Tree plotting in Python

问题:

I want to plot trees using Python. Decision trees, Organizational charts, etc. Any library that helps me with that?

回答1:

There's graphviz - http://www.graphviz.org/. It uses the "DOT" language to plot graphs. You can either generate the DOT code yourself, or use pydot - https://code.google.com/p/pydot/. You could also use networkx - http://networkx.lanl.gov/tutorial/tutorial.html#drawing-graphs, which make it easy to draw to either graphviz or matplotlib.

networkx + matplotlib + graphviz gives you the most flexibility and power, but you need to install a lot.

If you want a quick solution, try:

Install Graphviz.

open('hello.dot','w').write("digraph G {Hello->World}") import subprocess subprocess.call(["path/to/dot.exe","-Tpng","hello.dot","-o","graph1.png"])  # I think this is right - try it form the command line to debug 

Then you install pydot, because pydot already does this for you. Then you can use networkx to "drive" pydot.

回答2:

I develop ETE, which is a python package intended, among other stuff, for programmatic tree rendering and visualization. You can create your own layout functions and produce custom tree images:

It has a focus on phylogenetics, but it can actually deal with any type of hierarchical tree (clustering, decision trees, etc.)

回答3:

Plotly can plot tree diagrams using igraph. You can use it offline these days too. The example below is intended to be run in a Jupyter notebook

import plotly.plotly as py import plotly.graph_objs as go  import igraph from igraph import * # I do not endorse importing * like this  #Set Up Tree with igraph  nr_vertices = 25 v_label = map(str, range(nr_vertices)) G = Graph.Tree(nr_vertices, 2) # 2 stands for children number lay = G.layout('rt')  position = {k: lay[k] for k in range(nr_vertices)} Y = [lay[k][1] for k in range(nr_vertices)] M = max(Y)  es = EdgeSeq(G) # sequence of edges E = [e.tuple for e in G.es] # list of edges  L = len(position) Xn = [position[k][0] for k in range(L)] Yn = [2*M-position[k][1] for k in range(L)] Xe = [] Ye = [] for edge in E:     Xe+=[position[edge[0]][0],position[edge[1]][0], None]     Ye+=[2*M-position[edge[0]][1],2*M-position[edge[1]][1], None]   labels = v_label  #Create Plotly Traces  lines = go.Scatter(x=Xe,                    y=Ye,                    mode='lines',                    line=dict(color='rgb(210,210,210)', width=1),                    hoverinfo='none'                    ) dots = go.Scatter(x=Xn,                   y=Yn,                   mode='markers',                   name='',                   marker=dict(symbol='dot',                                 size=18,                                  color='#6175c1',    #'#DB4551',                                  line=dict(color='rgb(50,50,50)', width=1)                                 ),                   text=labels,                   hoverinfo='text',                   opacity=0.8                   )  # Create Text Inside the Circle via Annotations  def make_annotations(pos, text, font_size=10,                       font_color='rgb(250,250,250)'):     L=len(pos)     if len(text)!=L:         raise ValueError('The lists pos and text must have the same len')     annotations = go.Annotations()     for k in range(L):         annotations.append(             go.Annotation(                 text=labels[k], # or replace labels with a different list                                  # for the text within the circle                   x=pos[k][0], y=2*M-position[k][1],                 xref='x1', yref='y1',                 font=dict(color=font_color, size=font_size),                 showarrow=False)         )     return annotations    # Add Axis Specifications and Create the Layout  axis = dict(showline=False, # hide axis line, grid, ticklabels and  title             zeroline=False,             showgrid=False,             showticklabels=False,             )  layout = dict(title= 'Tree with Reingold-Tilford Layout',                 annotations=make_annotations(position, v_label),               font=dict(size=12),               showlegend=False,               xaxis=go.XAxis(axis),               yaxis=go.YAxis(axis),                         margin=dict(l=40, r=40, b=85, t=100),               hovermode='closest',               plot_bgcolor='rgb(248,248,248)'                         )  # Plot  data=go.Data([lines, dots]) fig=dict(data=data, layout=layout) fig['layout'].update(annotations=make_annotations(position, v_label)) py.iplot(fig, filename='Tree-Reingold-Tilf') # use py.plot instead of py.iplot if you're not using a Jupyter notebook 

Output

回答4:

It's expirmental, but Google has a GraphViz api. It's convenient if you just want to quickly visualize a graph, but don't want to install any software.

文章来源: Tree plotting in Python