lsst.jointcal.testUtils Namespace Reference

Functions
	canRunTests ()
	createTwoFakeCcdImages (num1=4, num2=4, seed=100, fakeDetectorId=12, photoCalibMean1=1e-2, photoCalibMean2=1.2e-2, fakeWcses=(None, None), fakeVisitInfos=(None, None))
	createFakeCcdImage (butler, visit, num, fluxFieldName, photoCalibMean=1e-2, photoCalibErr=1.0, fakeDetectorId=12, fakeWcs=None, fakeVisitInfo=None)
	createFakeCatalog (num, bbox, fluxFieldName, skyWcs=None, refCat=False)
	fillCatalog (schema, num, bbox, centroidKey, xErrKey, yErrKey, shapeKey, fluxFieldName, skyWcs=None, fluxErrFraction=0.05, refCat=False)
	getMeasuredStarsFromCatalog (catalog, pixToFocal)

Detailed Description

Functions to help create jointcal tests by generating fake data.

Function Documentation

canRunTests()

lsst.jointcal.testUtils.canRunTests

(

)

Returns True if the necessary packages and files are available.

We need ``obs_cfht`` to load the test/data/cfht_minimal dataset, which
includes the metadata that is used to build the fake catalogs.

Definition at line 39 of file testUtils.py.

def canRunTests():
    """Returns True if the necessary packages and files are available.
 
    We need ``obs_cfht`` to load the test/data/cfht_minimal dataset, which
    includes the metadata that is used to build the fake catalogs.
    """
    try:
        import lsst.obs.cfht  # noqa: F401
        return True
    except ImportError:
        return False
 
 

createFakeCatalog()

lsst.jointcal.testUtils.createFakeCatalog	(		num,
			bbox,
			fluxFieldName,
			skyWcs = None,
			refCat = False )

Return a fake minimally-useful catalog for jointcal.

Parameters
----------
num : `int`
    Number of sources to put in the catalogs. Should be
    a square, to have sqrt(num) centroids on a grid.
bbox : `lsst.geom.Box2I`
    Bounding Box of the detector to populate.
fluxFieldName : `str`
    Name of the flux field to populate in the catalog, without `_instFlux`
    (e.g. "slot_CalibFlux").
skyWcs : `lsst.afw.geom.SkyWcs` or None, optional
    If supplied, use this to fill in coordinates from centroids.
refCat : `bool`, optional
    Return a ``SimpleCatalog`` so that it behaves like a reference catalog?

Returns
-------
catalog : `lsst.afw.table.SourceCatalog`
    A populated source catalog.

Definition at line 191 of file testUtils.py.

def createFakeCatalog(num, bbox, fluxFieldName, skyWcs=None, refCat=False):
    """Return a fake minimally-useful catalog for jointcal.
 
    Parameters
    ----------
    num : `int`
        Number of sources to put in the catalogs. Should be
        a square, to have sqrt(num) centroids on a grid.
    bbox : `lsst.geom.Box2I`
        Bounding Box of the detector to populate.
    fluxFieldName : `str`
        Name of the flux field to populate in the catalog, without `_instFlux`
        (e.g. "slot_CalibFlux").
    skyWcs : `lsst.afw.geom.SkyWcs` or None, optional
        If supplied, use this to fill in coordinates from centroids.
    refCat : `bool`, optional
        Return a ``SimpleCatalog`` so that it behaves like a reference catalog?
 
    Returns
    -------
    catalog : `lsst.afw.table.SourceCatalog`
        A populated source catalog.
    """
    schema = lsst.afw.table.SourceTable.makeMinimalSchema()
    # centroid
    centroidKey = lsst.afw.table.Point2DKey.addFields(schema, "centroid", "centroid", "pixels")
    xErrKey = schema.addField("centroid_xErr", type="F")
    yErrKey = schema.addField("centroid_yErr", type="F")
    # coordinate erros
    lsst.afw.table.CoordKey.addErrorFields(schema)
    # shape
    shapeKey = lsst.afw.table.QuadrupoleKey.addFields(schema, "shape", "",
                                                      lsst.afw.table.CoordinateType.PIXEL)
    # Put the fake sources in the minimal catalog.
    schema.addField(fluxFieldName+"_instFlux", type="D", doc="post-ISR instFlux")
    schema.addField(fluxFieldName+"_instFluxErr", type="D", doc="post-ISR instFlux stddev")
    schema.addField(fluxFieldName+"_flux", type="D", doc="source flux (nJy)")
    schema.addField(fluxFieldName+"_fluxErr", type="D", doc="flux stddev (nJy)")
    schema.addField(fluxFieldName+"_mag", type="D", doc="magnitude")
    schema.addField(fluxFieldName+"_magErr", type="D", doc="magnitude stddev")
    return fillCatalog(schema, num, bbox,
                       centroidKey, xErrKey, yErrKey, shapeKey, fluxFieldName,
                       skyWcs=skyWcs, refCat=refCat)
 
