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: Model

Simple Imaging Polynomial (SIP) model.

The SIP convention is used to represent distortions in FITS image headers. See [1] for a description of the SIP convention.

Parameters:

crpixlist or (2,) ndarray: CRPIX values
a_orderint: SIP polynomial order for first axis
b_orderint: SIP order for second axis
a_coeffdict: SIP coefficients for first axis
b_coeffdict: SIP coefficients for the second axis
ap_orderint: order for the inverse transformation (AP coefficients)
bp_orderint: order for the inverse transformation (BP coefficients)
ap_coeffdict: coefficients for the inverse transform
bp_coeffdict: coefficients for the inverse transform

References

[1]

David Shupe, et al, ADASS, ASP Conference Series, Vol. 347, 2005

Attributes Summary

`n_inputs`	The number of inputs.
`n_outputs`	The number of 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#: The number of inputs.

n_outputs = 2#: The number of outputs.

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.