SIP¶
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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 [1] 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
[1] (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
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inputs
= ('u', 'v')¶
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outputs
= ('x', 'y')¶
Methods Documentation
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__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.
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evaluate
(x, y)[source] [edit on github]¶ Evaluate the model on some input variables.