def calculate(self, validation_name, cluster_name, source_name='parent'):
"""
Calls the function titled by validation_name on the data matrix set by source_name (default 'parent') and clustering solution by cluster_name
Appends to validation with key value equal to the validation_name+source_name+cluster_name
Returns
-------
output_name: str
The handle name for accessing validation results
"""
output_name = "%s_%s_%s" % (validation_name, source_name, cluster_name)
#check that the validation has not already been calcluated
if output_name in self.validation:
warnings.warn(
'Validation of type requested already exists and will not be added to validation dictionary',
UserWarning)
return
#CHECK that the source exists
if source_name not in self.dataObj.D:
raise ValueError(
"ERROR: the source you requested for validation does not exist by that name %s"
% (source_name))
if cluster_name not in self.cObj.labels:
raise ValueError(
"ERROR: the clustering solution you requested for validation does not exist by the name %s"
% (source_name))
FCN_DICT = self.validation_metrics_available()
if validation_name not in FCN_DICT:
raise ValueError(
"The validation metric you requested does not exist, currently the following are supported %s"
% (list(FCN_DICT.keys())))
v = val.validation(self.dataObj.D[source_name],
self.cObj.labels[cluster_name])
func = getattr(v, validation_name)
func()
self.validation[output_name] = v.validation
self.description[output_name] = v.description
self.source_name[output_name] = source_name
self.cluster_name[output_name] = cluster_name
return output_name
def validation_metrics_available(self):
""" Return all available validation metrics """
validation = val.validation(self.dataObj.D['parent'], [])
FCN_DICT = validation.validation_metrics_available()
return FCN_DICT