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( ...@@ -67,18 +67,18 @@ def lal_binary_black_hole(
mode_array: mode_array:
Activate a specific mode array and evaluate the model using those Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments = 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 returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g. specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g. mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 = 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 the 22 and 4-4 of IMRPhenomXHM.
Returns Returns
...@@ -150,18 +150,18 @@ def lal_binary_neutron_star( ...@@ -150,18 +150,18 @@ def lal_binary_neutron_star(
mode_array: mode_array:
Activate a specific mode array and evaluate the model using those Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments = 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 returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g. specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g. mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 = 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 the 22 and 4-4 of IMRPhenomXHM.
Returns Returns
...@@ -217,18 +217,18 @@ def lal_eccentric_binary_black_hole_no_spins( ...@@ -217,18 +217,18 @@ def lal_eccentric_binary_black_hole_no_spins(
mode_array: mode_array:
Activate a specific mode array and evaluate the model using those Activate a specific mode array and evaluate the model using those
modes only. e.g. waveform_arguments = 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 returns the 22 and 2-2 modes only of IMRPhenomHM. You can only
specify modes that are included in that particular model. e.g. specify modes that are included in that particular model. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 55 modes are not included in this model. Be aware that some models
only take positive modes and return the positive and the negative only take positive modes and return the positive and the negative
mode together, while others need to call both. e.g. mode together, while others need to call both. e.g.
waveform_arguments = dict(waveform_approximant='IMRPhenomHM', 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 = 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 the 22 and 4-4 of IMRPhenomXHM.
Returns Returns
...@@ -343,12 +343,12 @@ def _base_lal_cbc_fd_waveform( ...@@ -343,12 +343,12 @@ def _base_lal_cbc_fd_waveform(
lalsim_SimInspiralWaveformParamsInsertTidalLambda2( lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
waveform_dictionary, lambda_2) waveform_dictionary, lambda_2)
if 'modearray' in waveform_kwargs: if ('mode_array' in waveform_kwargs) and waveform_kwargs['mode_array'] is not None:
modearray = waveform_kwargs['modearray'] mode_array = waveform_kwargs['mode_array']
mode_array = lalsim.SimInspiralCreateModeArray() mode_array_lal = lalsim.SimInspiralCreateModeArray()
for mode in modearray: for mode in mode_array:
lalsim.SimInspiralModeArrayActivateMode(mode_array, mode[0], mode[1]) lalsim.SimInspiralModeArrayActivateMode(mode_array_lal, mode[0], mode[1])
lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array) lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array_lal)
if lalsim.SimInspiralImplementedFDApproximants(approximant): if lalsim.SimInspiralImplementedFDApproximants(approximant):
wf_func = lalsim_SimInspiralChooseFDWaveform wf_func = lalsim_SimInspiralChooseFDWaveform
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment