NIRCAMForwardRowGrismDispersion

class stdatamodels.jwst.transforms.NIRCAMForwardRowGrismDispersion(orders, lmodels=None, xmodels=None, ymodels=None, inv_lmodels=None, inv_xmodels=None, inv_ymodels=None, sampling=40)

Bases: _NIRCAMForwardGrismDispersion

Forward grism dispersion model for NIRCAM (row-wise).

Initialize the model.

Parameters:

orderslist[int]

List of spectral orders corresponding to the dispersion models given by the lmodels, xmodels, and ymodels parameters.

lmodelslist[astropy.modeling.polynomial.Polynomial1D]

The forward dispersion polynomial models, one per order, such that wavelength = lmodel(t) computes the wavelength from the trace parameter.

xmodelslist[astropy.modeling.polynomial.Polynomial1D] or list[list[astropy.modeling.polynomial.Polynomial2D]]

The models encoding the x-position of the spectral trace. Because the shape of the trace depends on the direct-image x0, y0 position, this takes the form dx = C0(x0, y0) + C1(x0, y0) * t + C2(x0, y0) * t^2. The inner list corresponds to the 2-D polynomials (C0, C1, C2). The outer list corresponds to the different spectral orders. Legacy calibrations of the trace did not encode the x0, y0 dependence; models of the form dx = xmodel(t) were used instead, and are also supported here.

ymodelslist[astropy.modeling.polynomial.Polynomial1D] or list[list[astropy.modeling.polynomial.Polynomial2D]]

Not used for row-wise dispersion, since y is the cross-dispersion direction.

inv_lmodelslist[astropy.modeling.core.Model]

Not used for the forward transform.

inv_xmodelslist[astropy.modeling.polynomial.Polynomial1D]

The inverse dispersion polynomial models, one per order, such that t = inv_xmodel(dx) computes the trace parameter from the x-position. The inverse models are no longer used for newer calibrations because the field dependence of the trace shape is not easily invertible. The use of inverse models is still supported for use by legacy trace calibrations.

inv_ymodelslist[astropy.modeling.polynomial.Polynomial1D]

Not used for row-wise dispersion, since y is the cross-dispersion direction.

samplingint, optional

Number of sampling points in t to use; these will be linearly interpolated.