def LoadSpokeXML(fname):
# load the xml file
P_list = lalsimutils.xml_to_ChooseWaveformParams_array(fname)
# group by spokes
sdHere = {}
for P in P_list:
# spoke_id = str( [round(elem, 3) for elem in ChooseWaveformParams_to_spoke_label(P)])
spoke_id = str(ChooseWaveformParams_to_spoke_label(P))
if sdHere.has_key(spoke_id):
sdHere[spoke_id].append(P)
else:
sdHere[spoke_id] = [P]
# return
return sdHere
dlist_ranges = []
if len(dlist) != len(dlist_ranges):
print(" downselect parameters inconsistent", dlist, dlist_ranges)
for indx in np.arange(len(dlist_ranges)):
downselect_dict[dlist[indx]] = dlist_ranges[indx]
if otps.verbose:
print(downselect_dict)
# downselection procedure: fix units so I can downselect on mass parameters
for p in ['mc', 'm1', 'm2', 'mtot']:
if p in downselect_dict.keys():
downselect_dict[p] = np.array(downselect_dict[p], dtype=np.float64)
downselect_dict[p] *= lal.MSUN_SI # add back units
P_list_in = lalsimutils.xml_to_ChooseWaveformParams_array(opts.fname)
P_inj = lalsimutils.xml_to_ChooseWaveformParams_array(opts.fname)[opts.event]
param_ref_vals = {}
for param in downselect_dict.keys():
param_ref_vals[param] = P_inj.extract_param(param)
P_list = []
for P in P_list_in:
include_item = True
for param in downselect_dict.keys():
param_here = P.extract_param(param)
if not (param_here > downselect_dict[param][0]
and param_here < downselect_dict[param][1]):
include_item = False
continue
if include_item:
IP_list[ifo] = lalsimutils.ComplexIP(fNyq=fNyq,
deltaF=df,
analyticPSD_Q=analyticPSD_Q,
psd=psd_dict[ifo],
fMax=opts.fmax,
fLow=fmin)
###
### Load injection XML
###
if opts.inj is None:
print(" --inj required")
sys.exit(0)
print(" Reading injection file 1 for comparison ", opts.inj)
P1_list = lalsimutils.xml_to_ChooseWaveformParams_array(opts.inj)
nlines1 = len(P1_list)
print(" Read ", nlines1, " injections")
if nlines1 < 1:
print(" No data in ", opts.inj)
tref = float((P1_list[0]).tref) # default
if not (opts.tref is None):
tref = opts.tref
if opts.inj2 is None:
print(" --inj2 required")
sys.exit(0)
print(" Reading injection file 1 for comparison ", opts.inj2)
P2_list = lalsimutils.xml_to_ChooseWaveformParams_array(opts.inj2)
def likelihood_function(x, y, z, a, b, c, d, e, f, g):
if isinstance(x, float):
return np.exp(my_fit([x, y, z, a, b, c, d, e, f, g]))
else:
return np.exp(
my_fit(
convert_coords(np.array([x, y, z, a, b, c, d, e, f,
g]).T)))
# PROCEDURE
# - Identify grid of desired parameters (e.g., ascii table)
# - Create
# Base
P_base = lalsimutils.xml_to_ChooseWaveformParams_array(opts.fname_xml_base)[0]
# Grid
samples_rec = np.genfromtxt(opts.fname_parameter_grid, names=True)
params_rec = samples_rec.dtype.names
# Conversion
P_list = []
grid_list = []
lnL_list = []
for indx in np.arange(len(samples_rec[params_rec[0]])):
P = P_base.manual_copy()
for param in params_rec:
val = samples_rec[param][indx]
fac = 1
if param in ['mc', 'm1', 'm2', 'mtot']:
parser = optparse.OptionParser()
parser.add_option("--output-file",
default="merged_output",
help="Filename, note xml.gz is appened automatically")
parser.add_option("--compare-parameter", action='append')
parser.add_option(
"--force-approximant", default=None
) # because there is a weird bug that sometimes hits me with type conversion
parser.add_option("--verbose")
opts, args = parser.parse_args()
# Loop over arguments, joining
P_list = []
for fname in args:
print(" File name : ", fname)
P_list_here = lalsimutils.xml_to_ChooseWaveformParams_array(fname)
print(" Read n= ", len(P_list_here))
for P in P_list_here:
P.tref = 0.0 # insure it is ok -- there have been problems with malformed times. DANGEROUS if used for another purpose than mine!
print(" Revised length before cutting: N = ", len(P_list_here))
if opts.force_approximant:
approx = lalsim.GetApproximantFromString(opts.force_approximant)
print(" Forcing approx = ", approx, " AKA ",
lalsim.GetStringFromApproximant(approx), " from ",
opts.force_approximant)
for P in P_list_here:
P.approx = approx
P_list = P_list + P_list_here
if opts.verbose:
for P in P_list:
#! /usr/bin/env python
import numpy as np
import RIFT.lalsimutils as lalsimutils
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--fname",
help="filename of *.dat file [standard ILE output]")
parser.add_argument("--fname-reference", help="xml also")
parser.add_argument("--parameter",
action='append',
help="list of parameter names")
opts = parser.parse_args()
P_list = lalsimutils.xml_to_ChooseWaveformParams_array(opts.fname)
P_ref_list = lalsimutils.xml_to_ChooseWaveformParams_array(
opts.fname_reference)
# Find the mean value of the reference point
parameters_to_center = [
'mc', 'eta'
] # could also add 'chieff_aligned', in cases with significant spin
if opts.parameter:
parameters_to_center = opts.parameter
dat = np.zeros((len(P_list), len(parameters_to_center)))
for indx in np.arange(len(P_list)):
for pIndex in np.arange(len(parameters_to_center)):
param = parameters_to_center[pIndex]
val = P_list[indx].extract_param(param)
dat[indx, pIndex] = val