SpanSetMoments#

class lsst.meas.algorithms.SpanSetMoments#

Bases: pybind11_object

Attributes Summary

`any_flags_set`
`bad_pixel_in_center`
`center`
`center_out_of_bounds`
`flux`
`shape`
`singular_second_moments`
`spans`
`too_many_bad_pixels`
`variance`

Methods Summary

`compute`(spans, masked_image, bad_bitmask, ...)
`fit_shapelets`(masked_image, moments, order, ...)
`get_x_array`(self)
`get_y_array`(self)

Attributes Documentation

any_flags_set#

bad_pixel_in_center#

center#

center_out_of_bounds#

flux#

shape#

singular_second_moments#

spans#

too_many_bad_pixels#

variance#

Methods Documentation

static compute(spans: lsst.afw.geom.SpanSet, masked_image: lsst.afw.image._maskedImage.MaskedImageF, bad_bitmask: SupportsInt | SupportsIndex, bad_pixel_max_fraction: SupportsFloat | SupportsIndex, bad_pixel_exclusion_radius: SupportsFloat | SupportsIndex) → lsst.meas.algorithms.SpanSetMoments#

static fit_shapelets(masked_image: lsst.afw.image._maskedImage.MaskedImageF, moments: collections.abc.Sequence[lsst.meas.algorithms.SpanSetMoments], order: SupportsInt | SupportsIndex, scale: SupportsFloat | SupportsIndex) → lsst::shapelet::ShapeletFunction#

get_x_array(self: lsst.meas.algorithms.SpanSetMoments) → ndarray::Array<float, 1, 1>#

get_y_array(self: lsst.meas.algorithms.SpanSetMoments) → ndarray::Array<float, 1, 1>#