chaospy.Distribution.inv

Distribution.inv(q_data, max_iterations=100, tollerance=1e-05)

Inverse Rosenblatt transformation.

If possible the transformation is done analytically. If not possible, transformation is approximated using an algorithm that alternates between Newton-Raphson and binary search.

Args:

q_data (numpy.ndarray):

Probabilities to be inverse. If any values are outside [0, 1], error will be raised. q_data.shape must be compatible with distribution shape.

max_iterations (int):

If approximation is used, this sets the maximum number of allowed iterations in the Newton-Raphson algorithm.

tollerance (float):

If approximation is used, this set the error tolerance level required to define a sample as converged.

Returns:

(numpy.ndarray):

Inverted probability values where out.shape == q_data.shape.