Welcome to the PyDDA documentation!

This is the main page for the documentation of PyDDA. Below are links that provide documentation on the installation and use of PyDDA as well as description of each of PyDDA’s subroutines.

User Guide

The cookbook provides in-depth information on how to use PyDDA, including how to get started. This is where to look for general conceptual descriptions on how to use parts of PyDDA, including how to make your first wind retrieval and the required data preprocessing to do so.

User Guide

Reference Guide

The reference guide contains detailed descriptions on every function and class within PyDDA. This is where to turn to understand how to use a particular feature or where to search for a specific tool

Developer Reference Manual

Developer Guide

Want to help make PyDDA better? Found something that’s not working quite right? You can find instructions on how to contribute to PyDDA here. You can also find detailed descriptions on tools useful for developing PyDDA.

Contributor’s Guide

Example Gallery

Check out PyDDA’s gallery of examples which contains sample code demonstrating various parts of PyDDA’s functionality.

PyDDA Example Gallery

System Requirements

This works on any modern version of Linux, Mac OS X, and Windows. For Windows, HRRR data integration is not supported. In addition, since PyDDA takes advtange of parallelism we recommend:

An Intel machine with at least 4 cores
8 GB RAM
1 GB hard drive space

While PyDDA will work on less than this, you may run into performance issues. In addition, we do not support Python versions less than 3.9. If you have an older version installed, PyDDA may work just fine but we will not provide support for any issues unless you are using at least Python 3.9.

Installation instructions

The GitHub repository for PyDDA is available at:

openradar/PyDDA

We do not support Python versions less than 3.9. If you use earlier Python versions, be aware, there is no testing done for these versions so problems may arise!

In order to use the HRRR data constraint, cfgrib needs to be installed. cfgrib currently only works on Mac OS and Linux, so this is an optional dependency of PyDDA so that Windows users can still use PyDDA. In order to install cfgrib, simply do:

pip install cfgrib

There are multiple ways to install PyDDA. The recommended way to install PyDDA is through the use of the Anaconda package manager. If you have anaconda installed simply type:

conda install -c conda-forge pydda

This will install PyDDA and all of the required dependencies. You still need to install cfgrib if you wish to read HRRR data. If you do not have anaconda, you can still install PyDDA using pip. Running this command will install PyDDA and the required dependencies:

pip install pydda

If you wish to contribute to PyDDA, you should install PyDDA from source. To do this, just type in the following commands assuming you have the above dependencies installed.

git clone https://github.com/openradar/PyDDA
cd PyDDA
python setup.py install

Finally, PyDDA now supports using Jax and TensorFlow for solving the three dimensional wind field. PyDDA requries TensorFlow 2.6 and the tensorflow-probability package for TensorFlow to be enabled. In addition, both of these packages can utilize CUDA-enabled GPUs for much faster processing. These two dependencies are optional as the user can still use PyDDA with the SciPy ecosystem. The Jax optimizer uses the same optimizer as SciPy’s (L-BFGS-B).

Known issues

The TensorFlow engine uses the unbounded version of this optimizer which removes the constraint that the the wind magnitudes must be less than 100 m/s. The removal of this constraint can sometimes result in numerical instability, so it is recommended that the user test out both Jax and TensorFlow if they desire GPU-accelerated retrievals.

Contents:

• User Guide
  • Overview
  • Reading in Radar Data in Native Radial Coordinates
    • Read in the Data
    • Plot the data
    • Summary
  • Radar Data Quality Control - Dealiasing
    • Read the Data
    • Determining Artifacts within Doppler Velocities
    • Apply Dealiasing
    • Summary
  • Converting the radar data to Cartesian coordinates with Py-ART
    • Gridding the data
    • References
  • Retrieving your first wind field
    • 3D variational technique
    • Doing your first wind retrieval
    • Using PyDDA’s data model
    • Using models for constraints
    • Set up your initialization
    • Retrieving your first wind field
    • Plotting the output winds
  • Optimizing your wind retrieval
  • Visualizing the wind retrieval
  • Retrieving your first wind field
    • 3D variational technique
    • Doing your first wind retrieval
    • Using PyDDA’s data model
    • Using models for constraints
    • Set up your initialization
    • Retrieving your first wind field
    • Plotting the output winds
  • Optimizing your wind retrieval
• Contributor’s Guide
  • Contributor Covenant Code of Conduct
  • Code Style
  • Python File Setup
  • Testing
  • GitHub
• PyDDA Example Gallery
• Developer Reference Manual
  • cost_functions Module
    • pydda.cost_functions (pydda.cost_functions)
  • retrieval Module
    • pydda.retrieval (pydda.retrieval)
  • vis Module
    • pydda.vis (pydda.vis)
  • initalization Module
    • pydda.initialization (pydda.initialization)
  • constraints Module
    • pydda.constraints (pydda.constraints)

Further support

We are now requesting that all questions related to PyDDA that are not potential software issues to be relegated to the openradar Discourse group <openradar.discourse.group> with a ‘pydda’ tag on it. This enables the entire open radar science community to answer questions related to PyDDA so that both the maintainer and users can answer questions people may have.

Indices and tables

• Index

• Module Index

• Search Page