gemseo.uncertainty.distributions.openturns.log_normal module#

The OpenTURNS-based log-normal distribution.

class OTLogNormalDistribution(mu=1.0, sigma=1.0, location=0.0, set_log=False, transformation='', lower_bound=None, upper_bound=None, threshold=0.5)[source]#

Bases: OTDistribution

The OpenTURNS-based log-normal distribution.

Examples

>>> from gemseo.uncertainty.distributions.openturns.distribution import (
...     OTDistribution,
... )
>>> distribution = OTDistribution("Exponential", (3, 2))
>>> print(distribution)
Exponential(3, 2)

Initialize self. See help(type(self)) for accurate signature.

Parameters:
  • mu (float) --

    Either the mean of the log-normal random variable or that of its logarithm when set_log is True.

    By default it is set to 1.0.

  • sigma (float) --

    Either the standard deviation of the log-normal random variable or that of its logarithm when set_log is True.

    By default it is set to 1.0.

  • location (float) --

    The location of the log-normal random variable.

    By default it is set to 0.0.

  • set_log (bool) --

    Whether mu and sigma apply to the logarithm of the log-normal random variable. Otherwise, mu and sigma apply to the log-normal random variable directly.

    By default it is set to False.

  • transformation (str) --

    A transformation applied to the random variable, e.g. \(\sin(x)\). If empty, no transformation.

    By default it is set to "".

  • lower_bound (float | None) -- A lower bound to truncate the probability distribution. If None, no lower truncation.

  • upper_bound (float | None) -- An upper bound to truncate the probability distribution. If None, no upper truncation.

  • threshold (float) --

    A threshold in [0,1] (see OpenTURNS documentation).

    By default it is set to 0.5.