Skip to main content

No project description provided

Project description

About mesalab pipeline

DOI Documentation Status

⚠️NOTE: This project is currently under active development. Features and APIs may change, and new functionalities are continuously being added.

The Python package mesalab is designed for processing and analyzing stellar evolution simulations performed with MESA (Modules for Experiments in Stellar Astrophysics). It is developed to efficiently handle large grids of simulations, such as those where stellar mass (M) and metallicity (Z) are systematically varied.

The primary goal of this pipeline is to take your MESA outputs and automatically:

  1. Analyze each simulation within your grid.
  2. Identify if the star enters the blue loop phase and crosses the instability strip.
  3. Based on these findings, prepare GYRE input files and run the corresponding pulsation simulations.

Installation

Install from pip

To install mesalab with pip:

$ pip install mesalab

Building from Source (Recommended for Developers)

For scientific packages with complex dependencies like mesalab, we highly recommend using a conda environment to build from source. This ensures all binary dependencies are handled correctly, avoiding common compiler errors.

Step 1: Set up the conda environment (Python version between 3.9 and 3.11) Create a dedicated environment with all the necessary scientific packages. The conda-forge channel is required for some dependencies.

$ conda create --name mesalab_env python=3.9
$ conda activate mesalab_env
$ conda install -c conda-forge numpy pandas matplotlib scipy pyyaml tqdm numba swifter dask pyarrow h5py astropy

Step 2: Install mesalab from source Clone the repository and install the project in "editable" mode.

$ git clone https://github.com/konkolyseismolab/mesalab
$ cd mesalab
$ pip install -e .

Usage

To get started, you'll need to prepare a configuration file (e.g., config.yaml) that specifies your MESA input directories, output locations, and analysis preferences.

You can run mesalab by providing your configuration file:

$ mesalab --config myconfig.yaml

For a full list of command-line arguments and their descriptions, use the help command:

$ mesalab --help

For more detailed information on configuration options, command-line arguments, and advanced usage, please consult the official mesalab documentation on Read the Docs.


Contributing

If you're interested in improving mesalab, feel free to fork the repository, make your changes, and submit a pull request. You can also open an issue on GitHub if you encounter bugs or have feature suggestions.


License

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mesalab-2.2.0.tar.gz (92.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mesalab-2.2.0-py3-none-any.whl (78.2 kB view details)

Uploaded Python 3

File details

Details for the file mesalab-2.2.0.tar.gz.

File metadata

  • Download URL: mesalab-2.2.0.tar.gz
  • Upload date:
  • Size: 92.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for mesalab-2.2.0.tar.gz
Algorithm Hash digest
SHA256 d2c871de38566c451a69ec79ff1ca653b1e213a918f47a35e40f35c53e59ba6e
MD5 f944d7e060f9ac3e82f36318d057acac
BLAKE2b-256 92cd9bd1496c360084bf968cc97297769b41633cdf4c90df84a15091ab3c8805

See more details on using hashes here.

File details

Details for the file mesalab-2.2.0-py3-none-any.whl.

File metadata

  • Download URL: mesalab-2.2.0-py3-none-any.whl
  • Upload date:
  • Size: 78.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for mesalab-2.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9acd09df5c7e62fcb94795d6f3e77703110832e5b74fd71e37d8a716cef2cc0d
MD5 14e39ffaa00b1f28577e22eb09efa0f4
BLAKE2b-256 a367bcb0077c1eb0914746ded74223a1146811de43ac0b93f25fb30792345c9f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page