_fit

This module provides a set of types that can be used as building blocks in the aggregation of a Clustering object.

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Fitter

class commonnn._fit.FitterExtInterface
fit(self, Bundle bundle, **kwargs)
make_parameters(self, **kwargs) → Type['ClusterParameters']
class commonnn._fit.FitterExtCommonNNInterface
fit(self, Bundle bundle, **kwargs) → float
get_fit_signature(self)
make_parameters(self, **kwargs) → Type['ClusterParameters']
class commonnn._fit.Fitter

Defines the fitter interface

abstract fit(self, Bundle bundle, **kwargs)

Generic clustering outer function

abstract make_parameters(self, **kwargs) → Type['ClusterParameters']

Create fitter specific cluster parameters

class commonnn._fit.FitterCommonNN

Defines the fitter interface

fit(self, Bundle bundle, *, purge=True, info=True, **kwargs) -> (float, Type['ClusterParameters'])
get_fit_signature(self)
make_parameters(self, similarity_offset=0, original=False, **kwargs) → Type['ClusterParameters']
class commonnn._fit.FitterExtCommonNNBFS

Concrete implementation of the fitter interface

Realises a CommonNN clustering using a breadth-first-search

Parameters:

  • neighbours_getter – Any extension type implementing the neighbours getter interface.

  • neighbours – Any extension type implementing the neighbours interface.

  • neighbour_neighbourss – Any extension type implementing the neighbours interface.

  • similarity_checker – Any extension type implementing the similarity checker interface.

  • queue – Any extension type implementing the queue interface. Used during the clustering procedure.

classmethod get_builder_kwargs(type cls)
class commonnn._fit.FitterCommonNNBFS(neighbours_getter: Type['NeighboursGetter'], neighbours: Type['Neighbours'], neighbour_neighbours: Type['Neighbours'], similarity_checker: Type['SimilarityChecker'], queue: Type['Queue'])

Concrete implementation of the fitter interface

Parameters:

  • neighbours_getter – Any object implementing the neighbours getter interface.

  • neighbours – Any object implementing the neighbours interface.

  • neighbour_neighbourss – Any object implementing the neighbours interface.

  • similarity_checker – Any object implementing the similarity checker interface.

  • queue – Any object implementing the queue interface.

classmethod get_builder_kwargs(cls)
class commonnn._fit.FitterCommonNNBFSDebug(neighbours_getter: Type['NeighboursGetter'], neighbours: Type['Neighbours'], neighbour_neighbours: Type['Neighbours'], similarity_checker: Type['SimilarityChecker'], queue: Type['Queue'], verbose=True, yielding=True)

Concrete implementation of the fitter interface

Yields/prints information during the clustering.

Parameters:

  • neighbours_getter – Any extension type implementing the neighbours getter interface.

  • neighbours – Any extension type implementing the neighbours interface.

  • neighbour_neighbourss – Any extension type implementing the neighbours interface.

  • similarity_checker – Any extension type implementing the similarity checker interface.

  • queue – Any extension type implementing the queue interface. Used during the clustering procedure.

classmethod get_builder_kwargs(cls)

Hierarchical fitter

class commonnn._fit.HierarchicalFitter

Defines the hierarchical fitter interface

abstract fit(self, Bundle bundle, *args, **kwargs)

Generic clustering

class commonnn._fit.HierarchicalFitterCommonNNMSTPrim(neighbours_getter: Type['NeighboursGetter'], neighbours: Type['Neighbours'], neighbour_neighbours: Type['Neighbours'], similarity_checker: Type['SimilarityChecker'], priority_queue: Type['PriorityQueue'], priority_queue_tree: Type['PriorityQueue'])

Concrete implementation of the hierarchical fitter interface

Builds a minimum spanning tree on the density estimate using Prim’s algorithm and creates a cluster hierarchy via single linkage clustering.

Note

This is still experimental.

fit(self, Bundle bundle, *, sort_by_size: bool = True, member_cutoff: int = None, max_clusters: int = None, info: bool = True, v: bool = True, **kwargs)
classmethod get_builder_kwargs(cls)
make_parameters(self, **kwargs) → Type['ClusterParameters']
class commonnn._fit.HierarchicalFitterRepeat(fitter: Type['Fitter'])
fit(self, Bundle bundle, radius_cutoffs, similarity_cutoffs, *, sort_by_size=True, member_cutoff=None, max_clusters=None, info=True, v=False, **kwargs)
classmethod get_builder_kwargs(cls)

Predictor

class commonnn._fit.Predictor

Defines the predictor interface

abstract make_parameters(self, **kwargs) → Type['ClusterParameters']

Create fitter specific cluster parameters

abstract predict(self, Bundle bundle, Bundle other, **kwargs)

Generic prediction

class commonnn._fit.PredictorCommonNN
get_fit_signature(self)
make_parameters(self, **kwargs) → Type['ClusterParameters']
predict(self, Bundle bundle, Bundle other, *, clusters=None, purge=True, info=True, **kwargs)
class commonnn._fit.PredictorCommonNNFirstmatch(neighbours_getter: Type['NeighboursGetter'], neighbours_getter_other: Type['NeighboursGetter'], neighbours: Type['Neighbours'], neighbour_neighbours: Type['Neighbours'], similarity_checker: Type['SimilarityChecker'])
classmethod get_builder_kwargs(cls)