Legendre1D

class astropy.modeling.polynomial.Legendre1D(degree, domain=None, window=[-1, 1], n_models=None, model_set_axis=None, **params)

Bases: astropy.modeling.polynomial.PolynomialModel

1D Legendre polynomial.

Parameters:

degree : int

degree of the series

domain : list or None

window : list or None

If None, it is set to [-1,1] Fitters will remap the domain to this window

param_dim : int

number of parameter sets

**params : dict

keyword: value pairs, representing parameter_name: value

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.

Attributes Summary

input_names

list() -> new empty list

Methods Summary

clenshaw(x, coeffs)
evaluate(x, *coeffs)
fit_deriv(x, *params)	Computes the Vandermonde matrix.
prepare_inputs(x, **kwargs)

Attributes Documentation

input_names = []

Methods Documentation

static clenshaw(x, coeffs)

classmethod evaluate(x, *coeffs)

fit_deriv(x, *params)

Computes the Vandermonde matrix.

Parameters:

x : ndarray

input

params : throw away parameter

parameter list returned by non-linear fitters

Returns:

result : ndarray

The Vandermonde matrix

prepare_inputs(x, **kwargs)