Commit de9b28ea authored by Roland Haas's avatar Roland Haas
Browse files

Nakano: retardate time in the same way POWER does

the only use is to make comparison easier since it is just a constant
offset in time
parent af151618
......@@ -544,8 +544,12 @@ def eq_29(sim_path, radii_list, modes):
mode = (int(m.group(1)), int(m.group(2)))
dsets[(radius, mode)] = dset
# M and ADMMass are not identical since "M" is the mass of the final black
# hole while ADMMass is the total mas of the system. Using both is somewhat
# inconsistent
a, M = getFinalSpinFromQLM(sim_path)
f0 = getCutoffFrequencyFromTwoPuncturesBBH(main_dir+"/output-0000/%s/TwoPunctures.bbh" % (sim))
ADMMass = getADMMassFromTwoPunctureBBH(main_dir+"/output-0000/%s/TwoPunctures.bbh" % (sim))
extrapolated_strains = {}
for radius in radii_list:
......@@ -553,6 +557,14 @@ def eq_29(sim_path, radii_list, modes):
for (el,em) in modes:
ar = loadHDF5Series(simdirs+"mp_psi4.h5" , dsets[(radius, (el,em))]) # loads HDF5 Series from file mp_psi4.h5, specifically the "l%d_m%d_r100.00" ones ... let's loop this over all radii
# retardate time by estimated travel time to each detector,
# convert from psi4 to r*psi4 to account for initial 1/r falloff
# RH: it might be even better (though harder to define) to
# get a retardating time by looking at the time of the
# maximum (found as an optimization over an interpolating
# function, not argmax)
ar[:, 0] -= RadialToTortoise(radius, ADMMass)
psi = np.column_stack((ar[:,0], ar[:,1] + 1j * ar[:,2]))
# 1st column of ar, time data points
# 2nd column of ar, data points for psi
......
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