paropy

An open source python package to process data from PARODY-JA4.3 dynamo simulations with a stably-stratified F-layer at the base of the outer core.

Getting Started¶

Welcome! Here is my Python package to process data from PARODY-JA4.3 dynamo simulations with a stably-stratified F-layer at the base of the outer core.

Prerequisites¶

• Python3
• SHTns
• ChaosMagPy

Installing¶

Conda:

conda install -c jnywong paropy

Pip:

pip install paropy

Git:

Find the Git repo here.

Warning: IPython issue¶

Please note that iPython may not be compatible with jedi release 0.18.0. Please revert to version 0.17.2 for auto-complete features to work (see here).

Package structure¶

paropy/
  docs/
  paropy/
    __init__.py
    data_utils.py
    plot_utils.py
    routines.py
    scripts/
      convective_power.py
      diagnostics.py
      diagnostic_parameters.py
      filter_surface_field.py
      latitude_vs_Br.py
      latitude_vs_Br_with_CHAOS.py
      meridional_snapshot.py
      meridional_timeavg.py
      rotation_rate.py
      surface_snapshot.py
      surface_timeavg.py
    data/
      CHAOS-7.7.mat
  LICENSE.md
  MANIFEST.in
  README.md
  setup.py

Examples¶

Diagnostics¶

Example scripts can be found within the module paropy.

1. Open paropy/scripts/diagnostics.py

2. Set path to simulation data by setting

run_ID = <run_ID> # PARODY simulation tag
directory = <path_to_data>
saveDir = <path_to_savefigs>

3. Run paropy/scripts/diagnostics.py

4. Admire the output:

Meridional snapshots¶

1. Open paropy/scripts/meridional_snapshot.py

2. Set path to simulation data and snapshot time by setting

run_ID, timestamp = 'c-200a', '16.84707134'
directory = <path_to_data>
saveDir = <path_to_savefigs>

3. Run paropy/scripts/meridional_snapshot.py

4. Admire the output:

Surface snapshots¶

1. Open paropy/scripts/surface_snapshot.py

2. Set path to simulation data and snapshot time by setting

run_ID, timestamp = 'c-200a', '16.84707134'
directory = <path_to_data>
saveDir = <path_to_savefigs>

3. Run paropy/scripts/surface_snapshot.py

4. Admire the output:

Links¶

• PyPI
• Anaconda Cloud

Data¶

• CHAOS-7.7 (Finlay et al. 2020)

Authors¶

• Jenny Wong - Institut de Physique du Globe de Paris - Institut des Sciences de la Terre

License¶

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments¶

• Del Duca Foundation
• ERC SEIC

🎉