locs12

Code to study the localization of S1 and S2 signals in DarkSide20k.

Alphabetical file index by category

Data

• plot_saturation.root: temporal and spatial distribution of S2 hits.

Scripts

• plot_saturation.py: plot the contents of plot_saturation.root.

• temps1plots20210131.py: save performance and diagnostic plots of s1 temporal localization filters with the version of temps1.py from January 31, 2021.

• temps1plots20210203.py: save performance and diagnostic plots of s1 temporal localization filters with the version of temps1.py from February 3, 2021.

All the following temps1series*.py scripts write the results to temps1series*.npy and have a companion script temps1series*plot.py to do the plots, which can be used while the main script is still running to show partial results. The digits in the name are month-day.

• temps1series0203.py: (OUTDATED) efficiency vs. number of photons.

• temps1series0213.py: ER/NR discrimination and KDE bandwidth.

• temps1series0214.py: fast/slow discrimination and KDE bandwidth.

• temps1series0222.py: (OUTDATED) compare likelihood, cross correlation, and coincidence.

• temps1series0224.py: (OUTDATED) find optimal coincidence time.

• temps1series02240.py: (OUTDATED) compare likelihood, cross correlation, and coincidence.

• temps1series0226.py: find optimal coincidence time.

• temps1series0226z.py: find optimal cross correlation template sigma.

• temps1series0227.py: compare likelihood, cross correlation, and coincidence.

Modules

• aligntwin.py: code to align the ticks of multiple plot scales.

• ccdelta.py: compute the cross-correlation of dicrete points with a continuous function.

• clusterargsort.py: filter away values which are close to an higher value in a signal.

• coincth.py: formulas for the coincidence rate.

• dcr.py: generate uniform hits.

• downcast.py: downcast numpy data types recursively.

• filters.py: filters to be applied to a temporal sequence of hits.

• named_cartesian_product.py: cartesian product of arrays.

• npzload.py: class to serialize objects to numpy archives.

• numba_scipy_special/: module to add support for scipy.special functions in numba.

• pS1.py: (DEPRECATED) compute and sample the temporal distribution of S1 photons.

• ps12.py: compute and sample the temporal distribution of S1 and S2 photons.

• qsigma.py: equivalent of standard deviation with quantiles.

• runsliced.py: do something in batches with a progressbar.

• sampling_bounds.py: bounds for random ramples.

• symloglocator.py: class to place minor ticks on symlog scales.

• temps1.py: simulate the temporal localization of S1 signals.

• testccfilter.py: class to study where to evaluate the cross correlation filter.

• textbox.py: draw a box with text on a plot.

Dependencies

Should work with Python >= 3.6 and the standard Python scientific stack. Just in case: developed on Python 3.8.2, required modules with version numbers are listed in requirements.txt.