GraphCalc
GraphCalc: A Python Package for Computing Graph Invariants in Automated Conjecturing Systems - Published in JOSS (2025)
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Published in Journal of Open Source Software
Keywords
Scientific Fields
Repository
A repository for computation of graph invariants
Basic Info
- Host: GitHub
- Owner: RandyRDavila
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://graphcalc.readthedocs.io/en/latest/
- Size: 300 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 5
- Releases: 4
Topics
Metadata Files
README.md
GraphCalc
Overview
GraphCalc is a Python library for computing a broad range of graph-theoretic invariants, purpose-built to support research in combinatorics, network science, and automated reasoning. It offers exact implementations of over 100 functions, spanning classical invariants (e.g., independence number, chromatic number, spectral radius) and a wide array of lesser-known parameters central to contemporary graph theory.
Originally developed as the invariant engine for the automated conjecturing system TxGraffiti, GraphCalc has since matured into a general-purpose research tool that facilitates the large-scale construction of structured, high-resolution invariant datasets. These datasets, often organized into tabular “knowledge tables,” form the basis for symbolic pattern mining, hypothesis generation, and downstream machine reasoning. For example,
```python
import graphcalc as gc from graphcalc.polytopes.generators import cubegraph, octahedrongraph graphs = [cubegraph(), octahedrongraph()] functions = ["order", "size", "spectralradius", "independencenumber"] gc.computeknowledgetable(functions, graphs) order size spectralradius independencenumber 0 8 12 3.0 4 1 6 12 4.0 2 ```
Features
- Maximum Clique: Finds the maximum clique in a given graph.
- Chromatic Number: Computes the minimum number of colors required for graph coloring.
- Vertex and Edge Cover: Determines vertex and edge covers.
- Matching and Independence: Calculates maximum matching and independent sets.
- Domination Number and its Variants: Calculates the domination number, total domination number, and many other domination variants.
- Degree Sequence Invariants: Calculates the residue, annihilaiton number, the slater number and more!
- Zero Forcing: Calculates the zero forcing number, the total zero forcing number, the positive semidefinite zero forcing number, and the power domination number.
Installation
To install graphcalc, make sure you have Python 3.7 or higher, then install it:
bash
pip install graphcalc
Linear and Integer Programming Solvers
Many of the NP-hard graph invariant computations of GraphCalc depend on third-party solvers.At least one of the following is required if you intend to use solver-based functions (e.g., gc.maximum_independent_set(G)):
- CBC (recommended):
bash
brew install cbc # macOS
sudo apt install coinor-cbc # Debian/Ubuntu
GraphCalc will attempt to automatically detect the solver if it is installed. You can also manually specify the solver in API calls.
Example Graph Usage
```python from graphcalc import ( independencenumber, dominationnumber, zeroforcingnumber, ) from graphcalc.generators import petersen_graph
Calculate and print the independence number of the Petersen graph.
G = petersengraph() print(f"Petersen graph independence number = {independencenumber(G)}")
Calculate and print the domination number of the Petersen graph.
print(f"Petersen graph domination number = {domination_number(G)}")
Calculate and print the zero forcing number of the Petersen graph.
print(f"Petersen graph zero forcing number = {zeroforcingnumber(G)}") ```
Example Polytope Usage
```python import graphcalc as gc from graphcalc.polytopes.generators import ( cubegraph, octahedrongraph, dodecahedrongraph, tetrahedrongraph, icosahedrongraph, convexpolytopestextexample, )
Generate polytope graphs (cubes, octahedra, etc.)
G1 = cubegraph() G2 = octahedrongraph() G3 = dodecahedrongraph() G4 = tetrahedrongraph() G5 = icosahedrongraph() G6 = convexpolytopestextexample(1) G7 = convexpolytopestext_example(2)
Function names to compute
functionnames = [ "order", # number of vertices "size", # number of edges "pvector", "independencenumber", "vertexcovernumber", "maximumdegree", "averagedegree", "minimumdegree", "spectralradius", "diameter", "radius", "girth", "algebraicconnectivity", "largestlaplacianeigenvalue", "secondlargestadjacencyeigenvalue", "smallestadjacency_eigenvalue", "fullerene", ]
Compute properties for multiple polytopes
graphs = [G1, G2, G3, G4, G5, G6, G7] df = gc.computeknowledgetable(function_names, graphs) ```
Creating Simple Graphs, Polytope Graphs, and Simple Polytope Graphs
```python import graphcalc as gc
Draw a simple graph
G = gc.SimpleGraph(name="Example Graph") G.addedgesfrom([(0, 1), (1, 2), (2, 3)]) G.draw() ```
Author
Randy Davila, PhD Email: rrd6@rice.edu
Owner
- Name: Randy Davila
- Login: RandyRDavila
- Kind: user
- Location: Houston
- Company: @RelationalAI
- Repositories: 7
- Profile: https://github.com/RandyRDavila
I am a mathematician with interests in data science. My research areas include graph theory, discrete optimization, and AI.
JOSS Publication
GraphCalc: A Python Package for Computing Graph Invariants in Automated Conjecturing Systems
Authors
Tags
graph theory graph invariants optimizationGitHub Events
Total
- Create event: 16
- Release event: 2
- Issues event: 10
- Delete event: 2
- Issue comment event: 11
- Push event: 109
- Pull request review comment event: 1
- Pull request review event: 3
- Pull request event: 21
- Fork event: 1
Last Year
- Create event: 18
- Release event: 2
- Issues event: 10
- Delete event: 2
- Issue comment event: 11
- Push event: 111
- Pull request review comment event: 1
- Pull request review event: 3
- Pull request event: 23
- Fork event: 1
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 7
- Total pull requests: 9
- Average time to close issues: 5 days
- Average time to close pull requests: about 1 hour
- Total issue authors: 4
- Total pull request authors: 2
- Average comments per issue: 0.86
- Average comments per pull request: 0.0
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 7
- Pull requests: 9
- Average time to close issues: 5 days
- Average time to close pull requests: about 1 hour
- Issue authors: 4
- Pull request authors: 2
- Average comments per issue: 0.86
- Average comments per pull request: 0.0
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- aadinoyiibrahim (3)
- szhorvat (2)
- aelliott50 (1)
- bbrimkov (1)
Pull Request Authors
- RandyRDavila (13)
- danielskatz (1)
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 1,777 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 38
- Total maintainers: 1
pypi.org: graphcalc
A Python package for graph computation functions
- Documentation: https://graphcalc.readthedocs.io/en/latest/
- License: MIT
-
Latest release: 1.2.14
published 4 months ago
Rankings
Maintainers (1)
Dependencies
- PuLP ==2.9.0
- contourpy ==1.3.0
- cycler ==0.12.1
- exceptiongroup ==1.2.2
- fonttools ==4.54.1
- importlib_resources ==6.4.5
- iniconfig ==2.0.0
- kiwisolver ==1.4.7
- networkx ==3.2.1
- numpy ==2.0.2
- packaging ==24.2
- pillow ==11.0.0
- pluggy ==1.5.0
- pyparsing ==3.2.0
- pytest ==8.3.3
- python-dateutil ==2.9.0.post0
- six ==1.16.0
- tomli ==2.1.0
- zipp ==3.21.0
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- sphinx *
- sphinx-rtd-theme *
