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Update ESIGMA calling mechanism
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@prayush
prayush committed Jun 12, 2024
1 parent 7e35626 commit 1337ff6
Showing 1 changed file with 74 additions and 47 deletions.
121 changes: 74 additions & 47 deletions pycbc/waveform/waveform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -342,11 +342,7 @@ def td_approximants(scheme=_scheme.mgr.state):
"""Return a list containing the available time domain approximants for
the given processing scheme.
"""
return list(td_wav[type(scheme)].keys()) + [
"IMRESIGMAHM",
"IMRESIGMA",
"InspiralESIGMAHM",
]
return list(td_wav[type(scheme)].keys())

def fd_approximants(scheme=_scheme.mgr.state):
"""Return a list containing the available fourier domain approximants for
Expand Down Expand Up @@ -591,26 +587,70 @@ def get_td_waveform(template=None, **kwargs):
"""
input_params = props(template, **kwargs)
if "ESIGMA" in input_params["approximant"]:
from gwnr.waveform import enigma_utils
from gwnr.waveform import esigma_utils

hp, hc = None, None
if input_params["approximant"] == "IMRESIGMAHM":
hp, hc = enigma_utils.get_imr_enigma_waveform(**input_params)
if input_params["approximant"] == "IMRESIGMA":
hp, hc = enigma_utils.get_imr_enigma_waveform(
**input_params, modes_to_use=[(2, 2)]
)
if input_params["approximant"] == "InspiralESIGMAHM":
_, hp, hc = enigma_utils.get_inspiral_enigma_waveform(**input_params)
if input_params["approximant"] == "InspiralESIGMA":
_, hp, hc = enigma_utils.get_inspiral_enigma_waveform(
**input_params, modes_to_use=[(2, 2)]
)
if hp is None or hc is None:
raise IOError(
f"Approximant {input_params['approximant']} not supported"
)
return hp, hc

os.environ["RadiationPNOrder"] = "8"
os.environ["ModePNOrder"] = "8"
os.environ["InspiralEndRadius"] = "4.0"

esigma_params = dict(
mass1=float(input_params["mass1"]),
mass2=float(input_params["mass2"]),
spin1z=float(input_params["spin1z"]),
spin2z=float(input_params["spin2z"]),
eccentricity=float(input_params["eccentricity"]),
mean_anomaly=float(input_params["mean_per_ano"]),
coa_phase=float(input_params["coa_phase"]),
distance=float(input_params["distance"]),
inclination=float(input_params["inclination"]),
f_lower=float(input_params["f_lower"]),
delta_t=float(input_params["delta_t"]),
# even thought we specify them, the inspiral ESIGMA methods
# will ignore the following arguments
mode_to_align_by=(2, 2),
include_conjugate_modes=True,
f_mr_transition=None,
f_window_mr_transition=None,
num_hyb_orbits=0.25,
hybridize_using_avg_orbital_frequency=False,
hybridize_aligning_merger_to_inspiral=False,
keep_f_mr_transition_at_center=False,
merger_ringdown_approximant="NRSur7dq4",
return_hybridization_info=False,
return_orbital_params=False,
failsafe=True,
verbose=False,
)

try:
if input_params["approximant"] == "IMRESIGMAHM":
hp, hc = esigma_utils.get_imr_esigma_waveform(
**esigma_params, modes_to_use=[(2, 2), (3, 3), (4, 4)]
)
elif input_params["approximant"] == "IMRESIGMA":
hp, hc = esigma_utils.get_imr_esigma_waveform(
**esigma_params, modes_to_use=[(2, 2)]
)
elif input_params["approximant"] == "InspiralESIGMAHM":
hp, hc = esigma_utils.get_inspiral_esigma_waveform(
**esigma_params, modes_to_use=[(2, 2), (3, 3), (4, 4)]
)
elif input_params["approximant"] == "InspiralESIGMA":
hp, hc = esigma_utils.get_inspiral_esigma_waveform(
**esigma_params, modes_to_use=[(2, 2)]
)
if hp is None or hc is None:
raise IOError(
f"Approximant {input_params['approximant']} not supported"
)
return hp, hc
except Exception as exc:
print(f"""Failed to generate waveform with input_params={input_params},
with error: {exc}
""")
return None, None
else:
wav_gen = td_wav[type(_scheme.mgr.state)]
if input_params['approximant'] not in wav_gen:
Expand All @@ -628,6 +668,15 @@ def get_td_waveform(template=None, **kwargs):
params=parameters.td_waveform_params.docstr(prefix=" ",
include_label=False).lstrip(' '))

cpu_td.update(
{
"InspiralESIGMA": get_td_waveform,
"InspiralESIGMAHM": get_td_waveform,
"IMRESIGMA": get_td_waveform,
"IMRESIGMAHM": get_td_waveform,
}
)

def get_fd_waveform(template=None, **kwargs):
"""Return a frequency domain gravitational waveform.
Expand Down Expand Up @@ -1331,30 +1380,8 @@ def get_two_pol_waveform_filter(outplus, outcross, template, **kwargs):
N = (n-1)*2
delta_f = 1.0 / (N * input_params['delta_t'])

if "ESIGMA" in input_params["approximant"]:
from gwnr.waveform import enigma_utils

hp, hc = None, None
if input_params["approximant"] == "IMRESIGMAHM":
hp, hc = enigma_utils.get_imr_enigma_waveform(**input_params)
if input_params["approximant"] == "IMRESIGMA":
hp, hc = enigma_utils.get_imr_enigma_waveform(
**input_params, modes_to_use=[(2, 2)]
)
if input_params["approximant"] == "InspiralESIGMAHM":
_, hp, hc = enigma_utils.get_inspiral_enigma_waveform(**input_params)
if input_params["approximant"] == "InspiralESIGMA":
_, hp, hc = enigma_utils.get_inspiral_enigma_waveform(
**input_params, modes_to_use=[(2, 2)]
)
if hp is None or hc is None:
raise IOError(
f"Approximant {input_params['approximant']} not supported"
)
print(f"ESIGMA length; {len(hp)}")
else:
wav_gen = td_wav[type(_scheme.mgr.state)]
hp, hc = wav_gen[input_params['approximant']](**input_params)
wav_gen = td_wav[type(_scheme.mgr.state)]
hp, hc = wav_gen[input_params['approximant']](**input_params)
# taper the time series hp if required
if 'taper' in input_params.keys() and \
input_params['taper'] is not None:
Expand Down

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