def from_labels(cls, labels_true, labels_pred, is_class_pos=num2bool):
"""Instantiates class from arrays of classes and cluster sizes
Parameters
----------
labels_true : array, shape = [n_samples]
Class labels. If binary, 'is_class_pos' is optional
labels_pred : array, shape = [n_samples]
Cluster labels to evaluate
is_class_pos: label_true -> Bool
Boolean predicate used to binarize true (class) labels
"""
clusters = labels_to_clusters(labels_true, labels_pred)
return cls.from_clusters(clusters, is_class_pos=is_class_pos)
def from_labels(cls, labels_true, labels_pred, is_class_pos=num2bool):
"""Instantiates class from arrays of classes and cluster sizes
Parameters
----------
labels_true : array, shape = [n_samples]
Class labels. If binary, 'is_class_pos' is optional
labels_pred : array, shape = [n_samples]
Cluster labels to evaluate
is_class_pos: label_true -> Bool
Boolean predicate used to binarize true (class) labels
"""
clusters = labels_to_clusters(labels_true, labels_pred)
return cls.from_clusters(clusters, is_class_pos=is_class_pos)
def show_cluster(self, idx, inverse=False):
grid = self.grid
a, b = (1, 0) if inverse else (0, 1)
return labels_to_clusters(grid[a][idx], grid[b][idx])
def show_cluster(self, idx, inverse=False):
grid = self.grid
a, b = (1, 0) if inverse else (0, 1)
return labels_to_clusters(grid[a][idx], grid[b][idx])
