Module mc

Expand description

Monte Carlo module

Modules§

DispersedState: A dispersed state
Dispersion: A dispersions configuration, allows specifying min/max bounds (by default, they are not set)
MonteCarlo: A Monte Carlo framework, automatically running on all threads via a thread pool. This framework is targeted toward analysis of time-continuous variables. One caveat of the design is that the trajectory is used for post processing, not each individual state. This may prevent some event switching from being shown in GNC simulations.
MvnSpacecraft: A multivariate spacecraft state generator for Monte Carlo analyses. Ensures that the covariance is properly applied on all provided state variables.
Normal: The Normal distribution N(μ, σ²).
Results: A structure of Monte Carlo results
SmallRng: A small-state, fast, non-crypto, non-portable PRNG
StateDispersion: A dispersions configuration, allows specifying min/max bounds (by default, they are not set)
StdRng: A strong, fast (amortized), non-portable RNG
ThreadRng: A reference to the thread-local generator
Uniform: Sample values uniformly between two bounds.

CryptoRng: A marker trait over RngCore for securely unpredictable RNGs
Distribution: Types (distributions) that can be used to create a random instance of T.
IndexedMutRandom: Extension trait on indexable lists, providing random sampling methods.
IndexedRandom: Extension trait on indexable lists, providing random sampling methods.
IteratorRandom: Extension trait on iterators, providing random sampling methods.
Rng: User-level interface for RNGs
RngCore: Implementation-level interface for RNGs
SeedableRng: A random number generator that can be explicitly seeded.
SliceRandom: Extension trait on slices, providing shuffling methods.
Stats: Statistical measures of a single variable (one generic vector of data) and vector algebra applicable to a single (generic) vector. Thus these methods take no arguments.