climate.havlin¶
Provides classes for generating and analyzing complex climate networks.
- class pyunicorn.climate.havlin.HavlinClimateNetwork(data, max_delay, threshold=None, link_density=None, non_local=False, node_weight_type='surface', silence_level=0)[source]¶
Bases:
ClimateNetwork
Encapsulates a Havlin climate network.
The similarity matrix associated with a Havlin climate network is the maximum-lag correlation matrix with each entry normalized by the cross-correlation function’s standard deviation.
Havlin climate networks are undirected so far.
Havlin climate networks were studied for daily data in [Yamasaki2008], [Gozolchiani2008], [Yamasaki2009].
Note
So far, the cross-correlation functions are estimated using convolution in Fourier space (FFT). This may not be reliable for larger delays.
- __cache_state__() Tuple[Hashable, ...] [source]¶
Hashable tuple of mutable object attributes, which will determine the instance identity for ALL cached method lookups in this class, in addition to the built-in object id(). Returning an empty tuple amounts to declaring the object immutable in general. Mutable dependencies that are specific to a method should instead be declared via @Cached.method(attrs=(…)).
NOTE: A subclass is responsible for the consistency and cost of this state descriptor. For example, hashing a large array attribute may be circumvented by declaring it as a property, with a custom setter method that increments a dedicated mutation counter.
- __init__(data, max_delay, threshold=None, link_density=None, non_local=False, node_weight_type='surface', silence_level=0)[source]¶
Initialize an instance of HavlinClimateNetwork.
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.
max_delay (int) – Maximum delay for cross-correlation functions.
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.
silence_level (int) – The inverse level of verbosity of the object.
- Possible choices for
- __rec_cache_state__() Tuple[object, ...] [source]¶
Similar to __cache_state__(), but lists attributes which are themselves instances of Cached. Empty by default.
- _calculate_correlation_strength(anomaly, max_delay, gamma=0.2)[source]¶
Calculate correlation strength and maximum lag matrices.
Follows the method described in [Yamasaki2008].
Also returns the time lag at maximum correlation for each link.
- Parameters:
anomaly (2D array [time, index]) – The anomaly data for network construction.
max_delay (int) – The maximum delay for cross-correlation functions.
gamma (float) – The width of decay region in cosine shaped window used for FFT cross-correlation estimation.
- Return type:
tuple of two 2D arrays [index, index]
- Returns:
the correlation strength and maximum lag matrices.
- _set_max_delay(max_delay)[source]¶
Set the maximum lag time used for cross-correlation estimation.
- Parameters:
max_delay (int) – The maximum delay for cross-correlation functions.
- correlation_lag()[source]¶
Return the lag at maximum cross-correlation matrix.
- Return type:
2D array [index, index]
- Returns:
the lag at maximum cross-correlation matrix.
- correlation_lag_weighted_average_path_length()[source]¶
Return correlation lag weighted average path length.
- Return float:
the correlation lag weighted average path length.
- correlation_lag_weighted_closeness()[source]¶
Return correlation lag weighted closeness.
- Return type:
1D array [index]
- Returns:
the correlation lag weighted closeness sequence.
- correlation_strength()[source]¶
Return the correlation strength matrix.
- Return type:
2D array [index, index]
- Returns:
the correlation strength matrix.
- correlation_strength_weighted_average_path_length()[source]¶
Return correlation strength weighted average path length.
- Return float:
the correlation strength weighted average path length.
- correlation_strength_weighted_closeness()[source]¶
Return correlation strength weighted closeness.
- Return type:
1D array [index]
- Returns:
the correlation strength weighted closeness sequence.
- data: ClimateData¶
The climate data used for network construction.
- get_max_delay()[source]¶
Return the maximum delay used for cross-correlation estimation.
- Return float:
the maximum delay used for cross-correlation estimation.
- local_correlation_lag_weighted_vulnerability()[source]¶
Return correlation lag weighted vulnerability.
- Return type:
1D array [index]
- Returns:
the correlation lag weighted vulnerability sequence.