By default, networkx has problems with drawing self-loops in graphs.

Overview

networkx drawing self-loops

By default, networkx has problems with drawing self-loops in graphs. It makes it hard to draw a graph with self-loops or to make a nicely looking chord diagram. This repository provides some code to draw self-loops nicely

Examples

Let's have a look on how networkx draws graphs with self-loops

import matplotlib.pyplot as plt
import networkx as nx
import numpy as np 

from drawing import chord_diagram  # Code from this repo

# Create graph with some weights
graph = nx.DiGraph(
    np.array([
        [1, 2, 1, 3, 5],
        [1, 0, 3, 0, 0],
        [1, 1, 3, 0, 1],
        [0, 0, 2, 0, 1],
        [1, 1, 1, 1, 1]
    ])
)

fig, ax = plt.subplots(figsize=(10, 10))

nx.draw_circular(graph, ax=ax)
ax.set_title("Graph drawn with networkx")

fig.savefig("images/0_simple_graph_networkx.png")

Simple graph networkx

Self-loops are drawn, but they are pretty ugly. When the graph gets bigger, it is not possible to see them anymore, especially at the inner side of the polygon. This repository provides a code for the much nicer plots:

fig, ax = plt.subplots(figsize=(10, 10))

ax = chord_diagram(graph, ax)
ax.set_xlim(-1.5, 1.5)
ax.set_ylim(-1.5, 1.5)
ax.set_title("A simple graph drawn better")

fig.savefig("images/1_simple_graph.png")

Simple graph

Much better, huh? Let's have a look at the real world example. This is cells communication network from single-cell RNA-seq data. What you get by vanilla networkx:

Cells communication networkx

And by code from this repo:

Cells communication

Of course, you can make networkx plots with colors and arc curvy edges too. But notice, how vanilla networkx draws self-loops. They always have the same directions. While the code from this repo draws them from the center of the layout. More than that, it is possible to control self-loops' width and length. And, if necessary, draw them inside the polygon. Check documentation of the function draw_self_loop() from drawing.py

You can see more code examples in example.py

What can be done better

This repository can become better. If people use it, I will definitely continue developing. If you want to help me, PRs and suggestions are always welcome!

If you want to contribute, here are some ideas of what can be done better:

  • Make code more flexible. In the current version, a lot of things (e. g. plot colors, edges curvature) are hardcoded inside the functions from drawing.py. It would be great to make them parameters of the functions.
  • Make chord_diagram a PyPi package. It would be great to do a simple pip install package_name instead of copy-pasting code from this repo
  • Write some tests. It is not simple to automatically test plots, as they are mostly evaluated visually. But it is definitely a good idea to test some math related functions from drawing.py.
  • Nicely draw self-loops in a complicated layout. For now, self-loops look nicely if the graph has circular layout centered around (0, 0). In more complicated graphs, you will most likely get ugly plots. For example, this is a graph with Kamada-Kawai layout: Not circular layout

You can see at least 2 problems on this plot:

  1. Loops get bigger as they get further away from the center. This is an expected outcome from the current version of the code. But maybe we want to make it constant
  2. There are some weird extra self-loops. Tbh, I am not sure, where do they come from

Installation

  1. Install requirements:

pip install -r requirements.txt

Note that you need pandas only to run some examples. If you want to use only the code for the chord diagram, pandas is not necessary.

  1. Use code from drawing.py or check examples.py to see some code examples
Owner
Vladimir Shitov
I am a student at the Siberian State Medical University in Tomsk, Russia. I enjoy bioinformatics, programming and data analysis.
Vladimir Shitov
A script written in Python that generate output custom color (HEX or RGB input to x1b hexadecimal)

ColorShell ─ 1.5 Planned for v2: setup.sh for setup alias This script converts HEX and RGB code to x1b x1b is code for colorize outputs, works on ou

Riley 4 Oct 31, 2021
Visualise top-rated GitHub repositories in a barchart by keyword

This python script was written for simple purpose -- to visualise top-rated GitHub repositories in a barchart by keyword. Script generates html-page with barchart and information about repository own

