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[pre-commit.ci] pre-commit autoupdate #51

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[pre-commit.ci] pre-commit autoupdate #51

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46be476
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Feb 3, 2025
2b4302b
[pre-commit.ci] auto fixes from pre-commit hooks
pre-commit-ci[bot] Feb 3, 2025
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8 changes: 4 additions & 4 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ default_language_version:

repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.6.0
rev: v5.0.0
hooks:
- id: trailing-whitespace
- id: check-added-large-files
Expand All @@ -21,20 +21,20 @@ repos:
args: ['--fix=no']

- repo: https://github.com/PyCQA/isort
rev: 5.13.2
rev: 6.0.0
hooks:
- id: isort
args: ["--profile", "black"]

- repo: https://github.com/psf/black
rev: 24.4.2
rev: 25.1.0
hooks:
- id: black
language_version: python3
args: [--line-length=125]

- repo: https://github.com/pycqa/flake8
rev: 7.1.0
rev: 7.1.1
hooks:
- id: flake8
# black-compatible flake-8 config
Expand Down
2 changes: 1 addition & 1 deletion models/bdt_trained_on_hhh_qcd.json
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26 changes: 8 additions & 18 deletions src/analysis/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,18 +25,18 @@ def calc_pur_eff(target_path, pred_path, bins, num_higgs=3):
LUT_resolved_pred, LUT_resolved_target, _ = parse_resolved_w_target(
target_h5, pred_h5, fjs_reco=None, num_higgs=num_higgs
)

# note: wOR LUTs only mark which resolved pred overlapped with any boosted pred
# Overlapped resolved pred. are NOT REMOVED
LUT_resolved_wOR_pred, LUT_resolved_wOR_target, _ = parse_resolved_w_target(
target_h5, pred_h5, fjs_reco=fjs_reco, num_higgs=num_higgs
)

# Calculate the number of bad removed particle reconstructions
# bad: removed due to overlapping but the target only has reconstruction in this topology
resolved_reco_is_correct = LUT_resolved_wOR_pred[:,:,0]==1
resolved_reco_is_reomved = LUT_resolved_wOR_pred[:,:,2]==1
resolved_target_has_no_boosted_target = LUT_resolved_wOR_pred[:,:,3]==0
resolved_reco_is_correct = LUT_resolved_wOR_pred[:, :, 0] == 1
resolved_reco_is_reomved = LUT_resolved_wOR_pred[:, :, 2] == 1
resolved_target_has_no_boosted_target = LUT_resolved_wOR_pred[:, :, 3] == 0
bad_OR = resolved_reco_is_correct & resolved_reco_is_reomved & resolved_target_has_no_boosted_target
good_OR = resolved_reco_is_correct & resolved_reco_is_reomved & ~resolved_target_has_no_boosted_target
surprising_OR = ~resolved_reco_is_correct & resolved_reco_is_reomved
Expand Down Expand Up @@ -75,7 +75,6 @@ def calc_pur_eff(target_path, pred_path, bins, num_higgs=3):

results["pur_r_or"], results["purerr_r_or"], _, _ = calc_pur(None, LUT_resolved_pred_no_OR, bins)
results["eff_r_or"], results["efferr_r_or"], _, _ = calc_eff(None, LUT_resolved_target_no_OR, bins)


print("Average purity:")
print("merged", avg_pur_m, "boosted", avg_pur_b, "resolved", avg_pur_r)
Expand All @@ -94,18 +93,9 @@ def calc_pur_eff(target_path, pred_path, bins, num_higgs=3):
"Number of Resolved Prediction after OR:",
np.array([pred for event in LUT_resolved_pred_no_OR for pred in event]).shape[0],
)
print(
"Number of bad overlap-removal:",
np.sum(bad_OR)
)
print(
"Number of good overlap-removal:",
np.sum(good_OR)
)
print(
"Number of surprising overlap-removal:",
np.sum(surprising_OR)
)
print("Number of bad overlap-removal:", np.sum(bad_OR))
print("Number of good overlap-removal:", np.sum(good_OR))
print("Number of surprising overlap-removal:", np.sum(surprising_OR))

return results

Expand Down
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