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https://github.com/beefsack/go-astar

Go implementation of the A* search algorithm
https://github.com/beefsack/go-astar

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Go implementation of the A* search algorithm

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go-astar

========



**A\* pathfinding implementation for Go**



[![Build Status](https://travis-ci.org/beefsack/go-astar.svg?branch=master)](https://travis-ci.org/beefsack/go-astar)



The [A\* pathfinding algorithm](http://en.wikipedia.org/wiki/A*_search_algorithm) is a pathfinding algorithm noted for its performance and accuracy and is commonly used in game development.  It can be used to find short paths for any weighted graph.



A fantastic overview of A\* can be found at [Amit Patel's Stanford website](http://theory.stanford.edu/~amitp/GameProgramming/AStarComparison.html).



Examples

--------



The following crude examples were taken directly from the automated tests.  Please see `path_test.go` for more examples.



### Key



*   `.` - Plain (movement cost 1)

*   `~` - River (movement cost 2)

*   `M` - Mountain (movement cost 3)

*   `X` - Blocker, unable to move through

*   `F` - From / start position

*   `T` - To / goal position

*   `●` - Calculated path



### Straight line



```

.....~......      .....~......

.....MM.....      .....MM.....

.F........T.  ->  .●●●●●●●●●●.

....MMM.....      ....MMM.....

............      ............

```



### Around a mountain



```

.....~......      .....~......

.....MM.....      .....MM.....

.F..MMMM..T.  ->  .●●●MMMM●●●.

....MMM.....      ...●MMM●●...

............      ...●●●●●....

```



### Blocked path



```

............      

.........XXX

.F.......XTX  ->  No path

.........XXX

............

```



### Maze



```

FX.X........      ●X.X●●●●●●..

.X...XXXX.X.      ●X●●●XXXX●X.

.X.X.X....X.  ->  ●X●X.X●●●●X.

...X.X.XXXXX      ●●●X.X●XXXXX

.XX..X.....T      .XX..X●●●●●●

```



### Mountain climber



```

..F..M......      ..●●●●●●●●●.

.....MM.....      .....MM...●.

....MMMM..T.  ->  ....MMMM..●.

....MMM.....      ....MMM.....

............      ............

```



### River swimmer



```

.....~......      .....~......

.....~......      ....●●●.....

.F...X...T..  ->  .●●●●X●●●●..

.....M......      .....M......

.....M......      .....M......

```



Usage

-----



### Import the package



```go

import "github.com/beefsack/go-astar"

```



### Implement Pather interface



An example implementation is done for the tests in `path_test.go` for the Tile type.



The `PathNeighbors` method should return a slice of the direct neighbors.



The `PathNeighborCost` method should calculate an exact movement cost for direct neighbors.



The `PathEstimatedCost` is a heuristic method for estimating the distance between arbitrary tiles.  The examples in the test files use [Manhattan distance](http://en.wikipedia.org/wiki/Taxicab_geometry) to estimate orthogonal distance between tiles.



```go

type Tile struct{}



func (t *Tile) PathNeighbors() []astar.Pather {

	return []astar.Pather{

		t.Up(),

		t.Right(),

		t.Down(),

		t.Left(),

	}

}



func (t *Tile) PathNeighborCost(to astar.Pather) float64 {

	return to.MovementCost

}



func (t *Tile) PathEstimatedCost(to astar.Pather) float64 {

	return t.ManhattanDistance(to)

}

```



### Call Path function



```go

// t1 and t2 are *Tile objects from inside the world.

path, distance, found := astar.Path(t1, t2)

if !found {

	log.Println("Could not find path")

}

// path is a slice of Pather objects which you can cast back to *Tile.

```



Authors

-------



Michael Alexander 

Robin Ranjit Chauhan