DES_SuperNNova

Application of SuperNNova to DES

• Visualization of data original_data_visualization.py

• Testing light-curve skimming options run_skim_and_classification.py (Just the skimming can be done using skim_data_lcs.py)

• notebooks with data and peak exploration

Beware!!! Skimmed photometry fits tables can't be used as input for SNANA fits the original fits tables have assitional extensions with survey info

#Requirements:

Clone SuperNNova

it must be cloned in this repository

git clone https://github.com/supernnova/supernnova.git

Set up SuperNNova environment with conda

cd SuperNNova/env

# Create conda environment
conda create --name <env> --file <conda_file_of_your_choice>

# Activate conda environment
source activate <env>

DES data environment variable

setup an environment variable where data is. E.g. in bash/mac osx add to your ~/.bashrc or ~/.bash_profile

export DES_DATA=/Users/yourpathto/DES/data/