Skip to main content

Read, Modify and Create new shape files for the Leica LMD6 & LMD7

Project description

Python package Python package Python package website

logo

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:

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

py_lmd-1.0.0.tar.gz (20.5 kB view details)

Uploaded Source

Built Distribution

py_lmd-1.0.0-py3-none-any.whl (20.2 kB view details)

Uploaded Python 3

File details

Details for the file py_lmd-1.0.0.tar.gz.

File metadata

  • Download URL: py_lmd-1.0.0.tar.gz
  • Upload date:
  • Size: 20.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.19

File hashes

Hashes for py_lmd-1.0.0.tar.gz
Algorithm Hash digest
SHA256 735c968d31187c7a41ff8047796a94a01c25672a43b5c442b096c82e889f0584
MD5 a79ff8c5df8f20659863a4e945753dd3
BLAKE2b-256 9600e527ae761b603a658b7518fb794d57181d938aedcaa87afa901e78f55e4c

See more details on using hashes here.

File details

Details for the file py_lmd-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: py_lmd-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 20.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.19

File hashes

Hashes for py_lmd-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 dea2a5a4912781655f97f768efd34efc456ef79bce517302ecf022cef2dfe43d
MD5 17f169819a1c38d15de89ab25b6e9ef5
BLAKE2b-256 4039ed99119f1b5a6a0f19a94547c7b48688b30c5dd2ebbae74344a6db1ac524

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page