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Align output formats and data return options between inspiral-only and IMR generation functions #12

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dbcb517
Initial plan
Copilot May 5, 2026
2d00d5f
Align IMR output formats with inspiral functions: add return_pycbc_ti…
Copilot May 5, 2026
8820ee3
Add .gitignore to exclude __pycache__ and build artifacts
Copilot May 5, 2026
63eb262
Fix exec() security issue: use direct dict assignment instead of exec…
Copilot May 5, 2026
faa2ae3
Merge branch 'master' into copilot/align-output-formats-imr-inspiral
prayush May 7, 2026
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148 changes: 103 additions & 45 deletions esigmapy/generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -673,6 +673,7 @@ def get_imr_esigma_modes(
merger_ringdown_approximant="NRSur7dq4",
return_hybridization_info=False,
return_orbital_params=False,
return_pycbc_timeseries=True,
failsafe=True,
verbose=False,
):
Expand Down Expand Up @@ -748,19 +749,26 @@ def get_imr_esigma_modes(
['x', 'e', 'l', 'phi', 'phidot', 'r', 'rdot'].
Note that these are available only for the
inspiral portion of the waveform!
return_pycbc_timeseries -- If True, returns modes as PyCBC TimeSeries.
If False, returns modes as NumPy arrays along
with a time grid as the first return value.
True by default.
failsafe -- If True, we make reasonable choices for the
user, if the inputs to this method lead
into exceptions.
verbose -- Verbosity level. Available values are: 0, 1, 2

Returns:
--------
modes_imr -- Dictionary of IMR GW modes (PyCBC TimeSeries)
t -- Time grid (in seconds).
Returned only if return_pycbc_timeseries=False
orbital_var_dict -- Dictionary of evolution of orbital elements.
Returned only if the flag `return_orbital_params`
is set
retval -- Hybridization related data. Returned only if the
flag `return_hybridization_info` is set
modes_imr -- Dictionary of IMR GW modes (PyCBC TimeSeries or
NumPy arrays depending on return_pycbc_timeseries)
"""
check_available_mr_approximants(merger_ringdown_approximant)
if (mean_anomaly is None) and (coa_phase is None):
Expand Down Expand Up @@ -839,7 +847,7 @@ def get_imr_esigma_modes(
f_Schwarz = 6.0**-1.5 / (mass1 + mass2) / lal.MTSUN_SI / lal.PI
f_mr_transition = min(f_Kerr, f_Schwarz) * (mode_to_align_by_em / 2)

retval = get_inspiral_esigma_modes(
inspiral_retval = get_inspiral_esigma_modes(
mass1=mass1,
mass2=mass2,
spin1z=spin1z,
Expand All @@ -858,15 +866,15 @@ def get_imr_esigma_modes(
)

# Retrieve modes, orbital phase and frequency from the returned list
modes_inspiral_numpy = retval[-1]
modes_inspiral_numpy = inspiral_retval[-1]
if mode_to_align_by not in modes_inspiral_numpy:
raise RuntimeError(
f"""The inspiral modes do not contain the primary
desired {mode_to_align_by} multipole. It currently holds only the following:
{modes_inspiral_numpy.keys()}"""
)

orbital_eccentricity = retval[-2]["e"]
orbital_eccentricity = inspiral_retval[-2]["e"]
# Throw error if eccentricity at the end of inspiral is definitely unsafe
if orbital_eccentricity[-1] > ECCENTRICITY_LEVEL_ISCO_ERROR:
raise IOError(
Expand All @@ -887,18 +895,24 @@ def get_imr_esigma_modes(
if (f_window_mr_transition is None) or failsafe or (verbose > 1):
if blend_using_avg_orbital_frequency:
orbital_frequency = (
retval[-2]["x"] ** 1.5 / ((mass1 + mass2) * lal.MTSUN_SI) / (2 * np.pi)
inspiral_retval[-2]["x"] ** 1.5 / ((mass1 + mass2) * lal.MTSUN_SI) / (2 * np.pi)
)
else:
orbital_frequency = (
retval[-2]["phidot"] / ((mass1 + mass2) * lal.MTSUN_SI) / (2 * np.pi)
inspiral_retval[-2]["phidot"] / ((mass1 + mass2) * lal.MTSUN_SI) / (2 * np.pi)
)

