#ND4S: Scala bindings for ND4J
ND4S is an Apache2 Licensed open-sourced Scala bindings for ND4J.
#Main Features
- NDArray manipulation syntax sugar with safer type.
- NDArray slicing syntax, similar with NumPy.
#Installation
##Clone from the GitHub Repo
ND4S is actively developed. You can clone the repository, compile it, and reference it in your project.
Clone the repository:
$ git clone https://github.com/deeplearning4j/nd4s.git
Compile the project:
$ cd nd4s
$ sbt +publish-local
#CheatSheet(WIP)
ND4S syntax | Equivalent NumPy syntax | Result |
---|---|---|
Array(Array(1,2,3),Array(4,5,6)).toNDArray | np.array([[1, 2 , 3], [4, 5, 6]]) | [[1.0, 2.0, 3.0] [4.0, 5.0, 6.0]] |
val arr = (1 to 9).asNDArray(3,3) | arr = np.array([[1, 2 , 3], [4, 5, 6],[7, 8, 9]]) | [[1.0, 2.0, 3.0] [4.0, 5.0, 6.0] ,[7.0, 8.0, 9.0]] |
arr(0,0) | arr[0,0] | 1.0 |
arr(0,->) | arr[0,:] | [1.0, 2.0, 3.0] |
arr(--->) | arr[...] | [[1.0, 2.0, 3.0] [4.0, 5.0, 6.0] ,[7.0, 8.0, 9.0]] |
arr(0 -> 3 by 2, ->) | arr[0:3:2,:] | [[1.0, 2.0, 3.0] [7.0, 8.0, 9.0]] |
arr(0 to 2 by 2, ->) | arr[0:3:2,:] | [[1.0, 2.0, 3.0] [7.0, 8.0, 9.0]] |
arr.filter(_ > 3) | [[0.0, 0.0, 0.0] [4.0, 5.0, 6.0] ,[7.0, 8.0, 9.0]] | |
arr.map(_ % 3) | [[1.0, 2.0, 0.0] [1.0, 2.0, 0.0] ,[1.0, 2.0, 0.0]] | |
arr.filterBit(_ < 4) | [[1.0, 1.0, 1.0] [0.0, 0.0, 0.0] ,[0.0, 0.0, 0.0]] | |
arr + arr | arr + arr | [[2.0, 4.0, 6.0] [8.0, 10.0, 12.0] ,[14.0, 16.0, 18.0]] |
arr * arr | arr * arr | [[1.0, 4.0, 9.0] [16.0, 25.0, 36.0] ,[49.0, 64.0, 81.0]] |
arr dot arr | np.dot(arr, arr) | [[30.0, 36.0, 42.0] [66.0, 81.0, 96.0] ,[102.0, 126.0, 150.0]] |
arr.sumT | np.sum(arr) | 45.0 //returns Double value |
val comp = Array(1 + i, 1 + 2 * i).toNDArray | comp = np.array([1 + 1j, 1 + 2j]) | [1.0 + 1.0i ,1.0 + 2.0i] |
comp.sumT | np.sum(comp) | 2.0 + 3.0i //returns IComplexNumber value |