39 releases (5 stable)
2.3.0 | May 17, 2023 |
---|---|
2.1.0 | Mar 23, 2023 |
1.0.1 | Mar 9, 2023 |
0.24.0 | Mar 9, 2023 |
0.14.2 | Dec 22, 2022 |
#1216 in Algorithms
118 downloads per month
57KB
922 lines
Entromatica
Entromatica is a library for constructing, simulating and analyzing markov chains.
It is split into two main parts: the simulation
module and the models
module
collection.
The simulation
module contains primarily the Simulation
struct, which takes
an initial state and a StateTransitionGenerator
. This generator is a function
that takes a state and returns a list of the next states in the markov chain
with their respective relative probabilities.
The models
module contains a collection of structs and functions that try
to make constructing the state transition generator easier. Currently this
includes only a single model: rules
.
// This is a simple onedimensional random walk
use entromatica::prelude::*;
use std::sync::Arc;
// The initial state. It has to be Hash + Clone + Send + Sync + PartialEq + Eq + Debug
let initial_state: i32 = 0;
// The state transition generator. The simulation panics if the probabilities don't sum up to 1.0
let state_transition_generator =
Arc::new(|state: i32| vec![(state + 1, "next", 0.5), (state - 1, "previous", 0.5)]);
let mut simulation = Simulation::new(initial_state, state_transition_generator);
// The Shannon-entropy at the given time
assert_eq!(simulation.entropy(0), 0.0);
simulation.next_step();
assert_eq!(simulation.entropy(1), 1.0);
License
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
Dependencies
~8–15MB
~191K SLoC