Source code for pyLIMA.microltoolbox

# -*- coding: utf-8 -*-
"""
Created on Mon May 23 17:18:15 2016

@author: ebachelet
"""

import numpy as np

# magnitude reference
MAGNITUDE_CONSTANT = 27.4


[docs]def chichi(residuals_fn, fit_process_parameters):
    """Return the chi^2 .


    :param func residuals_fn: a function which compute the residuals
    :param list fit_process_parameters: the model parameters ingested by the correpsonding
    fitting routine.

    :returns: the chi^2

    :rtype: float
    """

    residuals = residuals_fn(fit_process_parameters)
    _chichi = (residuals ** 2).sum()

    return _chichi


[docs]def magnitude_to_flux(magnitude):
    """ Transform the injected magnitude to the the corresponding flux.

    :param array_like magnitude: the magnitude you want to transform.

    :return: the transformed magnitude in flux unit
    :rtype: array_like
    """

    flux = 10 ** ((MAGNITUDE_CONSTANT - magnitude) / 2.5)

    return flux


[docs]def flux_to_magnitude(flux):
    """ Transform the injected flux to the the corresponding magnitude.

    :param array_like flux: the flux you want to transform.

    :return: the transformed magnitude
    :rtype: array_like
    """

    mag = MAGNITUDE_CONSTANT - 2.5 * np.log10(flux)

    return mag


[docs]def error_magnitude_to_error_flux(error_magnitude, flux):
    """ Transform the injected magnitude error to the the corresponding error in flux.

    :param array_like error_magnitude: the magnitude errors measurements you want to transform.
    :param array_like flux: the fluxes corresponding to these errors

    :return: the transformed errors in flux units
    :rtype: array_like
    """

    error_flux = -error_magnitude * flux * np.log(10) / 2.5

    return error_flux


[docs]def error_flux_to_error_magnitude(error_flux, flux):
    """ Transform the injected flux error to the the corresponding error in magnitude.

    :param array_like error_flux: the flux errors measurements you want to transform.
    :param array_like flux: the fluxes corresponding to these errors

    :return: the transformed errors in magnitude
    :rtype: array_like
    """
    error_magnitude = -2.5 * error_flux / (flux * np.log(10))

    return error_magnitude