 

createFakeCcdImage()

lsst.jointcal.testUtils.createFakeCcdImage	(		butler,
			visit,
			num,
			fluxFieldName,
			photoCalibMean = 1e-2,
			photoCalibErr = 1.0,
			fakeDetectorId = 12,
			fakeWcs = None,
			fakeVisitInfo = None )

Create a fake CcdImage by making a fake catalog.

Parameters
----------
butler : `lsst.daf.butler.Butler`
    Butler to load metadata from.
visit : `int`
    Visit identifier to build a butler dataId.
num : `int`
    Number of sources to put in the catalogs. Should be
    a square, to have sqrt(num) centroids on a grid.
fluxFieldName : `str`
    Name of the flux field to populate in the catalog, without `_instFlux`
    (e.g. "slot_CalibFlux").
photoCalibMean : `float`, optional
    Value to set for calibrationMean in the created PhotoCalib.
    Note: this value is 1/instFluxMag0, so it should be less than 1.
photoCalibErr : `float`, optional
    Value to set for calibrationErr in the created PhotoCalib.
fakeDetectorId : `int`, optional
    Use this as the detectorId in the returned CcdImage.
fakeWcs : `lsst.afw.geom.SkyWcs`, optional
    A SkyWcs to use instead of one read from disk.
fakeVisitInfo : `lsst.afw.image.VisitInfo`, optional
    A VisitInfo to use instead of one read from disk.

Returns
-------
struct : `lsst.pipe.base.Struct`
   Result struct with components:

   - `catalog` : Catalogs containing fake sources
       (`lsst.afw.table.SourceCatalog`).
   - `ccdImage` : CcdImage containing the metadata and fake sources
       (`lsst.jointcal.CcdImage`).
   - `bbox` : Bounding Box of the image (`lsst.geom.Box2I`).
   - `skyWcs` : SkyWcs of the image (`lsst.afw.geom.SkyWcs`).

Definition at line 133 of file testUtils.py.

                       fakeWcs=None, fakeVisitInfo=None):
    """Create a fake CcdImage by making a fake catalog.
 
    Parameters
    ----------
    butler : `lsst.daf.butler.Butler`
        Butler to load metadata from.
    visit : `int`
        Visit identifier to build a butler dataId.
    num : `int`
        Number of sources to put in the catalogs. Should be
        a square, to have sqrt(num) centroids on a grid.
    fluxFieldName : `str`
        Name of the flux field to populate in the catalog, without `_instFlux`
        (e.g. "slot_CalibFlux").
    photoCalibMean : `float`, optional
        Value to set for calibrationMean in the created PhotoCalib.
        Note: this value is 1/instFluxMag0, so it should be less than 1.
    photoCalibErr : `float`, optional
        Value to set for calibrationErr in the created PhotoCalib.
    fakeDetectorId : `int`, optional
        Use this as the detectorId in the returned CcdImage.
    fakeWcs : `lsst.afw.geom.SkyWcs`, optional
        A SkyWcs to use instead of one read from disk.
    fakeVisitInfo : `lsst.afw.image.VisitInfo`, optional
        A VisitInfo to use instead of one read from disk.
 
    Returns
    -------
    struct : `lsst.pipe.base.Struct`
       Result struct with components:
 
       - `catalog` : Catalogs containing fake sources
           (`lsst.afw.table.SourceCatalog`).
       - `ccdImage` : CcdImage containing the metadata and fake sources
           (`lsst.jointcal.CcdImage`).
       - `bbox` : Bounding Box of the image (`lsst.geom.Box2I`).
       - `skyWcs` : SkyWcs of the image (`lsst.afw.geom.SkyWcs`).
    """
    detectorId = 12  # we only have data for detector=12
 
