TraceAnalyser

A standalone application for analysing time series data, which includes features for processing/labelling/filtering traces and facilitates the detection of hidden states using Hidden Markov Modelling (HMM). It also includes embdedded pre-trained Deep Learning (InceptionTime) models for classifying/labelling traces.

This is still undergoing development, so some features may not work as expected.

This was built by Dr Piers Turner from the Kapanidis Lab, University of Oxford.

Installation

You can install TraceAnalyser via PyPI:

conda create –-name TraceAnalyser python==3.9
conda activate TraceAnalyser

pip install traceanalyser

To upgrade TraceAnalyser to the latest version, use the following command:

pip install traceanalyser --upgrade

You can install the latest development version of TraceAnalyser from source by running:

conda create –-name TraceAnalyser python==3.9
conda activate TraceAnalyser
conda install -c anaconda git
conda update --all

pip install git+https://github.com/piedrro/TraceAnalyser.git

To install MATLAB engine (Windows):

python 3.9 requires MATLAB >= 2021b

MATLAB compatibility: https://uk.mathworks.com/support/requirements/python-compatibility.html

pip install matlabengine

This will likely fail due to a MATLAB version issue. Read the traceback, and install the recomended verison. Then try again:

pip install matlabengine==XXXX

Terminal Commands

To launch the Trace Analyser App:

analysis

To launch an ebFRET instance (requires matlab engine installation):

ebFRET

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the MIT license, "TraceAnalyser" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.