On branch feature/visualize-verflechtungen

pyproject.toml

@@ -76,6 +76,9 @@ torchvision = {version = "*", source = "torch-cpu"}
 tqdm = "^4.66.1"
 transformers = {version = "*", extras = ["torch"]}
 xmltodict = "^0.13.0"
+dash_cytoscape = "^0.2.0"
+dashvis = "^0.1.3"
+
 
 [tool.poetry.extras]
 ingest = ["selenium", "deutschland", "xmltodict"]

src/aki_prj23_transparenzregister/ui/cytoscape_dash.py

@@ -0,0 +1,25 @@
+import dash_cytoscape as cyto
+from dash import Dash, html
+
+app = Dash(__name__)
+
+app.layout = html.Div(
+    [
+        html.P("Dash Cytoscape:"),
+        cyto.Cytoscape(
+            id="cytoscape",
+            elements=[
+                {"data": {"id": "ca", "label": "Canada"}},
+                {"data": {"id": "on", "label": "Ontario"}},
+                {"data": {"id": "qc", "label": "Quebec"}},
+                {"data": {"source": "ca", "target": "on"}},
+                {"data": {"source": "ca", "target": "qc"}},
+            ],
+            layout={"name": "breadthfirst"},
+            style={"width": "400px", "height": "500px"},
+        ),
+    ]
+)
+
+if __name__ == "__main__":
+    app.run_server(debug=True)

src/aki_prj23_transparenzregister/ui/dashvis_networkx.py

@@ -0,0 +1,11 @@
+# https://pypi.org/project/dashvis/
+
+import dash
+from dash import html
+from dashvis import DashNetwork
+
+app = dash.Dash()
+app.layout = html.Div([DashNetwork(1)])
+
+if __name__ == "__main__":
+    app.run_server(debug=True)

src/aki_prj23_transparenzregister/ui/networkx_dash.py

@@ -0,0 +1,139 @@
+import pandas as pd
+import networkx as nx
+import plotly.graph_objects as go
+from dash import Dash, Input, Output, dcc, html
+from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider
+from aki_prj23_transparenzregister.utils.sql import connector, entities
+
+test_company = 13 #2213 # 13
+
+def find_company_relations(company_id: int) -> pd.DataFrame:
+    session = connector.get_session(JsonFileConfigProvider("./secrets.json"))
+    query_companies = session.query(entities.Company)
+    query_relations = session.query(entities.CompanyRelation)
+
+    companies_df: pd.DataFrame = pd.read_sql(str(query_companies), session.bind)  # type: ignore
+    companies_relations_df: pd.DataFrame = pd.read_sql(str(query_relations), session.bind)  # type: ignore
+
+    companies_relations_df = companies_relations_df.loc[companies_relations_df["relation_id"] == company_id,:][["relation_id","company_relation_company2_id"]]
+    
+    company_name = []
+    connected_company_name = []
+
+    for _, row in companies_relations_df.iterrows(): 
+        # print(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0])     
+        company_name.append(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0])
+        connected_company_name.append(companies_df.loc[companies_df["company_id"] == row["company_relation_company2_id"]]["company_name"].values[0])
+        
+    # print(company_name)
+    companies_relations_df["company_name"] = company_name
+    companies_relations_df["connected_company_name"] = connected_company_name
+    # print(companies_relations_df)
+    return companies_relations_df
+
+# Plotly figure
+def networkGraph(EGDE_VAR: None) -> go.Figure:
+    # df = find_company_relations(test_company)
+    edges = []
+    for index, row in find_company_relations(test_company).iterrows():
+        edges.append([row["company_name"], row["connected_company_name"]])
+        # print(row["company_name"], row["connected_company_name"])
+    # print(edges)
+    # edges = df[["relation_id","company_relation_company2_id"]]
+    # edges = [[EGDE_VAR, "B"], ["B", "C"], ["B", "D"]]
+    network_graph = nx.Graph()
+    network_graph.add_edges_from(edges)
+    pos = nx.spring_layout(network_graph)
+
+    # edges trace
+    edge_x = []
+    edge_y = []
+    for edge in network_graph.edges():
+        x0, y0 = pos[edge[0]]
+        x1, y1 = pos[edge[1]]
+        edge_x.append(x0)
+        edge_x.append(x1)
+        edge_x.append(None)
+        edge_y.append(y0)
+        edge_y.append(y1)
+        edge_y.append(None)
+
+    edge_trace = go.Scatter(
+        x=edge_x,
+        y=edge_y,
+        line={"color": "black", "width": 1},
+        hoverinfo="none",
+        showlegend=False,
+        mode="lines",
+    )
+
+    # nodes trace
+    node_x = []
+    node_y = []
+    text = []
+    for node in network_graph.nodes():
+        x, y = pos[node]
+        node_x.append(x)
+        node_y.append(y)
+        text.append(node)
+
+    node_trace = go.Scatter(
+        x=node_x,
+        y=node_y,
+        text=text,
+        mode="markers+text",
+        showlegend=False,
+        hoverinfo="none",
+        marker={"color": "pink", "size": 50, "line": {"color": "black", "width": 1}},
+    )
+
+    # layout
+    layout = {
+        "plot_bgcolor": "white",
+        "paper_bgcolor": "white",
+        "margin": {"t": 10, "b": 10, "l": 10, "r": 10, "pad": 0},
+        "xaxis": {
+            "linecolor": "black",
+            "showgrid": False,
+            "showticklabels": False,
+            "mirror": True,
+        },
+        "yaxis": {
+            "linecolor": "black",
+            "showgrid": False,
+            "showticklabels": False,
+            "mirror": True,
+        },
+    }
+
+    # figure
+    return go.Figure(data=[edge_trace, node_trace], layout=layout)
+
+
+# Dash App
+
+
+app = Dash(__name__)
+
+app.title = "Dash Networkx"
+
+app.layout = html.Div(
+    [
+        html.I("Write your EDGE_VAR"),
+        html.Br(),
+        dcc.Input(id="EGDE_VAR", type="text", value="K", debounce=True),
+        dcc.Graph(id="my-graph"),
+    ]
+)
+
+
+@app.callback(
+    Output("my-graph", "figure"),
+    [Input("EGDE_VAR", "value")],
+)
+def update_output(EGDE_VAR: None) -> None:
+    return networkGraph(EGDE_VAR)
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

