This repo is forked from Geir's repo. My data analysis scripts are stored in the data/ folder.
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Data analysis for the temporal peaks classification using convolution
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Data analsysis for the temporal peaks classification using cluster analysis/ unsupervised learning
Classifying events in a nuclear physics experiment - an example
Standalone repository for classification example on simulated data that can be used in ML course.
This notebook contains a walkthrough from the first import of the data, formatting the data, initial analysis and exploration, and finally storing the data in a desired format.
A starting point for working with the traces datafile.
Scikit-Learn example on using logistic regression to classify the data. Presents the metrics we use to assess the performance of a binary classifier.
Keras example on using a fully-connected neural network to classify the data
Keras example on using a convolutional neural network to classify the data
Collection of functions developed throughout the notebooks that are useful to store for easier re-use.
- CeBr10k_1.txt
- file with 10000 events
- CeBr200k_Mix.txt.gz
- file with 200k events, compressed to comply with githubs max file size for regular repositories.
- training_pm_nosat_150k.dat.gz
- file with 150k traces, compressed.
- 3 python files used for data analysis. Placed in the same directory for convenience.
- Add example on model saving
- data exploration
- correlations
- energy distributions
- position distributions (including separation distances)