From 2386bdfb5852d997c023bc7b4188ff00e2a565dc Mon Sep 17 00:00:00 2001 From: Chad Hanna <chad.hanna@comp-hd-002.gwave.ics.psu.edu> Date: Fri, 9 Aug 2019 15:15:34 -0400 Subject: [PATCH] inspiral_lr: further tuning of numerator snr chisq --- gstlal-inspiral/python/stats/inspiral_lr.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/gstlal-inspiral/python/stats/inspiral_lr.py b/gstlal-inspiral/python/stats/inspiral_lr.py index a6a4b332f4..a6ceaa00c7 100644 --- a/gstlal-inspiral/python/stats/inspiral_lr.py +++ b/gstlal-inspiral/python/stats/inspiral_lr.py @@ -423,10 +423,10 @@ class LnSignalDensity(LnLRDensity): vtdict = self.horizon_history.functional_integral_dict(window.shift(float(gps)), lambda D: D**3.) return dict((instrument, (vt / t)**(1./3.)) for instrument, vt in vtdict.items()) - def add_signal_model(self, prefactors_range = (0.001, 0.01), df = 400, inv_snr_pow = 4.): + def add_signal_model(self, prefactors_range = (0.001, 0.30), df = 200, inv_snr_pow = 4.): # normalize to 10 *mi*llion signals. this count makes the # density estimation code choose a suitable kernel size - inspiral_extrinsics.NumeratorSNRCHIPDF.add_signal_model(self.densities["snr_chi"], 10000000., prefactors_range, df, inv_snr_pow = inv_snr_pow, snr_min = self.snr_min) + inspiral_extrinsics.NumeratorSNRCHIPDF.add_signal_model(self.densities["snr_chi"], 1e12, prefactors_range, df, inv_snr_pow = inv_snr_pow, snr_min = self.snr_min) self.densities["snr_chi"].normalize() def candidate_count_model(self, rate = 1000.): -- GitLab