Source code for jwst.datamodels.rampfitoutput

from .model_base import DataModel


__all__ = ['RampFitOutputModel']


[docs]class RampFitOutputModel(DataModel): """ A data model for the optional output of the ramp fitting step. In the parameter definitions below, `n_int` is the number of integrations, `max_seg` is the maximum number of segments that were fit, `nreads` is the number of reads in an integration, and `ny` and `nx` are the height and width of the image. Parameters __________ slope : numpy float32 array (n_int, max_seg, ny, nx) Segment-specific slope sigslope : numpy float32 array (n_int, max_seg, ny, nx) Sigma for segment-specific slope var_poisson : numpy float32 array (n_int, max_seg, ny, nx) Variance due to poisson noise for segment-specific slope var_rnoise : numpy float32 array (n_int, max_seg, ny, nx) Variance due to read noise for segment-specific slope yint : numpy float32 array (n_int, max_seg, ny, nx) Segment-specific y-intercept sigyint : numpy float32 array (n_int, max_seg, ny, nx) Sigma for segment-specific y-intercept pedestal : numpy float32 array (n_int, max_seg, ny, nx) Pedestal array weights : numpy float32 array (n_int, max_seg, ny, nx) Weights for segment-specific fits crmag : numpy float32 array (n_int, max_seg, ny, nx) Approximate CR magnitudes """ schema_url = "http://stsci.edu/schemas/jwst_datamodel/rampfitoutput.schema"