A python toolbox for deriving rainfall information from commerical microwave link (CML) data.
pycomlink works with Python 2.7 and Python 3.6 and can be installed via pip.
$ pip install pycomlink
However, for using scientific Python packages it is in general recommended to
install the [Anaconda Python distribution](https://store.continuum.io/cshop/anaconda/) and use
its package manager conda for managing all Python packages. pycomlink is, however,
not yet installable via the Anaconda community package channel [conda-forge](https://conda-forge.org/).
Hence, it is recommended to install all pycomlink dependencies (listed in requirements.txt)
via conda and then use pip to install pycomlink.
To run the example notebooks you will also need the [Jupyter Notebook](https://jupyter.org/)
and ipython, both also available via conda or pip.
The following jupyter notebooks showcase some use cases of pycomlink
- Read and write the [common data format cmlh5 for CML data](https://github.com/cmlh5/cmlh5)
- Quickly visualize the CML network on a dynamic map
- Perform all required CML data processing steps to derive rainfall information from raw signal levels:
- data sanity checks
- wet/dry classification
- baseline calculation
- wet antenna correction
- transformation from attenuation to rain rate
- Generate rainfall maps from the data of a CML network
- Validate you results against gridded rainfall data or rain gauges networks
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.