pysteps.utils.cleansing.decluster#
- pysteps.utils.cleansing.decluster(coord, input_array, scale, min_samples=1, verbose=False)#
Decluster a set of sparse data points by aggregating, that is, taking the median value of all values lying within a certain distance (i.e., a cluster).
- Parameters:
coord (array_like) – Array of shape (n, d) containing the coordinates of the input data into a space of d dimensions.
input_array (array_like) – Array of shape (n) or (n, m), where n is the number of samples and m the number of variables. All values in
input_array
are required to have finite values.scale (float or array_like) – The
scale
parameter in the same units ofcoord
. It can be a scalar or an array_like of shape (d). Data points within the declusteringscale
are aggregated.min_samples (int, optional) – The minimum number of samples for computing the median within a given cluster.
verbose (bool, optional) – Print out information.
- Returns:
out – A two-element tuple (
out_coord
,output_array
) containing the declustered coordinates (l, d) and input array (l, m), where l is the new number of samples with l <= n.- Return type:
tuple of ndarrays