pysteps.utils.interpolate.idwinterp2d¶

pysteps.utils.interpolate.idwinterp2d(xy_coord, values, xgrid, ygrid, power=0.5, k=20, dist_offset=0.5, **kwargs)¶

Inverse distance weighting interpolation of a sparse (multivariate) array.

Parameters

xy_coord: ndarray_: Array of shape (n, 2) containing the coordinates of the data points in a 2-dimensional space.
values: ndarray_: Array of shape (n) or (n, m) containing the values of the data points, where n is the number of data points and m the number of co-located variables. All elements in values are required to be finite.
xgrid, ygrid: ndarray_: 1-D arrays representing the coordinates of the 2-D output grid.
power: positive float, optional: The power parameter used to compute the distance weights as weight = distance ** (-power).
k: positive int or None, optional: The number of nearest neighbours used for each target location. If set to None, it interpolates using all the data points at once.
dist_offset: float, optional: A small, positive constant that is added to distances to avoid zero values. It has units of pixels.

Returns

output_array: ndarray: The interpolated field(s) having shape (ygrid.size, xgrid.size) or (m, ygrid.size, xgrid.size).

Other Parameters

nchunks: int, optional: Split and process the destination grid in nchunks. Useful for large grids to limit the memory footprint.