ConvChain (Rust Port)

A port of Maxim Gumin's [ConvChain] to Rust:

ConvChain is a Markov chain of images that converges to input-like images. That is, the distribution of NxN patterns in the outputs converges to the distribution of NxN patterns in the input as the process goes on.

Please have a look on the original repo for a more thorough description of the application of the [Metropolis algorithm] to the problem.

```rust fn main() { // Generate a sample (this is the SimpleMaze example): let pattern = [ true, true, true, true, true, false, false, false, true, false, true, false, true, false, false, false, ]; let sample = ConvChainSample::new(&pattern, 4, 4);

// Initialize the chain using given sample and a
// - 32x32 output size
// - receptor size of 2
// - temperature of 1.0
let mut chain = ConvChain::new(&sample, 32, 2, 1.0);

// Generate the 32x32 field using 10 iterations.
let field: &[bool] = chain.process(10);

} ```

Example run

Here are a couple of outputs generated with the code, using different values for the receptor size and number of iterations:

| Input | r=3, it=10 | r=5, it=10 | r=5, it=20 | r=5, it=100 |
|---|---|---|---|---| | | | | | |

This repository provides ports of both original "slow" and "fast" implementations. To run the example, execute the following from the repository root:

console $ cargo run --release --example fast

This will process the jobs defined in [resources/samples.xml] and produce output images in the current directory.

To run the benchmarks, execute

console $ cargo bench