probabilistic_model.utils

probabilistic_model.utils#

A defaultdict that returns the default value when the key is missing and does not add the key to the dict.

`simple_interval_as_array`(→ numpy.ndarray)	Convert a simple interval to a numpy array.
`interval_as_array`(→ numpy.ndarray)	Convert an interval to a numpy array.
`timeit`(func)	Decorator to measure the time a function takes to execute.
`timeit_print`(func)
`neighbouring_points`(→ numpy.array)	Embed the point in an array with the next left and next right point.

probabilistic_model.utils.simple_interval_as_array(interval: random_events.interval.SimpleInterval) → numpy.ndarray#: Convert a simple interval to a numpy array. :param interval: The interval :return: [lower, upper] as numpy array

probabilistic_model.utils.interval_as_array(interval: random_events.interval.Interval) → numpy.ndarray#: Convert an interval to a numpy array. The resulting array has shape (n, 2) where n is the number of simple intervals in the interval. The first column contains the lower bounds and the second column the upper bounds of the simple intervals. :param interval: The interval :return: as numpy array

class probabilistic_model.utils.MissingDict#

Bases: collections.defaultdict

A defaultdict that returns the default value when the key is missing and does not add the key to the dict.

probabilistic_model.utils.timeit(func)#: Decorator to measure the time a function takes to execute.

probabilistic_model.utils.neighbouring_points(point: float) → numpy.array#

Embed the point in an array with the next left and next right point.