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# Limb Darkening¶

## Setup¶

As always, let’s do imports and initialize a logger and a new bundle. See Building a System for more details.

%matplotlib inline

import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt

logger = phoebe.logger()

b = phoebe.default_binary()


We’ll just add an ‘lc’ dataset

b.add_dataset('lc', times=np.linspace(0,1,101), dataset='lc01')

<ParameterSet: 15 parameters | contexts: compute, dataset>


## Relevant Parameters¶

print b['ld_func_bol@primary']

Parameter: ld_func_bol@primary@component
Qualifier: ld_func_bol
Description: Bolometric limb darkening model
Value: logarithmic
Choices: linear, logarithmic, quadratic, square_root, power

print b['ld_func_bol@primary'].choices

['linear', 'logarithmic', 'quadratic', 'square_root', 'power']

print b['ld_coeffs_bol@primary']

Parameter: ld_coeffs_bol@primary@component
Qualifier: ld_coeffs_bol
Description: Bolometric limb darkening coefficients
Value: [0.5 0.5]
Constrained by:
Constrains: None
Related to: None

print b['ld_func@lc01']

ParameterSet: 2 parameters
ld_func@primary@lc01@dataset: interp
ld_func@secondary@lc01@dataset: interp

print b['ld_func@lc01@primary'].choices

['interp', 'linear', 'logarithmic', 'quadratic', 'square_root', 'power']


Note that ld_coeffs isn’t visible (relevant) if ld_func==’interp’

b['ld_func@lc01@primary'] = 'logarithmic'

print b['ld_coeffs@lc01@primary']

Parameter: ld_coeffs@primary@lc01@dataset
Qualifier: ld_coeffs
Description: Limb darkening coefficients
Value: [0.5 0.5]
Constrained by:
Constrains: None
Related to: None
Only visible if: ld_func:!interp


## Influence on Light Curves (fluxes)¶

b.run_compute(model='mymodel')

<ParameterSet: 2 parameters | qualifiers: fluxes, times>

afig, mplfig = b['lc01@mymodel'].plot(show=True)

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Last update: 10/29/2018 9:20 a.m. (CET)