The sdt-python package

sdt-python is a collection of tools for analysis of fluorescence microscopy data.

It contains

• algorithms for localization of fluorescent features in images
• methods for evaluation of tracking data
• functions to evaluate brightness data
• as well as multi-color data
• support for automated determination and correction of chromatic aberrations
• methods for reading and writing single molecule data in various formats
• handling of ROIs (both rectangular and described by arbitrary paths)
• methods for simulation of fluorescence microscopy images
• much more.

A repository of tutorials is provided at https://github.com/schuetzgroup/sdt-python-tutorials. API documentation can be found at https://schuetzgroup.github.io/sdt-python.

If you use sdt-python in a project resulting in a scientific publication, please cite the software.

Installation

Using uv (recommended)

• Install uv according to the official instructions or using e.g. your Linux distribution's package manager.

• Create a folder for your project.

• Inside this folder, run

  uv init
  

  in a console prompt to create a new project. See the official guide for more information.

• Add sdt-python and optional dependencies by running

  uv add sdt-python
  uv add opencv trackpy lmfit ipympl scikit-learn pyqt
  

• Start the python interpreter by executing

  uv run python
  

  or Jupyter Lab by executing

  uv run --with jupyter jupyter lab
  

  (see the official documentation for details).

Using conda-forge

Set up a conda forge-enabled installation by downloading and executing an installer from the web page.

Then open a Miniforge prompt and type

conda install sdt-python
conda install opencv trackpy lmfit ipympl scikit-learn pyqt

to install the sdt-python package and some optional, recommended packages.

Using pip

Install some Python distribution and run (possibly in a virtual environment)

pip install sdt-python

Updating

If using uv, execute

uv sync -P sdt-python

to update only sdt-python or

uv sync -U

to update everything.

If the conda-forge installation is used, type

conda update sdt-python

in a Miniforge prompt.

If pip is used, run

pip install --upgrade sdt-python

Requirements

• Python >= 3.10
• matplotlib
• numpy >= 2.1
• pandas >= 2.2.3
• imageio >= 2.29
• tifffile >= 0.7.0
• pyyaml
• lazy_loader

Recommended packages

• PyQt5 >= 5.12
• opencv
• trackpy
• lmfit
• ipympl
• scikit-learn
• pywavelets >= 0.3.0