NIRISSForwardColumnGrismDispersion

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

Bases: astropy.modeling.core.Model

This model calculates the dispersion extent of NIRISS pixels.

The dispersion polynomial is relative to the input x,y pixels in the direct image for a given wavelength.

Parameters:
  • xmodels (list[tuple]) – The list of tuple(models) for the polynomial model in x
  • ymodels (list[tuple]) – The list of tuple(models) for the polynomial model in y
  • lmodels (list) – The list of models for the polynomial model in l
  • orders (list) – The list of orders which are available to the model

Notes

Given the x,y, source location, order, it returns the tuple of x,y,wavelength,order on the dispersed image. It also requires FWCPOS from the image header, this is the filter wheel position in degrees.

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

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)[source]

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

Parameters:
  • x0 (int,float) – Source object x-center
  • y0 (int,float) – Source object y-center
  • x (int,float) – Input x location
  • y (int,float) – Input y location
  • order (int) – Spectral order to use
  • theta (float) – input filter wheel rotation angle in degrees
Returns:

  • x, y, lambda, order, in the direct image for the pixel that was
  • specified as input using the wavelength l and spectral order

Notes

There’s spatial dependence for NIRISS as well as rotation for the filter wheel