StitchedImagePlanes¶
- class lsst.cell_coadds.StitchedImagePlanes¶
- Bases: - ImagePlanes- An ImagePlanes intermediate base class that stitches together per-cell images. - Parameters:
- bboxBox2I
- The region over which contiguous piecewise images are desired. 
 
- bbox
 - Notes - This class simply inserts subimages from each cell into the full image, doing so when an attribute is first accessed to avoid stitching together planes that may never be accessed. - Attributes Summary - The bounding box common to all image planes. - Object that defines the piecewise grid this object stitches together. - The data image itself. - An integer bitmask. - The names of all mask planes whose fractions were propagated in any cell. - The (weighted) fraction of masked pixels that contribute to each pixel. - The number of noise realizations cells are guaranteed to have. - A sequence of noise realizations that were coadded with the same operations that were appled to the data image. - Per-pixel variances for the image. - Methods Summary - Return an - lsst.afw.image.MaskedImageview of the image, mask, and variance planes.- Remove any cached - imageplane.- Remove any cached - maskplane.- Remove any cached - mask_fractionplanes.- Remove any cached - noise_realizationplanes.- Remove any cached - varianceplane.- Attributes Documentation - bbox¶
- The bounding box common to all image planes. 
 - grid¶
- Object that defines the piecewise grid this object stitches together. - This may include cells outside the region covered by these image planes. 
 - image¶
 - mask¶
 - mask_fraction_names¶
- The names of all mask planes whose fractions were propagated in any cell. - Cells that do not have a mask fraction for a particular name may be assumed to have the fraction for that mask plane uniformly zero. 
 - mask_fractions¶
 - n_noise_realizations¶
- The number of noise realizations cells are guaranteed to have. 
 - noise_realizations¶
 - variance¶
 - Methods Documentation - asMaskedImage() MaskedImageF¶
- Return an - lsst.afw.image.MaskedImageview of the image, mask, and variance planes.