Cur1iosity 2 Feb 07, 2022
Customizing Visual Styles in Plotly

Customizing Visual Styles in Plotly Code for a workshop originally developed for an Unconference session during the Outlier Conference hosted by Data

Data Design Dimension 9 Aug 03, 2022
Graphical display tools, to help students debug their class implementations in the Carcassonne family of projects

carcassonne_tools Graphical display tools, to help students debug their class implementations in the Carcassonne family of projects NOTE NOTE NOTE The

1 Nov 08, 2021
Leyna's Visualizing Data With Python

Leyna's Visualizing Data Below is information on the number of bilingual students in three school districts in Massachusetts. You will also find infor

11 Oct 28, 2021
2021 grafana arbitrary file read

2021_grafana_arbitrary_file_read base on pocsuite3 try 40 default plugins of grafana alertlist annolist barchart cloudwatch dashlist elasticsearch gra

ATpiu 5 Nov 09, 2022
An interactive GUI for WhiteboxTools in a Jupyter-based environment

whiteboxgui An interactive GUI for WhiteboxTools in a Jupyter-based environment GitHub repo: https://github.com/giswqs/whiteboxgui Documentation: http

Qiusheng Wu 105 Dec 15, 2022
Functions for easily making publication-quality figures with matplotlib.

Data-viz utils 📈 Functions for data visualization in matplotlib 📚 API Can be installed using pip install dvu and then imported with import dvu. You

Chandan Singh 16 Sep 15, 2022
ScisorWiz: Differential Isoform Visualizer for Long-Read RNA Sequencing Data

ScisorWiz: Vizualizer for Differential Isoform Expression README ScisorWiz is a linux-based R-package for visualizing differential isoform expression

Alexander Stein 6 Oct 04, 2022
A Python package for caclulations and visualizations in geological sciences.

geo_calcs A Python package for caclulations and visualizations in geological sciences. Free software: MIT license Documentation: https://geo-calcs.rea

Drew Heasman 1 Jul 12, 2022
Jupyter notebook and datasets from the pandas Q&A video series

Python pandas Q&A video series Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas. Jupyter Note

Kevin Markham 2k Jan 05, 2023
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph

TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the comput

Eric Jang 1.4k Dec 15, 2022
Create animated and pretty Pandas Dataframe or Pandas Series

Rich DataFrame Create animated and pretty Pandas Dataframe or Pandas Series, as shown below: Installation pip install rich-dataframe Usage Minimal exa

Khuyen Tran 92 Dec 26, 2022
Getting started with Python, Dash and Plot.ly for the Data Dashboards team

data_dashboards Getting started with Python, Dash and Plot.ly for the Data Dashboards team Getting started MacOS users: # Install the pyenv version ma

Department for Levelling Up, Housing and Communities 1 Nov 08, 2021
Cryptocurrency Centralized Exchange Visualization

This is a simple one that uses Grafina to visualize cryptocurrency from the Bitkub exchange. This service will make a request to the Bitkub API from your wallet and save the response to Postgresql. G

Popboon Mahachanawong 1 Nov 24, 2021
By default, networkx has problems with drawing self-loops in graphs.

By default, networkx has problems with drawing self-loops in graphs. It makes it hard to draw a graph with self-loops or to make a nicely looking chord diagram. This repository provides some code to

Vladimir Shitov 5 Jan 06, 2022
Lime: Explaining the predictions of any machine learning classifier

lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict

Marco Tulio Correia Ribeiro 10.3k Dec 29, 2022
Lightweight data validation and adaptation Python library.

Valideer Lightweight data validation and adaptation library for Python. At a Glance: Supports both validation (check if a value is valid) and adaptati

Podio 258 Nov 22, 2022
Mapomatic - Automatic mapping of compiled circuits to low-noise sub-graphs

mapomatic Automatic mapping of compiled circuits to low-noise sub-graphs Overvie

Qiskit Partners 27 Nov 06, 2022
A python script editor for napari based on PyQode.

napari-script-editor A python script editor for napari based on PyQode. This napari plugin was generated with Cookiecutter using with @napari's cookie

Robert Haase 9 Sep 20, 2022