    dataId = dict(visit=visit, detector=detectorId, instrument="MegaPrime")
    skyWcs = fakeWcs if fakeWcs is not None else butler.get('calexp.wcs', dataId=dataId)
    visitInfo = fakeVisitInfo if fakeVisitInfo is not None else butler.get('calexp.visitInfo', dataId=dataId)
    bbox = butler.get('calexp.bbox', dataId=dataId)
    detector = butler.get('calexp.detector', dataId=dataId)
    filt = butler.get("calexp.filter", dataId=dataId).bandLabel
    photoCalib = lsst.afw.image.PhotoCalib(photoCalibMean, photoCalibErr)
 
    catalog = createFakeCatalog(num, bbox, fluxFieldName, skyWcs=skyWcs)
    ccdImage = lsst.jointcal.CcdImage(catalog, skyWcs, visitInfo, bbox, filt, photoCalib,
                                      detector, visit, fakeDetectorId, fluxFieldName)
 
    return lsst.pipe.base.Struct(catalog=catalog, ccdImage=ccdImage, bbox=bbox, skyWcs=skyWcs)
 
 

createTwoFakeCcdImages()

lsst.jointcal.testUtils.createTwoFakeCcdImages	(		num1 = 4,
			num2 = 4,
			seed = 100,
			fakeDetectorId = 12,
			photoCalibMean1 = 1e-2,
			photoCalibMean2 = 1.2e-2,
			fakeWcses = (None, None),
			fakeVisitInfos = (None, None) )

Return two fake ccdImages built on CFHT Megacam metadata.

If ``num1 == num2``, the catalogs will align on-sky so each source will
have a match in the other catalog.

This uses the butler dataset stored in `tests/data/cfht_minimal` to
bootstrap the metadata.

Parameters
----------
num1, num2 : `int`, optional
    Number of sources to put in the first and second catalogs. Should be
    a square, to have sqrt(num) centroids on a grid.
seed : `int`, optional
    Seed value for np.random.
fakeDetectorId : `int`, optional
    Sensor identifier to use for both CcdImages. The wcs, bbox, photoCalib, etc.
    will still be drawn from the CFHT ccd=12 files, as that is the only
    testdata that is included in this simple test dataset.
photoCalibMean1, photoCalibMean2: `float`, optional
    The mean photometric calibration to pass to each ccdImage construction.
    Note: this value is 1/instFluxMag0, so it should be less than 1.
fakeWcses : `list` [`lsst.afw.geom.SkyWcs`], optional
    The SkyWcses to use instead of the ones read from disk.
fakeWcses : `list` [`lsst.afw.image.VisitInfo`], optional
    The VisitInfos to use instead of the ones read from disk.

Returns
-------
struct : `lsst.pipe.base.Struct`
   Result struct with components:

   - `camera` : Camera representing these catalogs
       (`lsst.afw.cameraGeom.Camera`).
   - `catalogs` : Catalogs containing fake sources
       (`list` of `lsst.afw.table.SourceCatalog`).
   - `ccdImageList` : CcdImages containing the metadata and fake sources
       (`list` of `lsst.jointcal.CcdImage`).
   - `bbox` : Bounding Box of the image (`lsst.geom.Box2I`).
   - 'fluxFieldName' : name of the instFlux field in the catalogs ('str').

Definition at line 52 of file testUtils.py.

                           fakeVisitInfos=(None, None)):
    """Return two fake ccdImages built on CFHT Megacam metadata.
 
    If ``num1 == num2``, the catalogs will align on-sky so each source will
    have a match in the other catalog.
 
    This uses the butler dataset stored in `tests/data/cfht_minimal` to
    bootstrap the metadata.
 
    Parameters
    ----------
    num1, num2 : `int`, optional
        Number of sources to put in the first and second catalogs. Should be
        a square, to have sqrt(num) centroids on a grid.
    seed : `int`, optional
        Seed value for np.random.
    fakeDetectorId : `int`, optional
        Sensor identifier to use for both CcdImages. The wcs, bbox, photoCalib, etc.
        will still be drawn from the CFHT ccd=12 files, as that is the only
        testdata that is included in this simple test dataset.
    photoCalibMean1, photoCalibMean2: `float`, optional
        The mean photometric calibration to pass to each ccdImage construction.
        Note: this value is 1/instFluxMag0, so it should be less than 1.
    fakeWcses : `list` [`lsst.afw.geom.SkyWcs`], optional
        The SkyWcses to use instead of the ones read from disk.
    fakeWcses : `list` [`lsst.afw.image.VisitInfo`], optional
        The VisitInfos to use instead of the ones read from disk.
 
