def visualize_graph_html(nx_graph,
output_dir=None,
title_text='',
layout='kamada_kawai',
should_show=False):
"""
This method visualizes a NetworkX graph using Bokeh.
:param nx_graph: NetworkX graph with node attributes containing image filenames.
:param output_dir: Optional output directory for saving html.
:param title_text: String to be displayed above the visualization.
:param layout: Which layout function to use.
:param should_show: Open the browser to look at the graph.
"""
from bokeh import palettes
from bokeh.io import output_file, show
from bokeh.models import Circle, HoverTool, MultiLine, Plot, Range1d, TapTool
# noinspection PyProtectedMember
from bokeh.models.graphs import from_networkx, NodesAndLinkedEdges, NodesOnly
pos = parse_layout(nx_graph, layout)
hover_tool = HoverTool(
tooltips='<img src="@imgs" height="200" alt="@imgs" width="200"></img>',
show_arrow=False)
plot = Plot(plot_width=800,
plot_height=800,
x_range=Range1d(-1.1, 1.1),
y_range=Range1d(-1.1, 1.1))
if title_text != '':
plot.title.text = title_text
plot.title.align = 'center'
plot.min_border = 0
plot.outline_line_color = None
plot.add_tools(hover_tool, TapTool())
plot.toolbar.logo = None
plot.toolbar_location = None
graph_renderer = from_networkx(nx_graph, pos)
graph_renderer.node_renderer.data_source.data['imgs'] = [
n[1]['img'] for n in nx_graph.nodes(data=True)
]
graph_renderer.node_renderer.glyph = Circle(
size=10, fill_color=palettes.Spectral4[0], line_color=None)
graph_renderer.node_renderer.selection_glyph = Circle(
size=10, fill_color=palettes.Spectral4[2], line_color=None)
graph_renderer.node_renderer.hover_glyph = Circle(
size=10, fill_color=palettes.Spectral4[1], line_color=None)
graph_renderer.edge_renderer.glyph = MultiLine(line_color='#CCCCCC',
line_alpha=0.8,
line_width=1.5)
graph_renderer.edge_renderer.selection_glyph = MultiLine(
line_color=palettes.Spectral4[2], line_width=2)
graph_renderer.selection_policy = NodesAndLinkedEdges()
graph_renderer.inspection_policy = NodesOnly()
plot.renderers.append(graph_renderer)
if output_dir:
ensure_dir_exists(output_dir)
output_file(join(output_dir, 'visualize_graph.html'))
if should_show:
show(plot)
