NIRCAMForwardColumnGrismDispersion

class jwst.transforms.NIRCAMForwardColumnGrismDispersion(orders, lmodels=None, xmodels=None, ymodels=None, name=None, meta=None)

Bases: astropy.modeling.core.Model

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

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 input delta pix 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
inputs
linear
outputs
standard_broadcasting

Methods Summary

__call__(x, y, x0, y0, order[, …])	Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.
evaluate(x, y, x0, y0, order)	Return the transform from grism to image for the given spectral order.

Attributes Documentation

fittable = False

inputs = ('x', 'y', 'x0', 'y0', 'order')

linear = False

outputs = ('x', 'y', 'wavelength', 'order')

standard_broadcasting = False

Methods Documentation

__call__(x, y, x0, y0, order, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None)

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

evaluate(x, y, x0, y0, order)

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

Parameters:

• x (float) – input x pixel
• y (float) – intput y pixel
• x0 (float) – input x-center of object
• y0 (float) – input y-center of object
• order (int) – the spectral order to use