Welcome to pyLIMA documentation!

pyLIMA is the first microlensing analysis open-source software, primarly designed to fit real data. But more can be done, see the Examples. You can find more information on the pyLIMA paper(s).

Quickstart

After the Installation step, you can check the version and run a quick test fit after downloading the data:

import matplotlib.pyplot as plt
import numpy as np

import pyLIMA
print(pyLIMA.__version__)


from pyLIMA.fits import TRFfit
from pyLIMA.models import PSPL_model

from pyLIMA import event
from pyLIMA import telescopes

your_event = event.Event()
your_event.name = 'pyLIMA example'

data_1 = np.loadtxt('path_to_the_data/Survey_1.dat')
telescope_1 = telescopes.Telescope(name='OGLE',
                               camera_filter='I',
                               light_curve=data_1.astype(float),
                               light_curve_names=['time', 'mag', 'err_mag'],
                               light_curve_units=['JD', 'mag', 'mag'])

telescope_1.plot_data()
plt.show()

your_event.telescopes.append(telescope_1)


pspl = PSPL_model.PSPLmodel(your_event)

my_fit = TRFfit(pspl)
my_fit.model_parameters_guess = [79.9, 0.008, 10.1]
my_fit.fit()
my_fit.fit_outputs()

For more details, check the Conventions and pyLIMA Modules.

User Guide

• Installation
• Conventions
• Examples
• Notes on fits

pyLIMA modules details

Here is the (hopefully up-to-date) documentation for all submodules.

• pyLIMA Modules