Philipp/aki_prj23_transparenzregister
Philipp/aki_prj23_transparenzregister
1
0
Fork 0
mirror of https://github.com/fhswf/aki_prj23_transparenzregister.git synced 2025-05-14 10:38:45 +02:00
Code Issues Packages Projects Releases Wiki Activity

Added more customizing

Browse Source
This commit is contained in:
Tim 2023-10-30 10:47:02 +01:00
parent 30f9e4506f
commit b594add257
4 changed files with 185 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
src/aki_prj23_transparenzregister/ui/assets/networkx_style.css
View File

@ -74,6 +74,7 @@
margin-top: 1px;
padding-left: 10px;
width: 80%;
display: inline-block;
/* background-color: var(--raisin-black); */
}
@ -81,7 +82,7 @@
.networkx_style .switch-style .jAjsxw {
align-self: left;
float: none;
display: inline;
display: inline-block;
padding: 0px;
margin: 0px;
@ -90,12 +91,14 @@
}
.networkx_style .graph-style {
margin-top: 10px;
padding-bottom: 0px;
display: inline;
display: inline-block;
margin: 0px;
width: 100%;
height: 100%;
/* float: inline-end, */
/* background-color: var(--raisin-black); */
}

130
src/aki_prj23_transparenzregister/ui/pages/home.py
View File

@ -56,6 +56,18 @@ graph, metrices = initialize_network(nodes = nodes, edges = edges)
# print(graph)
metric = None
network = create_3d_graph(graph, nodes, edges, metrics, metric)
# Create Edge and Node List from data
nodes, edges = create_edge_and_node_list(person_relation, company_relation)
# Initialize the Network and receive the Graph and a DataFrame with Metrics
node_count = len(nodes)
edge_count = len(edges)
graph, metrics = initialize_network(nodes=nodes, edges=edges)
metric = "None"
layout = "Spring"
switch_node_annotaion_value = False
switch_edge_annotaion_value = True
egde_thickness = 1
network = create_3d_graph(graph, nodes, edges, metrics, metric, layout, switch_node_annotaion_value, 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()
@ -136,21 +148,112 @@ layout = html.Div(
),
],
),
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=["Choose Layout:"],
),
dcc.Dropdown(
[
"Spring",
# "Bipartite",
"Circular",
"Kamada Kawai",
"Planar",
"Random",
"Shell",
"Spectral",
"Spiral",
"Multipartite"
],
"Spring",
id="dropdown_layout",
className="dropdown_style",
),
],
),
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=["Adjust Edge Thickness"],
),
dcc.Slider( 1, 4, 1,
value=1,
id='slider',
),
],),
],
),
html.Div(
className="filter-wrapper-item",
className="filter-wrapper",
children=[
html.H5(
className="filter-description",
children=["Switch to 2D Diagramm"],
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=["Switch to 2D Diagramm"],
),
html.Div(
className="switch-style",
children=[daq.BooleanSwitch(id="switch", on=False)],
),
],
),
html.Div(
className="switch-style",
children=[daq.BooleanSwitch(id="switch", on=False)],
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 Edge Annotation"],
),
html.Div(
className="switch-style",
children=[daq.BooleanSwitch(id="switch_edge_annotation", on=False)],
),
],
),
],
),
html.Div(
className="filter-wrapper",
children=[
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=[f"""Number of shown Nodes: {node_count}"""],
),
],),
html.Div(
className="filter-wrapper-item",
children=[
html.H5(
className="filter-description",
children=[f"""Number of shown Edges: {edge_count}"""],
),
],),
],
),
dcc.Graph(figure=network, id="my-graph", className="graph-style"),
],
),
@ -174,6 +277,8 @@ def update_graph_data(
# Create Edge and Node List from data
nodes, edges = create_edge_and_node_list(person_relation, company_relation)
# node_count = len(nodes)
# edge_count = len(edges)
graph, metrics = initialize_network(nodes=nodes, edges=edges)
return graph, metrics
@ -184,8 +289,12 @@ def update_graph_data(
[
Input("dropdown", "value"),
Input("switch", "on"),
Input("switch_node_annotation", "on"),
Input("switch_edge_annotation", "on"),
Input("dropdown_company_relation_filter", "value"),
Input("dropdown_person_relation_filter", "value"),
Input("dropdown_layout", "value"),
Input('slider', 'value')
],
prevent_initial_call=True,
allow_duplicate=True,
@ -194,8 +303,12 @@ def update_graph_data(
def update_figure(
selected_metric: str,
switch_value: bool,
switch_node_annotaion_value: bool,
switch_edge_annotaion_value: bool,
c_relation_filter_value: str,
p_relation_filter_value: str,
layout: str,
slider_value: float
) -> go.Figure:
"""In this Callback the Value of the Dropdown is used to filter the Data. In Addition it takes the filter for the Graph metrics and creates a new graph, or switches between 3D and 2D.
@ -217,10 +330,11 @@ def update_figure(
# print(graph)
graph, metrics = 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)
return create_2d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_node_annotaion_value, switch_edge_annotaion_value, slider_value)
else:
return create_3d_graph(graph, nodes, edges, metrics, selected_metric)
return create_3d_graph(graph, nodes, edges, metrics, selected_metric, layout, switch_node_annotaion_value, switch_edge_annotaion_value, slider_value)

