RampFitOutputModel

class jwst.datamodels.RampFitOutputModel(init=None, schema=None, memmap=False, pass_invalid_values=None, strict_validation=None, ignore_missing_extensions=True, **kwargs)[source]

Bases: jwst.datamodels.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

  • init (str, tuple, HDUList, ndarray, dict, None) –

    • None : Create a default data model with no shape.

    • tuple : Shape of the data array. Initialize with empty data array with shape specified by the.

    • file path: Initialize from the given file (FITS or ASDF)

    • readable file object: Initialize from the given file object

    • HDUList : Initialize from the given HDUList.

    • A numpy array: Used to initialize the data array

    • dict: The object model tree for the data model

  • schema (dict, str (optional)) – Tree of objects representing a JSON schema, or string naming a schema. The schema to use to understand the elements on the model. If not provided, the schema associated with this class will be used.

  • memmap (bool) – Turn memmap of FITS file on or off. (default: False). Ignored for ASDF files.

  • pass_invalid_values (bool or None) – If True, values that do not validate the schema will be added to the metadata. If False, they will be set to None. If None, value will be taken from the environmental PASS_INVALID_VALUES. Otherwise the default value is False.

  • strict_validation (bool or None) – If True, schema validation errors will generate an exception. If False, they will generate a warning. If None, value will be taken from the environmental STRICT_VALIDATION. Otherwise, the default value is False.

  • ignore_missing_extensions (bool) – When False, raise warnings when a file is read that contains metadata about extensions that are not available. Defaults to True.

  • kwargs (dict) – Additional arguments passed to lower level functions.

  • available built-in formats are (The) –

  • ==== ===== ============= (=========) – Format Read Write Auto-identify

  • ==== ===== =============

  • Yes Yes Yes (datamodel) –

  • ==== ===== =============

Attributes Summary

schema_url

Attributes Documentation

schema_url = 'http://stsci.edu/schemas/jwst_datamodel/rampfitoutput.schema'