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This commit updates the estimate_errors() function so that it works
without a list of constraints and uses arrays of low and high bounds
passed in instead of hardcoded constraints.
I can now call this function from the chi2 analysis to get the stepsizes
before running the MCMC.
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- delete instrumental tags in both scripts since we already tag them in
get_events()
- apply the same cuts to the MC as to the data
- add a comment about the fitted fraction
- quit if we don't have at least 1 type of each instrumental
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memory
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instrumentals
This commit updates the contamination analysis scripts to take into account the
fact that we only fit a fraction of some of the instrumental events.
Based on the recent rate at which my jobs have been running on the grid,
fitting all the events would take *way* too long. Therefore, I'm now planning
to only fit 10% of muon, flasher, and neck events. With this commit the
contamination analysis will now correctly take into account the fact that we
aren't fitting all the instrumental events.
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- print out mean acceptance fraction and autocorrelation time
- print standard normal distribution pdf with pull plot histograms
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This commit updates the step size used for the MCMC in the contamination
analysis to 0.5 times the error returned by scanning near the minimum. I ran
some tests and this seemed to be pretty efficient compared to either the full
error or 0.1 times the error. I also reduced the number of workers to 10.
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- fix Constraint.renormalize_no_fix() which could enter an infinite loop if the
fixed parameter was greater than 1 - EPSILON
- don't divide by psi twice in get_events()
- only use prompt events and cut on nhit_cal < 100
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