This repository provide the software to create, manipulate and analyze Multi Angle Snowflake Camera (MASC) data.
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MASC is a community-based effort to collect, standardize and homogenize Multi Angle Snowflake Camera (MASC) data from around the world.
pymascdb can be installed via conda on Linux, Mac, and Windows. Install the package by typing the following command in the terminal:
conda install -c conda-forge pymascdbIn case conda-forge is not set up for your system yet, see the easy to follow instructions on conda-forge.
pymascdb can be installed also via pip on Linux, Mac, and Windows. On Windows you can install WinPython to get Python and pip running.
Then, install the pymascdb package by typing the following command in the terminal:
pip install pymascdbTo install the latest development version via pip, see the documentation.
The folder tutorials provides code examples to explore the capabilities of pymascdb.
A selection of of jupyter notebooks illustrates a selection of pymascdb functionalities.
These jupyter notebooks tutorial can also be consulted in the online documentation.
To discover more about the MASCDB products, the pymascdb processing and analysis capabilities, or how to contribute your own data to MASCDB, please read the software documentation available at https://pymascdb.readthedocs.io/en/latest/index.html.
If you aim to contribute your data or discuss the future development of MASCDB, feel free to also open a GitHub Issue or a GitHub Discussion specific to your questions or ideas.
You can cite the MASCDB project by:
Gionata Ghiggi, Jacopo Grazioli, Alexis Berne (2025). ltelab/pymascdb Zenodo. https://doi.org10.5281/zenodo.7398284 Grazioli, J., Ghiggi, G., & Berne, A. (2023). MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8046497 Grazioli, J., Ghiggi, G., Billault-Roux, AC. et al. MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall. Sci Data 9, 186 (2022). https://doi.org/10.1038/s41597-022-01269-7
If you want to cite a specific version of pymascdb, have a look at the Zenodo software archive repository.
The content of this repository is released under the terms of the MIT license.