def compute(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None):
log.debug("Computing correlation for clusters {0:s}.".format(
str(list(clusters_selected))))
if len(clusters_selected) == 0:
return {}
if self.sm is None:
self.sm = SimilarityMatrix(features, masks)
correlations = self.sm.compute_matrix(clusters, clusters_selected)
return correlations
class SimilarityMatrixTask(QtCore.QObject):
correlationMatrixComputed = QtCore.pyqtSignal(np.ndarray, object,
np.ndarray, np.ndarray, object)
def __init__(self, parent=None):
super(SimilarityMatrixTask, self).__init__(parent)
self.sm = None
def compute(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None):
log.debug("Computing correlation for clusters {0:s}.".format(
str(list(clusters_selected))))
if len(clusters_selected) == 0:
return {}
if self.sm is None:
self.sm = SimilarityMatrix(features, masks)
correlations = self.sm.compute_matrix(clusters, clusters_selected)
return correlations
def compute_done(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None, _result=None):
correlations = _result
self.correlationMatrixComputed.emit(np.array(clusters_selected),
correlations,
get_array(clusters, copy=True),
get_array(cluster_groups, copy=True),
target_next)
class SimilarityMatrixTask(QtCore.QObject):
correlationMatrixComputed = QtCore.pyqtSignal(np.ndarray, object,
np.ndarray, np.ndarray, object)
def __init__(self, parent=None):
super(SimilarityMatrixTask, self).__init__(parent)
self.sm = None
def compute(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None):
log.debug("Computing correlation for clusters {0:s}.".format(
str(list(clusters_selected))))
if len(clusters_selected) == 0:
return {}
if self.sm is None:
self.sm = SimilarityMatrix(features, masks)
correlations = self.sm.compute_matrix(clusters, clusters_selected)
return correlations
def compute_done(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None, _result=None):
correlations = _result
self.correlationMatrixComputed.emit(np.array(clusters_selected),
correlations,
get_array(clusters, copy=True),
get_array(cluster_groups, copy=True),
target_next)
def compute(self, features, clusters,
cluster_groups, masks, clusters_selected, target_next=None,
similarity_measure=None):
log.debug("Computing correlation for clusters {0:s}.".format(
str(list(clusters_selected))))
if len(clusters_selected) == 0:
return {}
if self.sm is None:
self.sm = SimilarityMatrix(features, masks)
correlations = self.sm.compute_matrix(clusters, clusters_selected)
return correlations