tracking

Simulation instructions:

If you don't wanna deal with the mess, all you care about are the files (ordered by dependence):

Transform.py

Simulate.py

produce.py

runMany.sh

N is the number of events per run, M is the average poissonian multiplicity. You can edit produce.py for pt distribution if you want.

add to .gitignore:

*~ .* *.csv *.pyc *.txt *.zip

Name		Name	Last commit message	Last commit date
Latest commit History 75 Commits
data		data
starting_kit		starting_kit
Clustering.py		Clustering.py
Fitting.py		Fitting.py
Hough.py		Hough.py
LinearApproximation.py		LinearApproximation.py
NearestHit.py		NearestHit.py
Plotting.py		Plotting.py
README.md		README.md
Score_assignment.py		Score_assignment.py
Score_cluster.py		Score_cluster.py
Score_event.py		Score_event.py
Score_physics.py		Score_physics.py
Simulate.py		Simulate.py
Tracking.py		Tracking.py
Transform.py		Transform.py
analyze.py		analyze.py
clusterer.py		clusterer.py
combine_dataset.sh		combine_dataset.sh
fast_hough3.py		fast_hough3.py
fast_hough3_yy_01.py		fast_hough3_yy_01.py
fit_track.py		fit_track.py
formulate.py		formulate.py
hough1.py		hough1.py
hough1_yy01.py		hough1_yy01.py
hyperbelle_tree_6.py		hyperbelle_tree_6.py
hyperbelle_tree_yy_01.py		hyperbelle_tree_yy_01.py
notebook.ipynb		notebook.ipynb
notebook_fitting.ipynb		notebook_fitting.ipynb
notebook_fitting_dev.ipynb		notebook_fitting_dev.ipynb
notebook_scoring.ipynb		notebook_scoring.ipynb
notebook_simulation.ipynb		notebook_simulation.ipynb
notebook_starting_kit.ipynb		notebook_starting_kit.ipynb
notebook_track_formula.ipynb		notebook_track_formula.ipynb
produce.py		produce.py
reconstruct.py		reconstruct.py
runMany.sh		runMany.sh
user_test_submission.py		user_test_submission.py

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