Python tools for MW link data processing
Project description
A python toolbox for MW link data processing and rain rate estimation
Installation
pycomlink works with Python 2.7 and depends on numpy, scipy, pandas, matplotlib and cartopy. You can install it via pip, but it is recommended that you install the dependecies first. We recommend the usage of the [Anaconda Python distribution](https://store.continuum.io/cshop/anaconda/) for all scientific python packages.
The pip command to install pycomlink is the following:
$ pip install pycomlink
Usage
IPython notebook showing the [basic workflow](http://nbviewer.ipython.org/urls/bitbucket.org/cchwala/pycomlink/raw/566962d7c0a16c484d56aec7a0a34b84cc68a27d/notebooks/example_workflow.ipynb)
IPython notebook on [how to use your MW link CSV data](http://nbviewer.ipython.org/urls/bitbucket.org/cchwala/pycomlink/raw/28f359b359d750434c896d288900844c9b6ef500/notebooks/How%20to%20use%20your%20MW%20link%20data%20from%20a%20CSV%20file.ipynb)
Have a look at the [documentation](http://pycomlink.readthedocs.org)
Status
The basic functionality is already working. However, pycomlink is currently in ongoing development. Hence, there may be changes to the interface in the future.
Features
Easily parse your MW link data and use and object oriented approach to do all the processing
Two wet/dry classification methods available
Different baseline methods available
One wet antenna estimation method available
2D plots using IDW or Kriging interpolation
Project details
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