Tracé d'arbre en Python

Question

Je veux tracer des arbres en utilisant Python. Arbres de décision, organigrammes, etc. Une bibliothèque qui m'aide ?

Answer 1

Pour une visualisation de base , j'envisagerais d' utiliser treelib ,

C'est très simple et facile à utiliser :

  from treelib import Node, Tree

 tree = Tree()

 tree.create_node("Harry", "harry")  # No parent means its the root node
 tree.create_node("Jane",  "jane"   , parent="harry")
 tree.create_node("Bill",  "bill"   , parent="harry")
 tree.create_node("Diane", "diane"  , parent="jane")
 tree.create_node("Mary",  "mary"   , parent="diane")
 tree.create_node("Mark",  "mark"   , parent="jane")

 tree.show()

Sortir:

 Harry
 Bill
 Jane
     Diane
        Mary
     Mark 

Answer 2

Plotly peut tracer des arborescences à l'aide d'igraph. Vous pouvez également l'utiliser hors ligne ces jours-ci. L'exemple ci-dessous est destiné à être exécuté dans un bloc-notes Jupyter

 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

Sortir

Answer 3

C'est expirmental, mais Google a une api GraphViz . C'est pratique si vous voulez juste visualiser rapidement un graphique, mais que vous ne voulez pas installer de logiciel.