kernels.ccdclip

kernels.ccdclip(
    arr,
    *,
    mask=None,
    sigma=(3.0, 3.0),
    maxiters=5,
    ddof=0,
    nkeep=1,
    maxrej=None,
    cenfunc='median',
    clip_cen=None,
    revert_on_nkeep=True,
    rdnoise=0.0,
    gain=1.0,
    snoise=0.0,
    scale_ref=1.0,
    zero_ref=0.0,
    grow=None,
    validate=True,
)

CCD noise-model clipping.

Parameters

arr : (ndarray, shape(N, *spatial))

Image stack. Accepted dtypes are uint8, uint16, int16, int32, float32, and float64. Integer inputs are promoted to the package’s floating workspace when validate is True. Inputs with more than 3 dimensions are flattened internally; output shapes match the trailing spatial dimensions of the input.

mask : ndarray of bool = None

Input mask; True means already masked. Must have the same shape as arr before any internal flattening.

sigma : float or tuple of float = (3.0, 3.0)

User-supplied clipping multiplier, not the measured data spread itself. Values are clipped when their residual from the clipping center exceeds sigma * spread. A scalar applies the same multiplier to both tails; a 2-tuple (sigma_lower, sigma_upper) clips asymmetrically. Thresholds must be finite and non-negative.

maxiters : int = 5

Maximum number of clipping iterations per pixel.

ddof : int = 0

Delta degrees of freedom for the per-pixel spread estimator.

nkeep : int = 1

Minimum number of unmasked values to preserve at each pixel. An iteration that would drop below this count is reverted in full. The default, 1, prevents clipping from rejecting every finite sample in a per-output stack. Set 0 only when all samples may be rejected.

maxrej : int or None = None

Maximum number of values that may be rejected at each pixel. None means no limit.

cenfunc : ('median', 'lmedian', 'mean') = "median"

Center estimator used each iteration. lmedian accepts the alias lmed and uses the lower of the two middle samples for even valid counts.

clip_cen : ('median', 'lmedian', 'mean') = "median"

Center used when computing the spread for iterative rejection. None uses the same center as cenfunc; lmedian also accepts lmed.

revert_on_nkeep : bool = True

If True, an iteration that would leave fewer than nkeep usable samples at a pixel is reverted in full for that pixel. Input masks, threshold masks, and non-finite samples remain excluded. The default is True. If False, clipping is strict and may leave fewer than nkeep samples.

rdnoise : float = 0.0

Read noise in electrons.

snoise : float = 0.0

Sky-noise coefficient. Adds a Poisson-like contribution scaled by the local count level.

scale_ref : float = 1.0

Reference scale factor. Typically the inverse of the exposure-time normalization applied during reduction.

zero_ref : float = 0.0

Reference zero-point offset. Accounts for a known DC bias that shifts the effective noise level.

grow : float or None = None

Optional radius in pixels used to grow mask_rej spatially after rejection. Axis 0 is the stack axis and is never grown across. None disables growth and skips the extra calculation.

validate : bool = True

If True, check dimensionality and normalize dtype/contiguity before entering the Rust kernel. If False, callers must provide inputs that satisfy the compiled kernel assumptions.

Returns

mask_rej : ndarray of bool, shape (N, *spatial)

True where a value was rejected by this kernel. mask_rej.sum(axis=0) is the per-output rejected count.

std : (ndarray, shape(*spatial) or None)

Per-pixel spread used by sigma/CCD clipping. None for rejection algorithms without a spread diagnostic.

low : (ndarray, shape(*spatial))

Lower retained-value bound. Bounds are inclusive: values equal to low are retained.

upp : (ndarray, shape(*spatial))

Upper retained-value bound. Bounds are inclusive: values equal to upp are retained.

nit : ndarray of uint8, shape (*spatial)

Iteration-count map.

output_flags : ndarray of uint8, shape (*spatial)

Bit-coded status. 0 means normal completion; bit 1 means at least one pre-masked sample at this output element; bit 16 means grow added at least one rejected sample at this output element. Iterative kernels also use bit 2 for maxiters, bit 4 for nkeep, and bit 8 for maxrej. Bits are OR-ed. output_flags is a per-output diagnostic; use mask_rej.sum(axis=0) to count samples rejected by this step.

Notes

The kernel evaluates CCD rejection on gain-corrected scratch values (electrons). The per-pixel noise threshold is approximately::

sqrt((1 + snoise) * abs(noise_center + zero_ref) * scale_ref + rdnoise**2)