deeplenstronomy 0.0.1.0

wrap lenstronomy for efficient simulation generation

Welcome to deeplenstronomy!

deeplenstronomy is a tool for simulating large datasets for applying deep learning to strong gravitational lensing. It works by wrapping the functionalities of lenstronomy in a convenient yaml-style interface, allowing users to embrace the astronomer part of their brain rather than their programmer part when generating training datasets.

Installation

• Step 0: Set up an environment. This can be done straightforwardly with a conda installation:

conda create -n deeplens python=3.7 jupyter scipy pandas numpy matplotlib astropy h5py PyYAML mpmath future
conda activate deeplens

• Step 1: pip install lenstronomy
• Step 2: pip install deeplenstronomy

Documentation

Start by reading the Getting Started Guide to familiarize yourself with the deeplenstronomy style.

After that, check out the example notebooks below:

Notebooks for deeplenstronomy Utilities

• Creating deeplenstronomy Configuration Files
• Generating Datasets
• Visualizing deeplenstronomy Images
• Utilizing Astronomical Surveys
• Defining Your Own Probability Distributions
• Using Your Own Images as Backgrounds
• Simulating Time-Series Datasets

Notebooks for Applying deeplenstronomy to Machine Learning Analyses

• Using deeplenstronomy for Active Learning
• Using deeplenstronomy for Classification and Regression

Notebooks for Suggested Science Cases

• A Walkthrough of Using deeplenstronomy for Science

Contact

If you have any questions or run into any errors with the beta release of deeplenstronomy, please don't hesitate to reach out:

Rob Morgan
robert [dot] morgan [at] wisc.edu

You can also message me on the DES, DELVE, LSSTC, deepskies, or lenstronomers Slack workspaces