liger_iris_pipeline.datamodels

class liger_iris_pipeline.datamodels.DQModel(init=None, **kwargs)[source]

Bases: ReferenceFileModel

A data model for 2D masks for Liger data.

Parameters

dqnumpy uint32 array

The mask

dq_defnumpy table

DQ flag definitions

get_primary_array_name()[source]

Returns the name “primary” array for this model, which controls the size of other arrays that are implicitly created. This is intended to be overridden in the subclasses if the primary array’s name is not “data”.

schema_url = 'https://oirlab.github.io/schemas/DQModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.DarkModel(init=None, **kwargs)[source]

Bases: ReferenceFileModel

A data model for darks from either the Liger or IRIS Imager or IFU.

schema_url = 'https://oirlab.github.io/schemas/DarkModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.FlatModel(init=None, **kwargs)[source]

Bases: ReferenceFileModel

A data model for flat field images from either the Liger or IRIS Imager or IFU.

schema_url = 'https://oirlab.github.io/schemas/FlatModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.IFUCubeModel(init=None, **kwargs)[source]

Bases: LigerIRISDataModel

A data model for IFU data at the 3D cube stage.

Parameters: wavelength (np.ndarray): The wavelength vector. data (np.ndarray): The science data cube. err (np.ndarray): : The error array cube. dq (np.ndarray): The 3D data quality array cube.

schema_url = 'https://oirlab.github.io/schemas/IFUCubeModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.IFUImageModel(init=None, **kwargs)[source]

Bases: LigerIRISDataModel

A data model for IFU data at the 2D image stage.

Parameters: data (np.ndarray): The science data. err (np.ndarray): : The error array. dq (np.ndarray): The 2D data quality array.

schema_url = 'https://oirlab.github.io/schemas/IFUImageModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.ImagerModel(*args, **kwargs)[source]

Bases: LigerIRISDataModel

A data model for the typical data product from the Liger or IRIS imager (single detector).

Parameters: data (np.ndarray): The science data array. err (np.ndarray): : The error array. dq (np.ndarray): 2D data quality array.

schema_url = 'https://oirlab.github.io/schemas/ImagerModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.LigerIRISDataModel(init=None, **kwargs)[source]

Bases: DataModel

The base data model for Liger and IRIS data products. This class should not be instantiated on its own.

property crds_observatory

Get the CRDS observatory code for this model.

Returns

str

generate_filename(instrument: str | None = None, sem_id: str | None = None, program_number: str | None = None, obs_number: str | None = None, detector: str | None = None, exptype: str | None = None, level: int | str | None = None, exp: int | str | None = None, subarray: int | str | None = None)[source]
get_crds_parameters()[source]

Get parameters used by CRDS to select references for this model.

Returns: dict : the CRDS parameters

get_primary_array_name()[source]

Returns the name “primary” array for this model, which controls the size of other arrays that are implicitly created. This is intended to be overridden in the subclasses if the primary array’s name is not “data”.

property input_path
property instrument
on_init(init)[source]

Hook invoked by the base class before returning a newly created model instance.

on_save(init)[source]

Hook invoked by the base class before writing a model to a file (FITS or ASDF).

save(path=None, dir_path: str | None = None, **kwargs)[source]

Save the model to a file.

Args:

path (str) : The path to the file to save the model to. dir_path (str, optional) : The path to the directory to save the file to

schema_url = 'https://oirlab.github.io/schemas/LigerIRISDataModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

property telescope
class liger_iris_pipeline.datamodels.NonlinearReadoutParametersModel(init=None, **kwargs)[source]

Bases: ReferenceFileModel

A data model for the detector nonlinear readout polynomial coeffs.

schema_url = 'https://oirlab.github.io/schemas/NonlinearReadoutParametersModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.RampModel(init=None, **kwargs)[source]

Bases: LigerIRISDataModel

A data model for 4D ramps from Liger or IRIS for the IFU or Imager. 4D arrays are formatted as (groups, reads, pixely, pixelx).

Parameters: data (np.ndarray): 4-D array of counts for each read. dq (np.ndarray): 4-D data quality array for each read.

schema_url = 'https://oirlab.github.io/schemas/RampModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

class liger_iris_pipeline.datamodels.ReferenceFileModel(init=None, **kwargs)[source]

Bases: LigerIRISDataModel

A base data model for Liger and IRIS calibration reference data.

generate_filename(instrument: str | None = None, detector: str | None = None, reftype: str | None = None, date: str | None = None, version: str | None = None)[source]
print_err(message)[source]
save(path, dir_path=None, *args, **kwargs)[source]

Save data model. If the ‘dq’ and ‘dq_def’ exist they need special handling.

schema_url = 'https://oirlab.github.io/schemas/ReferenceFileModel.schema'

The schema URI to validate the model against. If None, only basic validation of required metadata properties (filename, model_type) will occur.

liger_iris_pipeline.datamodels.open(init=None, memmap: bool = False, copy: bool = False, **kwargs)[source]

Creates a DataModel from a number of different types.

Args:
init (None | tuple | str | file object | astropy.io.fits.HDUList | numpy.ndarray | dict):

The input used to initialize the model:

  • None: A default data model with no shape.

  • tuple: A shape tuple to initialize empty data.

  • str: A file path to load data from (FITS, JSON, or ASDF).

  • file object: A readable file object.

  • astropy.io.fits.HDUList: Initialize from an ~astropy.io.fits.HDUList.

  • numpy.ndarray: A NumPy array to initialize the data.

  • dict: An object model tree for the data model.

memmap: (bool) (Turn memmap of file on or off. (default: False).

kwargs (dict): Additional arguments used to initialize the model.

  • validate_arrays (bool): If True, arrays will be validated against ndim, max_ndim, and datatype validators in the schemas.

Returns:

LigerIRISDataModel : The specific LigerIRISDataModel instance.

Modules

bias

dark

dq

dqflags

Liger and IRIS Data Quality Flags copied from jwst.

flat

ifu

imager

integration

This module supports the entry points for ASDF support for the liger_iris_pipeline.datamodels.

model_base

nonlin_readout_params

ramp

referencefile

utils