cluster

A cluster is an ordered set of hits related to a model which satisfy the model distance constraints.

cluster

class macsypy.cluster.Cluster(hits, model, hit_wheights)

Handle hits relative to a model which collocates

__contains__(v_hit)

Parameters

v_hit (macsypy.hit.ValidHit object) – The hit to test

Returns

True if the hit is in the cluster hits, False otherwise

__init__(hits, model, hit_wheights)

Parameters

• hits ([ macsypy.hit.Hit | macsypy.hit.ValidHit, … ]) – the hits constituting this cluster

• model (macsypy.model.Model) – the model associated to this cluster

__str__()

Returns

a string representation of this cluster

__weakref__

list of weak references to the object (if defined)

_check_replicon_consistency()

Raise

MacsypyError if all hits of a cluster are NOT related to the same replicon

fulfilled_function(gene)

Parameters

gene (macsypy.gene.Gene object) – The gene which must be tested.

Returns

True if the cluster contains one hit which fulfill the function corresponding to the gene (the gene hitself or an exchageable)

merge(cluster, before=False)

merge the cluster in this one. (do it in place)

Parameters

• cluster (macsypy.cluster.Cluster object) –

• before (bool) – If False the hits of the cluster will be add at the end of this one, Otherwise the cluster hits will be inserted before the hits of this one.

Returns

None

Raises

MacsypyError – if the two clusters have not the same model

macsypy.cluster.build_clusters(hits, rep_info, model, hit_weights)

From a list of filtered hits, and replicon information (topology, length), build all lists of hits that satisfied the constraints:

• max_gene_inter_space

• loner

• multi_system

If Yes create a cluster A cluster contains at least two hits separated by less or equal than max_gene_inter_space Except for loner genes which are allowed to be alone in a cluster

Parameters

• hits (list of macsypy.hit.Hit objects) – list of filtered hits

• rep_info (macsypy.Indexes.RepliconInfo object) – the replicon to analyse

• model (macsypy.model.Model object) – the model to study

Returns

list of clusters

Return type

List of Cluster objects

macsypy.cluster.filter_loners(cluster, loners)

filter loners to remove those which are already in the cluster

Parameters

• cluster (macsypy.cluster.Cluster object) – The cluster

• loners (list of cluster [Cluster, ..]) – the clusters constituted by one loner to filter

Returns

list of loners which are not already in the cluster

Return type

[Clsuter, ..]

macsypy.cluster.get_loners(hits, model, hit_weights)

Create a list of Clusters each cluster is build with one hit matching a loner

Parameters

• hits – The list of hits to filter

• model (macsypy.model.Model object) – the model which will used to build the clusters

Returns

The list of cluster which each element is build at least with one loner

Return type

[Cluster, ..]