src/aki_prj23_transparenzregister/ui/networkx_dash_overall.py

@@ -0,0 +1,173 @@
+import pandas as pd
+import networkx as nx
+import plotly.graph_objects as go
+from dash import Dash, Input, Output, dcc, html
+from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider
+from aki_prj23_transparenzregister.utils.sql import connector, entities
+
+test_company = 13 #2213 # 13
+
+def find_all_company_relations() -> pd.DataFrame:
+    session = connector.get_session(JsonFileConfigProvider("./secrets.json"))
+    query_companies = session.query(entities.Company) #.all()
+    query_relations = session.query(entities.CompanyRelation) # .all()
+
+    companies_df: pd.DataFrame = pd.read_sql(str(query_companies), session.bind)  # type: ignore
+    companies_relations_df: pd.DataFrame = pd.read_sql(str(query_relations), session.bind)  # type: ignore
+    # print(companies_relations_df)
+    companies_relations_df = companies_relations_df[["relation_id","company_relation_company2_id"]]
+    # print(companies_relations_df)
+    company_name = []
+    connected_company_name = []
+
+    companies_relations_df = companies_relations_df.head()
+    # print(companies_relations_df)
+
+    for _, row in companies_relations_df.iterrows(): 
+        # print(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0]) 
+        # print("TEst")    
+        company_name.append(companies_df.loc[companies_df["company_id"] == row["relation_id"]]["company_name"].values[0])
+        
+        connected_company_name.append(companies_df.loc[companies_df["company_id"] == row["company_relation_company2_id"]]["company_name"].values[0])
+        # print(connected_company_name)
+        
+    # print(company_name)
+    companies_relations_df["company_name"] = company_name
+    companies_relations_df["connected_company_name"] = connected_company_name
+    # print("Test")
+    # print(companies_relations_df)
+    return companies_relations_df
+
+# Plotly figure
+def networkGraph(EGDE_VAR: None) -> go.Figure:
+    # find_all_company_relations()
+    
+    edges = []
+    for index, row in find_all_company_relations().iterrows():
+        edges.append([row["company_name"], row["connected_company_name"]])
+        # print(row["company_name"], row["connected_company_name"])
+        # print(edges)
+    # edges = df[["relation_id","company_relation_company2_id"]]
+    # edges = [[EGDE_VAR, "B"], ["B", "C"], ["B", "D"]]
+    network_graph = nx.Graph()
+    network_graph.add_edges_from(edges)
+    pos = nx.spring_layout(network_graph)
+
+    # edges trace
+    edge_x = []
+    edge_y = []
+    for edge in network_graph.edges():
+        x0, y0 = pos[edge[0]]
+        x1, y1 = pos[edge[1]]
+        edge_x.append(x0)
+        edge_x.append(x1)
+        edge_x.append(None)
+        edge_y.append(y0)
+        edge_y.append(y1)
+        edge_y.append(None)
+
+    edge_trace = go.Scatter(
+        x=edge_x,
+        y=edge_y,
+        line={"color": "black", "width": 1},
+        hoverinfo="none",
+        showlegend=False,
+        mode="lines",
+    )
+
+    # nodes trace
+    node_x = []
+    node_y = []
+    text = []
