PathpyG Visualisations

This page provides an overview of the available visualisations and the supported backends. It also describes which displaying and saving options are available as well as the supported keyword arguments for customized plot styling.

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Methods

• show(**kwargs): Show Visualisation
• save(filename: str, **kwargs): Save Visualisation to hard drive

kwargs for saving Manim plots:

• filename (str): Name to assign to the output file. This keyword is necessary for saving.

For display use the show() method instead of save().

Supported Features by Backend

Backend	Static Networks	Temporal Networks	Available File Formats
d3.js	✔️	✔️	svg, html, json (dynamic)
manim	❌	✔️	mp4, gif
matplotlib	✔️	❌	png, svg, pdf, etc.
tikz	✔️	❌	pdf, tex

Keyword Arguments Overview

Argument	d3.js	manim	matplotlib	tikz	Short Description
General
delta	✔️	✔️	❌		Duration of timestep (ms)
start	✔️	✔️	❌		Animation start timestep
end	✔️	✔️	❌		Animation end timestep (last edge by default)
intervals	✔️	✔️	❌		Number of animation intervals
dynamic_layout_interval	❌	✔️	❌		Steps between layout recalculations
background_color	❌	✔️	❌		Background color (name, hex, RGB)
width	✔️	❌	❌		Width of the output
height	✔️	❌	❌		Height of the output
lookahead	❌	✔️	❌	❌	for layout computation
lookbehind	❌	✔️	❌	❌	for layout computation
Nodes
node_size	✔️	✔️	✔️	✔️	Radius of nodes (uniform or per-node)
node_color	🟨	✔️	🟨	🟨	Node fill color
node_cmap	✔️	✔️	✔️	✔️	Colormap for scalar node values
node_opacity	✔️	✔️	✔️	✔️	Node fill opacity (0 transparent, 1 solid)
node_label	✔️	✔️	❌		Label text shown with nodes
Edges
edge_size	✔️	✔️	✔️	✔️	Edge width (uniform or per-edge)
edge_color	✔️	✔️	✔️	✔️	Edge line color
edge_cmap	✔️	✔️	✔️	✔️	Colormap for scalar edge values
edge_opacity	✔️	✔️	✔️	✔️	Edge line opacity (0 transparent, 1 solid)

Legend: ✔️ Supported 🟨 Partially Supported ❌ Not Supported

Detailed Description of Keywords

The default values may differ for each individual Backend.

General

• delta (int): Duration (in milliseconds) of each animation timestep.
• start (int): Starting timestep of the animation sequence.
• end(int or None): Ending timestep; defaults to the last timestamp of the input data.
• intervals(int): Number of discrete animation steps.
• dynamic_layout_interval (int): How often (in timesteps) the layout recomputes.
• background_color(str or tuple): Background color of the plot, accepts color names, hex codes or RGB tuples.
• width (int): width of the output
• height (int): height of the output
• look_ahead (int): timesteps in the future to include while calculating layout
• look_behind (int): timesteps into the past to include while calculating layout

Nodes

• node_size: Node radius; either a single float applied to all nodes or a dictionary with sizes per node ID.
• node_color: Fill color(s) for nodes. Can be a single color string referred to by name ("blue"), HEX ("#ff0000"), RGB((255,0,0)), float, a list of colors cycling through nodes or a dictionary with color per node in one of the given formats. Manim additionally supports timed node color changes in the format {"node_id-timestep": color} (i.e. {a-2.0" : "yellow"})
• node_cmap: Colormap used when node colors are numeric.
• node_opacity: Opacity level for nodes, either uniform or per node.
• node_label (dict): Assign text labels to nodes

Edges

• edge_size: Width of edges, can be uniform or specified per edge in a dictionary with size per edge ID.
• edge_color: Color(s) of edges; supports single or multiple colors (see node_color above).
• edge_cmap: Colormap used when edge colors are numeric.
• edge_opacity: Opacity for edges, uniform or per edge.

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Usage Examples

d3.js

import pathpyG as pp

# Example network data
tedges = [('a', 'b', 1),('a', 'b', 2), ('b', 'a', 3), ('b', 'c', 3), ('d', 'c', 4), ('a', 'b', 4), ('c', 'b', 4),
              ('c', 'd', 5), ('b', 'a', 5), ('c', 'b', 6)]
t = pp.TemporalGraph.from_edge_list(tedges)

# Create temporal plot with custom settings and display inline
pp.plot(
    t,
    backend= 'd3js', 
    node_size = {"a": 15, "b": 5},
    node_color = "grey",
    edge_opacity = 0.7,
)

manim

import pathpyG as pp

# Example network data
tedges = [('a', 'b', 1),('a', 'b', 2), ('b', 'a', 3), ('b', 'c', 3), ('d', 'c', 4), ('a', 'b', 4), ('c', 'b', 4),
              ('c', 'd', 5), ('b', 'a', 5), ('c', 'b', 6)]
t = pp.TemporalGraph.from_edge_list(tedges)

# Create temporal plot with custom settings and display inline
pp.plot(
    t,
    backend="manim",
    dynamic_layout_interval=1,
    edge_color={"b-a-3.0": "red", "c-b-4.0": (220,30,50)},
    node_color = {"c-3.0" : "yellow"},
    edge_size=6,
    node_label={"a": "a", "b": "b", "c": "c", "d" : "d"},
    font_size=20,
)

matplotlib

import pathpyG as pp

# Example network data (static)
g = Graph.from_edge_index(torch.tensor([[0,1,0], [2,2,1]]))

# Create static plot with custom settings and display inline
pp.plot(
    g,
    backend= 'matplotlib', 
    edge_color= "grey",
    node_color = "blue"
)

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For more details and usage examples, see Manim Visualisation Tutorial,Visualisation Tutorial and Develop your own plot Functions