pyLIMA.microlmagnification module

Created on Tue Dec 8 14:37:33 2015

@author: ebachelet

pyLIMA.microlmagnification.Jacobian_amplification_FSPL(tau, uo, rho, gamma, yoo_table)[source]

Same function as above, just also returns the impact parameter needed for the Jacobian FSPL model. The Yoo et al. Finite Source Point Lens magnification and the impact parameter U(t). “OGLE-2003-BLG-262: Finite-Source Effects from a Point-Mass Lens”,Yoo, J. et al 2004 http://adsabs.harvard.edu/abs/2004ApJ...603..139Y

Parameters:
Returns:

the FSPL magnification A_FSPL(t) and the impact parameter U(t)
Return type:

tuple, tuple of two array_like
pyLIMA.microlmagnification.Jacobian_amplification_PSPL(tau, uo)[source]

Same function as above, just also returns the impact parameter needed for the Jacobian PSPL model. The Paczynski Point Source Point Lens magnification and the impact parameter U(t). “Gravitational microlensing by the galactic halo”,Paczynski, B. 1986 http://adsabs.harvard.edu/abs/1986ApJ...304....1P

Parameters:
Returns:

the PSPL magnification A_PSPL(t) and the impact parameter U(t)
Return type:

tuple, tuple of two array_like
pyLIMA.microlmagnification.amplification_FSBL(separation, mass_ratio, x_source, y_source, rho, limb_darkening_coefficient)[source]

The Uniform Source Binary Lens amplification, based on the work of Valerio Bozza, thanks :) “Microlensing with an advanced contour integration algorithm: Green’s theorem to third order, error control, optimal sampling and limb darkening ”,Bozza, Valerio 2010. Please cite the paper if you used this. http://mnras.oxfordjournals.org/content/408/4/2188

Parameters:
  • separation (array_like) – the projected normalised angular distance between the two bodies
  • mass_ratio (float) – the mass ratio of the two bodies
  • x_source (array_like) – the horizontal positions of the source center in the source plane
  • y_source (array_like) – the vertical positions of the source center in the source plane
  • limb_darkening_coefficient (float) – the linear limb-darkening coefficient
  • rho (float) – the normalised (to :math:`theta_E’) angular source star radius
  • tolerance (float) – the relative precision desired in the magnification
Returns:

the USBL magnification A_USBL(t)
Return type:

array_like
pyLIMA.microlmagnification.amplification_FSPL(tau, uo, rho, gamma, yoo_table)[source]

The Yoo et al. Finite Source Point Lens magnification. “OGLE-2003-BLG-262: Finite-Source Effects from a Point-Mass Lens”,Yoo, J. et al 2004 http://adsabs.harvard.edu/abs/2004ApJ...603..139Y

Parameters:
Returns:

the FSPL magnification A_FSPL(t)
Return type:

array_like
pyLIMA.microlmagnification.amplification_FSPL_for_Lyrae(tau, uo, rho, gamma, yoo_table)[source]

The Yoo et al Finite Source Point Lens magnification. “OGLE-2003-BLG-262: Finite-Source Effects from a Point-Mass Lens”,Yoo, J. et al 2004 http://adsabs.harvard.edu/abs/2004ApJ...603..139Y

Parameters:
Returns:

the FSPL magnification A_FSPL(t)
Return type:

array_like
pyLIMA.microlmagnification.amplification_PSBL(separation, mass_ratio, x_source, y_source)[source]

The Point Source Binary Lens amplification, based on the work of Valerio Bozza, thanks :) “Microlensing with an advanced contour integration algorithm: Green’s theorem to third order, error control, optimal sampling and limb darkening ”,Bozza, Valerio 2010. Please cite the paper if you used this. http://mnras.oxfordjournals.org/content/408/4/2188

Parameters:
  • separation (array_like) – the projected normalised angular distance between the two bodies
  • mass_ratio (float) – the mass ratio of the two bodies
  • x_source (array_like) – the horizontal positions of the source center in the source plane
  • y_source (array_like) – the vertical positions of the source center in the source plane
Returns:

the PSBL magnification A_PSBL(t)
Return type:

array_like
pyLIMA.microlmagnification.amplification_PSPL(tau, uo)[source]

The Paczynski Point Source Point Lens magnification and the impact parameter U(t). “Gravitational microlensing by the galactic halo”,Paczynski, B. 1986 http://adsabs.harvard.edu/abs/1986ApJ...304....1P

Parameters:
Returns:

the PSPL magnification A_PSPL(t) and the impact parameter U(t)
Return type:

tuple, tuple of two array_like
pyLIMA.microlmagnification.amplification_USBL(separation, mass_ratio, x_source, y_source, rho)[source]

The Uniform Source Binary Lens amplification, based on the work of Valerio Bozza, thanks :) “Microlensing with an advanced contour integration algorithm: Green’s theorem to third order, error control, optimal sampling and limb darkening ”,Bozza, Valerio 2010. Please cite the paper if you used this. http://mnras.oxfordjournals.org/content/408/4/2188

Parameters:
  • separation (array_like) – the projected normalised angular distance between the two bodies
  • mass_ratio (float) – the mass ratio of the two bodies
  • x_source (array_like) – the horizontal positions of the source center in the source plane
  • y_source (array_like) – the vertical positions of the source center in the source plane
  • rho (float) – the normalised (to :math:`theta_E’) angular source star radius
  • tolerance (float) – the relative precision desired in the magnification
Returns:

the USBL magnification A_USBL(t)
Return type:

array_like
pyLIMA.microlmagnification.impact_parameter(tau, uo)[source]

The impact parameter U(t). “Gravitational microlensing by the galactic halo”,Paczynski, B. 1986 http://adsabs.harvard.edu/abs/1986ApJ...304....1P

Parameters:
Returns:

the impact parameter U(t)
Return type:

array_like