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] [edit on github]

Bases: astropy.modeling.Model

Simple Imaging Polynomial (SIP) model.

The SIP convention is used to represent distortions in FITS image headers. See [R19] 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

[R19](1, 2) David Shupe, et al, ADASS, ASP Conference Series, Vol. 347, 2005

Attributes Summary

inputs
outputs

Methods Summary

__call__(u, v[, 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

inputs = ('u', 'v')
outputs = ('x', 'y')

Methods Documentation

__call__(u, v, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None) [edit on github]

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

evaluate(x, y)[source] [edit on github]

Evaluate the model on some input variables.