42
src/aki_prj23_transparenzregister/utils/networkx/network_2d.py
View File

@ -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
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, node_annotation: bool, edge_annotation: bool, edge_thickness: int
) -> go.Figure:
"""This Method creates a 2d Network in Plotly with a Scatter Graph and retuns it.
@ -20,8 +20,29 @@ def create_2d_graph(
Returns:
_type_: Plotly Figure
"""
# Set 2D Layout
# Set 2D Layout
pos = nx.spring_layout(graph)
match layout:
case "Spring":
pos = nx.spring_layout(graph)
# case "Bipartite":
# pos = nx.bipartite_layout(graph)
case "Circular":
pos = nx.circular_layout(graph)
case "Kamada Kawai":
pos = nx.kamada_kawai_layout(graph)
# case "Planar":
# pos = nx.planar_layout(graph)
case "Random":
pos = nx.random_layout(graph)
case "Shell":
pos = nx.shell_layout(graph)
# case "Spectral":
# pos = nx.spectral_layout(graph)
case "Spiral":
pos = nx.spiral_layout(graph)
# case "Multipartite":
# pos = nx.multipartite_layout(graph)
# Initialize Variables to set the Position of the Edges.
edge_x = []
@ -90,7 +111,7 @@ def create_2d_graph(
"xanchor": "left",
"titleside": "right",
},
"line_width": 2,
"line_width": edge_thickness,
},
)
@ -111,12 +132,17 @@ def create_2d_graph(
if metric != "None":
node_trace.marker.size = list(np.sqrt(metrics[metric]) * 200)
# Add Relation_Type as a Descriptin for the edges.
edge_type_list = []
for row in edges:
edge_type_list.append(row["type"])
# Add Relation_Type as a Description for the edges.
if edge_annotation:
edge_type_list = []
for row in edges:
edge_type_list.append(row["type"])
edge_weights_trace.text = edge_type_list
edge_weights_trace.text = edge_type_list
if node_annotation:
print("Test")
# node_trace.text = nodes.
# Return the Plotly Figure
return go.Figure(

27
src/aki_prj23_transparenzregister/utils/networkx/network_3d.py
View File

@ -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
graph: nx.Graph, nodes: dict, edges: list, metrics: pd.DataFrame, metric: str | None, layout: str, node_annotation: bool, edge_annotation: bool, edge_thickness: int
) -> go.Figure:
"""This Method creates a 3D Network in Plotly with a Scatter Graph and retuns it.
@ -21,7 +21,28 @@ def create_3d_graph(
_type_: Plotly Figure
"""
# 3d spring layout
pos = nx.spring_layout(graph, dim=3, seed=779)
pos = nx.spring_layout(graph, dim=3)
match layout:
case "Spring":
pos = nx.spring_layout(graph, dim=3)
# case "Bipartite":
# pos = nx.bipartite_layout(graph, dim=3)
case "Circular":
pos = nx.circular_layout(graph, dim=3)
case "Kamada Kawai":
pos = nx.kamada_kawai_layout(graph, dim=3)
# case "Planar":
# pos = nx.planar_layout(graph, dim=3)
case "Random":
pos = nx.random_layout(graph, dim=3)
# case "Shell":
# pos = nx.shell_layout(graph, dim=3)
# case "Spectral":
# pos = nx.spectral_layout(graph, dim=3)
# case "Spiral":
# pos = nx.spiral_layout(graph, dim=3)
# case "Multipartite":
# pos = nx.multipartite_layout(graph, dim=3)
# Initialize Variables to set the Position of the Edges.
edge_x = []
@ -140,7 +161,7 @@ def create_3d_graph(
edge_colors.append("rgb(255,0,0)")
else:
edge_colors.append("rgb(255,105,180)")
edge_trace.line = {"color": edge_colors, "width": 2}
edge_trace.line = {"color": edge_colors, "width": edge_thickness}
# Return the Plotly Figure
data = [edge_trace, node_trace]