Uncertain<T>
Fast and correct computations with uncertain values.
When working with values which are not exactly determined, such as sensor data, it can be difficult to handle uncertainties correctly.
The Uncertain trait makes such computations as natural as regular computations:
```rust use uncertain::{Uncertain, Distribution}; use rand_distr::Normal;
// Some inputs about which we are not sure let x = Distribution::from(Normal::new(5.0, 2.0).unwrap()); let y = Distribution::from(Normal::new(7.0, 3.0).unwrap());
// Do some computations let distance = x.sub(y).map(|diff: f64| diff.abs());
// Ask a question about the result let isitfar = distance.map(|dist| dist > 2.0);
// Check how certain the answer is asserteq!(isitfar.pr(0.9), false); asserteq!(isitfar.pr(0.5), true); ```
This works by sampling a Bayesian network which is implicitly created by describing the computation
on the uncertain type. The Uncertain trait only permits tests for simple boolean hypotheses. This
is by design: using Wald's sequential probability ratio test, evaluation typically
takes less than 100 samples.
While this crate is released as version 0.x, breaking API changes should be expected.
The Uncertain trait exported from the library is an implementation of
the paper Uncertain<T>.