Anaconda Version

pycomlink

A python toolbox for deriving rainfall information from commercial microwave link (CML) data.

Installation

pycomlink is tested with Python 3.7, 3.8 and 3.9. It should also work without problems on Python 3.6. It might still work with Python 2.7, but this is not tested. It can be installed via conda-forge:

$ conda install -c conda-forge pycomlink

If you are new to conda or if you are unsure, it is recommended to create a new conda environment, activate it, add the conda-forge channel and then install.

Installation via pip is also possible:

$ pip install pycomlink

If you install via pip, there might be problems with some dependencies, though. E.g. the dependency pykrige may only install if scipy, numpy and matplotlib have been installed before.

To run the example notebooks you will also need the Jupyter Notebook and ipython, both also available via conda or pip.

If you want to clone the repository for developing purposes follow these steps (installation of Jupyter Notebook included):

$ git clone https://github.com/pycomlink/pycomlink.git
$ cd pycomlink
$ conda env create environment_dev.yml
$ conda activate pycomlink-dev
$ cd ..
$ pip install -e pycomlink

Usage

The following jupyter notebooks showcase some use cases of pycomlink

Basic example CML processing workflow
more to come... (see some notebooks with old outdated pycomlink API)

Features

Perform all required CML data processing steps to derive rainfall information from raw signal levels:
- data sanity checks
- anomaly detection
- 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