if return_orbital_params_user:
orbital_vars_dict = {
key: pt.TimeSeries(retval[-2][key], delta_t=delta_t, epoch=retval[0][0])
for key in return_orbital_params_user
}
if return_pycbc_timeseries:
orbital_vars_dict = {
key: pt.TimeSeries(inspiral_retval[-2][key], delta_t=delta_t, epoch=inspiral_retval[0][0])
for key in return_orbital_params_user
}
else:
orbital_vars_dict = {
key: inspiral_retval[-2][key]
for key in return_orbital_params_user
}

# DEBUG
if verbose > 5:
Expand Down Expand Up @@ -947,7 +961,7 @@ def get_imr_esigma_modes(
if f_window_mr_transition is None:
f_window_mr_transition = (
_get_transition_frequency_window(
retval[-2]["phi"],
inspiral_retval[-2]["phi"],
orbital_frequency,
delta_t,
f_mr_transition / mode_to_align_by_em,
Expand Down Expand Up @@ -1033,29 +1047,42 @@ def get_imr_esigma_modes(
idx_peak = abs(modes_imr_numpy[mode_to_align_by]).argmax()
t_peak = idx_peak * delta_t

itime = time.perf_counter()
modes_imr = {}
for el, em in modes_imr_numpy:
modes_imr[(el, em)] = pt.TimeSeries(
modes_imr_numpy[(el, em)], delta_t=delta_t, epoch=-1 * t_peak
)
if verbose > 4:
print(
"Time taken to store in pycbc.TimeSeries is {} secs".format(
time.perf_counter() - itime
if return_pycbc_timeseries:
itime = time.perf_counter()
modes_imr = {}
for el, em in modes_imr_numpy:
modes_imr[(el, em)] = pt.TimeSeries(
modes_imr_numpy[(el, em)], delta_t=delta_t, epoch=-1 * t_peak
)
)
if verbose > 4:
print(
"Time taken to store in pycbc.TimeSeries is {} secs".format(
time.perf_counter() - itime
)
)
else:
modes_imr = modes_imr_numpy
t_imr = np.arange(len(next(iter(modes_imr_numpy.values())))) * delta_t - t_peak
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@Akash-Maurya-0899 Akash-Maurya-0899 May 5, 2026 •
edited by prayush
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@Akash-Maurya-0899 / @copilot Check if this matches with the time-grid generated by the sample_times method of the corresponding PyCBC TimeSeries modes.


if verbose:
print("blended.")

if return_hybridization_info and return_orbital_params_user:
return modes_imr, orbital_vars_dict, retval
elif return_orbital_params_user:
return modes_imr, orbital_vars_dict
elif return_hybridization_info:
return modes_imr, retval
return modes_imr
if return_pycbc_timeseries:
if return_hybridization_info and return_orbital_params_user:
return orbital_vars_dict, retval, modes_imr
elif return_orbital_params_user:
return orbital_vars_dict, modes_imr
elif return_hybridization_info:
return retval, modes_imr
return modes_imr
else:
if return_hybridization_info and return_orbital_params_user:
return t_imr, orbital_vars_dict, retval, modes_imr
elif return_orbital_params_user:
return t_imr, orbital_vars_dict, modes_imr
elif return_hybridization_info:
return t_imr, retval, modes_imr
return t_imr, modes_imr


