NIRCAMBackwardGrismDispersion¶

class jwst.transforms.models.NIRCAMBackwardGrismDispersion(orders, lmodels=None, xmodels=None, ymodels=None, name=None, meta=None)[source]¶

Bases: astropy.modeling.core.Model

Return the valid pixel(s) and wavelengths given center x,y and lam

Parameters

orders (list [int]) – List of orders which are available
lmodels (list [astropy.modeling.Model]) – List of models which govern the wavelength solutions
xmodels (list [astropy.modeling.Model]) – List of models which govern the x solutions
ymodels (list [astropy.modeling.Model]) – List of models which givern the y solutions

Returns

x, y, lam, order in the grism image for the pixel at x0,y0 that was
specified as input using the wavelength l for the specified order

Notes

The evaluation here is lineaer because higher orders have not yet been defined for NIRCAM (NIRCAM polynomials currently do not have any field dependence)

Attributes Summary

`fittable`
`linear`
`n_inputs`
`n_outputs`
`standard_broadcasting`

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, wavelength, order)	Return the tranfrom from image to grism for the given spectral order.

Attributes Documentation

fittable = False¶

linear = False¶

n_inputs = 4¶

n_outputs = 5¶

standard_broadcasting = False¶

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, wavelength, order)[source]¶

Return the tranfrom from image to grism for the given spectral order.

Parameters

x (float) – input x pixel
y (float) – intput y pixel
wavelength (float) – input wavelength in angstroms
order (int) – specifies the spectral order