[FEAT] Order2 Only

src/Gargantext/Core/Methods/Similarities.hs

@@ -31,19 +31,17 @@ import Test.QuickCheck.Arbitrary
 import qualified Data.Text as Text 
 
 ------------------------------------------------------------------------
-data Similarity = Conditional | Distributional_A | Distributional_B
+data Similarity = Conditional | Distributional
   deriving (Show, Eq)
 
 measure :: Similarity -> Matrix Int -> Matrix Double
 measure Conditional    x = measureConditional x
-measure Distributional_A x = logDistributional2 1 x
-measure Distributional_B x = logDistributional2 0 x
+measure Distributional x = logDistributional2 x
 
 ------------------------------------------------------------------------
 withMetric :: GraphMetric -> Similarity
 withMetric Order1 = Conditional
-withMetric Order2_A = Distributional_A
-withMetric _        = Distributional_B
+withMetric _ = Distributional
 
 ------------------------------------------------------------------------
 -- Order2 type is for keeping Database json compatibility

src/Gargantext/Core/Methods/Similarities/Accelerate/Distributional.hs

@@ -168,16 +168,16 @@ distributional m' = run $ result
 
     result = termDivNan z_1 z_2
 
-logDistributional2 :: Exp Double -> Matrix Int -> Matrix Double
-logDistributional2 o m = trace ("logDistributional2, dim=" `mappend` show n) . run
+logDistributional2 :: Matrix Int -> Matrix Double
+logDistributional2 m = trace ("logDistributional2, dim=" `mappend` show n) . run
                      $ diagNull n
                      $ matMaxMini
-                       $ logDistributional' o n m
+                     $ logDistributional' n m
   where
     n = dim m
 
-logDistributional' :: Exp Double -> Int -> Matrix Int -> Acc (Matrix Double)
-logDistributional' o n m' = trace ("logDistributional'") result
+logDistributional' :: Int -> Matrix Int -> Acc (Matrix Double)
+logDistributional' n m' = trace ("logDistributional'") result
  where
     -- From Matrix Int to Matrix Double, i.e :
     -- m :: Matrix Int -> Matrix Double
@@ -204,7 +204,7 @@ logDistributional' o n m' = trace ("logDistributional'") result
     -- m_{i,j} = 0 if n_{i,j} = 0 or i = j, 
     -- m_{i,j} = log(to * n_{i,j} / s_{i,j}) otherwise.
     mi = (.*) (matrixEye n)
-              (map (lift1 (\x -> let x' = o + x * to in cond (x' < 1) 0 (log x'))) ((./) m ss))
+              (map (lift1 (\x -> let x' = x * to in cond (x' < 1) 0 (log x'))) ((./) m ss))
     -- mi_nnz :: Int
     -- mi_nnz = flip indexArray Z . run $
     --   foldAll (+) 0 $ map (\a -> ifThenElse (abs a < 10^(-6 :: Exp Int)) 0 1) mi