tree.py and metric.py: use scipy default finite difference

gstlal-ugly/python/metric.py

@@ -162,7 +162,7 @@ class Metric(object):
 		self.delta_t = {}
 		self.t_factor = {}
 		self.neg_t_factor = {}
-		delta_t = numpy.finfo(numpy.float32).eps * 2
+		delta_t = 1e-6
 		t_factor = numpy.exp(-2j * numpy.pi * (numpy.arange(self.working_length) * self.df - self.fhigh) * delta_t)
 		neg_t_factor = numpy.exp(-2j * numpy.pi * (numpy.arange(self.working_length) * self.df - self.fhigh) * (-delta_t))
 		for t in numpy.array([1.,2.,4.,8.,16.,32.,64.,128.,256.,512.,1024]):

gstlal-ugly/python/tree.py

@@ -109,7 +109,7 @@ class HyperCube(object):
 		self.deltas = numpy.array([c[1] - c[0] for c in boundaries])
 		self.metric = metric
 		# FIXME don't assume m1 m2 and the spin coords are the coordinates we have here.
-		deltas = numpy.finfo(numpy.float32).eps * 1.2 * numpy.ones(len(self.center))
+		deltas = 1e-6 * numpy.ones(len(self.center))
 		#deltas = 5e-7 * numpy.ones(len(self.center))
 		deltas[0:2] *= self.center[0:2]
 		#deltas[2:] = 1.3e-4