From 5fdfe893afd968654ee4de4ffbb2647d45dcddc8 Mon Sep 17 00:00:00 2001
From: Chad Hanna <chad.hanna@ligo.org>
Date: Tue, 17 Apr 2018 10:21:49 -0700
Subject: [PATCH] inspiral_extrinsics: extend support for new p(instruments|H)
code
---
.../python/stats/inspiral_extrinsics.py | 14 ++++++++++++--
1 file changed, 12 insertions(+), 2 deletions(-)
diff --git a/gstlal-inspiral/python/stats/inspiral_extrinsics.py b/gstlal-inspiral/python/stats/inspiral_extrinsics.py
index 206fe31ea1..d599ac62e4 100644
--- a/gstlal-inspiral/python/stats/inspiral_extrinsics.py
+++ b/gstlal-inspiral/python/stats/inspiral_extrinsics.py
@@ -945,12 +945,22 @@ class InspiralExtrinsics(object):
DEFAULT_FILENAME = os.path.join(gstlal_config_paths["pkgdatadir"], "inspiral_dtdphi_pdf.h5")
self.TimePhaseSNR = TimePhaseSNR.from_hdf5(DEFAULT_FILENAME)
self.p_of_ifos = {}
+ # FIXME these need to be renormalized based on a
+ # min_instruments which this class will need to take as a
+ # parameter
+ self.p_of_ifos[("H1", "L1", "V1",)] = p_of_instruments_given_horizons.from_hdf5(os.path.join(gstlal_config_paths["pkgdatadir"], "H1L1V1_p_of_instruments_given_H_d.h5"))
self.p_of_ifos[("H1", "L1",)] = p_of_instruments_given_horizons.from_hdf5(os.path.join(gstlal_config_paths["pkgdatadir"], "H1L1_p_of_instruments_given_H_d.h5"))
+ self.p_of_ifos[("H1", "V1",)] = p_of_instruments_given_horizons.from_hdf5(os.path.join(gstlal_config_paths["pkgdatadir"], "H1V1_p_of_instruments_given_H_d.h5"))
+ self.p_of_ifos[("L1", "V1",)] = p_of_instruments_given_horizons.from_hdf5(os.path.join(gstlal_config_paths["pkgdatadir"], "L1V1_p_of_instruments_given_H_d.h5"))
def p_of_instruments_given_horizons(self, instruments, horizons):
horizons = dict((k,v) for k,v in horizons.items() if v != 0)
+ # if only one instrument is on the probability is 1.0
+ if set(horizons) & set(instruments) != set(instruments):
+ raise ValueError("A trigger exists for a detector with zero horizon distance")
+ if len(horizons) == 1:
+ return 1.0
on_ifos = tuple(sorted(horizons.keys()))
- print self.p_of_ifos
return self.p_of_ifos[on_ifos](instruments, horizons)
def chunker(seq, size):
@@ -1241,7 +1251,7 @@ class p_of_instruments_given_horizons(object):
def __call__(self, instruments, horizon_distances):
H = [horizon_distances[k] for k in sorted(horizon_distances)]
- return self.histograms[tuple(sorted(instruments))]([min(max(h / H[0], self.first_center), self.last_center) for h in H[1:]])
+ return self.histograms[tuple(sorted(instruments))](*[min(max(h / H[0], self.first_center), self.last_center) for h in H[1:]])
def to_hdf5(self, fname):
f = h5py.File(fname, "w")
--
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