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])