Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
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!pip install -I "phoebe>=2.2,<2.3"
As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
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%matplotlib inline
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import phoebe
from phoebe import u # units
logger = phoebe.logger()
b = phoebe.default_binary()
Let's add a lightcurve dataset to the Bundle (see also the lc API docs). Some parameters are only visible based on the values of other parameters, so we'll pass check_visible=False (see the filter API docs for more details). These visibility rules will be explained below.
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b.add_dataset('lc')
print(b.get_dataset(kind='lc', check_visible=False))
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print(b.get_parameter(qualifier='times'))
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print(b.get_parameter(qualifier='fluxes'))
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print(b.get_parameter(qualifier='sigmas'))
See the Compute Times & Phases tutorial.
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print(b.get_parameter(qualifier='compute_times'))
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print(b.get_parameter(qualifier='compute_phases', context='dataset'))
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print(b.get_parameter(qualifier='compute_phases_t0'))
See the Limb Darkening tutorial
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print(b.get_parameter(qualifier='ld_mode', component='primary'))
ld_func will only be available if ld_mode is not 'interp', so let's set it to 'lookup'. See the limb darkening tutorial for more details.
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b.set_value('ld_mode', component='primary', value='lookup')
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print(b.get_parameter(qualifier='ld_func', component='primary'))
ld_coeffs_source will only be available if ld_mode is 'lookup'. See the limb darkening tutorial for more details.
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print(b.get_parameter(qualifier='ld_coeffs_source', component='primary'))
ld_coeffs will only be available if ld_mode is set to 'manual'. See the limb darkening tutorial for more details.
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b.set_value('ld_mode', component='primary', value='manual')
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print(b.get_parameter(qualifier='ld_coeffs', component='primary'))
See the Atmospheres & Passbands tutorial
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print(b.get_parameter(qualifier='passband'))
See the Intensity Weighting tutorial
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print(b.get_parameter(qualifier='intens_weighting'))
See the Passband Luminosity tutorial
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print(b.get_parameter(qualifier='pblum_mode'))
pblum_component is only available if pblum_mode is set to 'component-coupled'. See the passband luminosity tutorial for more details.
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b.set_value('pblum_mode', value='component-coupled')
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print(b.get_parameter(qualifier='pblum_component'))
pblum_dataset is only available if pblum_mode is set to 'dataset-coupled'. In this case we'll get a warning because there is only one dataset. See the passband luminosity tutorial for more details.
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b.set_value('pblum_mode', value='dataset-coupled')
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print(b.get_parameter(qualifier='pblum_dataset'))
pblum is only available if pblum_mode is set to 'decoupled' (in which case there is a pblum entry per-star) or 'component-coupled' (in which case there is only an entry for the star chosen by pblum_component). See the passband luminosity tutorial for more details.
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b.set_value('pblum_mode', value='decoupled')
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print(b.get_parameter(qualifier='pblum', component='primary'))
See the "Third" Light tutorial
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print(b.get_parameter(qualifier='l3_mode'))
l3 is only avaible if l3_mode is set to 'flux'. See the "Third" Light tutorial for more details.
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b.set_value('l3_mode', value='flux')
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print(b.get_parameter(qualifier='l3'))
l3_frac is only avaible if l3_mode is set to 'fraction'. See the "Third" Light tutorial for more details.
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b.set_value('l3_mode', value='fraction')
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print(b.get_parameter(qualifier='l3_frac'))
Let's look at the compute options (for the default PHOEBE 2 backend) that relate to computing fluxes and the LC dataset.
Other compute options are covered elsewhere:
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print(b.get_compute())
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print(b.get_parameter(qualifier='lc_method'))
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print(b.get_parameter(qualifier='irrad_method'))
For more details on irradiation, see the Irradiation tutorial
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print(b.get_parameter(qualifier='boosting_method'))
For more details on boosting, see the Beaming and Boosting example script
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print(b.get_parameter(qualifier='atm', component='primary'))
For more details on atmospheres, see the Atmospheres & Passbands tutorial
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b.set_value('times', phoebe.linspace(0,1,101))
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b.run_compute()
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print(b.filter(context='model').twigs)
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print(b.get_parameter(qualifier='times', kind='lc', context='model'))
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print(b.get_parameter(qualifier='fluxes', kind='lc', context='model'))
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afig, mplfig = b.plot(show=True)
Since these are the only two columns available in the synthetic model, the only other option is to plot in phase instead of time.
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afig, mplfig = b.plot(x='phases', show=True)
In system hierarchies where there may be multiple periods, it is also possible to determine whose period to use for phasing.
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print(b.filter(qualifier='period').components)
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afig, mplfig = b.plot(x='phases:binary', show=True)
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b.add_dataset('mesh', times=[0], dataset='mesh01')
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print(b.get_parameter(qualifier='columns').choices)
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b.set_value('columns', value=['intensities@lc01',
'abs_intensities@lc01',
'normal_intensities@lc01',
'abs_normal_intensities@lc01',
'pblum_ext@lc01',
'boost_factors@lc01'])
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b.run_compute()
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print(b.get_model().datasets)
These new columns are stored with the lc's dataset tag, but with the 'mesh' dataset-kind.
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print(b.filter(dataset='lc01', kind='mesh', context='model').twigs)
Any of these columns are then available to use as edge or facecolors when plotting the mesh (see the section on the mesh dataset).
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afig, mplfig = b.filter(kind='mesh').plot(fc='intensities', ec='None', show=True)
Now let's look at each of the available fields.
For more details, see the tutorial on Passband Luminosities
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print(b.get_parameter(qualifier='pblum_ext',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
pblum_ext is the extrinsic passband luminosity of the entire star/mesh - this is a single value (unlike most of the parameters in the mesh) and does not have per-element values.
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print(b.get_parameter(qualifier='abs_normal_intensities',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
abs_normal_intensities are the absolute normal intensities per-element.
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print(b.get_parameter(qualifier='normal_intensities',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
normal_intensities are the relative normal intensities per-element.
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print(b.get_parameter(qualifier='abs_intensities',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
abs_intensities are the projected absolute intensities (towards the observer) per-element.
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print(b.get_parameter(qualifier='intensities',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
intensities are the projected relative intensities (towards the observer) per-element.
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print(b.get_parameter(qualifier='boost_factors',
component='primary',
dataset='lc01',
kind='mesh',
context='model'))
boost_factors are the boosting amplitudes per-element. See the boosting tutorial for more details.