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pydarnmusic's Introduction

pyDARN Multiple Signal Classification (MUSIC) algorithm for MSTID parameter estimations

Create a folder for PyDARNMusic on your local computer

Use your terminal to cd into that directory

Initilize git inside PyDARNMusic directory using command: git init

Clone PyDARNMusic with command: git clone https://github.com/HamSCI/pyDARNmusic.git

Create a virtual environment inside the PyDARNMusic directory example: conda create -n name-of-virtual-environment python=3.8.13

Open vscode and open folder where PyDARNMusic is cloned.

Open terminal in vscode and activate virtual environment example: conda activate name-of-virtual-environment

After virtual environment is activated install PyDARNMusic with the following command: pip install -e .

Open notebook and on the top right hand side select kernal and select python environment: select the conda environment you created from the list of virtual environments

Change the data directory path to match your computer path to the data

Click clear output and click Run All to run the whole notebook

pydarnmusic's People

Contributors

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Stargazers

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Watchers

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pydarnmusic's Issues

Make ground scatter mapping and half slant mapping consistant

The original MUSIC code used the Bristow et al. [1994] ground scatter mapping. This mapping in the current version of PyDARN does not return the full FOV array and therefore is incompatible with this version of MUSIC. To make this version of MUSIC work, we set the GS mapping to use the half_slant mapping in PyDARN. This is compatible, and will likely produce similar results to the Bristow et al. ground scatter mapping.

The code needs to be cleaned up to:

  1. At the very least, make it clear that half_slant is being used instead of Bristow et al. 1994.
  2. Better would be to make both the Bristow ground mapping and half_slant mapping both work and be accessible.

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