Learning the Epoch of Reionization - LEoR

Code for the paper : https://arxiv.org/pdf/1805.02699.pdf A Convolutional Neural Network (CNN) taking 2D slice of light-cones (LC) and recover the 21cmFast input parameters.

Getting Started

The purpose of this repo is mainly a personal saving of the code.

Prerequisites

It need the database : LC_SLICE10_px100_2200_N10000_randICs_train.hdf5 (~70GB). Ask me for the data. The code has been run on SNS-Nefertem

Installing

• jupyter notebook
• keras
• theano (the paper as been made with theano) (or tensorflow: the code as been optimize after the publication to GPU for futur study)

Running

• set the parameters of the CNN :
  • param_all4_2D_smallFilter_1batchNorm_multiSlice.py
  • the name of the parameter file can be change in CNN_lightcone_2D.py
• Learning:

python CNN_lightcone_2D.py

• Analisis and plots:
  • jupyter notebook : CNN_analyseNet.ipynb
  • will load the learned CNN and validation/testing dataset for the plots.
• The already trained CNN is available in CNN_analyseNet.ipynb

Authors

• Nicolas Gillet - LEoR

License

Acknowledgments

• The database has been made by Bradley Greig