normal module¶
The SciPy-based normal distribution.
- class gemseo.uncertainty.distributions.scipy.normal.SPNormalDistribution(variable='x', mu=0.0, sigma=1.0, dimension=1)[source]
Bases:
SPDistribution
The SciPy-based normal distribution.
Examples
>>> from gemseo.uncertainty.distributions.scipy.normal import ( ... SPNormalDistribution, ... ) >>> distribution = SPNormalDistribution("x", -1, 2) >>> print(distribution) norm(mu=-1, sigma=2)
- Parameters:
variable (str) –
The name of the random variable.
By default it is set to “x”.
mu (float) –
The mean of the normal random variable.
By default it is set to 0.0.
sigma (float) –
The standard deviation of the normal random variable.
By default it is set to 1.0.
dimension (int) –
The dimension of the random variable. If greater than 1, the probability distribution is applied to all components of the random variable under the hypothesis that these components are stochastically independent. To be removed in a future version; use a
ComposedDistribution
instead.By default it is set to 1.
- dimension: int
The number of dimensions of the random variable.
- distribution: type
The probability distribution of the random variable.
- distribution_name: str
The name of the probability distribution.
- math_lower_bound: ndarray
The mathematical lower bound of the random variable.
- math_upper_bound: ndarray
The mathematical upper bound of the random variable.
- num_lower_bound: ndarray
The numerical lower bound of the random variable.
- num_upper_bound: ndarray
The numerical upper bound of the random variable.
- standard_parameters: dict[str, str] | None
The standard representation of the parameters of the distribution, used for its string representation.
- transformation: str
The transformation applied to the random variable, e.g. ‘sin(x)’.
- variable_name: str
The name of the random variable.