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Shuffling NTSeason background events in RA and updates on sensitivity curve errorbars #450

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Shuffling NTSeason background events in RA and updates on sensitivity curve errorbars #450

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00f37ef
introduce another way to estimate error on sensitivity curve errorbars
Mar 19, 2026
63ca455
shuffle NTSeason background events in RA
Mar 19, 2026
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14 changes: 10 additions & 4 deletions flarestack/core/results.py
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Original file line number Diff line number Diff line change
Expand Up @@ -521,7 +521,7 @@ def find_overfluctuations(self, ts_val, savepath=None):
either case, a plot of the overfluctuations as a function of the
injected signal is produced.
"""
x_acc, y, yerr = [], [], []
x_acc, y, yerr, yerr_ts_jitter = [], [], [], []
x = self.scale_labels

for scale in x:
Expand All @@ -542,6 +542,12 @@ def find_overfluctuations(self, ts_val, savepath=None):
x_acc.append(float(scale))
yerr.append(1.0 / np.sqrt(float(len(ts_array))))

# another way to estimate the error on the overfluctuation fractions
ts_mean_fluc = np.mean(ts_array) / np.sqrt(len(ts_array))
frac_ul = float(len(ts_array[ts_array + ts_mean_fluc > ts_val])) / (float(len(ts_array)))
frac_ll = float(len(ts_array[ts_array - ts_mean_fluc > ts_val])) / (float(len(ts_array)))
yerr_ts_jitter.append(np.max([(frac_ul-frac_ll)/2., 1e-5]))

if frac != 0.0:
logger.info(f"Making plot for {scale=}, {frac=}")
self.make_plots(scale)
Expand All @@ -555,13 +561,13 @@ def find_overfluctuations(self, ts_val, savepath=None):
)

x = np.array(x_acc)
self.overfluctuations[ts_val] = x, y, yerr
self.overfluctuations[ts_val] = x, y, yerr, yerr_ts_jitter

fit, err, extrapolated = self.sensitivity_fit(savepath, ts_val)
return fit, err, extrapolated

def sensitivity_fit(self, savepath, ts_val):
x, y, yerr = self.overfluctuations[ts_val]
x, y, yerr, yerr_ts_jitter = self.overfluctuations[ts_val]
x_flux = k_to_flux(x)

threshold = 0.9
Expand Down Expand Up @@ -612,7 +618,7 @@ def best_f(x, sd=0.0):

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.errorbar(x_flux, y, yerr=yerr, color="black", fmt=" ", marker="o")
ax1.errorbar(x_flux, y, yerr=yerr_ts_jitter, color="black", fmt=" ", marker="o")
ax1.plot(k_to_flux(xrange), best_f(xrange), color="blue")
ax1.fill_between(
k_to_flux(xrange),
Expand Down
1 change: 1 addition & 0 deletions flarestack/data/icecube/northern_tracks/__init__.py
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Expand Up @@ -177,6 +177,7 @@ def simulate_background(
)

sim_bkg = mc[ind]
sim_bkg["ra"] = np.random.uniform(0, 2 * np.pi, size=n_bkg)

time_pdf = self.get_time_pdf()

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