RampFitOutputModel
- class jwst.datamodels.RampFitOutputModel(init=None, schema=None, memmap=False, pass_invalid_values=None, strict_validation=None, validate_on_assignment=None, validate_arrays=False, ignore_missing_extensions=True, **kwargs)
Bases:
JwstDataModel
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
- slopenumpy float32 array (n_int, max_seg, ny, nx)
Segment-specific slope
- sigslopenumpy float32 array (n_int, max_seg, ny, nx)
Sigma for segment-specific slope
- var_poissonnumpy float32 array (n_int, max_seg, ny, nx)
Variance due to poisson noise for segment-specific slope
- var_rnoisenumpy float32 array (n_int, max_seg, ny, nx)
Variance due to read noise for segment-specific slope
- yintnumpy float32 array (n_int, max_seg, ny, nx)
Segment-specific y-intercept
- sigyintnumpy float32 array (n_int, max_seg, ny, nx)
Sigma for segment-specific y-intercept
- pedestalnumpy float32 array (n_int, max_seg, ny, nx)
Pedestal array
- weightsnumpy float32 array (n_int, max_seg, ny, nx)
Weights for segment-specific fits
- crmagnumpy float32 array (n_int, max_seg, ny, nx)
Approximate CR magnitudes
- Parameters:
- initstr, tuple, ~astropy.io.fits.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
~astropy.io.fits.HDUList : Initialize from the given ~astropy.io.fits.HDUList.
A numpy array: Used to initialize the data array
dict: The object model tree for the data model
- schemadict, 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.
- memmapbool
Turn memmap of FITS/ASDF file on or off. (default: False).
- pass_invalid_valuesbool 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_validationbool 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.
- validate_on_assignmentbool or None
Defaults to ‘None’. If None, value will be taken from the environmental VALIDATE_ON_ASSIGNMENT, defaulting to ‘True’ if no environment variable is set. If ‘True’, attribute assignments are validated at the time of assignment. Validation errors generate warnings and values will be set to None. If ‘False’, schema validation occurs only once at the time of write. Validation errors generate warnings.
- validate_arraysbool
If True, arrays will be validated against ndim, max_ndim, and datatype validators in the schemas.
- ignore_missing_extensionsbool
When False, raise warnings when a file is read that contains metadata about extensions that are not available. Defaults to True.
- kwargsdict
Additional keyword arguments passed to lower level functions. These arguments are generally file format-specific. Arguments of note are:
FITS
- skip_fits_update - bool or None
DEPRECATED True to skip updating the ASDF tree from the FITS headers, if possible. If None, value will be taken from the environmental SKIP_FITS_UPDATE. Otherwise, the default value is True.
Attributes Summary
The schema URI to validate the model against.
Attributes Documentation
- schema_url = 'http://stsci.edu/schemas/jwst_datamodel/rampfitoutput.schema'
The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.