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.

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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.