pypeit.calibrations module

Class for guiding calibration object generation in PypeIt.

class pypeit.calibrations.Calibrations(fitstbl, par, spectrograph, caldir, qadir=None, reuse_calibs=False, show=False, user_slits=None, chk_version=True)[source]

Bases: object

Class designed to guide the generation of calibration images and objects in PypeIt.

Parameters:

fitstbl (PypeItMetaData) – The class holding the metadata for all the frames in this PypeIt run. If None, we are using this class as a glorified dict to hold the objects.
par (CalibrationsPar) – Parameter set defining optional parameters of PypeIt’s algorithms for Calibrations
spectrograph (Spectrograph) – Spectrograph object
caldir (str, Path) – Path for the processed calibration files.
qadir (str, optional) – Path for quality assessment output. If not provided, no QA plots are saved.
reuse_calibs (bool, optional) – Instead of reprocessing them, load existing calibration files from disk if they exist.
show (bool, optional) – Show plots of PypeIt’s results as the code progresses. Requires interaction from the user.
user_slits (dict, optional) – A limited set of slits selected by the user for analysis. See user_mask().
chk_version (bool, optional) – When reading in existing files written by PypeIt, perform strict version checking to ensure a valid file. If False, the code will try to keep going, but this may lead to faults and quiet failures. User beware!

fitstbl

See instantiation arguments.

Type:: PypeItMetaData

par

See instantiation arguments.

Type:: CalibrationsPar

spectrograph

See instantiation arguments.

Type:: Spectrograph

calib_dir

Path for the processed calibration files.

Type:: Path

qa_path

Path for the QA diagnostics.

Type:: Path

reuse_calibs

See instantiation arguments.

Type:: bool

show

See instantiation arguments.

Type:: bool

user_slits

See instantiation arguments.

Type:: dict

det

The single detector or set of detectors in a mosaic to process.

Type:: int, tuple

frame

The index of a raw file in fitstbl used to set the calibration group.

Type:: int

calib_ID

The calibration group associated with frame.

Type:: int

msarc

Arc calibration frame

Type:: ArcImage

mstilt

Tilt calibration frame

Type:: TiltImage

alignments

Alignment calibration frame

Type:: Alignments

msbias

Bias calibration frame

Type:: BiasImage

msdark

Dark calibration frame

Type:: DarkImage

msbpm

Boolean array with the bad-pixel mask (pixels that should masked are set to True).

Type:: numpy.ndarray

wv_calib

Wavelength calibration frame

Type:: WaveCalib

slits

Slit tracing calibration frame

Type:: SlitTraceSet

wavetilts

Tilts calibration frame

Type:: WaveTilts

flatimages

Flat-field calibration frame

Type:: FlatImages

steps

A list of strings setting the set of processing steps to be completed (not necessarily those that were successful). See the default_steps functions of each subclass.

Type:: list

success

Flag that the calibrations were all generated successfully.

Type:: bool

failed_step

If the calibrations were unsuccessful, this is the step that led to the fault.

Type:: str

_chk_objs(items)[source]

Check that the input items exist internally as attributes

Parameters:: items (list) –
Returns:: True if all exist
Return type:: bool

_chk_set(items)[source]

Check whether a needed attribute has previously been set

Parameters:: items (list) – Attributes to check

static association_summary(ofile, fitstbl, spectrograph, caldir, subset=None, det=None, overwrite=False)[source]

Write a file listing the associations between the processed calibration frames and their source raw files for every setup and every calibration group.

Parameters:

ofile (str, Path) – Full path to the output file.
fitstbl (PypeItMetaData) – The class holding the metadata for all the frames to process.
spectrograph (pypeit.spectrographs.spectrograph.Spectrograph) – Spectrograph object
caldir (str, Path) – Path for the processed calibration frames.
subset (numpy.ndarray, optional) – A boolean array selecting a subset of rows from fitstbl for output.
det (int, tuple, optional) – The specific detector (or mosaic) to use when constructing the output processed calibration group file names. If None, a placeholder is used.
overwrite (bool, optional) – Overwrite any existing file of the same name.

find_calibrations(frametype, frameclass)[source]

Find calibration files and identifiers.

Parameters:

frametype (str) – Calibration frame type. Must be a valid frame type; see valid_frametype().
frameclass (CalibFrame) – The subclass used to store the processed calibration data.

Returns:

raw_files (list) – The list of raw files in fitstbl with the provided frametype.
cal_file (Path) – The path with/for the processed calibration frame
calib_key (str) – The calibration identifier
setup (str) – The setup/configuration identifier
calib_id (list) – The calibration groups
detname (str) – The detector/mosaic identifier

get_align()[source]

Load or generate the alignment calibration frame.

Returns:: The processed alignment image.
Return type:: Alignments

get_arc()[source]

Load or generate the arc calibration frame.

Returns:: The processed calibration image.
Return type:: ArcImage

static get_association(fitstbl, spectrograph, caldir, setup, calib_ID, det, must_exist=True, subset=None, include_science=False, proc_only=False)[source]

Construct a dictionary with the association between raw files and processed calibration frames.

