Skip to main content

MCMC fitting code for low temperature atmosphere spectra

Project description

UCDMCMC

Markov Chain Monte Carlo (MCMC) fitting code for low-temperature stars, brown dwarfs ande extrasolar planet spectra, tuned particularly to the near-infrared.

INSTALLATION NOTES

ucdmcmc can be installed from pip:

pip install ucdmcmc

or from git:

git clone
cd ucdmcmc
python -m setup.py install

It is recommended that you install in a conda environment to ensure the dependencies do not conflict with your own installation

conda create -n ucdmcmc python=3.13
conda activate ucdmcmc
pip install ucdmcmc

A check that this worked is that you can import ucdmcmc into python/jupyter noteobook, and that the ucdmcmc.MODEL_FOLDER points to the models folder that was downloaded

ucdmcmc uses the following extenal packages:

  • astropy
  • astroquery
  • corner
  • emcee
  • matplotlib
  • numpy<2.0
  • pandas
  • tables
  • requests
  • scipy
  • statsmodels
  • tqdm

Optionally install SPLAT

To generate new model sets using the built-in generateModels() function, you will need to install SPLAT (note: this is not necessary for the other functionality in this code). SPLAT is not automatically installed on setup. The instructions are essentially the same:

git clone https://github.com/aburgasser/splat.git
cd splat
python -m pip install .

See https://github.com/aburgasser/splat for additional instructions

Models

ucdmcmc comes with a starter set of models that play nicely with the code. An extended set can be downloaded from https://spexarchive.coolstarlab.ucsd.edu/ucdmcmc/

Spectra

ucdmcmc comes with a starter set of spectra for the following instruments:

Usage

[TBD examples]

Citing the code

[TBD]

ucdmcmc and its antecedents has been used in the following publications:

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

ucdmcmc-1.0.5.tar.gz (44.1 MB view details)

Uploaded Source

Built Distribution

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

ucdmcmc-1.0.5-py3-none-any.whl (44.1 MB view details)

Uploaded Python 3

File details

Details for the file ucdmcmc-1.0.5.tar.gz.

File metadata

  • Download URL: ucdmcmc-1.0.5.tar.gz
  • Upload date:
  • Size: 44.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ucdmcmc-1.0.5.tar.gz
Algorithm Hash digest
SHA256 6b64e388a549aeb16b345a65778e87a2e6ac35c4b4977bb1d6c6d896d1e23f69
MD5 7838708981830466eaf231167748f368
BLAKE2b-256 6a33a2a1beb21b1c21a0044beb72667b616ad91acbc5ed68ff6cb2a759270835

See more details on using hashes here.

Provenance

The following attestation bundles were made for ucdmcmc-1.0.5.tar.gz:

Publisher: pypi-publish.yml on aburgasser/ucdmcmc

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ucdmcmc-1.0.5-py3-none-any.whl.

File metadata

  • Download URL: ucdmcmc-1.0.5-py3-none-any.whl
  • Upload date:
  • Size: 44.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ucdmcmc-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 13e3604eb78a2a9e886cc11ffc1bd6330a4437a95d18c9bd2d55d2b33ab6c6b9
MD5 27ec625f9ad86ba0df46d0005863acd0
BLAKE2b-256 4494ea54b54670e758ed52b854a206dfa56a635110c04fd4b596512872c56c30

See more details on using hashes here.

Provenance

The following attestation bundles were made for ucdmcmc-1.0.5-py3-none-any.whl:

Publisher: pypi-publish.yml on aburgasser/ucdmcmc

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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