focal.focal_majority

focal.focal_majority(a: Array, *, window: int | tuple[int, ...] | list[int] | ndarray[tuple[int, ...], bool] | Window, fraction_accepted: float = 0.7, verbose: bool = False, reduce: bool = False, chunks: int | tuple[int, int] | None = None, majority_mode: MajorityMode = MajorityMode.NAN, out: Array | None = None) → ndarray[tuple[int, int], float64]

Focal majority.

Parameters:

• a (Array) – Input array. Must be two-dimensional.

• window (int, array-like, or Window) –

  Window applied over the input array. It can be:

  • An integer (interpreted as a square window),

  • A sequence of integers (interpreted as a rectangular window),

  • A boolean array,

  • Or a pyspatialstats.windows.Window object.

• fraction_accepted (float, optional) –

  Fraction of valid (non-NaN) cells per window required for the statistic to be computed.

  • 0: all windows with at least 1 valid value are used

  • 1: only fully valid windows are used

  • Between 0 and 1: minimum acceptable fraction

  Default is 0.7.

• verbose (bool, optional) – If True, print progress message with timing. Default is False.

• reduce (bool, optional) – If True, each pixel is used exactly once without overlapping windows. The resulting array will have shape a_shape / window_shape. Default is False.

• chunks (int or tuple of int, optional) – Shape of chunks to split the array into. If None, the array is not split into chunks, which is the default.

• majority_mode (MajorityMode, optional) –

  Strategy for resolving ties when multiple values occur with equal highest frequency:

  • NAN: assign NaN when there’s a tie (default)

  • ASCENDING: assign the lowest tied value

  • DESCENDING: assign the highest tied value

  Default is MajorityMode.NAN.

• out (ndarray, optional) – Output array.

Return type:

ndarray