Box2D

class astropy.modeling.functional_models.Box2D

Bases: astropy.modeling.Fittable2DModel

Two dimensional Box model.

Parameters:

amplitude : float

Amplitude A

x_0 : float

x position of the center of the box function

x_width : float

Width in x direction of the box

y_0 : float

y position of the center of the box function

y_width : float

Width in y direction of the box

Other Parameters:  

fixed : a dict

A dictionary {parameter_name: boolean} of parameters to not be varied during fitting. True means the parameter is held fixed. Alternatively the fixed property of a parameter may be used.

tied : dict

A dictionary {parameter_name: callable} of parameters which are linked to some other parameter. The dictionary values are callables providing the linking relationship. Alternatively the tied property of a parameter may be used.

bounds : dict

A dictionary {parameter_name: boolean} of lower and upper bounds of parameters. Keys are parameter names. Values are a list of length 2 giving the desired range for the parameter. Alternatively the min and max properties of a parameter may be used.

eqcons : list

A list of functions of length n such that eqcons[j](x0,*args) == 0.0 in a successfully optimized problem.

ineqcons : list

A list of functions of length n such that ieqcons[j](x0,*args) >= 0.0 is a successfully optimized problem.

See also

Box1D, Gaussian2D, Moffat2D

Notes

Model formula:

f(x, y) = \left \{ \begin{array}{ll} A & : x_0 - w_x/2 \geq x \geq x_0 + w_x/2 \\ A & : y_0 - w_y/2 \geq y \geq y_0 + w_y/2 \\ 0 & : \textnormal{else} \end{array} \right.

Attributes Summary

amplitude
param_names
x_0
x_width
y_0
y_width

Methods Summary

evaluate(x, y, amplitude, x_0, y_0, x_width, ...)

Two dimensional Box model function

Attributes Documentation

amplitude

param_names = ('amplitude', 'x_0', 'y_0', 'x_width', 'y_width')

x_0

x_width

y_0

y_width

Methods Documentation

static evaluate(x, y, amplitude, x_0, y_0, x_width, y_width)

Two dimensional Box model function