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
isTrue
.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
isTrue
.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
andsigma
apply to the logarithm of the log-normal random variable. Otherwise,mu
andsigma
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.