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)
Changelog
- version 0.0.4.3. Now the plotting function allows you to pass a show_edges and edges_weights parameters to display edges. Useful for visualizing attention maps.
Metadata
Release files for sparticles 0.0.4.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| sparticles-0.0.4.5.tar.gz | 12.0 kB | Without provenance | Details for sparticles-0.0.4.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| sparticles-0.0.4.5-py3-none-any.whl | Python 3 | none | any | Details for sparticles-0.0.4.5-py3-none-any.whl |
Total release size: 24.6 kB
Release files / sparticles-0.0.4.5.tar.gz
| Download URL | sparticles-0.0.4.5.tar.gz |
|---|---|
| Size | 12.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
05e68e1d758ce28b48887aa6da035f4f563a02d3eaa7b9bcabb41ed176763a24
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No |
| Uploaded via |
twine/4.0.2 CPython/3.9.13
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Release files / sparticles-0.0.4.5-py3-none-any.whl
| Download URL | sparticles-0.0.4.5-py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
001a15ac05a856b6990fb8e8f6cd83931b8437261118346946657b9b51bf6dc4
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BLAKE2b-256 checksum How to use checksums |
d3870085d13b21d4fe01fdf1a081b0e7439eff490a5943d9f7d5dc6a82d59eb2
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.13
|
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