(** Sample usage of Skeleton functional semantics
    We use a dummy Image format (array of array of pixels) 
    and we define some functions over images to be used in 
    pipeline stages. 
    Functions are defined as map s *) 

open Skeleton

(** the type of black and white pixels: levels of gray *)
type bw_pixel = BWP of int;;
(** the type of black and white images: 2 dim array of pixels *)
type bw_image = BWImage of bw_pixel array array;;

(** the type of color pixels: RGB *)
type col_pixel = CP of int * int * int;;
(** the type of color images: 2 dim array of pixels *)
type col_image = Image of col_pixel array array;;

(** sample image definition *)
let p1 = CP(127,127,127);;
let p2 = CP(0,0,64);;
let p3 = CP(0,64,0);;
let p4 = CP(64,0,0);;
let a = Image [| [| p1; p1; p1; p2; p2 |] ; 
                 [| p2; p3; p3; p4; p1 |] ; 
	         [| p1; p1; p1; p1; p1 |] ; 
		 [| p1; p2; p2; p2; p1 |] |];;

(** changes color pixels to black and white *)
let col_to_bw x  = 
  match x with
  CP(r,g,b) -> BWP(r+g+b);;

(** kind of smooth pixel *)
let average = 
  function
    CP(x,y,z) -> 
      let n = ((x+y+z)/3) in 
      CP(n,n,n);;

(** invert colors *)
let invert = function
  CP(r,g,b) -> CP(255-r, 255-g, 255-b);;


(** kind of saturation *)
let sq = function
  CP(r,g,b) -> let msq x = ((x*x) mod 256) in 
    CP((msq r), (msq g), (msq b));;

(** generic stage: takes a pixel processing function (Color to Color) and 
    returns the stage working on the whole array of arrays
    @param f the function to be applied *)
let stage f = 
  function
    Image x -> Image ( (map (map f)) x);;

(** sample stage definitions *)
let stage_average = stage average;;
let stage_sq = stage sq;;

(** color to black and white stage: this could not be defined through stage function
    as the type of the output image changes ... *)
let c_to_bw_stage = function
  Image x -> BWImage((map (map col_to_bw)) x);;

(** sample main program *)
let main = 
  pipe 
    (pipe (stage invert) (stage average))
    c_to_bw_stage ;;