HG1G2

class sbpy.photometry.HG1G2(*args, **kwargs)

Bases: HG12BaseClass

HG1G2 photometric phase model (Muinonen et al. 2010)

Examples

>>> # Define the phase function for Themis with
>>> # H = 7.063, G1 = 0.62, G2 = 0.14
>>>
>>> import astropy.units as u
>>> from sbpy.calib import solar_fluxd
>>> from sbpy.photometry import HG1G2
>>> themis = HG1G2(7.063 * u.mag, 0.62, 0.14, radius = 100 * u.km,
...     wfb = 'V')
>>> with solar_fluxd.set({'V': -26.77 * u.mag}):
...     print('geometric albedo = {0:.4f}'.format(themis.geomalb))
...     print('phase integral = {0:.4f}'.format(themis.phaseint))
geometric albedo = 0.0656
phase integral = 0.3742

Initialize DiskIntegratedPhaseFunc

Parameters:

radiusastropy.units.Quantity, optional

Radius of object. Required if conversion between magnitude and reflectance is involved.

wfbQuantity, SpectralElement, string

Wavelengths, frequencies, or bandpasses. Bandpasses may be a filter name (string). Required if conversion between magnitude and reflectance is involved.

**kwargsoptional parameters accepted by

astropy.modeling.Model.__init__()

Attributes Summary

G1
G2
H
param_names	Names of the parameters that describe models of this type.

Methods Summary

evaluate(ph, h, g1, g2)	Evaluate the model on some input variables.
fit_deriv(ph, h, g1, g2)

Attributes Documentation

G1 = Parameter('G1', value=0.2, bounds=[0, 1])

G2 = Parameter('G2', value=0.2, bounds=[0, 1])

H = Parameter('H', value=8.0)

param_names = ('H', 'G1', 'G2')

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the Parameter attributes defined in the class body.

Methods Documentation

static evaluate(ph, h, g1, g2)

Evaluate the model on some input variables.

static fit_deriv(ph, h, g1, g2)