Box1D

class astropy.modeling.functional_models.Box1D(amplitude, x_0, width, **constraints)

Bases: astropy.modeling.core.Parametric1DModel

One dimensional Box model.

Parameters:

amplitude : float

Amplitude A

x_0 : float

Position of the center of the box function

width : float

Width of the box

See also

Box2D, TrapezoidDisk2D

Notes

Model formula:

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

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.

Attributes Summary

amplitude
param_names	list() -> new empty list
width
x_0

Methods Summary

deriv(x, amplitude, x_0, width)	One dimensional Box model derivative
eval(x, amplitude, x_0, width)	One dimensional Box model function

Attributes Documentation

amplitude

param_names = ['amplitude', 'x_0', 'width']

width

x_0

Methods Documentation

classmethod deriv(x, amplitude, x_0, width)

One dimensional Box model derivative

static eval(x, amplitude, x_0, width)

One dimensional Box model function