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 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.
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
and ipython, both also available via conda or pip.
The following jupyter notebooks showcase some use cases of pycomlink
- How to do baseline determination
- How to do spatial interpolation of CML rainfall
- How to get started with your CML data from a CSV file
- Read and write the common data format
cmlh5for CML data - 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