def make_cluster_column(ATelement,Elementclusters): cluster = [] for i in ATelement.T.index: included=False for j in Elementclusters.keys(): if i in Elementclusters[j]: cluster.append(j) included=True if not included: cluster.append(None) return cluster
def clusters_at(tree, sampled, cutpoint):
""" returns a list of lists of clusters occuring after cutpoint """
branches = branches_sampled(tree, sampled)
branches = list(branches)
branches.sort(key=lambda x: x.i_time)
clusters = []
for branch in branches:
if branch.i_time > cutpoint:
children = all_children_of(tree, branch)
if branch in sampled:
children.append(branch)
cluster = []
for child in children:
if child in sampled:
cluster.append(child)
sampled.remove(child)
clusters.append(cluster)
return clusters
def clusters_at(tree, sampled, cutpoint): """ returns a list of lists of clusters occuring after cutpoint """ branches = branches_sampled(tree, sampled) branches = list(branches) branches.sort(key=lambda x: x.i_time) clusters = [] for branch in branches: if branch.i_time > cutpoint: children = all_children_of(tree, branch) if branch in sampled: children.append(branch) cluster = [] for child in children: if child in sampled: cluster.append(child) sampled.remove(child) clusters.append(cluster) return clusters
def brown_clusters(tree, sampled, s_time):
""" returns a list of lists of clusters in tree
according to the standard in Brown et al. """
cbound = s_time - 12
clusterlist = []
clustered = []
bpoints = branches_sampled(tree, sampled)
for bp in sorted(bpoints, key=lambda x: x.i_time):
if bp.i_time >= cbound:
cluster = []
childs = all_children_of(tree, bp)
print childs
for cbp in childs:
if cbp in sampled and cbp not in clustered:
cluster.append(cbp)
clustered.append(cbp)
clusterlist.append(cluster)
print len(clustered), clustered
return clusterlist
def brown_clusters(tree, sampled, s_time): """ returns a list of lists of clusters in tree according to the standard in Brown et al. """ cbound = s_time - 12 clusterlist = [] clustered = [] bpoints = branches_sampled(tree, sampled) for bp in sorted(bpoints, key=lambda x: x.i_time): if bp.i_time >= cbound: cluster = [] childs = all_children_of(tree, bp) print childs for cbp in childs: if cbp in sampled and cbp not in clustered: cluster.append(cbp) clustered.append(cbp) clusterlist.append(cluster) print len(clustered), clustered return clusterlist
def get_cluster(id, labels):
cluster = []
for i in range(len(labels)):
if labels[i] == id:
cluster.append(i)
return cluster
