Iterative Bayesian 3D (t, x, y) S2 merging #1513
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dachengx
commented
Jan 10, 2025
| } | ||
| local_rses = {"UC_DALI_USERDISK": r".rcc.", "SDSC_USERDISK": r".sdsc."} | ||
| local_rses = {"UC_DALI_USERDISK": r"^dali(\w*).rcc.", "SDSC_USERDISK": r".sdsc."} |
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Only load UC_DALI_USERDISK rucio when on dali servers.
…1521) * Reduce storage usage by creating new `data_type` `enhanced_peaklet_classification_dtype` * Constraint boundaries
straxen/plugins/events/events.py
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Isnt selecting that the merging is type 1 or 2 a bit different from making sure it is not type 20? As maybe type 0 and other types get merged? Why not just exclude type 20 instead?
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Because S0 can anyway not trigger an event before this PR. Before this PR only S2 trigger events.
dachengx
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Jan 15, 2025
juehang
reviewed
Jan 16, 2025
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| n_tpc_pmts = straxen.URLConfig(type=int, help="Number of TPC PMTs") | ||
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| n_top_pmts = straxen.URLConfig(type=int, help="Number of top TPC array PMTs") | ||
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| default_reconstruction_algorithm = straxen.URLConfig( |
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This variable is never used, the code seems to stick to DEFAULT_POSREC_ALGO.
3 tasks
* Add URLconfig option and code to use contour area for weights * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add use_uncertainty_weights to get_merge_instructions * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Resolving pre-commit-hook changes * use copied contour variable to avoid self-modification issues * remove doubled line * Minor change --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: juehang <qinjuehang@rice.edu> Co-authored-by: dachengx <dx2227@columbia.edu>
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Before you submit this PR: make sure to put all operations-related information in a wiki-note, a PR should be about code and is publicly accessible
Depends on AxFoundation/strax#946 and AxFoundation/strax#951
Combining #1495 and #1512.
What does the code in this PR do / what does it improve?
Merge S2 based on the probability that the two peaklets are from the same normal distribution.
Can you briefly describe how it works?
For more details please refer to https://xe1t-wiki.lngs.infn.it/doku.php?id=xenon:xenonnt:analysis:s2_merging_time_position.
Can you give a minimal working example (or illustrate with a figure)?
Please include the following if applicable:
Notes on testing
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