+    for node in network_graph.nodes():
+        x, y = pos[node]
+        node_x.append(x)
+        node_y.append(y)
+        text.append(node)
+
+    node_trace = go.Scatter(
+        x=node_x,
+        y=node_y,
+        text=text,
+        mode="markers+text",
+        showlegend=False,
+        hoverinfo="none",
+        marker={"color": "pink", "size": 50, "line": {"color": "black", "width": 1}},
+    )
+
+    # layout
+    layout = {
+        "plot_bgcolor": "white",
+        "paper_bgcolor": "white",
+        "margin": {"t": 10, "b": 10, "l": 10, "r": 10, "pad": 0},
+        "xaxis": {
+            "linecolor": "black",
+            "showgrid": False,
+            "showticklabels": False,
+            "mirror": True,
+        },
+        "yaxis": {
+            "linecolor": "black",
+            "showgrid": False,
+            "showticklabels": False,
+            "mirror": True,
+        },
+    }
+     
+    print(nx.eigenvector_centrality(network_graph))
+    measure_vector = {}
+    network_metrics_df = pd.DataFrame()
+
+    
+    measure_vector = nx.eigenvector_centrality(network_graph)
+    network_metrics_df["eigenvector"] = measure_vector.values()
+
+    measure_vector = nx.degree_centrality(network_graph)
+    network_metrics_df["degree"] = measure_vector.values()
+
+    measure_vector = nx.betweenness_centrality(network_graph)
+    network_metrics_df["betweeness"] = measure_vector.values()
+
+    measure_vector = nx.closeness_centrality(network_graph)
+    network_metrics_df["closeness"] = measure_vector.values()
+
+    # measure_vector = nx.pagerank(network_graph)
+    # network_metrics_df["pagerank"] = measure_vector.values()
+
+    # measure_vector = nx.average_degree_connectivity(network_graph)
+    # network_metrics_df["average_degree"] = measure_vector.values()
+    print(network_metrics_df)
+
+    # figure
+    return go.Figure(data=[edge_trace, node_trace], layout=layout)
+
+
+# Dash App
+
+
+app = Dash(__name__)
+
+app.title = "Dash Networkx"
+
+app.layout = html.Div(
+    [
+        html.I("Write your EDGE_VAR"),
+        html.Br(),
+        # dcc.Dropdown(['eigenvector', 'degree', 'betweeness', 'closeness'], 'eigenvector', id='metric-dropdown'),
+        dcc.Input(id="EGDE_VAR", type="text", value="K", debounce=True),
+        dcc.Graph(id="my-graph"),
+    ]
+)
+
+
+@app.callback(
+    Output("my-graph", "figure"),
+    # Input('metric-dropdown', 'value'),
+    [Input("EGDE_VAR", "value")],
+)
+def update_output(EGDE_VAR: None) -> None:
+    return networkGraph(EGDE_VAR)
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

tests/ui/cytoscape_dash_test.py

@@ -0,0 +1,6 @@
+"""Test for the NetworkX Component."""
+
+
+# def networkGraph(Edges) -> None:
+#     """Checks if an import co company_stats_dash can be made."""
+#     assert networkx_dash is not None

tests/ui/dashvis_networkx_test.py

@@ -0,0 +1,6 @@
+"""Test for the NetworkX Component."""
+
+
+# def networkGraph(Edges) -> None:
+#     """Checks if an import co company_stats_dash can be made."""
+#     assert networkx_dash is not None

tests/ui/networkx_dash_test.py

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