sddm - Code for the self-destructing dark matter search in SNO

Age	Commit message (Collapse)	Author
2021-01-03	cache results from get_events()	tlatorre

2020-12-15	add code to reweight the tau neutrino events	tlatorre
	This commit updates the code to reweight the MC data from tau neutrinos since I stupidly simulated the muon neutrino flux instead of the tau neutrino flux.
2020-11-30	update code to work with python3	tlatorre
	This commit updates the python code to work with python 3 and with a newer version of matplotlib. - zip_longest -> izip_longest - fix tick marks for log plots - scipy.misc -> scipy.special
2020-10-05	major updates to the chi2 analysis	tlatorre
	This commit fixes the chi2 analysis so that it is no longer biased. Previously, the chi2 analysis pull plots showed a consistent bias. At first, I thought this was due to the fact that the posterior wasn't gaussian, but even after switching to percentile plots based on the algorithm outlined in "Validating Bayesian Inference Algorithms with Simulation-Based Calibration", I was still seeing a bias. I finally tracked it down to the fact that I was applying the energy scale parameters to the data instead of the Monte Carlo. Therefore, in this commit I update the posterior to now apply the energy scale parameters to the Monte Carlo instead of the data. This has the slight disadvantage that the final histograms will be binned in the biased energy, but that's not really a big deal. In addition, this commit contains several other updates: - switch to plotting percentile plots based on the algorithm in "Validating Bayesian Inference Algorithms with Simulation-Based Calibration" instead of pull plots - apply both the energy scale and resolution at the individual particle level, i.e. there is no longer an energy resolution term for electron + muon fits - separate pull plots and coverage plots. Previously I was making both the p-value coverage plots and the pull plots at the same time. However, the pull plots shouldn't have anything to do with the GENIE weights whereas the p-value coverage plots should draw samples weighted by the GENIE weights. In addition, for the pull plots we draw new truth parameters on every iteration whereas for the p-value coverage plots we only draw them once. - switch to using KDEMove() for the MCMC since I think it samples multimodal distributions a lot better than the default emcee move. - I now correct for the reconstruction energy bias in plot-michel and plot-muons
2020-06-16	update read_hdf() to open hdf5 files in read only mode	tlatorre

2020-06-16	update follower cuts to be more memory efficient by using ffill()	tlatorre

2020-05-12	add a read_hdf() method that doesn't require pytables	tlatorre

2020-05-11	add setup_matplotlib function and switch to logarithmic bins	tlatorre
	This commit contains the following small updates: - create a setup_matplotlib() function to set up matplotlib correctly depending on if we are saving the plots or just displaying them - change default font size to 12 when displaying plots - switch to using logarithmic bins in plot-energy - fix despine() function when x axis is logarithmic
2020-05-11	don't import everything in __init__.py	tlatorre
	This commit updates utils/sddm/__init__.py to not import everything by default. The reason is that on the open science grid login machine they don't have the module scipy.stats by default.
2020-05-11	update utils/ folder to make a python package called sddm	tlatorre
	This commit adds an sddm python package to the utils/ folder. This allows me to consolidate code used across all the various scripts. This package is now installed by default to /home/tlatorre/local/lib/python2.7/site-packages so you should add the following to your .bashrc file: export PYTHONPATH=$HOME/local/lib/python2.7/site-packages/:$PYTHONPATH before using the scripts installed to ~/local/bin.