def get_imr_esigma_waveform(
Expand All @@ -1082,6 +1109,7 @@ def get_imr_esigma_waveform(
merger_ringdown_approximant="NRSur7dq4",
return_hybridization_info=False,
return_orbital_params=False,
return_pycbc_timeseries=True,
failsafe=True,
verbose=False,
**kwargs,
Expand Down Expand Up @@ -1149,21 +1177,29 @@ def get_imr_esigma_waveform(
['x', 'e', 'l', 'phi', 'phidot', 'r', 'rdot'].
Note that these are available only for the
inspiral portion of the waveform!
return_pycbc_timeseries -- If True, returns polarizations as PyCBC
TimeSeries. If False, returns polarizations
as NumPy arrays along with a time grid as
the first return value.
True by default.
failsafe -- If True, we make reasonable choices for the
user, if the inputs to this method lead
into exceptions.
verbose -- Verbosity level. Available values are: 0, 1, 2

Returns:
--------
hp, hc -- Plus and cross IMR GW polarizations PyCBC TimeSeries
t -- Time grid (in seconds).
Returned only if return_pycbc_timeseries=False
orbital_vars_dict -- Dictionary of evolution of orbital elements.
Returned only if return_orbital_params is specified
retval -- Hybridization related data.
Returned only if return_hybridization_info is True
Returned only if return_orbital_params is specified
retval -- Hybridization related data.
Returned only if return_hybridization_info is True
hp, hc -- Plus and cross IMR GW polarizations (PyCBC TimeSeries
or NumPy arrays depending on return_pycbc_timeseries)
"""

retval = get_imr_esigma_modes(
imr_modes_output = get_imr_esigma_modes(
mass1=mass1,
mass2=mass2,
spin1z=spin1z,
Expand All @@ -1187,17 +1223,18 @@ def get_imr_esigma_waveform(
merger_ringdown_approximant=merger_ringdown_approximant,
return_hybridization_info=return_hybridization_info,
return_orbital_params=return_orbital_params,
return_pycbc_timeseries=False,
failsafe=failsafe,
verbose=verbose,
)
if return_hybridization_info and return_orbital_params:
modes_imr, orbital_vars_dict, retval = retval
t_imr, orbital_vars_dict, hyb_info, modes_imr = imr_modes_output
elif return_hybridization_info:
modes_imr, retval = retval
t_imr, hyb_info, modes_imr = imr_modes_output
elif return_orbital_params:
modes_imr, orbital_vars_dict = retval
t_imr, orbital_vars_dict, modes_imr = imr_modes_output
else:
modes_imr = retval
t_imr, modes_imr = imr_modes_output

hp, hc = esigmapy.utils.get_polarizations_from_multipoles(
modes_imr,
Expand All @@ -1206,10 +1243,31 @@ def get_imr_esigma_waveform(
verbose=verbose,
)

if return_hybridization_info and return_orbital_params:
return hp, hc, orbital_vars_dict, retval
elif return_hybridization_info:
return hp, hc, retval
elif return_orbital_params:
return hp, hc, orbital_vars_dict
return hp, hc
if return_pycbc_timeseries:
hp = pt.TimeSeries(hp, delta_t=delta_t, epoch=t_imr[0])
hc = pt.TimeSeries(hc, delta_t=delta_t, epoch=t_imr[0])

if return_orbital_params and return_pycbc_timeseries:
for name in list(orbital_vars_dict.keys()):
orbital_vars_dict[name] = pt.TimeSeries(
orbital_vars_dict[name],
delta_t=delta_t,
epoch=-delta_t * (len(orbital_vars_dict[name]) - 1),
)

if return_pycbc_timeseries:
if return_hybridization_info and return_orbital_params:
return orbital_vars_dict, hyb_info, hp, hc
elif return_hybridization_info:
return hyb_info, hp, hc
elif return_orbital_params:
return orbital_vars_dict, hp, hc
return hp, hc
else:
if return_hybridization_info and return_orbital_params:
return t_imr, orbital_vars_dict, hyb_info, hp, hc
elif return_hybridization_info:
return t_imr, hyb_info, hp, hc
elif return_orbital_params:
return t_imr, orbital_vars_dict, hp, hc
return t_imr, hp, hc
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