zELDA’s documentation

Contents:

• Introduction
  • Authors
  • Publication links
  • Origins and motivation
• Installation
  • Python package
  • LyaRT data grids
  • Partial installation for testing
• About the LyaRT data grids
  • Getting started
  • Line profile LyaRT data grids
  • Line profile grids with smaller RAM occupation
• Tutorial : Computing ideal line profiles
  • Computing one ideal line profile
  • Computing many ideal line profile
• Tutorial : Computing mock line profiles
  • Mocking Lyman-alpha line profiles
  • Plotting cooler line profiles
• Tutorial : Fitting a line profile using deep learning
  • Getting started
  • Using the DNN in the un-perturbed line profile
  • Using the DNN with Monte Carlo perturbations
• Tutorial : Train your own neural network
  • Generating data sets for the training
  • Get your DNN ready!
  • Using your custom DNN
• Tutorial : Fitting a line profile using Monte Carlo Markov Chains
  • Getting started
  • The MCMC anlysis
  • Tool to make corraltion plots
• Tutorial : Computing Lyman-alpha escape fractions
  • Default computation of escape fractions
  • Deeper options on predicting the escape fraction
• funcs module

Indices and tables

• Index