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 of coord. It can be a scalar or an array_like of shape (d). Data points within the declustering scale 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: tuple of ndarrays: 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.