Parameters:

fitstbl (PypeItMetaData) – The class holding the metadata for all the frames to process.
spectrograph (pypeit.spectrographs.spectrograph.Spectrograph) – Spectrograph object
caldir (str, Path) – Path for the processed calibration frames.
setup (str) – The setup/configuration of the association.
calib_ID (str, int) – The single calibration group of the association.
det (int, tuple) – The detector/mosaic of the association.
must_exist (bool, optional) – If True, only existing calibration frames in the association are included. If False, the nominal set of processed calibration frame file names are returned, regardless of whether or not they exist.
subset (numpy.ndarray, optional) – A boolean array selecting a subset of rows from fitstbl for output.
include_science (bool, optional) – Include science and standard frames in the association. This parameter is mutually exclusive with proc_only; if both are true, proc_only takes precedence.
proc_only (bool, optional) – If True, only return a dictionary with the names of the processed calibration frames. The dictionary sets the calibration directory to DIR, and the other keys are the capitalized versions of the calibration type keywords; e.g., asn['ARC'] is the processed arc frame. This parameter is mutually exclusive with include_science; if both are true, proc_only takes precedence.

Returns:

The set of raw and processed calibration frames associated with the selected calibration group. This only includes the processed frames if proc_only is True, and it includes the science/standard frames if include_science is True.

Return type:

dict

get_bias()[source]

Load or generate the bias calibration frame.

Returns:: The processed calibration image.
Return type:: BiasImage

get_bpm(frame=None)[source]

Load or generate the bad pixel mask.

This is primarily a wrapper for bpm().

Returns:: The bad pixel mask, which should match the shape and orientation of a trimmed and PypeIt-oriented science image!
Return type:: numpy.ndarray

get_dark()[source]

Load or generate the dark calibration frame.

Returns:: The processed calibration image.
Return type:: DarkImage

get_flats()[source]

Load or generate the flat-field calibration images.

Returns:: The processed calibration image.
Return type:: FlatImages

static get_instance(fitstbl, par, spectrograph, caldir, **kwargs)[source]: Get the instance of the appropriate subclass of Calibrations to use for reducing data from the provided spectrograph. For argument descriptions, see Calibrations.

get_scattlight()[source]

Load or generate the scattered light model.

Returns:: The processed calibration image including the model.
Return type:: ScatteredLight

get_slits()[source]

Load or generate the definition of the slit boundaries.

Returns:: Traces of the slit edges; also kept internally as slits.
Return type:: SlitTraceSet

get_tiltimg()[source]

Load or generate the tilt calibration frame.

Returns:: The processed calibration image.
Return type:: TiltImage

get_tilts()[source]

Load or generate the wavelength tilts calibration frame

Returns:: Object containing the wavelength tilt calibration.
Return type:: WaveTilts

get_wv_calib()[source]

Load or generate the 1D wavelength calibrations

Returns:: Object containing wavelength calibrations and the updated slit mask array.
Return type:: WaveCalib

run_the_steps()[source]: Run full the full recipe of calibration steps.

set_config(frame, det, par=None)[source]

Specify the critical attributes of the class to perform a set of calibrations.

Operations are:

Set the frame

Use the frame to find the calibration group

Set the detector/mosaic

Set the parameters

Parameters:

frame (int) – The row index in fitstbl with the frame to calibrate.
det (int) – Detector number.
par (CalibrationsPar, optional) – Parameters used by the calibration procedures. If None, use par.

class pypeit.calibrations.IFUCalibrations(fitstbl, par, spectrograph, caldir, qadir=None, reuse_calibs=False, show=False, user_slits=None, chk_version=True)[source]

Bases: Calibrations

Child of Calibrations class for performing IFU calibrations. See Calibrations for arguments.

static default_steps()[source]

This defines the steps for calibrations and their order

Returns:: Calibration steps, in order of execution
Return type:: list

class pypeit.calibrations.MultiSlitCalibrations(fitstbl, par, spectrograph, caldir, qadir=None, reuse_calibs=False, show=False, user_slits=None, chk_version=True)[source]

Bases: Calibrations

Calibration class for performing multi-slit calibrations (and also long-slit and echelle). See Calibrations for arguments.

Note

Calibrations are not sufficiently different yet to warrant a different class for echelle reductions. This may change if a different order is eventually required for the set of processing steps (see default_steps()).

static default_steps()[source]

This defines the calibration steps and their order.

Returns:: Calibration steps, in order of execution.
Return type:: list

pypeit.calibrations.check_for_calibs(par, fitstbl, raise_error=True, cut_cfg=None)[source]

Perform a somewhat quick and dirty check to see if the user has provided all of the calibration frametype’s to reduce the science frames

Parameters:

par (PypeItPar) –
fitstbl (PypeItMetaData, None) – The class holding the metadata for all the frames in this PypeIt run.
raise_error (bool, optional) – If True, crash out
cut_cfg (numpy.ndarray, optional) – Also cut on this restricted configuration (mainly for chk_calibs)

Returns:

True if we passed all checks

Return type:

bool