TidalPy 0.5.4

Description:

TidalPy 0.5.4

TidalPy










Tidal Dynamics and Thermal-Orbital Evolution Software Suite Implemented in Cython and Python
TidalPy is an open-source software suite that utilizes a semi-analytic approach to estimate tidal heating,
orbit-rotation evolution, and thermal changes for rocky and icy worlds. It has been used to simulate the thermal-orbital
evolution of moons within our Solar System as well as exoplanets beyond. TidalPy's RadialSolver package can accurately
estimate the viscoelastic Love and Shida numbers for a multi-layered world, including the effects of liquid layers,
compressibility, dynamic tides, and advanced rheological models. This model has been used to study the tidal response
of Mercury, Venus, Earth, our Moon, and Mars.
Have any questions? Feel free to leave an issue or send a message to
[email protected].
Related Software
Below is a non-exhaustive list of publicly available software that perform similar or parallel calculations as TidalPy.

Are you interested in the habitability of a planet? With considerations of tides, atmospheres, water content, solar
interactions? Check out...

VPLanet


Are you interested in the orbital evolution of multiple planets with each planet influencing one another? Consider an
N-body approach like...

Posidonius (formerly Mercury-T)
ReboundX


Don't care about tides or orbital dynamics but are instead interested in interior structure and composition of
planets?

BurnMan
PerpleX


Are you interested in tides, interiors, and the chemical evolution of small worlds but don't care about
non-synchronous rotation or compressibility of planets?

IcyDwarf



However, if you want high fidelity tidal, orbital, spin, and interior models --- then you have come to the right place!
Read below for instructions on how to install and use TidalPy.
How to Install
Compatibility
As of TidalPy v0.5.0:

Windows-Latest: Installation & tests passed.
MacOS-Latest: Installation & tests passed.
Ubuntu-Latest: Installation & tests passed.

Basic Installation
Installing TidalPy is ass simple as ensuring 64-bit Python 3.9+ is installed on your
system and performing the following in a terminal:
pip install TidalPy
TidalPy can not currently be installed via conda install.
Accessing Jupyter Notebooks
There are several jupyter notebooks with TidalPy demos found in the /Demos/ folder of this repository.
In order to access these you will need to make sure you install Jupyter and a few related packages:
pip install ipympl ipython ipywidgets jupyter
or
conda install ipympl ipython ipywidgets jupyter
You can then clone this GitHub repository,
git clone https://github.com/jrenaud90/TidalPy
to a local directory. Navigate to this directory and the Demos sub-directory then access the notebooks by using the command,
jupyter notebook.
Cartopy
TidalPy offers the ability to make nice 2D plots using the cartopy package for some of
3d projection map plotting. In turn, cartopy relies on GEOS which is not a python
package and must be installed outside of pip.
The easiest way to install cartopy is using an Anaconda environment by,
conda install -c conda-forge cartopy
If you are not using a conda environment then you will need to find and install the GEOS binaries manually:
Windows: Follow instructions here
On Ubuntu: sudo apt-get install libgeos-dev
On MacOS: brew install geos
After GEOS is installed you can pip install the rest,
pip install pyproj shapely pyshp cartopy
DiffEqPy / Julia
TidalPy provides the option to use the Julia programming language's differential equation
solver for python: diffeqpy. To utilize this package you first need to ensure
that Julia is installed on your machine and available via the system's environment path.

Install the Julia language from https://julialang.org/downloads/
Add Julia's directory and its bin subdirectory to your system's path.
Open an elevated ("as administrator") terminal, command prompt, or powershell.

If you are using a virtual Python environment make sure it is active.


Install julia and diffeqpy for python using pip

Run pip install julia diffeqpy


Open Python on your elevated terminal (the following steps may take a while to compile).

Run import julia; julia.install(); import diffeqpy; diffeqpy.install()



Installation Troubleshooting
If you ran into a problem that is not listed below please submit an issue and we will work on addressing it!
Known Problems:

The setuptools package is required before TidalPy can be installed. Usually it is automatically installed, but if
you are starting with a clean virtual environment it may not have been.

For Anaconda: conda install setuptools
Or for regular Python: pip install setuptools



How to Use TidalPy
Check out the Documentation\Getting Started.md file. This is pretty bare bones at the moment but offers some basic
info about TidalPy. For now the best way to learn how to use TidalPy is by checking out the Demos directory. There
are "beginner" Jupyter notebooks that are a great starting point.
Using TidalPy for Science
TidalPy has been used in several studies already, and we encourage you to use it in yours. We would appreciate you
include a link back to this page and cite one of the papers discussed in
the next section. We also would love to see where TidalPy is being used! Please feel free to send us an
email: [email protected] when a paper or presentation utilized TidalPy. Anyone is welcome to
make forks or copies of TidalPy as long as their work references back to this page. License information can be found at
the end of this file.
Citing TidalPy
If you use TidalPy for your research please cite its Zenodo doi: 10.5281/zenodo.7017474.
The science used in TidalPy is described in the following papers and software (and references therein):

Rheological Modeling Package:

Tidally Heated Terrestrial Exoplanets: Viscoelastic Response Models
Increased Tidal Dissipation Using Advanced Rheological Models


Non-synchronous Rotation Evolution and High Eccentricity Truncation Packages:

Tidal Dissipation in Dual-Body, Highly Eccentric, and Non-synchronously Rotating System
Tidal Evolution of the Keplerian Elements


Third Party Software:

Interior Model: BurnMan
Integration Routines: CyRK
CVD Conscious Color Maps: Geodynamic Color Maps
Projection Maps: Cartopy
Exoplanet data: Astroquery, AstroPy



Contribute to TidalPy
TidalPy is in early alpha and there are lots of areas where it can improve! If you are interested in helping out, please
check out the information in Documentation\Contribute.md.
Found a bug or have an idea for a new feature?

Go to TidalPy's Github page and click the "Issues" tab then make a new report.

If you ran into a bug please include a code snippet (in markdown: code is designated by Grave accents surrounding
the text) that reproduces the error (please keep this snippet as concise as possible).
It is helpful to triage issues when they are made. If you think you know the severity of a bug or can provide any
other at-a-glance context, consider adding a "label" (right-hand side of the github issue form) to the issue.



License Information
You are welcome to copy/fork TidalPy and make modifications assuming the following conditions are met:

Links are included that point back to this page.
Any software derived from TidalPy must remain open-source and non-commercial.

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view
a copy of this license,
visit http://creativecommons.org/licenses/by-nc-sa/4.0/ or send a
letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
Acknowledgements
TidalPy was partially developed with support from NASA Goddard Space Flight Center's
Sellers Exoplanet Environments Collaboration (SEEC) and Geodesy ISFM.
TidalPy is partially based upon work supported by NASA under award number 80GSFC21M0002 and the
Center for Research and Exploration in Space Science & Technology II (CRESST II) administered at the University of
Maryland, College Park.
TidalPy has been improved by numerous contributors some of which you can find here.
TidalPy has benefited from work and conversations with the following:

Wade G. Henning (U. of Maryland, College Park / NASA GSFC)
Sander Goossens (NASA GSFC)
Marc Neveu (U. of Maryland, College Park / NASA GSFC)
Gael Cascioli (U. of Maryland, Baltimore County / NASA GSFC)