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Add test for passing multiple percentiles to calculate_percentile_cut #312

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Add test for passing multiple percentiles to calculate_percentile_cut #312

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6 changes: 3 additions & 3 deletions pyirf/cut_optimization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,7 +75,7 @@ def optimize_cuts(
fill_value = signal['gh_score'].max()

sensitivities = []
cut_indicies = []
cut_indices = []
n_theta_cuts = len(theta_cut_efficiencies)
n_gh_cuts = len(gh_cut_efficiencies)
n_cuts = len(multiplicity_cuts) * n_theta_cuts * n_gh_cuts
Expand Down Expand Up @@ -156,7 +156,7 @@ def optimize_cuts(
signal_hist, background_hist, alpha=alpha,
**kwargs,
)
cut_indicies.append((multiplicity_index, theta_index, gh_index))
cut_indices.append((multiplicity_index, theta_index, gh_index))
sensitivities.append(sensitivity)
bar.update(1)

Expand Down Expand Up @@ -192,7 +192,7 @@ def optimize_cuts(
# if all are invalid, just use the first one
best = 0

multiplicity_index, theta_index, gh_index = cut_indicies[best]
multiplicity_index, theta_index, gh_index = cut_indices[best]

best_sensitivity[bin_id] = sensitivities[best][bin_id]

Expand Down
34 changes: 34 additions & 0 deletions pyirf/tests/test_cuts.py
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Expand Up @@ -178,3 +178,37 @@ def test_calculate_percentile_cuts_table():
[dist1.ppf(0.68), dist2.ppf(0.68)],
rtol=0.1,
)




def test_calculate_percentile_cuts_multiple():
from pyirf.cuts import calculate_percentile_cut

np.random.seed(0)

dist1 = norm(0, 1)
dist2 = norm(10, 1)
N = int(1e4)

values = np.append(dist1.rvs(size=N), dist2.rvs(size=N)) * u.deg
bin_values = np.append(np.zeros(N), np.ones(N)) * u.m
# add some values outside of binning to test that under/overflow are ignored
bin_values[10] = 5 * u.m
bin_values[30] = -1 * u.m

bins = [-0.5, 0.5, 1.5] * u.m

cuts = calculate_percentile_cut(values, bin_values, bins, fill_value=np.nan * u.deg, percentile=[50, 68, 95])
assert np.all(cuts["low"] == bins[:-1])
assert np.all(cuts["high"] == bins[1:])

np.testing.assert_allclose(
cuts["cut"].to_value(u.deg),
[
[dist1.ppf(0.5), dist1.ppf(0.68), dist1.ppf(0.95)],
[dist2.ppf(0.5), dist2.ppf(0.68), dist2.ppf(0.95)],
],
rtol=0.1,
atol=0.1, # dist1.ppf(0.5) == 0, so we also need a non-zero atol
)
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