[FIX] Order 2

src/Gargantext/Core/Methods/Similarities.hs

@@ -31,20 +31,24 @@ import Test.QuickCheck.Arbitrary
 import qualified Data.Text as Text 
 
 ------------------------------------------------------------------------
-data Similarity = Conditional | Distributional
+data Similarity = Conditional | Distributional_A | Distributional_B
   deriving (Show, Eq)
 
 measure :: Similarity -> Matrix Int -> Matrix Double
 measure Conditional      x = measureConditional x
-measure Distributional x = logDistributional2  x
+measure Distributional_A x = logDistributional2 1 x
+measure Distributional_B x = logDistributional2 0 x
 
 ------------------------------------------------------------------------
 withMetric :: GraphMetric -> Similarity
 withMetric Order1   = Conditional
-withMetric Order2 = Distributional
+withMetric Order2_A = Distributional_A
+withMetric _        = Distributional_B
 
 ------------------------------------------------------------------------
-data GraphMetric = Order1 | Order2
+-- Order2 type is for keeping Database json compatibility
+-- it is supposed to be removed in the future
+data GraphMetric = Order1 | Order2 | Order2_A | Order2_B
     deriving (Generic, Eq, Ord, Enum, Bounded, Show)
 
 instance FromJSON  GraphMetric

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

@@ -168,16 +168,16 @@ distributional m' = run $ result
 
     result = termDivNan z_1 z_2
 
-logDistributional2 :: Matrix Int -> Matrix Double
-logDistributional2 m = trace ("logDistributional2, dim=" `mappend` show n) . run
+logDistributional2 :: Exp Double -> Matrix Int -> Matrix Double
+logDistributional2 o m = trace ("logDistributional2, dim=" `mappend` show n) . run
                        $ diagNull n
                        $ matMaxMini
-                    $ logDistributional' n m
+                       $ logDistributional' o n m
   where
     n = dim m
 
-logDistributional' :: Int -> Matrix Int -> Acc (Matrix Double)
-logDistributional' n m' = trace ("logDistributional'") result
+logDistributional' :: Exp Double -> Int -> Matrix Int -> Acc (Matrix Double)
+logDistributional' o n m' = trace ("logDistributional'") result
  where
     -- From Matrix Int to Matrix Double, i.e :
     -- m :: Matrix Int -> Matrix Double
@@ -204,7 +204,7 @@ logDistributional' 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 -> cond (x == 0) 0 (log (1 + x * to)))) ((./) m ss))
+        (map (lift1 (\x -> cond (x == 0) 0 (log (o + x * to)))) ((./) 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

src/Gargantext/Core/Viz/Graph/Tools.hs

@@ -73,7 +73,6 @@ defaultClustering x = spinglass 1 x
 -------------------------------------------------------------
 type Threshold = Double
 
-
 cooc2graph' :: Ord t => Similarity
                      -> Double
                      -> Map (t, t) Int
@@ -84,7 +83,7 @@ cooc2graph' distance threshold myCooc
     $ measure distance
     $ case distance of
         Conditional    -> map2mat Triangle 0 tiSize
-        Distributional -> map2mat Square   0 tiSize
+        _              -> map2mat Square   0 tiSize
     $ Map.filter (> 1) myCooc'
 
      where
@@ -93,7 +92,6 @@ cooc2graph' distance threshold myCooc
         myCooc' = toIndex ti myCooc
 
 
-
 -- coocurrences graph computation
 cooc2graphWith :: PartitionMethod
                -> BridgenessMethod
@@ -197,7 +195,7 @@ doSimilarityMap Conditional threshold strength myCooc = (distanceMap, toIndex ti
                 $ Map.filter (> threshold)
                 $ similarities `seq` mat2map similarities
 
-doSimilarityMap Distributional threshold strength myCooc = (distanceMap, toIndex ti diag, ti)
+doSimilarityMap distriType threshold strength myCooc = (distanceMap, toIndex ti diag, ti)
   where
     -- TODO remove below
     (diag, theMatrix) = Map.partitionWithKey (\(x,y) _ -> x == y)
@@ -208,7 +206,7 @@ doSimilarityMap Distributional threshold strength myCooc = (distanceMap, toIndex
     tiSize  = Map.size ti
 
     similarities = (\m -> m `seq` m)
-                 $ (\m -> m `seq` measure Distributional m)
+                 $ (\m -> m `seq` measure distriType m)
                  $ (\m -> m `seq` map2mat Square 0 tiSize m)
                  $ theMatrix `seq` toIndex ti theMatrix