Centrality classes #164
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Centrality classes #164
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NGoetz
reviewed
Dec 7, 2023
| for i in range(1, len(self.centrality_bins_)): | ||
| MaxRecord = int(number_events * self.centrality_bins_[i] / 100.0) | ||
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| self.dNchdetaMax_.append(global_event_record[MinRecord]) |
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Why can this not happen in the loop above?
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Okay it should not affect the performance too much so we can leave it.
| events_multiplicity_ : list or numpy.ndarray | ||
| Stores the input multiplicity values for each event. | ||
| centrality_bins_ : list or numpy.ndarray | ||
| Stores the input boundaries of centrality classes. |
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This is from the usual cuts which are required to generate centrality classes. Its mostly charged particles and they are in a certain pseudorapidity range.
NGoetz
approved these changes
Dec 7, 2023
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This PR implements a CentralityClasses class, where the input is a list or array of multiplicity from events in a certain phase space. Then it generates centrality bins and there is a function to print these to a file.
If you then have a certain dNchdeta and want to know the class, then there is a function that returns the index of the corresponding class as an int.