def covers(self, proposal, min_match):
"""
Return True if any template in the bank has match with proposal
greater than min_match.
"""
# find templates in the bank "near" this tmplt
low, high = _find_neighborhood(self._mchirps, proposal._mchirp, self.flow)
tmpbank = self._templates[low:high]
if not tmpbank: return False
# sort the bank by its nearness to tmplt in mchirp
# NB: This sort comes up as a dominating cost if you profile,
# but it cuts the number of match evaluations by 80%, so turns out
# to be worth it even for metric match, where matches are cheap.
pm = proposal._mchirp
tmpbank.sort(key=lambda b: abs(b._mchirp - pm))
# set parameters of match calculation that are optimized for this block
df, PSD = get_neighborhood_PSD(tmpbank + [proposal], self.flow, self.noise_model)
# find and test matches
for tmplt in tmpbank:
self._nmatch += 1
match = self.compute_match(tmplt, proposal, df, PSD=PSD)
if match > min_match:
return True
return False
def finalize_as_template(self):
if not self.bank.use_metric: return
df, PSD = get_neighborhood_PSD([self], self.bank.flow, self.bank.noise_model)
if df not in self.bank._moments or len(PSD) - self.bank.flow // df > self.bank._moments[df][0].length:
real8vector_psd = CreateREAL8Vector(len(PSD))
real8vector_psd.data[:] = PSD
self.bank._moments[df] = create_moments(df, self.bank.flow, len(PSD))
SimInspiralTaylorF2RedSpinComputeNoiseMoments(*(self.bank._moments[df] + (real8vector_psd, self.bank.flow, df)))
self._metric = SimInspiralTaylorF2RedSpinMetricChirpTimes(self._theta0, self._theta3, self._theta3s, self.bank.flow, df, *self.bank._moments[df])
if isnan(self._metric[0]):
raise ValueError("g00 is nan")
def finalize_as_template(self):
if not self.bank.use_metric: return
df, PSD = get_neighborhood_PSD([self], self.flow, self.bank.noise_model)
if df not in self.bank._moments or len(PSD) - self.flow // df > self.bank._moments[df][0].length:
real8vector_psd = CreateREAL8Vector(len(PSD))
real8vector_psd.data[:] = PSD
self.bank._moments[df] = create_moments(df, self.flow, len(PSD))
lalsim.SimInspiralTaylorF2RedSpinComputeNoiseMoments(*(self.bank._moments[df] + (real8vector_psd, self.flow, df)))
self._metric = lalsim.SimInspiralTaylorF2RedSpinMetricChirpTimes(self._theta0, self._theta3, self._theta3s, self.flow, df, *self.bank._moments[df])
if isnan(self._metric[0]):
raise ValueError("g00 is nan")