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Tree-plots in Python

How to make interactive tree-plot in Python with Plotly. An examples of a tree-plot in Plotly.


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Set Up Tree with igraph

Install igraph with pip install python-igraph.

In [1]:
!pip install python-igraph
Requirement already satisfied: python-igraph in /home/circleci/project/doc/venv/lib/python3.7/site-packages (0.8.2)
Requirement already satisfied: texttable>=1.6.2 in /home/circleci/project/doc/venv/lib/python3.7/site-packages (from python-igraph) (1.6.2)
In [2]:
import igraph
from igraph import Graph, EdgeSeq
nr_vertices = 25
v_label = list(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

In [3]:
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=Xe,
                   y=Ye,
                   mode='lines',
                   line=dict(color='rgb(210,210,210)', width=1),
                   hoverinfo='none'
                   ))
fig.add_trace(go.Scatter(x=Xn,
                  y=Yn,
                  mode='markers',
                  name='bla',
                  marker=dict(symbol='circle-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

In [4]:
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 = []
    for k in range(L):
        annotations.append(
            dict(
                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

In [5]:
axis = dict(showline=False, # hide axis line, grid, ticklabels and  title
            zeroline=False,
            showgrid=False,
            showticklabels=False,
            )

fig.update_layout(title= 'Tree with Reingold-Tilford Layout',
              annotations=make_annotations(position, v_label),
              font_size=12,
              showlegend=False,
              xaxis=axis,
              yaxis=axis,
              margin=dict(l=40, r=40, b=85, t=100),
              hovermode='closest',
              plot_bgcolor='rgb(248,248,248)'
              )
fig.show()

Reference

See https://plotly.com/python/reference/ for more information and chart attribute options and http://igraph.org/python/ for more information about the igraph package!

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter