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 TidalPy@gmail.com.
Below is a non-exhaustive list of publicly available software that perform similar or parallel calculations as TidalPy.
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.
As of TidalPy v0.5.0:
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
.
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
.
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
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.
bin
subdirectory to your system's path.julia
and diffeqpy
for python using pip
pip install julia diffeqpy
import julia; julia.install(); import diffeqpy; diffeqpy.install()
If you ran into a problem that is not listed below please submit an issue and we will work on addressing it!
Known Problems:
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.
conda install setuptools
pip install setuptools
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.
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: TidalPy@gmail.com 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.
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):
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?
You are welcome to copy/fork TidalPy and make modifications assuming the following conditions are met:
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.
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: