pyesmda.distances_to_weights_beta_cumulative#

pyesmda.distances_to_weights_beta_cumulative(distances: ndarray[tuple[Any, ...], dtype[float64]], beta: float = 3, scaling_factor: float = 1.0) → ndarray[tuple[Any, ...], dtype[float64]][source]#

Transform the distances into weights between 0 and 1 with a beta function.

\[1 - \dfrac{1}{1 + \left(\dfrac{d}{s - d}\right)^{-\beta}}\]
Parameters:

  • distances (NDArrayFloat) – Input array of distances.

  • beta (float, optional) – Shape factor. The smalest beta, the slower the variation, the higher beta the sharpest the transition (tends to a dirac function). Must be strictly positive. The default is 3.

  • scaling_factor (float, optional) – The scaling factor. At 0, the function equals 1.0, at half the scaling factor, it equals 0.5, and at the scaling factor, is equals zero. The default is 1.0.

Returns:

Array of same dimension as input array.

Return type:

NDArrayFloat.