huracanpy.assess.match#
- huracanpy.assess.match(tracksets, names=None, max_dist=300, mean_dist=None, min_overlap=0, consecutive_overlap=False, tracks1_is_ref=False, distance_method='haversine')[source]#
Match the provided track sets between them.
- Parameters:
tracksets (list[xarray.Dataset]) – list of track datasets to match together. Must be of length two or more.
names (list, optional) – list of track datasets names. Must be the same size as tracksets. The default is [‘1’,’2’, …].
max_dist (float, optional) – Threshold for maximum distance between two tracks. The default is 300.
mean_dist (float, optional) – Threshold for mean distance between two tracks, taken over all timesteps that include both tracks.
min_overlap (int, optional) – Minimum number of overlapping time steps for matching. The default is 0.
consecutive_overlap (bool, optional) – If min_overlap > 1, require that min_overlap points also need to be consective
tracks1_is_ref (bool, optional) – If True, treat the first set of tracks as the reference set. If one track matches multiple reference tracks, only keep the longest match
distance_method (str, optional) – The method to use to calculate distance between track points. One of “haversine”, “geod”
- Returns:
- Dataframe containing the matching tracks with
the id from corresponding datasets the number of matching time steps (if only two datasets provided) the distance between two tracks (if only two datasets provided)
- Return type: