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app.py
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app.py
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import networkx as nx
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
from dash.dependencies import Input, Output
# Generate a random graph
def generate_random_graph(num_nodes, num_edges, graph_type):
if graph_type == 'erdos_renyi':
G = nx.erdos_renyi_graph(num_nodes, num_edges)
elif graph_type == 'barabasi_albert':
if isinstance(num_edges, float):
num_edges = int(num_edges)
G = nx.barabasi_albert_graph(num_nodes, num_edges)
elif graph_type == 'watts_strogatz':
if isinstance(num_edges, float):
num_edges = int(num_edges)
G = nx.watts_strogatz_graph(num_nodes, num_edges, 0.3) # p metric is already filled
elif graph_type == 'random_geometric':
G = nx.random_geometric_graph(num_nodes, 0.3) #radius is already selected
elif graph_type == 'connected_caveman':
if isinstance(num_edges, float):
num_edges = int(num_edges)
G = nx.connected_caveman_graph(num_nodes, num_edges // num_nodes) #cliques
else:
G = nx.erdos_renyi_graph(num_nodes, num_edges) # Default to Erdős-Rényi graph
return G
# Create a Dash application
app = dash.Dash(__name__)
# Custom CSS styles
external_stylesheets = ['https://stackpath.bootstrapcdn.com/bootswatch/4.5.2/lux/bootstrap.min.css']
# Layout for Dash application
app.layout = html.Div(style={'font-family': 'Arial, sans-serif', 'background-color': '#f8f9fa', 'color': '#495057', 'padding': '20px'}, children=[
html.H1('GRAPHY', style={'text-align': 'center', 'color': '#007bff', 'font-size': '36px', 'margin-bottom': '20px'}),
html.Div([
html.Div([
html.Label('Graph Type:', style={'font-weight': 'bold', 'font-size': '18px'}),
dcc.Dropdown(
id='dropdown-graph-type',
options=[
{'label': 'Erdős-Rényi', 'value': 'erdos_renyi'},
{'label': 'Barabási-Albert', 'value': 'barabasi_albert'},
{'label': 'Watts-Strogatz', 'value': 'watts_strogatz'},
{'label': 'Random Geometric', 'value': 'random_geometric'},
{'label': 'Connected Caveman', 'value': 'connected_caveman'}
],
value='erdos_renyi',
style={'width': '50%', 'margin-bottom': '10px', 'font-size': '16px'}
),
], style={'margin-bottom': '20px'}),
html.Div([
html.Label('Graph Layout:', style={'font-weight': 'bold', 'font-size': '18px'}),
dcc.Dropdown(
id='dropdown-layout',
options=[
{'label': 'Spring Layout', 'value': 'spring'},
{'label': 'Circular Layout', 'value': 'circular'},
{'label': 'Random Layout', 'value': 'random'},
{'label': 'Kamada-Kawai Layout', 'value': 'kamada_kawai'},
{'label': 'Fruchterman-Reingold Layout', 'value': 'fruchterman_reingold'}
],
value='spring',
style={'width': '50%', 'margin-bottom': '10px', 'font-size': '16px'}
),
], style={'margin-bottom': '20px'}),
html.Div([
html.Label('Number of Nodes:', style={'font-weight': 'bold', 'font-size': '18px'}),
dcc.Input(
id='input-num-nodes',
type='number',
value=20,
min=2,
max=100,
step=1,
style={'width': '10%', 'margin-right': '20px', 'font-size': '16px'}
),
html.Label('Number of Edges:', style={'font-weight': 'bold', 'font-size': '18px'}),
dcc.Input(
id='input-num-edges',
type='number',
value=30,
min=1,
max=200,
step=0.1,
style={'width': '10%', 'margin-right': '20px', 'font-size': '16px'}
),
], style={'margin-bottom': '20px'}),
], className='container'),
dcc.Graph(id='graph-visualization', style={'height': '70vh'}),
])
# Callback to update graph based on user input
@app.callback(
Output('graph-visualization', 'figure'),
[Input('dropdown-graph-type', 'value'),
Input('input-num-nodes', 'value'),
Input('input-num-edges', 'value'),
Input('dropdown-layout', 'value')]
)
def update_graph(graph_type, num_nodes, num_edges, layout_algorithm):
num_nodes = int(num_nodes)
num_edges = float(num_edges)
# Generate the random graph
G = generate_random_graph(num_nodes, num_edges, graph_type)
# Create positions for the nodes
if layout_algorithm == 'spring':
pos = nx.spring_layout(G)
elif layout_algorithm == 'circular':
pos = nx.circular_layout(G)
elif layout_algorithm == 'random':
pos = nx.random_layout(G)
elif layout_algorithm == 'kamada_kawai':
pos = nx.kamada_kawai_layout(G)
elif layout_algorithm == 'fruchterman_reingold':
pos = nx.fruchterman_reingold_layout(G)
else:
pos = nx.spring_layout(G) # Default to Spring layout
# Calculate degree centrality for coloring nodes
node_degrees = nx.degree_centrality(G)
node_colors = [node_degrees[node] for node in G.nodes()]
# Plotly trace for edges
edge_trace = go.Scatter(
x=[],
y=[],
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines'
)
# Populate edge_trace with data from G
for edge in G.edges():
x0, y0 = pos[edge[0]]
x1, y1 = pos[edge[1]]
edge_trace['x'] += tuple([x0, x1, None])
edge_trace['y'] += tuple([y0, y1, None])
# Plotly trace for nodes
node_trace = go.Scatter(
x=[],
y=[],
text=[],
mode='markers',
hoverinfo='text',
marker=dict(
showscale=True,
colorscale='YlGnBu',
reversescale=True,
color=node_colors, # Assign node colors based on degree centrality
size=10,
colorbar=dict(
thickness=15,
title='Node Attribute',
xanchor='left',
titleside='right'
),
line=dict(width=2)
)
)
# Populate node_trace with data from G
for node in G.nodes():
x, y = pos[node]
node_trace['x'] += tuple([x])
node_trace['y'] += tuple([y])
node_trace['text'] += tuple([f'Node {node}<br>Degree Centrality: {node_degrees[node]:.2f}'])
# Create figure object
figure = {
'data': [edge_trace, node_trace],
'layout': go.Layout(
title='Graph Visualized',
titlefont=dict(size=24, family='Arial, sans-serif', color='#007bff'),
showlegend=False,
hovermode='closest',
margin=dict(b=20, l=5, r=5, t=40),
annotations=[],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
plot_bgcolor='#f8f9fa', # Background color
paper_bgcolor='#f8f9fa' # Background color
)
}
return figure
# Main function to run the app
if __name__ == '__main__':
app.run_server(debug=True, port=8050)