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A package to manipulate particle collisions

Project description

Sparticles

Manipulate collision events via graphs and graph neural networks.

TL;DR

The EventsDataset, a Pytorch Geometric Dataset, allows you to download a dataset of graphs representing collisions.

from dataset import EventsDataset

graphs = EventsDataset(
            root='/Users/alessiodevoto/Desktop/test_dataset3',
            delete_raw_archive=False,
            event_subsets={'signal': 100, 'singletop': 100, 'ttbar': 100},
            url='<secret_url>')

graphs

EventsDataset(300)

Each event is a graph with 6/7 nodes. Each node is built from the raw file as follows:

Particle Feature 1 Feature 2 Feature 3 Feature 4 Feature 5 Feature 6
jet1 'pTj1' 'etaj1' 'phij1' 'j1_quantile' nan nan
jet2 'pTj2' 'etaj2' 'phij2' 'j2_quantile' nan nan
jet3 (optional) 'pTj3' 'etaj3' 'phij3' 'j3_quantile' nan nan
b1 'pTb1' 'etab1' 'phib1' 'b1_quantile' 'b1m' nan
b2 'pTb2' 'etab2' 'phib2' 'b2_quantile' 'b2m' nan
lepton 'pTl1' 'etal1' 'phil1' nan nan nan
energy 'ETMiss' nan 'ETMissPhi' nan nan 'metsig_New'
g = graphs[0]
print(g)

Data(x=[6, 6], edge_index=[2, 30], y=[1], event_id='signal_6350')

from visualize import plot_event_2d
plot_event_2d(graphs[100])
a_list_of_graphs = [graphs[i] for i in range(0, 300, 30)]
plot_event_2d(a_list_of_graphs, height=1500)

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