gemseo.uncertainty.distributions.scipy.log_normal module#
The SciPy-based log-normal distribution.
- class SPLogNormalDistribution(mu=1.0, sigma=1.0, location=0.0, set_log=False)[source]#
Bases:
SPDistribution
The SciPy-based log-normal distribution.
Examples
>>> from gemseo.uncertainty.distributions.scipy.distribution import ( ... SPDistribution, ... ) >>> distribution = SPDistribution("expon", {"loc": 3, "scale": 1 / 2.0}) >>> print(distribution) expon(loc=3, scale=0.5)
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.