wrap lenstronomy for efficient simulation generation
Project description
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
Notebooks for Suggested Science Cases
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
Project details
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