def commit(self):
if len(self.selection):
cluster_ids = set()
column_ids = set()
for (ir, ic) in self.selection:
cluster_ids.add(ir)
column_ids.add(ic)
new_domain = Domain([
self.data.domain[self.columns.values[col]]
for col in column_ids
], self.data.domain.class_vars, self.data.domain.metas)
selected_data = Values([
FilterDiscrete(self.cluster_var, [self.clusters[ir]])
for ir in cluster_ids
],
conjunction=False)(self.data)
selected_data = selected_data.transform(new_domain)
annotated_data = create_annotated_table(
self.data.transform(new_domain),
np.where(np.in1d(self.data.ids, selected_data.ids, True)))
else:
selected_data = None
annotated_data = create_annotated_table(self.data, [])
if self.ca is not None and self._task is None:
table = self.ca.create_contingency_table()
else:
table = None
self.Outputs.selected_data.send(selected_data)
self.Outputs.annotated_data.send(annotated_data)
self.Outputs.contingency.send(table)
def commit(self):
if self.data is None:
self.Outputs.selected_data.send(None)
self.Outputs.annotated_data.send(None)
self.Outputs.contingency.send(None)
return
if len(self.selection_indices):
cluster_ids = set()
gene_ids = set()
for (ir, ic) in self.selection_indices:
if not self.transpose:
cluster_ids.add(ir)
gene_ids.add(ic)
else:
cluster_ids.add(ic)
gene_ids.add(ir)
columns = self.clusters if self.transpose else [str(x) for x in self.matrix.domain.attributes]
rows = self.clusters if not self.transpose else [str(x) for x in self.matrix.domain.attributes]
new_domain = Domain([self.data.domain[columns[i]] for i in gene_ids],
self.data.domain.class_vars,
self.data.domain.metas)
selected_data = Values([FilterDiscrete(self.cluster_var, [rows[i]])
for i in cluster_ids],
conjunction=False)(self.data)
selected_data = selected_data.transform(new_domain)
annotated_data = create_annotated_table(self.data,
np.where(np.in1d(self.data.ids, selected_data.ids, True)))
else:
selected_data = None
annotated_data = create_annotated_table(self.data, [])
clusters_values = list(set(self.clusters))
table = ClusterAnalysis.contingency_table(
self.matrix,
DiscreteVariable("Gene" if self.transpose else self.cluster_var.name, clusters_values),
[str(x) for x in self.matrix.domain.attributes],
[[clusters_values.index(c)] for c in self.clusters]
)
self.Outputs.selected_data.send(selected_data)
self.Outputs.annotated_data.send(annotated_data)
self.Outputs.contingency.send(table)
def commit(self):
if len(self.selection):
cluster_ids = set()
gene_ids = set()
for (ir, ic) in self.selection:
if not self.transpose:
cluster_ids.add(ir)
gene_ids.add(ic)
else:
cluster_ids.add(ic)
gene_ids.add(ir)
new_domain = Domain(
[self.data.domain[self.genes[i]] for i in gene_ids],
self.data.domain.class_vars, self.data.domain.metas)
selected_data = Values([
FilterDiscrete(self.cluster_var, [self.clusters[i]])
for i in cluster_ids
],
conjunction=False)(self.data)
selected_data = selected_data.transform(new_domain)
annotated_data = create_annotated_table(
self.data.transform(new_domain),
np.where(np.in1d(self.data.ids, selected_data.ids, True)))
else:
selected_data = None
annotated_data = create_annotated_table(self.data, [])
if self.matrix is not None:
table = ClusterAnalysis.contingency_table(
self.matrix,
DiscreteVariable(self.cluster_var.name,
np.array(self.clusters)),
np.array(self.genes)[self.gene_order],
self.cluster_order[..., np.newaxis])
else:
table = None
self.Outputs.selected_data.send(selected_data)
self.Outputs.annotated_data.send(annotated_data)
self.Outputs.contingency.send(table)
