Introduction to MulensModel

How to create and plot a model and then add some data and fit for the source and blend fluxes.

This example shows OGLE-2003-BLG-235/MOA-2003-BLG-53, the first microlensing planet. See Bond et al. 2004. The data were downloaded from the NASA Exoplanet Archive.



In [1]:

    
# Import basic packages
import MulensModel
import matplotlib.pyplot as pl # MulensModel uses matplotlib for plotting.



In [2]:

    
# Define a point lens model:
my_pspl_model = MulensModel.Model(
    {'t_0': 2452848.06, 'u_0': 0.133, 't_E': 61.5})

# Or a model with 2-bodies:
my_1S2L_model = MulensModel.Model(
    {'t_0': 2452848.06, 'u_0': 0.133, 't_E': 61.5, 'rho': 0.00096, 
     'q': 0.0039, 's': 1.120, 'alpha': 223.8})
# Since rho is set, define a time range and method to apply 
# finite source effects:
my_1S2L_model.set_magnification_methods(
    [2452833., 'VBBL', 2452845.])



In [3]:

    
# Plot those models:
my_pspl_model.plot_magnification(
    t_range=[2452810, 2452890], subtract_2450000=True, color='red', 
    linestyle=':', label='PSPL')
my_1S2L_model.plot_magnification(
    t_range=[2452810, 2452890], subtract_2450000=True, color='black', 
    label='1S2L')
pl.legend(loc='best')
pl.show()



In [4]:

    
# Suppose you also had some data you want to import:

OGLE_data = MulensModel.MulensData(
    file_name='../data/OB03235/OB03235_OGLE.tbl.txt', comments=['\\','|'])

MOA_data = MulensModel.MulensData(
    file_name='../data/OB03235/OB03235_MOA.tbl.txt', phot_fmt='flux', 
    comments=['\\','|'])



In [5]:

    
# Now suppose you wanted to combine the two together:
my_event = MulensModel.Event(
    datasets=[MOA_data, OGLE_data], model=my_1S2L_model)

# And you wanted to plot the result:
my_event.plot_model(
    t_range=[2452810,2452890], subtract_2450000=True, color='black',
    data_ref=1)
my_event.plot_data(
    subtract_2450000=True, data_ref=1, label_list=['MOA', 'OGLE'], 
    color_list=['cyan', 'orange'], s=5)
# MulensModel automatically fits for the source and blend flux for the  
# given model.

# Customize the output
pl.legend(loc='best')
pl.title('OGLE-2003-BLG-235/MOA-2003-BLG-53')
pl.ylim(19., 16.5)
pl.xlim(2810,2890)
pl.show()









    



/h/corriedale0/MulensModel/MulensModel/source/MulensModel/utils.py:61: UserWarning: Flux to magnitude convertion approached negative flux
  UserWarning)
/h/corriedale0/MulensModel/MulensModel/source/MulensModel/utils.py:62: RuntimeWarning: invalid value encountered in log10
  mag = zeropoint - 2.5 * np.log10(flux)



In [6]:

    
# If you want to see how good the fit is, output the chi2:
print('Chi2 of the fit: {0:8.2f}'.format(my_event.get_chi2()))









    



Chi2 of the fit:  1782.60

If you want to optimize the chi2, we leave it up to you to determine the best method for doing this.



In [ ]: