HG1G2

class sbpy.photometry.HG1G2(H=8, G1=0.2, G2=0.2, **kwargs)[source]

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)
G2 = Parameter('G2', value=0.2)
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)[source]

Evaluate the model on some input variables.

static fit_deriv(ph, h, g1, g2)[source]