Age | Commit message (Collapse) | Author |
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This commit contains the following updates:
- remove hack to get rid of low energy events in plot-energy since while
writing the unidoc I realized it's not necessary now that we add +100 to
multi-particle fits
- update Ockham factor to use an energy resolution of 5%
- update submit-grid-jobs to submit jobs according to the following criteria:
- always submit prompt events with no data cleaning cuts
- submit 10% of prompt flasher events
- submit all other prompt events
- submit followers only if they have no data cleaning cuts
- update submit-grid-jobs to place the nhit cut of 100 on the calibrated nhit
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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.
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This commit updates the dc script to calculate the instrumental contamination
to now treat all 4 high level variables as correlated for muons. Previously I
had assumed that the reconstructed radius was independent from udotr, z, and
psi, but based on the corner plots it seems like the radius is strongly
correlated with udotr.
I also updated the plotting code when using the save command line argument to
be similar to plot-fit-results.
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This commit adds a script to calculate the background contamination using a
method inspired by the bifurcated analysis method used in SNO. The method works
by looking at the distribution of several high level variables (radius, udotr,
psi, and reconstructed z position) for events tagged by the different data
cleaning cuts and assuming that any background events which sneak past the data
cleaning cuts will have a similar distribution (for certain backgrounds this is
assumed and for others I will actually test this assumption. For more details
see the unidoc). Then, by looking at the distribution of these high level
variables for all the untagged events we can use a maximum likelihood fit to
determine the residual contamination.
There are also a few other updates to the plot-energy script:
- add a --dc command line argument to plot corner plots for the high level
variables used in the contamination analysis
- add a fudge factor to the Ockham factor of 100 per extra particle
- fix a bug by correctly setting the final kinetic energy to the sum of the
individual kinetic energies instead of just the first particle
- fix calculation of prompt events by applying at the run level
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