https://github.com/tom-draper/nlmrs

A Rust crate for building Neutral Landscape Models.
https://github.com/tom-draper/nlmrs

data-visualization environment landscape landscapes landscaping matplotlib model modeling models neutral-landscape-model nlm nlm-api patterns rust rust-lang simulation visualization world-building

Last synced: 27 days ago
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A Rust crate for building Neutral Landscape Models.

• Host: GitHub
• URL: https://github.com/tom-draper/nlmrs
• Owner: tom-draper
• Created: 2023-01-04T19:34:35.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-11-22T10:10:56.000Z (12 months ago)
• Last Synced: 2024-09-15T07:51:20.668Z (about 2 months ago)
• Topics: data-visualization, environment, landscape, landscapes, landscaping, matplotlib, model, modeling, models, neutral-landscape-model, nlm, nlm-api, patterns, rust, rust-lang, simulation, visualization, world-building
• Language: Rust
• Homepage:
• Size: 3.64 MB
• Stars: 3
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# NLMrs

A Rust crate for building Neutral Landscape Models.



Inspired by [nlmpy](https://pypi.org/project/nlmpy/) and [nlmr](https://github.com/ropensci/NLMR).

## Installation

```bash

cargo add nlmrs

```

## Example

```rs

use nlmrs;

fn main() {

    let arr: Vec> = nlmrs::midpoint_displacement(10, 10, 1.);

    println!("{:?}", arr);

}

```

### Export

The `export` module holds a collection of user-friendly functions to export your 2D NLM vector.

```rs

use nlmrs::{distance_gradient, export};

fn main() {

    let arr: Vec> = distance_gradient(50, 50);

    export::write_to_csv(arr, "./data/data.csv");

}

```

### Visualization

Running `scripts/visualize.py` will read any contents of `data/data.csv` and render them as a matplotlib plot.

## Algorithms

### Random

`random(rows: 100, cols: 100)`



### Random Element

`random_element(rows: 100, cols: 100, n: 50000.)`



### Planar Gradient

`planar_gradient(rows: 100, cols: 100, direction: Some(60.))`



### Edge Gradient

`edge_gradient(rows: 100, cols: 100, direction: Some(140.))`



### Distance Gradient

`distance_gradient(rows: 100, cols: 100)`



### Wave Gradient

`wave_gradient(rows: 100, cols: 100, period: 2.5, direction: Some(90.))`



### Midpoint Displacement

`midpoint_displacement(rows: 100, cols: 100, h: 1.)`



### Hill Grow

`hill_grow(rows: 100, cols: 100, n: 10000, runaway: true, kernel: None, only_grow: false)`



## Contributions

Contributions, issues and feature requests are welcome.

- Fork it (https://github.com/tom-draper/nlmrs)

- Create your feature branch (`git checkout -b my-new-feature`)

- Commit your changes (`git commit -am 'Add some feature'`)

- Push to the branch (`git push origin my-new-feature`)

- Create a new Pull Request