From 961d67ecf58234a3ae6b9daf16c8c4d37793827d Mon Sep 17 00:00:00 2001
From: Chad Hanna <crh184@psu.edu>
Date: Tue, 4 Apr 2017 15:04:35 -0400
Subject: [PATCH] metric.py: gracefully handle waveform errors and again change
the distance criteria
---
gstlal-ugly/python/metric.py | 28 +++++++++++++++++-----------
1 file changed, 17 insertions(+), 11 deletions(-)
diff --git a/gstlal-ugly/python/metric.py b/gstlal-ugly/python/metric.py
index c2f844113b..a89a502729 100644
--- a/gstlal-ugly/python/metric.py
+++ b/gstlal-ugly/python/metric.py
@@ -164,7 +164,8 @@ class Metric(object):
del hcross
except RuntimeError:
print p
- raise
+ #raise
+ return None
return fseries
def match(self, w1, w2):
@@ -172,27 +173,32 @@ class Metric(object):
n = numpy.real((numpy.conj(w) * w).sum())**.5 / self.duration**.5
return n
- self.w1w2.data.data[:] = numpy.conj(w1.data.data) * w2.data.data
- lal.COMPLEX16FreqTimeFFT(self.tseries, self.w1w2, self.revplan)
- m = numpy.real(numpy.abs(numpy.array(self.tseries.data.data)).max()) / norm(w1.data.data) / norm(w2.data.data)
- if m > 1.0000001:
- raise ValueError("Match is greater than 1 : %f" % m)
- return m
+ try:
+ self.w1w2.data.data[:] = numpy.conj(w1.data.data) * w2.data.data
+ lal.COMPLEX16FreqTimeFFT(self.tseries, self.w1w2, self.revplan)
+ m = numpy.real(numpy.abs(numpy.array(self.tseries.data.data)).max()) / norm(w1.data.data) / norm(w2.data.data)
+ if m > 1.0000001:
+ raise ValueError("Match is greater than 1 : %f" % m)
+ return m
+ except AttributeError:
+ return None
#def __set_diagonal_metric_tensor_component(self, i, center, deltas, g, w1, min_d2 = numpy.finfo(numpy.float32).eps * 5, max_d2 = numpy.finfo(numpy.float32).eps * 100):
def __set_diagonal_metric_tensor_component(self, i, center, deltas, g, w1):
- min_d2 = numpy.finfo(numpy.float32).eps / self.working_length / 10.
- #max_d2 = numpy.finfo(numpy.float32).eps / self.working_length * 100000
- max_d2 = numpy.finfo(numpy.float32).eps / self.working_length * 500.0
+ min_d2 = numpy.finfo(numpy.float32).eps * .01
+ max_d2 = numpy.finfo(numpy.float32).eps * 100
# make the vector to solve for the metric by choosing
# either a principle axis or a bisector depending on if
# this is a diagonal component or not
x = numpy.zeros(len(deltas))
x[i] = deltas[i]
- d2 = 1. - self.match(w1, self.waveform(center+x))
+ try:
+ d2 = 1. - self.match(w1, self.waveform(center+x))
+ except TypeError:
+ return self.__set_diagonal_metric_tensor_component(i, center, deltas * 1.1, g, w1)
if (d2 > max_d2):
return self.__set_diagonal_metric_tensor_component(i, center, deltas / 8, g, w1)
if (d2 < min_d2):
--
GitLab