gemseo.uncertainty.distributions.scipy.joint module#

The SciPy-based joint probability distribution.

SPJointDistribution is a BaseJointDistribution based on the SciPy library.

Warning

For the moment, there is no copula that can be used with SPJointDistribution; if you want to introduce dependency between random variables, please consider OTJointDistribution.

class SPJointDistribution(distributions, copula=None)[source]#

Bases: BaseJointDistribution

The SciPy-based joint probability distribution.

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

Parameters:

  • distributions (Sequence[SPDistribution]) -- The marginal distributions.

  • copula (None) -- A copula distribution defining the dependency structure between random variables; if None, consider an independent copula.

Raises:

NotImplementedError -- When the copula is not None.

compute_cdf(value)[source]#

Evaluate the cumulative density function (CDF).

Parameters:

value (Iterable[float]) -- The value of the random variable for which to evaluate the CDF.

Returns:

The value of the CDF.

Return type:

RealArray

compute_inverse_cdf(value)[source]#

Evaluate the inverse cumulative density function (ICDF).

Parameters:

value (Iterable[float]) -- The probability for which to evaluate the ICDF.

Returns:

The value of the ICDF.

Return type:

RealArray