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"""
.. _tutorials-iplotx:
==============================
Visualising graphs with iplotx
==============================
``iplotx`` (https://iplotx.readthedocs.io) is a library for visualisation of graphs/networks
with direct compatibility with both igraph and NetworkX. It uses ``matplotlib`` behind the
scenes so the results are compatible with the current igraph matplotlib backend and many
additional chart types (e.g. bar charts, annotations).
Compared to the standard visualisations shipped with igraph, ``iplotx`` offers:
- More styling options
- More consistent behaviour across DPI resolutions and backends
- More consistent matplotlib artists for plot editing and animation
"""
import igraph as ig
import iplotx as ipx
# Construct a graph with 5 vertices
n_vertices = 5
edges = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (3, 4)]
g = ig.Graph(n_vertices, edges)
# Set attributes for the graph, nodes, and edges
g["title"] = "Small Social Network"
g.vs["name"] = [
"Daniel Morillas",
"Kathy Archer",
"Kyle Ding",
"Joshua Walton",
"Jana Hoyer",
]
g.vs["gender"] = ["M", "F", "F", "M", "F"]
g.es["married"] = [False, False, False, False, False, False, False, True]
# Set individual attributes
g.vs[1]["name"] = "Kathy Morillas"
g.es[0]["married"] = True
# Plot using iplotx
ipx.network(
g,
layout="circle", # print nodes in a circular layout
vertex_marker="s",
vertex_size=45,
vertex_linewidth=2,
vertex_facecolor=[
"lightblue" if gender == "M" else "deeppink" for gender in g.vs["gender"]
],
vertex_label_color=[
"black" if gender == "M" else "white" for gender in g.vs["gender"]
],
vertex_edgecolor="black",
vertex_labels=[name.replace(" ", "\n") for name in g.vs["name"]],
edge_linewidth=[2 if married else 1 for married in g.es["married"]],
edge_color=["#7142cf" if married else "#AAA" for married in g.es["married"]],
edge_padding=3,
aspect=1.0,
)
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