Commit c768c983 authored by Cecilio Garcia-Quiros's avatar Cecilio Garcia-Quiros
Browse files

Modify name of mode_array variable and fix bug

parent 6785f0e3
......@@ -67,18 +67,18 @@ def lal_binary_black_hole(
mode_array:
Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments =
dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
dict(waveform_approximant='IMRPhenomHM', mode_array=[[2,2],[2,-2])
returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
mode_array=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[4,-4]]) returns the 22 and 2-2 of IMRPhenomHM.
mode_array=[[2,2],[4,-4]]) returns the 22 and 2-2 of IMRPhenomHM.
However, waveform_arguments =
dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
dict(waveform_approximant='IMRPhenomXHM', mode_array=[[2,2],[4,-4]])
returns the 22 and 4-4 of IMRPhenomXHM.
Returns
......@@ -150,18 +150,18 @@ def lal_binary_neutron_star(
mode_array:
Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments =
dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
dict(waveform_approximant='IMRPhenomHM', mode_array=[[2,2],[2,-2])
returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
mode_array=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[4,-4]]) returns the 22 a\nd 2-2 of IMRPhenomHM.
mode_array=[[2,2],[4,-4]]) returns the 22 a\nd 2-2 of IMRPhenomHM.
However, waveform_arguments =
dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
dict(waveform_approximant='IMRPhenomXHM', mode_array=[[2,2],[4,-4]])
returns the 22 and 4-4 of IMRPhenomXHM.
Returns
......@@ -217,18 +217,18 @@ def lal_eccentric_binary_black_hole_no_spins(
mode_array:
Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments =
dict(waveform_approximant='IMRPhenomHM', modearray=[[2,2],[2,-2])
dict(waveform_approximant='IMRPhenomHM', mode_array=[[2,2],[2,-2])
returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
mode_array=[[2,2],[2,-2],[5,5],[5,-5]]) is not allowed because the
55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM',
modearray=[[2,2],[4,-4]]) returns the 22 and 2-2 of IMRPhenomHM.
mode_array=[[2,2],[4,-4]]) returns the 22 and 2-2 of IMRPhenomHM.
However, waveform_arguments =
dict(waveform_approximant='IMRPhenomXHM', modearray=[[2,2],[4,-4]])
dict(waveform_approximant='IMRPhenomXHM', mode_array=[[2,2],[4,-4]])
returns the 22 and 4-4 of IMRPhenomXHM.
Returns
......@@ -343,12 +343,12 @@ def _base_lal_cbc_fd_waveform(
lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
waveform_dictionary, lambda_2)
if 'modearray' in waveform_kwargs:
modearray = waveform_kwargs['modearray']
mode_array = lalsim.SimInspiralCreateModeArray()
for mode in modearray:
lalsim.SimInspiralModeArrayActivateMode(mode_array, mode[0], mode[1])
lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array)
if ('mode_array' in waveform_kwargs) and waveform_kwargs['mode_array'] is not None:
mode_array = waveform_kwargs['mode_array']
mode_array_lal = lalsim.SimInspiralCreateModeArray()
for mode in mode_array:
lalsim.SimInspiralModeArrayActivateMode(mode_array_lal, mode[0], mode[1])
lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array_lal)
if lalsim.SimInspiralImplementedFDApproximants(approximant):
wf_func = lalsim_SimInspiralChooseFDWaveform
......
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