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Fix cut acceptance plotting #135

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merged 11 commits into from
May 7, 2024
Merged

Fix cut acceptance plotting #135

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30cc2a9
Add YBe Generator
May 3, 2024
7e8e438
Merge branch 'main' of https://github.com/FaroutYLq/saltax into main
May 6, 2024
b09744b
Fix Cut Acceptance Plotting
May 6, 2024
593d4ab
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] May 6, 2024
d5e5269
clean mess
May 6, 2024
462b9ed
clean more mess
May 6, 2024
27b4efc
Merge branch 'fix_cut_acc' of https://github.com/FaroutYLq/saltax int…
May 6, 2024
c2e579b
cut ac
FaroutYLq May 7, 2024
16dd98d
debug
FaroutYLq May 7, 2024
4c40353
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] May 7, 2024
f7aa125
revert (#136)
FaroutYLq May 7, 2024
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36 changes: 23 additions & 13 deletions saltax/match/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -671,13 +671,6 @@ def get_cut_eff(
else:
raise NotImplementedError

if indv_cut_type == "n_minus_1":
cut_func = apply_n_minus_1_cuts
elif indv_cut_type == "single":
cut_func = apply_single_cut
else:
raise NotImplementedError

result_dict = {}
for cut in all_cut_list:
result_dict[cut] = np.zeros(n_bins - 1)
Expand All @@ -698,13 +691,30 @@ def get_cut_eff(
result_dict["all_cuts"][i] = len(selected_events_all_cut) / len(selected_events)
result_dict["all_cuts_upper"][i] = interval.high
result_dict["all_cuts_lower"][i] = interval.low

for cut_oi in all_cut_list:
selected_events_cut_oi = selected_events[apply_single_cut(selected_events, cut_oi)]
# Efficiency curves with Clopper-Pearson uncertainty estimation
interval = binomtest(len(selected_events_cut_oi), len(selected_events)).proportion_ci()
result_dict[cut_oi][i] = len(selected_events_cut_oi) / len(selected_events)
result_dict[cut_oi + "_upper"][i] = interval.high
result_dict[cut_oi + "_lower"][i] = interval.low
if indv_cut_type == "n_minus_1":
selected_events_cut_oi = selected_events[
apply_n_minus_1_cuts(selected_events, cut_oi, all_cut_list)
]
# Efficiency curves with Clopper-Pearson uncertainty estimation
interval = binomtest(
len(selected_events_all_cut), len(selected_events_cut_oi)
).proportion_ci()
result_dict[cut_oi][i] = len(selected_events_all_cut) / len(selected_events_cut_oi)
result_dict[cut_oi + "_upper"][i] = interval.high
result_dict[cut_oi + "_lower"][i] = interval.low
elif indv_cut_type == "single":
selected_events_cut_oi = selected_events[apply_single_cut(selected_events, cut_oi)]
# Efficiency curves with Clopper-Pearson uncertainty estimation
interval = binomtest(
len(selected_events_cut_oi), len(selected_events)
).proportion_ci()
result_dict[cut_oi][i] = len(selected_events_cut_oi) / len(selected_events)
result_dict[cut_oi + "_upper"][i] = interval.high
result_dict[cut_oi + "_lower"][i] = interval.low
else:
raise NotImplementedError

if plot:
colors = plt.cm.rainbow(
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