Philipp/aki_prj23_transparenzregister
Philipp/aki_prj23_transparenzregister
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Tim 2023-11-04 12:00:23 +01:00
parent c5721362ac
commit 31d7098d48
8 changed files with 33 additions and 50 deletions
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0
src/aki_prj23_transparenzregister/ui/networkx_dash.py → src/aki_prj23_transparenzregister/ui/archive/networkx_dash.py
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2
src/aki_prj23_transparenzregister/ui/ui_elements.py → src/aki_prj23_transparenzregister/ui/archive/ui_elements.py
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@ -8,7 +8,7 @@ from sqlalchemy.engine import Engine
from sqlalchemy.orm import Session
from aki_prj23_transparenzregister.utils.sql import entities
from aki_prj23_transparenzregister.ui.networkx_dash import networkx_component
from aki_prj23_transparenzregister.ui.archive.networkx_dash import networkx_component
COLORS = {
"light": "#edefef",

1
src/aki_prj23_transparenzregister/ui/company_elements.py
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@ -10,7 +10,6 @@ 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
from aki_prj23_transparenzregister.utils.networkx.network_2d import create_2d_graph
from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
from aki_prj23_transparenzregister.utils.networkx.networkx_data import (

55
src/aki_prj23_transparenzregister/ui/pages/home.py
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@ -27,6 +27,7 @@ from aki_prj23_transparenzregister.utils.networkx.networkx_data import (
return_metric_table_df
)
dash.register_page(__name__, path="/")
# Get Data
person_relation = filter_relation_type(
@ -63,19 +64,16 @@ nodes, edges = create_edge_and_node_list(person_relation, company_relation)
graph, metrics = initialize_network(nodes=nodes, edges=edges)
metric = "None"
layout = "Spring"
switch_node_annotaion_value = False
# switch_node_annotaion_value = False
switch_edge_annotaion_value = False
egde_thickness = 1
network = create_3d_graph(graph, nodes, edges, metrics, metric, layout, switch_node_annotaion_value, switch_edge_annotaion_value, egde_thickness)
network = create_3d_graph(graph, nodes, edges, metrics, metric, layout, switch_edge_annotaion_value, egde_thickness)
# Get the possible Filter values for the Dropdowns.
company_relation_type_filter = get_all_person_relations()["relation_type"].unique()
person_relation_type_filter = get_all_company_relations()["relation_type"].unique()
person_relation_type_filter = get_all_person_relations()["relation_type"].unique()
company_relation_type_filter = get_all_company_relations()["relation_type"].unique()
top_companies_df = return_metric_table_df(metrics, nodes, "closeness") #find_top_companies()
# with open("src/aki_prj23_transparenzregister/ui/assets/network_graph.html") as file:
# html_content = file.read()
layout = html.Div(
children=html.Div(
@ -248,19 +246,19 @@ layout = html.Div(
),
],
),
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=["Enable Node Annotation"],
),
html.Div(
className="switch-style",
children=[daq.BooleanSwitch(id="switch_node_annotation", on=False)],
),
],
),
# html.Div(
# className="filter-wrapper-item",
# children=[
# html.H5(
# className="filter-description",
# children=["Enable Node Annotation"],
# ),
# html.Div(
# className="switch-style",
# children=[daq.BooleanSwitch(id="switch_node_annotation", on=False)],
# ),
# ],
# ),
html.Div(
className="filter-wrapper-item",
children=[
@ -292,7 +290,6 @@ def update_graph_data(
# Get Data
person_df = get_all_person_relations()
company_df = get_all_company_relations()
# print(company_df)
person_relation = filter_relation_type(person_df, person_relation_type)
company_relation = filter_relation_type(company_df, company_relation_type)
@ -311,7 +308,7 @@ def update_graph_data(
[
Input("dropdown", "value"),
Input("switch", "on"),
Input("switch_node_annotation", "on"),
# Input("switch_node_annotation", "on"),
Input("switch_edge_annotation", "on"),
Input("dropdown_company_relation_filter", "value"),
Input("dropdown_person_relation_filter", "value"),
@ -325,7 +322,7 @@ def update_graph_data(
def update_figure(
selected_metric: str,
switch_value: bool,
switch_node_annotaion_value: bool,
# switch_node_annotaion_value: bool,
switch_edge_annotaion_value: bool,
c_relation_filter_value: str,
p_relation_filter_value: str,
@ -344,18 +341,13 @@ def update_figure(
Network Graph(Plotly Figure): Plotly Figure in 3 or 2D
"""
_ = c_relation_filter_value, p_relation_filter_value
# triggered_id = ctx.triggered_id
# if triggered_id == 'dropdown_companyrelation_filter' or triggered_id == 'dropdown_personrelation_filter':
# print(selected_value)
# print(metrics)
# print(graph)
graph, metrics, nodes, edges = update_graph_data(person_relation_type= p_relation_filter_value, company_relation_type= c_relation_filter_value)
if switch_value:
return create_2d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_node_annotaion_value, switch_edge_annotaion_value, slider_value)
return create_2d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_edge_annotaion_value, slider_value)
else:
return create_3d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_node_annotaion_value, switch_edge_annotaion_value, slider_value)
return create_3d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_edge_annotaion_value, slider_value)
@callback(
@ -367,10 +359,7 @@ def update_figure(
def update_table(metric_dropdown_value: str) -> dict:
table_df = return_metric_table_df(metrics, nodes, metric_dropdown_value)
table_df.to_dict("records")
# print(table_df.to_dict("records"))
columns =[{"name": i, "id": i} for i in table_df.columns]
# print(columns)
return table_df.to_dict("records")

6
src/aki_prj23_transparenzregister/utils/networkx/network_2d.py
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@ -6,7 +6,7 @@ import plotly.graph_objects as go
def create_2d_graph(
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, node_annotation: bool, edge_annotation: bool, edge_thickness: int
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, edge_annotation: bool, edge_thickness: int
) -> go.Figure:
"""This Method creates a 2d Network in Plotly with a Scatter Graph and retuns it.
@ -141,9 +141,7 @@ def create_2d_graph(
edge_weights_trace.text = edge_type_list
# print(edge_type_list)
if node_annotation:
print("Test")
# node_trace.text = nodes.
# Return the Plotly Figure
return go.Figure(

2
src/aki_prj23_transparenzregister/utils/networkx/network_3d.py
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@ -6,7 +6,7 @@ import plotly.graph_objects as go
def create_3d_graph(
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, node_annotation: bool, edge_annotation: bool, edge_thickness: int
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, edge_annotation: bool, edge_thickness: int
) -> go.Figure:
"""This Method creates a 3D Network in Plotly with a Scatter Graph and retuns it.

5
src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py
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@ -158,10 +158,7 @@ def filter_relation_type(
Returns:
relation_dataframe (pd.DataFrame): The filtered DataFrame which now only contains entries with the selected Relation Type.
"""
print(selected_relation_type)
print(relation_dataframe.loc[
relation_dataframe["relation_type"] == selected_relation_type
])
return relation_dataframe.loc[
relation_dataframe["relation_type"] == selected_relation_type
]

8
tests/ui/home_page_test.py
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@ -1,7 +1,7 @@
"""Test for the Home Page."""
# from aki_prj23_transparenzregister.ui.pages.home import networkx_dash
from aki_prj23_transparenzregister.ui.pages import home
# def networkGraph(Edges: None) -> None:
# """Checks if an import co company_stats_dash can be made."""
# assert networkx_dash is not None
def test_import() -> None:
"""Checks if an import co company_stats_dash can be made."""
assert home is not None