sparseVector stumb

src/cdomains/vectorMatrix.ml

@@ -650,6 +650,138 @@ module ArrayMatrix: AbstractMatrix =
   end
 
 
+  module SparseVector: AbstractVector =
+  functor (A: RatOps) ->
+  struct
+    include ConvenienceOps (A)
+
+    type t = {
+      entries: (int * A.t) list ;
+      len: int
+    }[@@deriving eq, ord, hash]
+
+    let show v = 
+      failwith "TODO"
+
+    let keep_vals v n = 
+      let rec keep_vals_vec v n =
+          match v with 
+          | x::xs -> if fst x > n then [] else x::(keep_vals_vec xs n)
+          | [] -> []
+      in
+      if n >= v.len then v else (*could be left out but maybe performance??*)
+      {entries = keep_vals_vec v.entries n; len=n}
+
+    let remove_val v n = 
+      let dec_idx v = 
+        List.map (fun (a,b) -> (a-1, b)) v
+      in
+      let rec remove_val_vec v n =
+        match v with 
+        | x::xs -> 
+          if fst x = n then dec_idx xs else 
+          if fst x > n then dec_idx (x::xs) else
+          x::(remove_val_vec xs n)  
+        | [] -> []
+      in
+      if n >= v.len then v else (*could be left out but maybe performance??*)
+      {entries = remove_val_vec v.entries n; len = v.len - 1}
+
+    let set_val v n m = 
+      failwith "TODO"
+
+    let set_val_with v n m =
+      failwith "TODO"
+
+    let insert_val n m t = 
+      failwith "TODO"
+
+    let apply_with_c f m v = 
+      failwith "TODO"
+
+    let apply_with_c_with f m v = 
+      failwith "TODO"
+
+    let zero_vec n = 
+      failwith "TODO"
+
+    let nth v n = 
+      failwith "TODO"
+
+    let length v =
+      failwith "TODO"
+
+    let map2 f v v' = 
+      failwith "TODO"
+
+    let map2_with f v v' = 
+      failwith "TODO"
+
+    let findi f v = 
+      failwith "TODO"
+
+    let map f v = 
+      failwith "TODO"
+
+    let map_with f v  = 
+      failwith "TODO"
+
+    let compare_length_with v n = 
+      failwith "TODO"
+
+    let of_list l = 
+      failwith "TODO"
+
+    let to_list v = 
+      failwith "TODO"
+
+    let filteri f v = 
+      failwith "TODO"
+
+    let append v v' = 
+      failwith "TODO"
+
+    let exists f v  = 
+    failwith "TODO"
+
+    let rev v = 
+      failwith "TODO"
+
+    let rev_with v = 
+      failwith "TODO"
+
+    let map2i f v v' = 
+      failwith "TODO"
+
+    let map2i_with f v v' = 
+      failwith "TODO"
+
+    let mapi f v  = 
+      failwith "TODO"
+
+    let mapi_with f v = 
+      failwith "TODO"
+
+    let find2i f v v' = 
+      failwith "TODO"
+
+    let to_array v = 
+      failwith "TODO"
+
+    let of_array a =
+      failwith "TODO"
+
+    let copy v = v 
+
+    let of_sparse_list ls col_count =
+      failwith "TODO"
+
+    let to_sparse_list v = 
+      failwith "TODO"
+
+  end 
+
+
 (** Sparse matrix implementation.
     It provides a normalization function to reduce a matrix into reduced row echelon form.
     Operations exploit that the input matrix/matrices are in reduced row echelon form already. *)
@@ -689,14 +821,9 @@ module SparseMatrix: AbstractMatrix =
       timing_wrap "copy" (copy) m
 
     let add_empty_columns m (cols : int enumerable) =
-      let colsL = Array.to_list(cols) in
+      let colsL = List.sort (fun a b -> a-b) (Array.to_list cols) in
       let emptyT = A.zero in
       let rec list_of_all_before_index idx cols =
-        (*This should return two arrays
-          all the idices before idx and all those after, but I'm not sure if inclusive or not
-          e.g. list_of_all_before_index 3 [1,2,3,4] = ([1,2], [3,4]) or = ([1,2,3], [4])
-          right now its of the first form!
-        *)
         match  cols with
         | x::xs -> 
           if x < idx