From 94fe056d3767251bd446667d976fb3d17f498965 Mon Sep 17 00:00:00 2001
From: Chad Hanna <crh184@psu.edu>
Date: Mon, 15 May 2017 06:47:20 -0400
Subject: [PATCH] tree.py: simplify and remove cruft
---
gstlal-ugly/python/tree.py | 57 ++++++++++++++++----------------------
1 file changed, 24 insertions(+), 33 deletions(-)
diff --git a/gstlal-ugly/python/tree.py b/gstlal-ugly/python/tree.py
index 1845dc3117..64bd755605 100644
--- a/gstlal-ugly/python/tree.py
+++ b/gstlal-ugly/python/tree.py
@@ -31,17 +31,24 @@ def uber_constraint(vertices, mtotal = 100, ns_spin = 0.05):
def mass_sym_constraint(vertices, mass_ratio = float("inf"), total_mass = float("inf")):
# Assumes m_1 and m_2 are first
+ Q = []
+ M = []
for vertex in vertices:
m1,m2 = vertex[0:2]
- if m2 <= m1 and float(m1/m2) <= mass_ratio and (m1+m2) < total_mass:
- return True
- return False
+ Q.append(m1/m2)
+ M.append(m1+m2)
+ minq_condition = all([q < 1 for q in Q])
+ maxq_condition = all([q > mass_ratio for q in Q])
+ mtotal_condition = all([m > total_mass for m in M])
+ if minq_condition or maxq_condition or mtotal_condition:
+ return False
+ return True
def packing_density(n):
# this packing density puts two in a cell, we split if there are two or
# more expected in a cell
return 1.0
- #prefactor = 1.
+ prefactor = 1.
# From: http://mathworld.wolfram.com/HyperspherePacking.html
if n==1:
return prefactor
@@ -85,10 +92,10 @@ class HyperCube(object):
self.metric = metric
if self.metric is not None and metric_tensor is None:
try:
- self.metric_tensor, self.effective_dimension, self.det = self.metric(self.center - self.deltas / 1234.0 , self.deltas / 1000.)
+ self.metric_tensor, self.effective_dimension, self.det = self.metric(self.center, self.deltas / 5e4)
except RuntimeError:
- print "metric @", self.center - self.deltas / 1000.0, " failed, trying, ", self.center - self.deltas / 60.0
- self.metric_tensor, self.effective_dimension, self.det = self.metric(self.center - self.deltas / 123.0, self.deltas / 1000.)
+ print "metric @", self.center, " failed, trying, ", self.center - self.deltas / 2.
+ self.metric_tensor, self.effective_dimension, self.det = self.metric(self.center - self.deltas / 2., self.deltas / 5e4)
else:
self.metric_tensor = metric_tensor
self.effective_dimension = effective_dimension
@@ -208,7 +215,9 @@ class Node(object):
size = self.cube.num_tmps_per_side(mismatch)
splitdim = numpy.argmax(size)
aspect_ratios = size / min(size)
- aspect_factor = max(1., numpy.product(aspect_ratios[aspect_ratios > 2.0]))
+ aspect_factor = max(1., numpy.product(aspect_ratios[aspect_ratios>2.0]) / 2.0**len(aspect_ratios[aspect_ratios>2.0]))
+ if numpy.isnan(aspect_factor):
+ aspect_factor = 1.0
aspect_ratio = max(aspect_ratios)
if not self.parent:
@@ -219,44 +228,26 @@ class Node(object):
metric_diff = 1.0
else:
# Get the number of parent templates
- par_size = self.parent.cube.num_tmps_per_side(mismatch)
- par_aspect_ratios = par_size / min(par_size)
- par_aspect_factor = max(1., numpy.product(par_aspect_ratios[par_aspect_ratios > 2.0]))
- par_numtmps = self.parent.cube.num_templates(mismatch) * par_aspect_factor / 2.0
+ par_numtmps = self.parent.cube.num_templates(mismatch) / 2.0
# get the number of sibling templates
- sib_size = self.sibling.cube.num_tmps_per_side(mismatch)
- sib_aspect_ratios = sib_size / min(sib_size)
- sib_aspect_factor = max(1., numpy.product(sib_aspect_ratios[sib_aspect_ratios > 2.0]))
- sib_numtmps = self.sibling.cube.num_templates(mismatch) * sib_aspect_factor
+ sib_numtmps = self.sibling.cube.num_templates(mismatch)
# get our number of templates
- numtmps = self.cube.num_templates(mismatch) * aspect_factor
+ numtmps = self.cube.num_templates(mismatch)
metric_diff = self.cube.metric_tensor - self.sibling.cube.metric_tensor
metric_diff = numpy.linalg.norm(metric_diff) / numpy.linalg.norm(self.cube.metric_tensor)**.5 / numpy.linalg.norm(self.sibling.cube.metric_tensor)**.5
- #w, v = numpy.linalg.eigh(self.cube.metric_tensor)
- #ws, vs = numpy.linalg.eigh(self.sibling.cube.metric_tensor)
- #offsets = numpy.arccos([numpy.dot(v[i], vs[j]) for i, j in zip(numpy.argsort(w), numpy.argsort(ws))])
- #print "offsets: ", offsets
- #metric_diff = max(offsets)
- # check that the metric is not varying too much
- sib_vratio = numtmps / sib_numtmps
- volume_split_condition = (1./vtol < sib_vratio < vtol)
-
# take the bigger of self, sibling and parent
- numtmps = max(max(numtmps, par_numtmps), sib_numtmps)
+ numtmps = max(max(numtmps, par_numtmps), sib_numtmps) * aspect_factor
q = self.cube.center[1] / self.cube.center[0]
- #q_condition = (1.0 >= q >= 0.95) or (0.54 >= q >= 0.44) or (0.27 >= q >= 0.22) or (0.145 >= q >= 0.105)
- metric_tol = 0.1
- #if self.cube.constraint_func(self.cube.vertices + [self.cube.center]) and (numtmps >= split_num_templates or ((numtmps >= split_num_templates/2.) and metric_diff > metric_tol)):
- if self.cube.constraint_func(self.cube.vertices + [self.cube.center]) and (numtmps >= split_num_templates):
+ metric_tol = 0.03
+ if self.cube.constraint_func(self.cube.vertices + [self.cube.center]) and ((numtmps >= split_num_templates)):
self.template_count[0] = self.template_count[0] + 1
bifurcation += 1
- #if numtmps < 5**len(size) and metric_diff < max(mismatch, 0.01):#volume_split_condition:
- if metric_diff <= metric_tol:#volume_split_condition:
+ if metric_diff <= metric_tol and aspect_factor <= 1.0:
left, right = self.cube.split(splitdim, reuse_metric = True)
else:
left, right = self.cube.split(splitdim)
--
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