def boundary_similarity(*args, **kwargs): ''' Boundary Similarity (B). ''' return __fnc_metric__(__boundary_similarity__, args, kwargs, SIMILARITY_METRIC_DEFAULTS)
def boundary_statistics(*args, **kwargs): default_kwargs = dict(SIMILARITY_METRIC_DEFAULTS) del default_kwargs['one_minus'] del default_kwargs['return_parts'] return __fnc_metric__(__boundary_statistics__, args, kwargs, default_kwargs)
def pk(*args, **kwargs): return __fnc_metric__(__pk__, args, kwargs, WINDOW_METRIC_DEFAULTS)
def boundary_confusion_matrix(*args, **kwargs): return __fnc_metric__(__boundary_confusion_matrix__, args, kwargs, SIMILARITY_METRIC_DEFAULTS)
def window_diff(*args, **kwargs): return __fnc_metric__(__window_diff__, args, kwargs, WINDOWDIFF_METRIC_DEFAULTS)
def segmentation_similarity(*args, **kwargs): ''' Segmentation Similarity (S). ''' return __fnc_metric__(__segmentation_similarity__, args, kwargs, SIMILARITY_METRIC_DEFAULTS)