Add basic example and update README (#10)

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[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE-MIT)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE-APACHE)
Instance Distance is a fast pure-Rust implementation of the
[Hierarchical Navigable Small Worlds paper][paper] by Malkov and Yashunin
for finding approximate nearest neighbors. This implementation will power the
Instance Distance is a fast pure-Rust implementation of the [Hierarchical
Navigable Small Worlds paper][paper] by Malkov and Yashunin for finding
approximate nearest neighbors. This implementation powers the
[InstantDomainSearch.com][ids] backend services used for word vector indexing.
## What it does
Instant Distance is an implementation of a fast approximate nearest neighbor
search algorithm. The algorithm is used to find the closest point(s) to a given
point in a set.
## Using the library
### Rust
```toml
[dependencies]
instant-segment = "0.5.0"
```
## Example
```rust
use instant_distance::{Builder, Search};
fn main() {
let points = vec![Point(255, 0, 0), Point(255, 0, 0), Point(255, 0, 0)];
let values = vec!["red", "green", "blue"];
let map = Builder::default().build(points, values);
let mut search = Search::default();
let cambridge_blue = Point(163, 193, 173);
let closest_point = map.search(&cambridge_blue, &mut search).next().unwrap();
println!("{:?}", closest_point.value);
}
#[derive(Clone, Copy, Debug)]
struct Point(isize, isize, isize);
impl instant_distance::Point for Point {
fn distance(&self, other: &Self) -> f32 {
// Euclidean distance metric
(((self.0 - other.0).pow(2) + (self.1 - other.1).pow(2) + (self.2 - other.2).pow(2)) as f32)
.sqrt()
}
}
```
## Testing
Rust:
```
cargo t -p instant-distance --all-features
```
Python:
```
make test-python
```
[paper]: https://arxiv.org/abs/1603.09320
[ids]: https://instantdomainsearch.com/

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use instant_distance::{Builder, Search};
fn main() {
let points = vec![Point(255, 0, 0), Point(0, 255, 0), Point(0, 0, 255)];
let values = vec!["red", "green", "blue"];
let map = Builder::default().build(points, values);
let mut search = Search::default();
let burnt_orange = Point(204, 85, 0);
let closest_point = map.search(&burnt_orange, &mut search).next().unwrap();
println!("{:?}", closest_point.value);
}
#[derive(Clone, Copy, Debug)]
struct Point(isize, isize, isize);
impl instant_distance::Point for Point {
fn distance(&self, other: &Self) -> f32 {
// Euclidean distance metric
(((self.0 - other.0).pow(2) + (self.1 - other.1).pow(2) + (self.2 - other.2).pow(2)) as f32)
.sqrt()
}
}