apsum_rect_ann_exact

apsum_rect_ann_exact(
    data,
    x,
    y,
    w_in,
    h_in,
    w_out,
    h_out,
    theta_in=0.0,
    theta_out=None,
    *,
    mask=None,
    return_npix=True,
    validate=True,
)

Return exact rotated-rectangle-annulus aperture sums for one or many aperture centers.

Parameters

data : array_like

Two-dimensional image. For maximum performance with raw contiguous arrays, use import astroapers._rust as aapr and call the raw functions directly.

x, y : scalar or array_like

Aperture center coordinates in pixel units. Inputs are converted to contiguous float64 arrays. Shapes must match after numpy.atleast_1d. The return shape matches that broadcast-free input shape, so scalar inputs return one-element arrays.

w_in, h_in : float

Inner rectangle full width and height in pixels. w_in is measured along the inner rectangle’s local x axis, and h_in along its local y axis.

w_out, h_out : float

Outer rectangle full width and height in pixels. w_out is measured along the outer rectangle’s local x axis, and h_out along its local y axis. Each outer dimension must be no smaller than the corresponding inner dimension, and at least one outer dimension must be larger. At theta_out=0, the outer width axis is aligned with the image x axis and the outer height axis with the image y axis.

theta_in : float, optional = 0.0

Inner rectangle rotation angle in radians, measured counterclockwise from the positive image x axis to the inner rectangle’s local width axis.

theta_out : float or None, optional = None

Outer rectangle rotation angle in radians, measured counterclockwise from the positive image x axis to the outer rectangle’s local width axis. If None, uses theta_in.

mask : array_like of bool, optional = None

Boolean image mask with the same shape as data. True pixels are excluded from both the aperture sum and effective pixel count. Values are converted to boolean.

return_npix : bool, optional = True

If True, return (apsum, npix). If False, return only apsum.

Returns

apsum : ndarray

Sum of the unmasked data values multiplied by the aperture weights.

npix : ndarray

Effective in-frame pixel count, returned only when return_npix=True. This is the sum of aperture weights after image clipping and mask exclusion.

Notes

For more raw-call patterns, inspect astroapers.kernels; it is the Python layer that calls _rust internally. For matched inner and outer angles, this uses outer-minus-inner direct aperture summation. For split-angle annuli, it uses Rust-generated bbox-tight annulus weights and the same BoundingBox.apsum reduction.