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Pytesimal

Pytesimal models the conductive cooling of planetesimals with temperature-dependent material properties.

Pytesimal is a finite difference code to perform numerical models of a conductively cooling planetesimal, both with constant and temperature-dependent properties. It returns a thermal history of the planetesimal, and the estimated timing and depth of pallasite meteorite genesis. The conduction equation is solved numerically using an explicit finite difference scheme, FTCS (Forward-Time Central-Space). FTCS gives first-order convergence in time and second-order in space, and is conditionally stable when applied to the heat equation. In 1D, it must satisfy Von Neumann stability analysis - please see Murphy Quinlan et al. (2020 - preprint) for more information on choice of time-step.

The code currently recreates the cases described in Murphy Quinlan et al. (2020 - preprint). References for the default parameters used can be found therein. We plan to extend it and make it more modular in future updates.

Quick Start

To run a case with default parameters:

from modular_cond_cooling import conductive_cooling

# Give your model set-up a unique file name:
run_ID = "file_name"

# Point it to a folder to save the outputs:
folder = "folder_path" 

# Let your planetesimal evolve:
conductive_cooling(run_ID, folder,)

See the Jupyter notebooks provided for working examples.

To download data from NGDC and plot it:

Navigate to the downloading_and_plotting_data directory. From the command line, run the required script to download the .dat files from the NGDC:

$ python downloaddata.py

Once the data is downloaded from the NGDC, it is available to plot using coolingplot.py with the filename you wish to plot:

$ python coolingplot.py constant_properties.dat

For more information run:

$ python coolingplot.py -h

Features

  • Constant or variable material properties
  • Download and plot data from NGDC
  • Choose to return compressed .npz NumPy arrays of temperature and cooling rates through time and radius
  • Plot temperature or cooling rate heatmaps
  • Return timing of core solidification, and depth and timing of meteorite formation
  • Return pickle objects with output parameter values
  • Return a parameter .txt file with details of input parameters and results

Installation

This software relies on python (version 3) and various other python packages. Examples are distributed as Jupyter notebooks, which need Jupyter and Matplotlib to run. Installation and management of all these dependencies is most easily done in a conda environment. Download of the software and creation of an isolated conda environment can be done by running:

git clone https://github.com/murphyqm/pytesimal.git
cd pytesimal
conda create -n=pytesimal python=3.8
conda activate pytesimal
pip install -r requirements.txt

Contribute

  • Issue Tracker: github.com/murphyqm/pytesimal/issues
  • Source Code: github.com/murphyqm/pytesimal

Support

If you are having issues, please let us know. You can email us at eememq@leeds.ac.uk

License

The project is licensed under the MIT license.