# OrthoPolynomialBase¶

class astropy.modeling.polynomial.OrthoPolynomialBase(x_degree, y_degree, x_domain=None, x_window=None, y_domain=None, y_window=None, n_models=None, model_set_axis=None, name=None, meta=None, **params)[source]

Bases: astropy.modeling.polynomial.PolynomialBase

This is a base class for the 2D Chebyshev and Legendre models.

The polynomials implemented here require a maximum degree in x and y.

Parameters
x_degreeint

degree in x

y_degreeint

degree in y

x_domainlist or None, optional

domain of the x independent variable

x_windowlist or None, optional

range of the x independent variable

y_domainlist or None, optional

domain of the y independent variable

y_windowlist or None, optional

range of the y independent variable

**paramsdict

{keyword: value} pairs, representing {parameter_name: value}

Attributes Summary

Methods Summary

 __call__(self, x, y[, model_set_axis, …]) Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated. evaluate(self, x, y, \*coeffs) Evaluate the model on some input variables. get_num_coeff(self) Determine how many coefficients are needed imhorner(self, x, y, coeff) invlex_coeff(self, coeffs) prepare_inputs(self, x, y, \*\*kwargs) This method is used in __call__ to ensure that all the inputs to the model can be broadcast into compatible shapes (if one or both of them are input as arrays), particularly if there are more than one parameter sets.

Attributes Documentation

inputs = ('x', 'y')
outputs = ('z',)

Methods Documentation

__call__(self, x, y, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None)

Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

evaluate(self, x, y, *coeffs)[source]

Evaluate the model on some input variables.

get_num_coeff(self)[source]

Determine how many coefficients are needed

Returns
numcint

number of coefficients

imhorner(self, x, y, coeff)[source]
invlex_coeff(self, coeffs)[source]
prepare_inputs(self, x, y, **kwargs)[source]

This method is used in __call__ to ensure that all the inputs to the model can be broadcast into compatible shapes (if one or both of them are input as arrays), particularly if there are more than one parameter sets. This also makes sure that (if applicable) the units of the input will be compatible with the evaluate method.