BrightEyes-FFS
A toolbox for analysing Fluorescence Correlation Spectroscopy (FCS) and Fluorescence Fluctuation Spectroscopy (FFS) data with array detectors. The fcs module contains libraries for:
- Calculating autocorrelations and cross-correlations of raw FCS/FFS data (i.e. photon counts vs. time or photon arrival time traces). Supported file types include .h5, .ptu, and .czi.
- Fitting correlations to various 2D and 3D diffusion models
- Calibration-free FCS/FFS analysis such as circular-scanning FCS and pair-correlation analysis
- Miscellaneous tools
The fcs_gui module contains libraries for:
- Storing and loading FCS/FFS analysis sessions, as used in the GUI
The pch module contains libraries for:
- Calculating photon counting histograms
- Fitting histograms with Fluorescence Intensity Distribution Analysis (FIDA)
The tools module contains libraries for:
- Fitting various models to data (polynomial, Gaussian, power law, etc.)
- Stokes-Einstein relation
- Save/load 2D arrays to/from .csv files
- Save data to .tiff file
- Miscellaneous tools
Installation
You can install brighteyes-ffs via [pip] directly from [PyPI]:
pip install brighteyes-ffs
or using the version on GitHub:
pip install git+https://github.com/VicidominiLab/BrightEyes-FFS
It requires the following Python packages
h5py
joblib
matplotlib>=3.3.2
multipletau>=0.3.3
numpy>=1.19.4
pandas>=1.1.4
scipy
tifffile>=2020.9.29
seaborn
imutils
PyQt5
qdarkstyle
nbformat
ome_types
czifile
brighteyes_ism
notebook
ptufile
phconvert
GUI
For quick and common types of analysis, you can use the GUI (https://github.com/VicidominiLab/BrightEyes-FFS-GUI), which contains most of the basic features. In addition, there is an automatic Jupyter Notebook writing tool to convert an analysis session started in the GUI to a Notebook.
License
Distributed under the terms of the [GNU GPL v3.0] license, "BrightEyes-FFS" is free and open source software
Contributing
You want to contribute? Great! Contributing works best if you creat a pull request with your changes.
- Fork the project.
- Create a branch for your feature:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'My new feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request!
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