Integrated NetworkX graphs into App

src/aki_prj23_transparenzregister/ui/assets/networkx_style.css

@@ -0,0 +1,17 @@
+.networkx_style {
+    float: right;
+    margin-top: 20px;
+    margin-left: 20px;
+    border: 1px solid;
+    width: 45%;
+    height: 500px;
+}
+
+.top_companytable_style {
+    float: left;
+    margin-top: 20px;
+    margin-right: 20px;
+    border: 1px solid;
+    width: 45%;
+    height: 100%;
+}

src/aki_prj23_transparenzregister/ui/company_elements.py

@@ -10,6 +10,7 @@ from dash import dash_table, dcc, html
 from sqlalchemy.orm import Session
 
 from aki_prj23_transparenzregister.ui import data_elements, finance_elements
+from aki_prj23_transparenzregister.ui.networkx_dash import networkx_component
 
 COLORS = {
     "light": "#edefef",
@@ -353,4 +354,6 @@ def network_layout(selected_company_id: int) -> html:
     Returns:
         The html div to create the network tab of the company page.
     """
-    return html.Div([f"Netzwerk von Unternehmen mit ID: {selected_company_id}"])
+    selected_company_id
+    return networkx_component(selected_company_id)
+    # return html.Div([f"Netzwerk von Unternehmen mit ID: {selected_company_id}"])

src/aki_prj23_transparenzregister/ui/networkx_dash.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import networkx as nx
 import plotly.graph_objects as go
-from dash import Dash, Input, Output, dcc, html
+from dash import Dash, Input, Output, dcc, html, callback
 from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider
 from aki_prj23_transparenzregister.utils.sql import connector, entities
 
@@ -32,10 +32,10 @@ def find_company_relations(company_id: int) -> pd.DataFrame:
     return companies_relations_df
 
 # Plotly figure
-def networkGraph(EGDE_VAR: None) -> go.Figure:
+def networkGraph(company_id: int) -> go.Figure:
     # df = find_company_relations(test_company)
     edges = []
-    for index, row in find_company_relations(test_company).iterrows():
+    for index, row in find_company_relations(company_id).iterrows():
         edges.append([row["company_name"], row["connected_company_name"]])
         # print(row["company_name"], row["connected_company_name"])
     # print(edges)
@@ -113,27 +113,36 @@ def networkGraph(EGDE_VAR: None) -> go.Figure:
 # Dash App
 
 
-app = Dash(__name__)
+# app = Dash(__name__)
 
-app.title = "Dash Networkx"
+# app.title = "Dash Networkx"
 
-app.layout = html.Div(
+# 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"),
+#     ]
+# )
+def networkx_component(company_id: int):
+    
+    layout = html.Div(
     [
-        html.I("Write your EDGE_VAR"),
+        
-        html.Br(),
+        dcc.Graph(id="my-graph", figure=networkGraph(company_id)),
-        dcc.Input(id="EGDE_VAR", type="text", value="K", debounce=True),
-        dcc.Graph(id="my-graph"),
     ]
     )
+    return layout
+
+# callback(
+#     Output("my-graph", "figure", allow_duplicate=True),
+#     [Input("EGDE_VAR", "value")],
+#     prevent_initial_call=True,
+# )
+# def update_output() -> None:
+#     return networkGraph()
 
 
-@app.callback(
+# if __name__ == "__main__":
-    Output("my-graph", "figure"),
+#     app.run(debug=True)
-    [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

@@ -148,14 +148,16 @@ def networkGraph(EGDE_VAR: None) -> go.Figure:
 app = Dash(__name__)
 
 app.title = "Dash Networkx"
-
+# className="networkx_style"
 app.layout = html.Div(
-    [
+    
+    style={'width': '49%'},
+    children = [
         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"),
+        dcc.Graph(id="my-graph", style={'width': '49%'}),
     ]
 )
 

src/aki_prj23_transparenzregister/ui/pages/home.py

@@ -1,6 +1,12 @@
 """Content of home page."""
 import dash
 from dash import html
+import pandas as pd
+import networkx as nx
+import plotly.graph_objects as go
+from dash import Dash, Input, Output, dcc, html, callback
+from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider
+from aki_prj23_transparenzregister.utils.sql import connector, entities
 
 dash.register_page(
     __name__,
@@ -14,9 +20,177 @@ dash.register_page(
     ],
 )
 
+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"
+
 layout = html.Div(
-    [
+    
-        html.H1("This is our Home page", style={"margin": 0}),
+    children = html.Div(
-        html.Div("This is our Home page content."),
+        children=[
+            html.Div(
+                className="top_companytable_style",
+                children=[
+                    html.I("Write your EDGE_VAR")
+                ]
+            ),
+            html.Div(
+                className="networkx_style",
+                children=[
+                    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"),
                     ]
             )
+        ]
+    )
+)
+
+
+@callback(
+    Output("my-graph", "figure"),
+    # Input('metric-dropdown', 'value'),
+    [Input("EGDE_VAR", "value")],
+)
+def update_output(EGDE_VAR: None) -> None:
+    return networkGraph(EGDE_VAR)