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TauFactor is an application for calculating tortuosity factors from tomographic data

Project description

TauFactor

TauFactor is an application for calculating tortuosity factors from tomographic data.

TauFactor

PyPI ReadTheDocs MIT LICENSE github actions

Requirements

Before installing taufactor, download the most recent version of PyTorch. Ensure you have pytorch>=1.10 installed in your Python environment.

For example, for a Linux machine with CUDA GPU

conda install pytorch pytorch-cuda=11.7 -c pytorch -c nvidia

Quickstart

To install TauFactor via PyPI

pip install taufactor

To extract effective diffusivity and tortuosity factor from your data:

import taufactor as tau
import tifffile

# load image
img = tifffile.imread('path/filename')
# ensure 1s for conductive phase and 0s otherwise.

# create a solver object with loaded image
s = tau.Solver(img)

# call solve function
s.solve()

# view effective diffusivity and tau
print(s.D_eff, s.tau)

Tests

To run unit tests navigate to the root directory and run

pytest

Credits

This package was created by the tldr group at the Dyson School of Design Engineering, Imperial College London.

TauFactor MATLAB

The package in this repository refers to a Python implementation of the TauFactor solver. There is a deprecated MATLAB implementation, which is no longer maintained.

History

1.1.0 (2023-07-24)


  • Added comments from reviewers
  • Added examples to documentation
  • Added API documentation
  • Fix test times on comparison

1.0.0 (2023-03-23)


  • Migrated to PyTorch from CuPy
  • New convergence criteria
  • New documentation style
  • CI testing
  • Includes TauFactor paper

0.1.4 (2022-07-11)


  • Add TauE solver
  • Add triple phase boundary calculations
  • Fix cuboids not converging
  • Fix convergence messaging

0.1.3 (2021-03-25)


  • Hotfix code in taufactor.py

0.1.2 (2021-03-25)


  • Added multi-phase and periodic solvers and metrics calculations

0.1.1 (2021-02-10)


  • Removed CuPy from requirements and added installation instructions to README

0.1.0 (2021-02-08)


  • First release on PyPI.

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