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https://github.com/amberlee2427/gullsposteriors

Collects posterior distributions for Gulls simulation events

https://github.com/amberlee2427/gullsposteriors

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Repository

Collects posterior distributions for Gulls simulation events

Basic Info
  • Host: GitHub
  • Owner: AmberLee2427
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: no-LOM
  • Size: 58.4 MB
Statistics
  • Stars: 1
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed 10 months ago
Metadata Files
Readme License Agents

README.md

GullsPosteriors

This repository collects posterior distributions for microlensing events generated by the Gulls simulations. The code is organised into modular packages and a few run scripts that drive end‑to‑end fits.

Repository layout

  • Data – routines for loading light‑curve data. Data.load_data enumerates the file columns and explains how magnitudes may be derived from the fluxes.
  • Event – represents an individual microlensing event. It links Parallax and Orbit helpers to compute magnification curves.
  • Fit – parameter inference tools. Sampling is provided by emcee or dynesty with convenience routines for plotting chains and corner diagrams.
  • Orbit – uses JPL Horizons to fetch observatory ephemerides.
  • Parallax – converts observatory positions into north/east coordinates and provides parallax shifts.
  • Scripts and notebooks – utilities such as gulls_post_emcee_bound_w_pt.py run the full modelling workflow. Sample notebooks illustrate analyses.

Installing

Create and activate a conda environment using the packages listed in environment.yml:

```bash

Create the environment

conda env create -f environment.yml

Activate the environment

conda activate GullsPosteriors

Verify the installation

python -c "import emcee; import dynesty; import VBMicrolensing; print('Installation successful!')" ```

Key dependencies include Python 3.8, emcee, dynesty and the external VBMicrolensing package.

Example usage

The gulls_post_emcee_bound_w_pt.py script accepts the number of events to process and optional flags for sampler and threads, e.g.

bash python gulls_post_emcee_bound_w_pt.py 1 -s emcee -t 4

Plots and posterior samples are saved in the working directory.

Learning more

  • Examine Data.new_event and Data.load_data to understand the light‑curve format.
  • Event.projected_separation describes the source–lens geometry.
  • Fit exposes run_emcee and prior_transform for controlling MCMC or nested sampling.
  • The included notebooks showcase references and diagnostic plots.

License

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

Owner

  • Name: Amber
  • Login: AmberLee2427
  • Kind: user
  • Location: New Zealand

GitHub Events

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Last Year
  • Watch event: 1
  • Delete event: 24
  • Push event: 92
  • Public event: 1
  • Pull request event: 73
  • Create event: 35

Dependencies

environment.yml conda
  • astropy
  • astroquery
  • corner
  • dynesty
  • emcee
  • matplotlib
  • numpy
  • pandas
  • pip
  • python 3.12.*
  • scipy
requirements.txt pypi
  • VBMicrolensing *
  • astropy *
  • astroquery *
  • corner *
  • dynesty *
  • emcee *
  • matplotlib *
  • numpy *
  • pandas *
  • scipy *