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 anaconda (recommended)
Convert a miniconda installation to conda forge
The following will most likely fail on a full Anaconda install, hence it is recommended to use miniconda (minimal Anaconda) First, install miniconda (Python 3.x version). Then open an Anaconda prompt and type
conda config --add channels conda-forge conda config --set channel_priority strict conda update --all conda install sdt-python conda install opencv trackpy lmfit ipympl scikit-learn pyqt
The last line installs optional, recommended packages.
Instead of converting the whole installation to conda-forge, it is possible to
Create a new environment using conda forge
This method works for Anaconda / miniconda installs.
conda create -n sdt_env -c conda-forge --strict-channel-priority sdt-python conda install -n sdt_env -c conda-forge --strict-channel-priority opencv trackpy lmfit ipympl scikit-learn conda activate sdt_env
The second line installs optional, recommended packages. sdt_env is the
name of the new environment. For more information on conda environments,
have a look
here.
Using pip (untested)
Install some Python distribution. Download this source code, change into the root folder (where this README is located) and run:
python -m pip install .
Updating
If the conda installation was converted to conda forge, type
conda update sdt-python
in an Anaconda prompt.
If a separate environment is used, type
conda activate sdt_env conda update -c conda-forge --strict-channel-priority sdt-python
If you chose an environment name different from sdt_env when installing,
adapt accordingly.
Requirements
- Python >= 3.7
- matplotlib
- numpy >= 1.10
- pandas
- pims >= 0.3.0
- tifffile >= 0.7.0
- pyyaml
- pywavelets >= 0.3.0
Recommended packages
- PyQt5 >= 5.12
- opencv
- trackpy
- lmfit
- ipympl
- scikit-learn