Metadata-Version: 2.4
Name: ExoRM
Version: 4.0.4
Summary: a model for the mass of an exoplanet given the radius
Author: Kevin Zhu
Author-email: kzhu2099@gmail.com
Maintainer: Kevin Zhu
Maintainer-email: kzhu2099@gmail.com
License: MIT License
        
        Copyright (c) 2025 Kevin Zhu
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://github.com/kzhu2099/ExoRM
Project-URL: Issues, https://github.com/kzhu2099/ExoRM/issues
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: arviz
Requires-Dist: astroquery
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: platformdirs
Requires-Dist: pymc
Requires-Dist: pytensor

# ExoRM

ExoRM is a model for the mass of an exoplanet given the radius

- HomePage: https://github.com/kzhu2099/ExoRM
- Issues: https://github.com/kzhu2099/ExoRM/issues

[![PyPI Downloads](https://static.pepy.tech/badge/ExoRM)](https://pepy.tech/projects/ExoRM)

Author: Kevin Zhu

## Features

- continuous radius-mass relationship
- smooth
- simple usage, log10 and linear
- method to create your own model, existing model provided

## Installation

To install ExoRM, use pip: ```pip install ExoRM```.

However, many prefer to use a virtual environment (or any of their preferred choice).

macOS / Linux:

```sh
# make your desired directory
mkdir /path/to/your/directory
cd /path/to/your/directory

# setup the .venv (or whatever you want to name it)
pip install virtualenv
python3 -m venv .venv

# install ExoRM
source .venv/bin/activate
pip install ExoRM

deactivate # when you are completely done
```

Windows CMD:

```sh
# make your desired directory
mkdir C:path\to\your\directory
cd C:path\to\your\directory

# setup the .venv (or whatever you want to name it)
pip install virtualenv
python3 -m venv .venv

# install ExoRM
.venv\Scripts\activate
pip install ExoRM

deactivate # when you are completely done
```

## Usage

To first begin using ExoRM, the data and model must be initialized. This is due to the constant discovery of new exoplanets, adding to the data. You may also call these at any time to update the model.

There is an existing model created in `best_inputs.pkl` and `best_trace.nc`, simply provide these paths when you are using to avoid creating your own model.

However, to get your own data and create your own model, simply run `get_data()` and `initialize_model()`. Note: import those by using `from ExoRM.get_data import get_data()` and `from ExoRM.initialize_model() import initialize_model()`. A plot of the model will be shown for you to see. Both are stored in your OS's Application Data for ExoRM. ExoRM provides built in functions to retrieve from this folder.

Usage of the model requires initializiation of the class and loading of the trace from a .nc file.

Note that all files saved are located in `/Users/<username>/Library/Application Support/ExoRM` for macOS and `C:\Users\<username>\AppData\Local\ExoRM\ExoRM` for windows.

The model supports log10 and linear scale in earth radii. When using the `model([...]), .__call__([...]), or .predict([...])`, the log10 scale is used. Linear predictions are used in `.predict_linear([...])`.

Uncertainty (upper and lower bounds) can be accessed from `predict_full` and `predict_full_liner`.

An example is seen in the `example.ipynb`. Deep analysis is seen in `comparison.ipynb`, showing statistical results and a comparison with Forecaster. Those use additional libraries for visualization and statistics (seaborn and SciPy).

## Additional notes

ExoRM has an implementation of Forecaster for according to the NASA Exoplanet Archive.

Forecaster: https://github.com/chenjj2/forecaster
NASA Exoplanet Archive implementation: https://exoplanetarchive.ipac.caltech.edu/docs/pscp_calc.html

## License

The License is an MIT License found in the LICENSE file.
