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[bokeh-nx]Script to create interactive bokeh networkx plots. #bokeh #networkx
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| import networkx as nx | |
| from collections import namedtuple | |
| from math import sqrt | |
| import bokeh | |
| from bokeh.models import HoverTool | |
| from bokeh.plotting import show, figure | |
| from bokeh.colors import RGB | |
| import random | |
| #corresponding package on pypi is confusingly called python-louvain | |
| import community | |
| def create_bokeh_graph(graph): | |
| def gen_edge_coordinates(graph, layout): | |
| xs = [] | |
| ys = [] | |
| val = namedtuple("edges", "xs ys") | |
| for edge in graph.edges(): | |
| from_node = layout[edge[0]] | |
| to_node = layout[edge[1]] | |
| xs.append([from_node[0],to_node[0]]) | |
| ys.append([from_node[1], to_node[1]]) | |
| return val(xs=xs, ys=ys) | |
| def gen_node_coordinates(layout): | |
| names, coords = zip(*layout.items()) | |
| xs, ys = zip(*coords) | |
| val = namedtuple("nodes", "names xs ys") | |
| return val(names=names, xs=xs, ys=ys) | |
| #Calc Layout - Slowest Part | |
| plot_layout = nx.spring_layout(graph, | |
| k=1/(sqrt(graph.number_of_nodes() * 0.75)), | |
| iterations=60, | |
| scale = 2) | |
| _nodes = gen_node_coordinates(plot_layout) | |
| _edges = gen_edge_coordinates(graph, plot_layout) | |
| #Prepare Bokeh-Figure | |
| hover = HoverTool(tooltips=[('name', '@name'), | |
| ('node_id', '$index'), | |
| ('degree', '@degree'), | |
| ('betweenness centrality', '@betweenness'), | |
| ('clustering', '@clustering'), | |
| ('cluster_nr', '@community_nr')], names=["show_hover"]) | |
| fig = figure(width=800, height=600, | |
| tools=[hover, 'box_zoom', 'resize', 'reset', 'wheel_zoom', 'pan', 'lasso_select'], | |
| logo = None) | |
| fig.toolbar.logo = None | |
| fig.axis.visible = False | |
| fig.xgrid.grid_line_color = None | |
| fig.ygrid.grid_line_color = None | |
| #Draw Edges | |
| source_edges = bokeh.models.ColumnDataSource(dict(xs=_edges.xs, ys=_edges.ys)) | |
| fig.multi_line('xs', 'ys', line_color='navy', source=source_edges, alpha=0.17) | |
| #Calc numbers | |
| degrees = list(nx.degree(graph).values()) | |
| clustering = list(nx.clustering(graph).values()) | |
| communs = community.best_partition(graph) | |
| nodes, communities = zip(*communs.items()) | |
| betw = list(nx.betweenness_centrality(graph).values()) | |
| #create Colormaps | |
| colormap_coms = {x : RGB(random.randrange(0,256),random.randrange(0,256),random.randrange(0,256)) | |
| for x in list(set(communities))} | |
| community_color_list, community_nr = zip(*[(colormap_coms[communs[node]], communs[node]) for node in nodes]) | |
| graph_nodes = graph.number_of_nodes() | |
| colors = ['firebrick' for node in range(graph_nodes)] | |
| #Draw circles | |
| source_nodes = bokeh.models.ColumnDataSource(dict(xs=_nodes.xs, ys=_nodes.ys, name=_nodes.names, | |
| single_color = colors, | |
| color_by_community = community_color_list, | |
| degree=degrees, | |
| clustering=clustering, community_nr=community_nr, | |
| betweenness = betw)) | |
| r_circles = fig.circle('xs', 'ys', fill_color='single_color', line_color='single_color', | |
| source = source_nodes, alpha=0.7, size=9, name="show_hover") | |
| #Create Color-Selector | |
| colorcallback = bokeh.models.callbacks.CustomJS(args=dict(source=source_nodes, circles=r_circles), code=""" | |
| var value = cb_obj.get('value'); | |
| circles.glyph.line_color.field = value; | |
| circles.glyph.fill_color.field = value; | |
| source.trigger('change') | |
| """) | |
| button = bokeh.models.widgets.Select(title="Color", value="single_color", | |
| options=["single_color", "color_by_community"], | |
| callback=colorcallback) | |
| #Create grid and save | |
| layout_plot = bokeh.layouts.gridplot([[fig, button]]) | |
| #if file is wanted | |
| #bokeh.io.output_file(f"graph.html") | |
| #bokeh.io.save(layout_plot) | |
| show(layout_plot) | |
| #working example | |
| #graph = nx.barbell_graph(5,6) | |
| #create_bokeh_graph(graph) |
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