lsst.afw.detection.multiband Namespace Reference

Classes
class	MultibandFootprint

Functions
	getSpanSetFromImages (images, thresh=0, xy0=None)

Function Documentation

getSpanSetFromImages()

lsst.afw.detection.multiband.getSpanSetFromImages	(		images,
			thresh = 0,
			xy0 = None )

Create a Footprint from a set of Images

Parameters
----------
images : `lsst.afw.image.MultibandImage` or list of `lsst.afw.image.Image`, array
    Images to extract the footprint from
thresh : `float`
    All pixels above `thresh` will be included in the footprint
xy0 : `lsst.geom.Point2I`
    Location of the minimum value of the images bounding box
    (if images is an array, otherwise the image bounding box is used).

Returns
-------
spans : `lsst.afw.geom.SpanSet`
    Union of all spans in the images above the threshold
imageBBox : `lsst.afw.detection.Box2I`
    Bounding box for the input images.

Definition at line 38 of file multiband.py.

def getSpanSetFromImages(images, thresh=0, xy0=None):
    """Create a Footprint from a set of Images
 
    Parameters
    ----------
    images : `lsst.afw.image.MultibandImage` or list of `lsst.afw.image.Image`, array
        Images to extract the footprint from
    thresh : `float`
        All pixels above `thresh` will be included in the footprint
    xy0 : `lsst.geom.Point2I`
        Location of the minimum value of the images bounding box
        (if images is an array, otherwise the image bounding box is used).
 
    Returns
    -------
    spans : `lsst.afw.geom.SpanSet`
        Union of all spans in the images above the threshold
    imageBBox : `lsst.afw.detection.Box2I`
        Bounding box for the input images.
    """
    # Set the threshold for each band
    if not hasattr(thresh, "__len__"):
        thresh = [thresh] * len(images)
 
    # If images is a list of `afw Image` objects then
    # merge the SpanSet in each band into a single Footprint
    if isinstance(images, MultibandBase) or isinstance(images[0], Image):
        spans = SpanSet()
        for n, image in enumerate(images):
            mask = image.array > thresh[n]
            mask = Mask(mask.astype(np.int32), xy0=image.getBBox().getMin())
            spans = spans.union(SpanSet.fromMask(mask))
        imageBBox = images[0].getBBox()
    else:
        # Use thresh to detect the pixels above the threshold in each band
        thresh = np.array(thresh)
        if xy0 is None:
            xy0 = Point2I(0, 0)
        mask = np.any(images > thresh[:, None, None], axis=0)
        mask = Mask(mask.astype(np.int32), xy0=xy0)
        spans = SpanSet.fromMask(mask)
        imageBBox = mask.getBBox()
    return spans, imageBBox