Defects#

class lsst.ip.isr.Defects(defectList=None, metadata=None, *, normalize_on_init=True, **kwargs)#

Bases: IsrCalib

Calibration handler for collections of lsst.meas.algorithms.Defect.

Parameters#

defectListiterable, optional: Collections of defects to apply to the image. Can be an iterable of lsst.meas.algorithms.Defect or lsst.geom.BoxI.
metadatalsst.daf.base.PropertyList, optional: Metadata to associate with the defects. Will be copied and overwrite existing metadata, if any. If not supplied the existing metadata will be reset.
normalize_on_initbool: If True, normalization is applied to the defects in defectList to remove duplicates, eliminate overlaps, etc.

Notes#

Defects are stored within this collection in a “reduced” or “normalized” form: rather than simply storing the bounding boxes which are added to the collection, we eliminate overlaps and duplicates. This normalization procedure may introduce overhead when adding many new defects; it may be temporarily disabled using the Defects.bulk_update context manager if necessary.

The attributes stored in this calibration are:

_defectslist [lsst.meas.algorithms.Defect]: The collection of Defect objects.

Methods Summary

`append`(value)
`bulk_update`()	Temporarily suspend normalization of the defect list.
`copy`()	Copy the defects to a new list, creating new defects from the bounding boxes.
`fromDict`(dictionary)	Construct a calibration from a dictionary of properties.
`fromFootprintList`(fpList)	Compute a defect list from a footprint list, optionally growing the footprints.
`fromMask`(mask, maskName)	Compute a defect list from a specified mask plane.
`fromTable`(tableList[, normalize_on_init])	Construct a `Defects` from the contents of a `BaseCatalog`.
`insert`(index, value)
`maskPixels`(mask[, maskName])	Set mask plane based on these defects.
`readLsstDefectsFile`(filename[, ...])	Read defects information from a legacy LSST format text file.
`toDict`()	Return a dictionary containing the calibration properties.
`toFitsRegionTable`()	Convert defect list to `BaseCatalog` using the FITS region standard.
`toTable`()	Convert defects to a simple table form that we use to write to text files.
`transpose`()	Make a transposed copy of this defect list.
`updateCounters`([columns, hot, cold])	Update metadata with pixel and column counts.

Methods Documentation

append(value)#

bulk_update()#: Temporarily suspend normalization of the defect list.

copy()#

Copy the defects to a new list, creating new defects from the bounding boxes.

Returns#

newDefects: New list with new Defect entries.

Notes#

This is not a shallow copy in that new Defect instances are created from the original bounding boxes. It’s also not a deep copy since the bounding boxes are not recreated.

classmethod fromDict(dictionary)#

Construct a calibration from a dictionary of properties.

Must be implemented by the specific calibration subclasses.

Parameters#

dictionarydict: Dictionary of properties.

Returns#

caliblsst.ip.isr.CalibType: Constructed calibration.

Raises#

RuntimeError: Raised if the supplied dictionary is for a different calibration.

classmethod fromFootprintList(fpList)#

Compute a defect list from a footprint list, optionally growing the footprints.

Parameters#

fpListlist of lsst.afw.detection.Footprint: Footprint list to process.

Returns#

defectsDefects: List of defects.

classmethod fromMask(mask, maskName)#

Compute a defect list from a specified mask plane.

Parameters#

masklsst.afw.image.Mask or lsst.afw.image.MaskedImage: Image to process.
maskNamestr or list: Mask plane name, or list of names to convert.

Returns#

defectsDefects: Defect list constructed from masked pixels.

classmethod fromTable(tableList, normalize_on_init=True)#

Construct a Defects from the contents of a BaseCatalog.

Parameters#

tablelsst.afw.table.BaseCatalog: Table with one row per defect.
normalize_on_initbool, optional: If True, normalization is applied to the defects listed in the table to remove duplicates, eliminate overlaps, etc. Otherwise the defects in the returned object exactly match those in the table.

Returns#

defectsDefects: A Defects list.

Notes#

Two table formats are recognized. The first is the FITS regions definition tabular format written by toFitsRegionTable where the pixel origin is corrected from FITS 1-based to a 0-based origin. The second is the legacy defects format using columns x0, y0 (bottom left hand pixel of box in 0-based coordinates), width and height.

The FITS standard regions can only read BOX, POINT, or ROTBOX with a zero degree rotation.

insert(index, value)#

maskPixels(mask, maskName='BAD')#

Set mask plane based on these defects.

Parameters#

maskedImagelsst.afw.image.MaskedImage or lsst.afw.image.Mask: Image to process. Only the mask plane is updated.
maskNamestr, optional: Mask plane name to use.

classmethod readLsstDefectsFile(filename, normalize_on_init=False)#

Read defects information from a legacy LSST format text file.

Parameters#

filenamestr: Name of text file containing the defect information.
normalize_on_initbool, optional: If True, normalization is applied to the defects listed in the table to remove duplicates, eliminate overlaps, etc. Otherwise the defects in the returned object exactly match those in the table.

Returns#

defectsDefects: The defects.

Notes#

These defect text files are used as the human readable definitions of defects in calibration data definition repositories. The format is to use four columns defined as follows:

x0int: X coordinate of bottom left corner of box.
y0int: Y coordinate of bottom left corner of box.
widthint: X extent of the box.
heightint: Y extent of the box.

Files of this format were used historically to represent defects in simple text form. Use Defects.readText and Defects.writeText to use the more modern format.

toDict()#

Return a dictionary containing the calibration properties.

The dictionary should be able to be round-tripped through fromDict.

Returns#

dictionarydict: Dictionary of properties.

toFitsRegionTable()#

Convert defect list to BaseCatalog using the FITS region standard.

Returns#

tablelsst.afw.table.BaseCatalog: Defects in tabular form.

Notes#

The table created uses the FITS regions definition tabular format. The X and Y coordinates are converted to FITS Physical coordinates that have origin pixel (1, 1) rather than the (0, 0) used in LSST software.

toTable()#

Convert defects to a simple table form that we use to write to text files.

Returns#

tablelsst.afw.table.BaseCatalog: Defects in simple tabular form.

Notes#

These defect tables are used as the human readable definitions of defects in calibration data definition repositories. The format is to use four columns defined as follows:

x0int: X coordinate of bottom left corner of box.
y0int: Y coordinate of bottom left corner of box.
widthint: X extent of the box.
heightint: Y extent of the box.

transpose()#

Make a transposed copy of this defect list.

Returns#

retDefectListDefects: Transposed list of defects.

updateCounters(columns=None, hot=None, cold=None)#

Update metadata with pixel and column counts.

Parameters#

columnsint, optional: Number of full columns masked.
hotdict [str, int], optional: Dictionary with the count of hot pixels, indexed by amplifier name.
colddict [str, int], optional: Dictionary with the count of hot pixels, indexed by amplifier name.