bokeh学习总结_关系图绘制

最近在学习《Python数据可视化：基于Bokeh的可视化绘图》，因此这个系列主要是学习过程中的一些记录，很多代码都是书上的实例，本人只是做个记录

Bokeh (Bokeh.js) 是一个 Python 交互式可视化库，支持现代化 Web 浏览器，提供非常完美的展示功能。Bokeh 的目标是使用 D3.js 样式提供优雅，简洁新颖的图形化风格，同时提供大型数据集的高性能交互功能。Boken 可以快速的创建交互式的绘图，仪表盘和数据应用。

 

bokeh.models.graphs

import networkx as nx
from bokeh.io import show, curdoc
from bokeh.layouts import Row, Column
from bokeh.models import Plot, Range1d, MultiLine, Circle, HoverTool, TapTool, BoxSelectTool
from bokeh.models.graphs import from_networkx, NodesAndLinkedEdges, EdgesAndLinkedNodes
from bokeh.palettes import Spectral4
G=nx.karate_club_graph()
def create_graph(layout_func, inspection_policy=None, selection_policy=None, **kwargs):

    plot = Plot(plot_width=400, plot_height=400,
                x_range=Range1d(-1.1,1.1), y_range=Range1d(-1.1,1.1))
    graph_renderer = from_networkx(G, layout_func, **kwargs)

    graph_renderer.node_renderer.glyph = Circle(size=15, fill_color=Spectral4[0])
    graph_renderer.node_renderer.selection_glyph = Circle(size=15, fill_color=Spectral4[2])
    graph_renderer.node_renderer.hover_glyph = Circle(size=15, fill_color=Spectral4[1])

    graph_renderer.edge_renderer.glyph = MultiLine(line_color="#CCCCCC", line_alpha=0.8, line_width=5)
    graph_renderer.edge_renderer.selection_glyph = MultiLine(line_color=Spectral4[2], line_width=5)
    graph_renderer.edge_renderer.hover_glyph = MultiLine(line_color=Spectral4[1], line_width=5)

    graph_renderer.inspection_policy = inspection_policy
    graph_renderer.selection_policy = selection_policy

    plot.renderers.append(graph_renderer)

    return plot

plot_1 = create_graph(nx.circular_layout, inspection_policy=NodesAndLinkedEdges(), scale=1, center=(0,0))
plot_1.title.text = "Circular Layout (NodesAndLinkedEdges inspection policy)"
plot_1.add_tools(HoverTool(tooltips=None))

plot_2 = create_graph(nx.spring_layout, selection_policy=NodesAndLinkedEdges(), scale=2, center=(0,0))
plot_2.title.text = "Spring Layout (NodesAndLinkedEdges selection policy)"
plot_2.add_tools(TapTool(), BoxSelectTool())

plot_3 = create_graph(nx.random_layout, inspection_policy=EdgesAndLinkedNodes(), center=(0,0))
plot_3.title.text = "Random Layout (EdgesAndLinkedNodes inspection policy)"
plot_3.add_tools(HoverTool(tooltips=None))

plot_4 = create_graph(nx.fruchterman_reingold_layout, selection_policy=EdgesAndLinkedNodes(), scale=2, center=(0,0), dim=2)
plot_4.title.text = "FR Layout (EdgesAndLinkedNodes selection policy)"
plot_4.add_tools(TapTool())

layout = Column(Row(plot_1, plot_2), Row(plot_3, plot_4))
show(layout)