[](https://github.com/MannLabs/py-lmd/actions/workflows/python-package.yml) [](https://github.com/MannLabs/py-lmd/actions/workflows/python-package.yml) [](https://github.com/MannLabs/py-lmd/actions/workflows/python-package.yml)
[](https://mannlabs.github.io/py-lmd/html/index.html)
Read, create and write cutting data for the Leica LMD6 & LMD7 microscope.
Build reproducible workflows to calibrate, import SVG files and convert single-cell segmentation masks.
Installation from Github
========================
py-lmd has been tested with **Python 3.8 and 3.9**.
To install the py-lmd library clone the Github repository and use pip to install the library in your current environment.
It is recommended to use the library with a conda environment. Please make sure that the package is installed editable
like described. Otherwise static glyph files might not be available.
We recommend installing the non-python dependencies with conda before installing py-lmd:
```
git clone https://github.com/MannLabs/py-lmd
conda create -n "py-lmd-env"
conda activate py-lmd-env
conda install python=3.9 scipy 'scikit-image>=0.19' numpy numba -c conda-forge
pip install -e .
```
If you are installing on an M1 apple silicon Mac you will need to install `numba` via conda instead of pip before proceeding with the installation of the py-lmd library.
```
conda install numba
```
Documentation
========================
The current documentation can be found under https://mannlabs.github.io/py-lmd/html/index.html.
Citing our Work
=================
py-lmd was developed by Georg Wallmann, Sophia Mädler and Niklas Schmacke in the labs of Veit Hornung and Matthias Mann. If you use our code please cite the [following manuscript](https://www.biorxiv.org/content/10.1101/2023.06.01.542416v1):
SPARCS, a platform for genome-scale CRISPR screening for spatial cellular phenotypes
Niklas Arndt Schmacke, Sophia Clara Maedler, Georg Wallmann, Andreas Metousis, Marleen Berouti, Hartmann Harz, Heinrich Leonhardt, Matthias Mann, Veit Hornung
bioRxiv 2023.06.01.542416; doi: https://doi.org/10.1101/2023.06.01.542416
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