Temporal Clustering¶

TemporalClustering models communities that evolves as time goes by.

Each temporal community clustering observation is a Clustering object, thus it inherits all properties of its specific concrete class.

Overview¶

class TemporalClustering¶

add_clustering(clustering: object, time: object)¶

Add to the Temporal Clustering the communities observed at a given time

Parameters:	clustering – a Clustering object time – time of observation

add_matching(matching: list)¶

Add a precomputed matching of the communities.

Parameters:	matching – a list of tuples [(Ti_Ca, Tj_Cb, score), … ]. Community names needs to satisfy the pattern {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.

clustering_stability_trend(method: Callable[[object, object], float]) → list¶

Returns the trend for community stability. The stability index is computed for temporally adjacent clustering pairs.

Parameters:	method – a comparison score taking as input two Clustering objects (e.g., NMI, NF1, ARI…)
Returns:	a list of floats

community_matching(method: Callable[[set, set], float], two_sided: bool = False) → list¶

Reconstruct community matches across adjacent observations using a provided similarity function.

Parameters:	method – a set similarity function with co-domain in [0,1] (e.g., Jaccard) two_sided – boolean. Whether the match has to be applied only from the past to the future (False, default) or even from the future to the past (True)
Returns:	a list of tuples [(Ti_Ca, Tj_Cb, score), … ]. Community names are assigned following the pattern {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.

get_clustering_at(time: object) → object¶

Returns the clustering observed at a given time

Parameters:	time – the time of observation
Returns:	a Clustering object

get_community(cid: str) → list¶

Returns the nodes within a given temporal community

Parameters:	cid – community id of the form {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.
Returns:	list of nodes within cid

get_explicit_community_match() → list¶

Return an explicit matching of computed communities (if it exists)

Returns:	a list of tuple [(Ti_Ca, Tj_Cb, score), … ]. Community names are assigned following the pattern {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.

get_observation_ids() → list¶: Returns the list of temporal ids for the available clusterings :return: a list of temporal ids

has_explicit_match() → bool¶

Checks if the algorithm provided an explicit match of temporal communities

Returns:	a list of tuple [(Ti_Ca, Tj_Cb, score), … ]. Community names are assigned following the pattern {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.

lifecycle_polytree(method: Callable[[set, set], float] = None, two_sided: bool = False) → <Mock id='140350750723280'>¶

Reconstruct the poly-tree representing communities lifecycles using a provided similarity function.

Parameters:	method – a set similarity function with co-domain in [0,1] (e.g., Jaccard) two_sided – boolean. Whether the match has to be applied only from the past to the future (False, default) or even from the future to the past (True)
Returns:	a networkx DiGraph object. Nodes represent communities, their ids are assigned following the pattern {tid}_{cid}, where tid is the time of observation and cid is the position of the community within the Clustering object.

to_json()¶

Generate a JSON representation of the TemporalClustering object

Returns:	a JSON formatted string representing the object

`TemporalClustering.to_json`()	Generate a JSON representation of the TemporalClustering object
`TemporalClustering.get_observation_ids`()	Returns the list of temporal ids for the available clusterings :return: a list of temporal ids
`TemporalClustering.get_clustering_at`(time)	Returns the clustering observed at a given time
`TemporalClustering.add_clustering`(…)	Add to the Temporal Clustering the communities observed at a given time
`TemporalClustering.get_community`(cid)	Returns the nodes within a given temporal community

TemporalClustering.clustering_stability_trend(…) Returns the trend for community stability.

`TemporalClustering.community_matching`(…)	Reconstruct community matches across adjacent observations using a provided similarity function.
`TemporalClustering.lifecycle_polytree`(…)	Reconstruct the poly-tree representing communities lifecycles using a provided similarity function.