From 620648794b36927fa9f28832d741d9cf282c3d0d Mon Sep 17 00:00:00 2001
From: Leo Tsukada <leo.tsukada@ligo.org>
Date: Thu, 8 Aug 2019 00:10:27 -0700
Subject: [PATCH] inspiral_extrinsics.py : changed to pass snr dictioary and
psd file name to the output .h5 file
---
gstlal-inspiral/python/stats/inspiral_extrinsics.py | 12 ++++++++++--
1 file changed, 10 insertions(+), 2 deletions(-)
diff --git a/gstlal-inspiral/python/stats/inspiral_extrinsics.py b/gstlal-inspiral/python/stats/inspiral_extrinsics.py
index 74b8568498..50fd106c06 100644
--- a/gstlal-inspiral/python/stats/inspiral_extrinsics.py
+++ b/gstlal-inspiral/python/stats/inspiral_extrinsics.py
@@ -1187,7 +1187,7 @@ class TimePhaseSNR(object):
locations = {"H1":lal.CachedDetectors[lal.LHO_4K_DETECTOR].location, "L1":lal.CachedDetectors[lal.LLO_4K_DETECTOR].location, "V1":lal.CachedDetectors[lal.VIRGO_DETECTOR].location, "K1":lal.CachedDetectors[lal.KAGRA_DETECTOR].location}
numchunks = 20
- def __init__(self, transtt = None, transtp = None, transpt = None, transpp = None, transdd = None, norm = None, tree_data = None, margsky = None, verbose = False, margstart = 0, margstop = None):
+ def __init__(self, transtt = None, transtp = None, transpt = None, transpp = None, transdd = None, norm = None, tree_data = None, margsky = None, verbose = False, margstart = 0, margstop = None, SNR=None, psd_fname=None):
"""
Initialize a new class from scratch via explicit computation
of the tree data and marginalized probability distributions or by providing
@@ -1270,7 +1270,10 @@ class TimePhaseSNR(object):
self.tree_data = tree_data
self.margsky = margsky
- if self.tree_data is None or numpy.shape(self.tree_data)[1] != 1 + max(sum(self.slices.values(),[])):
+ self.snr = SNR
+ self.psd_fname = psd_fname
+
+ if self.tree_data is None:
time, phase, deff = TimePhaseSNR.tile(verbose = verbose)
self.tree_data = self.dtdphideffpoints(time, phase, deff, self.slices)
@@ -1325,6 +1328,11 @@ class TimePhaseSNR(object):
for k,v in mat.items():
group.create_dataset(",".join(sorted(k)), data = float(v))
+ f.create_dataset("psd", data=self.psd_fname)
+ h5_snr = f.create_group("SNR")
+ for ifo in self.snr:
+ h5_snr.create_dataset(ifo, data=self.snr[ifo].value)
+
f.close()
@staticmethod
--
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