openmc.stats.Discrete

class openmc.stats.Discrete(x, p)[source]

Distribution characterized by a probability mass function.

The Discrete distribution assigns probability values to discrete values of a random variable, rather than expressing the distribution as a continuous random variable.

Parameters:

x (Iterable of float) – Values of the random variable
p (Iterable of float) – Discrete probability for each value

Variables:

x (numpy.ndarray) – Values of the random variable
p (numpy.ndarray) – Discrete probability for each value

clip(tolerance: float = 1e-06, inplace: bool = False) → Discrete[source]

Remove low-importance points from discrete distribution.

Given a probability mass function \(p(x)\) with \(\{x_1, x_2, x_3, \dots\}\) the possible values of the random variable with corresponding probabilities \(\{p_1, p_2, p_3, \dots\}\), this function will remove any low-importance points such that \(\sum_i x_i p_i\) is preserved to within some threshold.

Added in version 0.14.0.

Parameters:

tolerance (float) – Maximum fraction of \(\sum_i x_i p_i\) that will be discarded.
inplace (bool) – Whether to modify the current object in-place or return a new one.

Return type:

Discrete distribution with low-importance points removed

classmethod from_xml_element(elem: Element)[source]

Generate discrete distribution from an XML element

Parameters:: elem (lxml.etree._Element) – XML element
Returns:: Discrete distribution generated from XML element
Return type:: openmc.stats.Discrete

integral()[source]

Return integral of distribution

Added in version 0.13.1.

Returns:: Integral of discrete distribution
Return type:: float

mean() → float[source]

Return mean of the discrete distribution

The mean is the weighted average of the discrete values.

Added in version 0.15.3.

Returns:: Mean of discrete distribution
Return type:: float

classmethod merge(dists: Sequence[Discrete], probs: Sequence[int])[source]

Merge multiple discrete distributions into a single distribution

Added in version 0.13.1.

Parameters:

dists (iterable of openmc.stats.Discrete) – Discrete distributions to combine
probs (iterable of float) – Probability of each distribution

Returns:

Combined discrete distribution

Return type:

openmc.stats.Discrete

normalize()[source]: Normalize the probabilities stored on the distribution

sample(n_samples=1, seed=None)[source]

Sample the univariate distribution

Parameters:

n_samples (int) – Number of sampled values to generate
seed (int or None) – Initial random number seed.

Returns:

A 1-D array of sampled values

Return type:

numpy.ndarray

to_xml_element(element_name)[source]

Return XML representation of the discrete distribution

Parameters:: element_name (str) – XML element name
Returns:: element – XML element containing discrete distribution data
Return type:: lxml.etree._Element