SIP

class astropy.modeling.polynomial.SIP(crpix, a_order, b_order, a_coeff={}, b_coeff={}, ap_order=None, bp_order=None, ap_coeff={}, bp_coeff={}, n_models=None, model_set_axis=None, name=None, meta=None)[source]

Bases: astropy.modeling.Model

Simple Imaging Polynomial (SIP) model.

The SIP convention is used to represent distortions in FITS image headers. See [R25] for a description of the SIP convention.

Parameters:

crpix : list or ndarray of length(2)

CRPIX values

a_order : int

SIP polynomial order for first axis

b_order : int

SIP order for second axis

a_coeff : dict

SIP coefficients for first axis

b_coeff : dict

SIP coefficients for the second axis

ap_order : int

order for the inverse transformation (AP coefficients)

bp_order : int

order for the inverse transformation (BP coefficients)

ap_coeff : dict

coefficients for the inverse transform

bp_coeff : dict

coefficients for the inverse transform

References

[R25](1, 2) David Shupe, et al, ADASS, ASP Conference Series, Vol. 347, 2005

Attributes Summary

n_inputs
n_outputs

Methods Summary

__call__(*inputs[, model_set_axis, …]) Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.
evaluate(x, y) Evaluate the model on some input variables.

Attributes Documentation

n_inputs = 2
n_outputs = 2

Methods Documentation

__call__(*inputs, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None, inputs_map=None, **new_inputs)

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

evaluate(x, y)[source]

Evaluate the model on some input variables.