I am trying to display a graph using networkx with bokeh 12.7 that
- Has node size based on node degrees
- Color based on another node attribute.
Desired Output:
Data Setup
import pandas as pd
import numpy as np
import networkx as nx
import seaborn as sns
from bokeh.io import show, output_notebook #output_file,
from bokeh.plotting import figure
from bokeh.models.graphs import from_networkx
from bokeh.models import GraphRenderer, StaticLayoutProvider, LinearColorMapper, ColumnDataSource
from bokeh.palettes import Spectral8, Spectral4
G = nx.karate_club_graph()
# Some Random index
node_color = {k:v for k, v in enumerate(np.random.uniform(low=0, high=21, size=(G.number_of_nodes(),)).round(1))}
# Set node attributes
nx.set_node_attributes(G, 'node_color', node_color)
nx.set_node_attributes(G, 'node_size', G.degree())
Try to graph using bokeh with cubehelix_palette
# Map cubehelix_palette
palette = sns.cubehelix_palette(21)
pal_hex_lst = palette.as_hex()
mapper = LinearColorMapper(palette=pal_hex_lst, low=0, high=21)
# Initiate bokeh plot
plot = figure(title="Resized Node Demo", x_range=(-1.1,1.1), y_range=(-1.1,1.1),
tools="", toolbar_location=None)
# Graph renderer using nx
graph = from_networkx(G, nx.spring_layout, scale=2, center=(0,0))
# Style node
graph.node_renderer.glyph = Circle(size='node_size', fill_color={'field': 'node_color', 'transform': mapper})
plot.renderers.append(graph)
output_notebook()
#output_file("networkx_graph.html")
show(plot)
Which gives this error: Glyph refers to nonexistent column name
I also tried this:
# 1. Create Plot container
plot = figure(title=endNode, x_range=(-1.1,1.1), y_range=(-1.1,1.1),
tools="", toolbar_location=None)
# 2. Create graph plot comtainer
graph = GraphRenderer()
node_link_dict = nx.readwrite.json_graph.node_link_data(G)
node_df = pd.DataFrame(node_link_dict['nodes'])
node_cds = ColumnDataSource.from_df(graph_data.node_df)
graph.node_renderer.data_source.data = node_cds
# 3. Set Node Style
graph.node_renderer.glyph = Circle(size='node_size', fill_color='node_color')
Any thoughts?


