545", "type": "HAFTENDER_GESELLSCHAFTER"},
-    ]
-    nodes: dict = {
-        "c_53": {
-            "id": "c_53",
-            "name": "1. Freiburger Solarfonds Beteiligungs-KG",
-            "color": "blue",
-        },
-        "p_545": {
-            "id": "p_545",
-            "name": "Jürgen Wenzel",
-            "date_of_birth": datetime.date(1962, 11, 15),
-            "color": "red",
-        },
-    }
-    graph, metrics = initialize_network(edges=edges, nodes=nodes)
-    assert type(graph) is nx.Graph
-    assert type(metrics) is pd.DataFrame
-    # assert list(metrics.columns) == [
-    #     "degree",
-    #     "eigenvector",
-    #     "betweeness",
-    #     "closeness",
-    #     "pagerank",
+@pytest.fixture(autouse=True)
+def _set_session(full_db: Session) -> Generator[None, None, None]:
+    """Sets a session for the dash application to be used."""
+    SessionHandler.session = full_db
+    yield
+    SessionHandler.session = None
+
+
+def test_import() -> None:
+    """Checks if an import co company_stats_dash can be made."""
+    assert networkx_data is not None
+
+
+# def test_initialize_network() -> None:
+#     edges: list = [
+#         {"from": "p_545", "to": "c_53", "type": "HAFTENDER_GESELLSCHAFTER"},
+#         {"from": "c_53", "to": "p_545", "type": "HAFTENDER_GESELLSCHAFTER"},
+#         {"from": "c_1", "to": "c_2", "type": "HAFTENDER_GESELLSCHAFTER"},
+#         {"from": "c_53", "to": "c_1", "type": "HAFTENDER_GESELLSCHAFTER"},
 #     ]
+#     nodes: dict = {
+#         "c_53": {
+#             "id": "c_53",
+#             "name": "1. Freiburger Solarfonds Beteiligungs-KG",
+#             "type": "company",
+#             "color": "blue",
+#         },
+#         "p_545": {
+#             "id": "p_545",
+#             "name": "Wetzel, Jürgen",
+#             "type": "person",
+#             "date_of_birth": datetime.date(1962, 11, 15),
+#             "color": "red",
+#         },
+#         "c_1": {
+#             "id": "c_1",
+#             "name": "Musterfirma",
+#             "type": "company",
+#             "color": "blue",
+#         },
+#         "c_2": {
+#             "id": "c_2",
+#             "name": "Firma 1",
+#             "type": "company",
+#             "color": "blur",
+#         },
+#     }
+
+
+def test_find_all_company_relations() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    company_relations_df = find_all_company_relations()
+    assert type(company_relations_df) is pd.DataFrame
+
+
+def test_get_all_company_relations() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    company_relations_df = get_all_company_relations()
+    assert type(company_relations_df) is pd.DataFrame
+
+
+def test_get_all_person_relations() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    company_relations_df = get_all_person_relations()
+    assert type(company_relations_df) is pd.DataFrame
+
+
+def test_filter_relation_type() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    relation_dataframe = get_all_company_relations()
+    selected_relation_type = "HAFTENDER_GESELLSCHAFTER"
+    company_relations_df = filter_relation_type(
+        relation_dataframe, selected_relation_type
+    )
+    assert type(company_relations_df) is pd.DataFrame
+
+
+def test_filter_relation_with_more_than_one_connection() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    relation_dataframe = get_all_company_relations()
+    id_column_name_to = "c_1"
+    id_column_name_from = "c_2"
+    relations_df = filter_relation_with_more_than_one_connection(
+        relation_dataframe, id_column_name_to, id_column_name_from
+    )
+    assert type(relations_df) is pd.DataFrame
+
+
+def test_create_edge_and_node_list() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    person_df = get_all_person_relations()
+    company_df = get_all_company_relations()
+    nodes, edges = create_edge_and_node_list(person_df, company_df)
+    assert isinstance(nodes, dict)
+    assert isinstance(edges, list)
+
+
+def test_find_company_relations() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    selected_company_id = 1
+    company_relations_df, person_df = find_company_relations(selected_company_id)
+    assert type(company_relations_df) is pd.DataFrame
+    assert type(person_df) is pd.DataFrame
+
+
+def test_create_edge_and_node_list_for_company() -> None:
+    """This Test methods tests if the correct type is returned for the corresponding Function."""
+    company_relations = get_all_company_relations()
+    nodes, edges = create_edge_and_node_list_for_company(company_relations)
+    assert isinstance(nodes, dict)
+    assert isinstance(edges, list)
+
+
+# @pytest.mark.tim()
+# def test_get_all_metrics_from_id() -> None:
+#     """This Test methods tests if the correct type is returned for the corresponding Function."""
+#     company_id = 2549
+#     metrics = get_all_metrics_from_id(company_id)
+#     assert type(metrics) is pd.Series
+
+# @pytest.mark.tim()
+# def test_get_relations_number_from_id() -> None:
+#     """This Test methods tests if the correct type and number of relations is received."""
+#     # id = "c_2549"
+#     id = "c_2667"
+#     relations_lvl_1, relations_lvl_2, relations_lvl_3 = get_relations_number_from_id(id)
+#     assert type(relations_lvl_1) is int
+#     assert type(relations_lvl_2) is int
+#     assert type(relations_lvl_3) is int