A library to plot Graphs with Plotly.
Project description
Interactive Graph Visualization
Table of Contents
Introduction
Interactive Graph Visualization (igviz) is a library to help visualize graphs interactively using Plotly. This library provides a customizable api for visualizing graphs in a neat, visually appealing plot. It keeps larger graphs much more clean by displaying minimal text information and highlights node properties and relationships using colour and size while providing the same text information when needed.
Usage
Example notebooks can be found here.
Basic
import networkx as nx
import igviz as ig
G = nx.random_geometric_graph(200, 0.125)
nx.set_node_attributes(G, 3, "prop")
ig.plot(G)
The default plot colors and sizes the nodes by the Degree but it is configurable.
Configurations
ig.plot(
G, # Your graph
title="My Graph",
size_method="static", # Makes node sizes the same
color_method="##ffcccb", # Makes all the node colours black,
node_text=["prop"], # Adds the 'prop' property to the hover text of the node
annotation_text="Visualization made by <a href='https://github.com/Ashton-Sidhu/plotly-graph'>igviz</a> & plotly.", # Adds a text annotation to the graph
)
ig.plot(
G,
title="My Graph",
size_method="prop", # Makes node sizes the size of the "prop" property
color_method="prop", # Colors the nodes based off the "prop" property and a color scale,
node_text=["prop"], # Adds the 'prop' property to the hover text of the node
)
How to add your own custom sizing method and colour method
To add your own custom sizing and color method, just pass a list to the size_method
and color_method
.
color_list = []
sizing_list = []
for node in G.nodes():
size_and_color = G.degree(node) * 3
color_list.append(size_and_color)
sizing_list.append(size_and_color)
ig.plot(
G,
title="My Graph",
size_method=sizing_list, # Makes node sizes the size of the "prop" property
color_method=color_list, # Colors the nodes based off the "prop" property and a color scale,
node_text=["prop"], # Adds the 'prop' property to the hover text of the node
)
Applying layouts
All layouts are calculated through the pos
property on each node. Networkx has built in layouts you can use and can invoke through igviz.
ig.plot(
G,
title="My Graph",
layout="kamada",
)
To add your own pos
property you can set it via the nx.set_node_attributes
function.
pos_dict = {
0: [1, 2], # X, Y coordinates for Node 0
1: [1.5, 3], # X, Y coordinates for Node 1
...
}
nx.set_node_attributes(G, pos_dict, "pos")
ig.plot(
G
)
Directed & Multi Graphs
Igviz also plots Directed and Multigraphs with no configuration chages. For Directed Graphs the arrows are shown from node to node. For Multi Graphs only one edge is shown and it is recommended to set show_edgetext=True
to display the weights of all edges between 2 Multi Graph nodes.
Note: show_edgetext=True
also works for vanilla and Directed Graphs.
Directed Graph
def createDiGraph():
# Create a directed graph (digraph) object; i.e., a graph in which the edges
# have a direction associated with them.
G = nx.DiGraph()
# Add nodes:
nodes = ['A', 'B', 'C', 'D', 'E']
G.add_nodes_from(nodes)
# Add edges or links between the nodes:
edges = [('A','B'), ('B','C'), ('B', 'D'), ('D', 'E')]
G.add_edges_from(edges)
return G
DG = createDiGraph()
ig.plot(DG, size_method="static")
Multi Graph
MG = nx.MultiGraph()
MG.add_weighted_edges_from([(1, 2, 0.5), (1, 2, 0.75), (2, 3, 0.5)])
ig.plot(
MG,
layout="spring",
size_method="static",
show_edgetext=True,
colorscale="Rainbow"
)
Installation
pip install igviz
Feedback
I appreciate any feedback so if you have any feature requests or issues make an issue with the appropriate tag or futhermore, send me an email at ashton.sidhu1994@gmail.com
Contributors
This project follows the all-contributors specification and is brought to you by these awesome contributors.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.