climate.spearman¶
Provides classes for generating and analyzing complex climate networks.
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class
pyunicorn.climate.spearman.
SpearmanClimateNetwork
(data, threshold=None, link_density=None, non_local=False, node_weight_type='surface', winter_only=True, silence_level=0)[source]¶ Bases:
pyunicorn.climate.tsonis.TsonisClimateNetwork
Encapsulate a Spearman climate network.
The Spearman climate network is constructed from the Spearman rank order correlation matrix (Spearman’s rho). Spearman’s rho is more robust with respect to ouliers and non-gaussian data distributions than the Pearson correlation coefficient used in
TsonisClimateNetwork
.Hence, Spearman climate networks are undirected due to the symmetry of the Spearman’s rho matrix.
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__init__
(data, threshold=None, link_density=None, non_local=False, node_weight_type='surface', winter_only=True, silence_level=0)[source]¶ Initialize an instance of
SpearmanClimateNetwork
.Note
Either threshold OR link_density have to be given!
- Possible choices for
node_weight_type
: - None (constant unit weights)
- “surface” (cos lat)
- “irrigation” (cos**2 lat)
Parameters: - data (
ClimateData
) – The climate data used for network construction. - threshold (float) – The threshold of similarity measure, above which two nodes are linked in the network.
- link_density (float) – The networks’s desired link density.
- non_local (bool) – Determines, whether links between spatially close nodes should be suppressed.
- node_weight_type (str) – The type of geographical node weight to be used.
- winter_only (bool) – Determines, whether only data points from the winter months (December, January and February) should be used for analysis. Possibly, this further suppresses the annual cycle in the time series.
- silence_level (int) – The inverse level of verbosity of the object.
- Possible choices for
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_calculate_correlation
(anomaly)[source]¶ Return Spearman’s rho matrix at zero lag.
Parameters: anomaly (2D Numpy array (time, index)) – the anomaly time series from to calculate the correlation matrix at zero lag. Return type: 2D Numpy array (index, index) Returns: the Spearman’s rho matrix at zero lag.
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