    Returns
    -------
    struct : `lsst.pipe.base.Struct`
       Result struct with components:
 
       - `camera` : Camera representing these catalogs
           (`lsst.afw.cameraGeom.Camera`).
       - `catalogs` : Catalogs containing fake sources
           (`list` of `lsst.afw.table.SourceCatalog`).
       - `ccdImageList` : CcdImages containing the metadata and fake sources
           (`list` of `lsst.jointcal.CcdImage`).
       - `bbox` : Bounding Box of the image (`lsst.geom.Box2I`).
       - 'fluxFieldName' : name of the instFlux field in the catalogs ('str').
    """
    if not canRunTests():
        msg = "Necessary packages not available to run tests that use the cfht_minimal dataset."
        raise unittest.SkipTest(msg)
 
    np.random.seed(seed)
 
    visit1 = 849375
    visit2 = 850587
    fluxFieldName = "SomeFlux"
 
    # Load or fake the necessary metadata for each CcdImage
    dataDir = lsst.utils.getPackageDir('jointcal')
    inputDir = os.path.join(dataDir, 'tests/data/cfht_minimal/repo')
    # Ensure this butler is not writeable, so that we don't mess up the repo accidentally.
    butler = lsst.daf.butler.Butler(inputDir, collections=["singleFrame"], writeable=False)
 
    # so we can access parts of the camera later (e.g. focal plane)
    camera = butler.get('camera', instrument="MegaPrime")
 
    struct1 = createFakeCcdImage(butler, visit1, num1, fluxFieldName,
                                 photoCalibMean=photoCalibMean1, photoCalibErr=1.0,
                                 fakeDetectorId=fakeDetectorId,
                                 fakeWcs=fakeWcses[0], fakeVisitInfo=fakeVisitInfos[0])
    struct2 = createFakeCcdImage(butler, visit2, num2, fluxFieldName,
                                 photoCalibMean=photoCalibMean2, photoCalibErr=5.0,
                                 fakeDetectorId=fakeDetectorId,
                                 fakeWcs=fakeWcses[1], fakeVisitInfo=fakeVisitInfos[1])
 
    return lsst.pipe.base.Struct(camera=camera,
                                 catalogs=[struct1.catalog, struct2.catalog],
                                 ccdImageList=[struct1.ccdImage, struct2.ccdImage],
                                 bbox=struct1.bbox,
                                 skyWcs=[struct1.skyWcs, struct2.skyWcs],
                                 fluxFieldName=fluxFieldName)
 
 

fillCatalog()

lsst.jointcal.testUtils.fillCatalog	(		schema,
			num,
			bbox,
			centroidKey,
			xErrKey,
			yErrKey,
			shapeKey,
			fluxFieldName,
			skyWcs = None,
			fluxErrFraction = 0.05,
			refCat = False )

Return a catalog populated with fake, but reasonable, sources.

Centroids are placed on a uniform grid, errors are normally distributed.

Parameters
----------
schema : `lsst.afw.table.Schema`
    Pre-built schema to make the catalog from.
num : `int`
    Number of sources to put in the catalog.
bbox : `lsst.geom.Box2I`
    Bounding box of the ccd to put sources in.
centroidKey : `lsst.afw.table.Key`
    Key for the centroid field to populate.
xErrKey : `lsst.afw.table.Key`
    Key for the xErr field to populate.
yErrKey : `lsst.afw.table.Key`
    Key for the yErr field to populate.
shapeKey : `lsst.afw.table.Key`
    Key for the shape field to populate.
fluxFieldName : `str`
    Name of the flux field to populate in the catalog, without `_instFlux`
    (e.g. "slot_CalibFlux").
skyWcs : `lsst.afw.geom.SkyWcs` or None, optional
    If supplied, use this to fill in coordinates from centroids.
fluxErrFraction : `float`, optional
    Fraction of instFlux to use for the instFluxErr.
refCat : `bool`, optional
    Return a ``SimpleCatalog`` so that it behaves like a reference catalog?

Returns
-------
catalog : `lsst.afw.table.SourceCatalog`
    The filled catalog.

Definition at line 236 of file testUtils.py.

                skyWcs=None, fluxErrFraction=0.05, refCat=False):
    """Return a catalog populated with fake, but reasonable, sources.
 
    Centroids are placed on a uniform grid, errors are normally distributed.
 
    Parameters
    ----------
    schema : `lsst.afw.table.Schema`
        Pre-built schema to make the catalog from.
    num : `int`
        Number of sources to put in the catalog.
    bbox : `lsst.geom.Box2I`
        Bounding box of the ccd to put sources in.
    centroidKey : `lsst.afw.table.Key`
        Key for the centroid field to populate.
    xErrKey : `lsst.afw.table.Key`
        Key for the xErr field to populate.
    yErrKey : `lsst.afw.table.Key`
        Key for the yErr field to populate.
    shapeKey : `lsst.afw.table.Key`
        Key for the shape field to populate.
    fluxFieldName : `str`
        Name of the flux field to populate in the catalog, without `_instFlux`
        (e.g. "slot_CalibFlux").
    skyWcs : `lsst.afw.geom.SkyWcs` or None, optional
        If supplied, use this to fill in coordinates from centroids.
    fluxErrFraction : `float`, optional
        Fraction of instFlux to use for the instFluxErr.
    refCat : `bool`, optional
        Return a ``SimpleCatalog`` so that it behaves like a reference catalog?
 
    Returns
    -------
    catalog : `lsst.afw.table.SourceCatalog`
        The filled catalog.
    """
    table = lsst.afw.table.SourceTable.make(schema)
    table.defineCentroid('centroid')
    table.defineShape('shape')
    table.defineCalibFlux(fluxFieldName)
    if refCat:
        catalog = lsst.afw.table.SimpleCatalog(table)
    else:
        catalog = lsst.afw.table.SourceCatalog(table)
 
    instFlux = np.random.random(num)*10000
    instFluxErr = np.abs(instFlux * np.random.normal(fluxErrFraction, scale=0.1, size=num))
    xx = np.linspace(bbox.getMinX(), bbox.getMaxX(), int(np.sqrt(num)))
    yy = np.linspace(bbox.getMinY(), bbox.getMaxY(), int(np.sqrt(num)))
    xv, yv = np.meshgrid(xx, yy)
    vx = np.random.normal(scale=0.1, size=num)
    vy = np.random.normal(scale=0.1, size=num)
 
    # make all the sources perfectly spherical, for simplicity.
    mxx = 1
    myy = 1
    mxy = 0
 
    for i, (x, y) in enumerate(zip(xv.ravel(), yv.ravel())):
        record = catalog.addNew()
        record.set('id', i)
        record.set(centroidKey, lsst.geom.Point2D(x, y))
        record.set(shapeKey, lsst.afw.geom.ellipses.Quadrupole(mxx, myy, mxy))
 
    if skyWcs is not None:
        lsst.afw.table.updateSourceCoords(skyWcs, catalog)
 
    catalog[xErrKey] = vx
    catalog[yErrKey] = vy
    catalog[fluxFieldName + '_instFlux'] = instFlux
    catalog[fluxFieldName + '_instFluxErr'] = instFluxErr
 
    return catalog
 
 

getMeasuredStarsFromCatalog()

lsst.jointcal.testUtils.getMeasuredStarsFromCatalog	(		catalog,
			pixToFocal )

Return a list of measuredStars built from a catalog.

Parameters
----------
catalog : `lsst.afw.table.SourceCatalog`
    The table to get sources from.
pixToFocal : `lsst.afw.geom.TransformPoint2ToPoint2`
    Transform that goes from pixel to focal plane coordinates, to set the
    MeasuredStar x/y focal points.

Returns
-------
stars : `list` of `lsst.jointcal.MeasuredStar`
    MeasuredStars built from the catalog sources.

Definition at line 313 of file testUtils.py.

def getMeasuredStarsFromCatalog(catalog, pixToFocal):
    """Return a list of measuredStars built from a catalog.
 
    Parameters
    ----------
    catalog : `lsst.afw.table.SourceCatalog`
        The table to get sources from.
    pixToFocal : `lsst.afw.geom.TransformPoint2ToPoint2`
        Transform that goes from pixel to focal plane coordinates, to set the
        MeasuredStar x/y focal points.
 
    Returns
    -------
    stars : `list` of `lsst.jointcal.MeasuredStar`
        MeasuredStars built from the catalog sources.
    """
    stars = []
    for record in catalog:
        star = lsst.jointcal.MeasuredStar()
        star.x = record.getX()
        star.y = record.getY()
        star.setInstFluxAndErr(record.getCalibInstFlux(), record.getCalibInstFluxErr())
        # TODO: cleanup after DM-4044
        point = lsst.geom.Point2D(star.x, star.y)
        pointFocal = pixToFocal.applyForward(point)
        star.setXFocal(pointFocal.getX())
        star.setYFocal(pointFocal.getY())
        stars.append(star)
 
    return stars