[TEST] hspec

gargantext-graph.cabal

@@ -4,7 +4,7 @@ cabal-version: 1.12
 --
 -- see: https://github.com/sol/hpack
 --
--- hash: c963b0693d31715c24d7005b13eb4c408cd00c23009b3e68b6dbf329a47db200
+-- hash: f8da0e8f0d95addc40b203c0fc52a4e61e8af8847f134c289ba4acc5bfefd8d7
 
 name:           gargantext-graph
 version:        0.1.0.0
@@ -102,7 +102,7 @@ executable gargantext-graph-exe
 
 test-suite gargantext-graph-test
   type: exitcode-stdio-1.0
-  main-is: Spec.hs
+  main-is: Main.hs
   other-modules:
       Paths_gargantext_graph
   hs-source-dirs:
@@ -110,7 +110,8 @@ test-suite gargantext-graph-test
   default-extensions: DataKinds FlexibleInstances OverloadedStrings
   ghc-options: -threaded -rtsopts -with-rtsopts=-N
   build-depends:
-      accelerate
+      QuickCheck
+    , accelerate
     , accelerate-arithmetic
     , accelerate-utility
     , base >=4.7 && <5
@@ -122,6 +123,7 @@ test-suite gargantext-graph-test
     , fgl
     , gargantext-graph
     , haskell-igraph >=0.6.0
+    , hspec
     , lens
     , pretty-simple
     , protolude

install

 #!/bin/bash
 
-stack install --profile # --test # --haddock
+stack install --profile --test # --haddock

package.yaml

@@ -62,10 +62,11 @@ executables:
     - -Wcompat
     dependencies:
     - gargantext-graph
+    - criterion
 
 tests:
   gargantext-graph-test:
-    main:                Spec.hs
+    main:                Main.hs
     source-dirs:         test
     ghc-options:
     - -threaded
@@ -73,3 +74,5 @@ tests:
     - -with-rtsopts=-N
     dependencies:
     - gargantext-graph
+    - hspec
+    - QuickCheck

src/Graph/BAC/ProxemyOptim.hs

@@ -152,9 +152,9 @@ adjacent (FiniteGraph g) isReflexive =
 transition :: KnownNat         n
            => AdjacencyMatrix  n
            -> TransitionMatrix n
-transition m = SMatrix.imap (\i j v -> v * (List.!!) s i) m
+transition m = SMatrix.imap (\i j v -> v * (VS.!) s i) m
   where
-    s = sumWith' Colonne (\s -> 1 / s) m
+    s = sumWith Colonne (\s -> 1 / s) m
 
 
 proxemie :: KnownNat         n
@@ -175,13 +175,13 @@ matconf :: forall n. KnownNat n
 matconf False a p = symmetry confmat
   where
     -- vcount  = natToInt @n
-    degs    = sumWith' Colonne identity a
-    sumdeg  = List.sum degs
+    degs    = sumWith Colonne identity a
+    sumdeg  = VS.sum degs
     confmat = DMatrix.imap (\  x   y   v ->
                             if x < y
                               then let
                                       prox_y_x_length = v
-                                      prox_y_x_infini = ((List.!!) degs x) / sumdeg
+                                      prox_y_x_infini = ((VS.!) degs x) / sumdeg
                                  in 
                                     (prox_y_x_length - prox_y_x_infini)
                                   / (prox_y_x_length + prox_y_x_infini)
@@ -219,15 +219,15 @@ edges_confluence l am tm = -- traceShow ("degs", degs) $
   SMatrix.toList matconf'
     where
       vcount   = natToInt @n
-      degs     = sumWith' Colonne identity am
-      sumdeg   = List.sum degs
+      degs     = sumWith Colonne identity am
+      sumdeg   = VS.sum degs
       matconf' = SMatrix.imap
                  (\x y _ ->
                    if x < y
                       then
                         let
-                            deg_x = (List.!!) degs x - 1
-                            deg_y = (List.!!) degs y - 1
+                            deg_x = (VS.!) degs x - 1
+                            deg_y = (VS.!) degs y - 1
 
                             tm' = SMatrix.imap (\i j v -> if (i == x && j == y) || ( i == y && j == x)
                                                             then 0
@@ -404,7 +404,6 @@ symmetryS :: KnownNat n => MatrixS n -> MatrixS n
 symmetryS m = SMatrix.imap (\x y v -> if x < y then v else coeffSM y x m) m
 
 ---------------------------
-
 class KnownNat n => Vector n a where
   fromList :: KnownNat n => Proxy n -> [(Integer,Double)] -> a
 
@@ -425,7 +424,6 @@ vectorFromListD :: KnownNat n => Proxy n -> [(Integer, Double)] -> VectorD n
 vectorFromListD pn ns = toMatrix $ vectorFromListS pn ns
 
 ------------------------------
-
 data Direction = Ligne | Colonne
 
 sumWith :: ( Elem a
@@ -440,17 +438,4 @@ sumWith dir f m = VS.fromList
           where
             somme m' = map (sum . SMatrix.toMatrix) m'
 
-sumWith' :: ( Elem a
-           , Elem t
-           , KnownNat n
-           ) => Direction -> (t -> a) -> SparseMatrix n n t -> [a]
-sumWith' dir f m = map (\v -> f v)
-       $ case dir of
-           Colonne -> somme $ SMatrix.getCols m
-           Ligne   -> somme $ SMatrix.getRows m
-          where
-            somme m' = map (sum . SMatrix.toMatrix) m'
-
-
 --------------------------------------------
-

test/Main.hs

+
+{-# LANGUAGE NoImplicitPrelude       #-}
+
+module Main where
+
+import Data.Set as Set
+import Data.String.Conversions (cs)
+import Data.Text (Text)
+import qualified Eigen.Matrix as Matrix
+import Graph.BAC.ProxemyOptim
+import Graph.FGL
+import Graph.Types
+import Graph.Tools.Random
+import Prelude (String)
+import Protolude
+import Graph.BAC.ProxemyOptim
+import Test.Hspec
+import qualified Data.IntMap                       as Dict
+import qualified Eigen.SparseMatrix as SMatrix
+import qualified Prelude as Prelude
+import qualified Data.List as List
+
+
+main :: IO ()
+main = hspec $ do
+  describe "Graph Toy first test" $ do
+    let 
+
+        edges_test :: [(Int,Int)]
+        edges_test=[(0,1),(0,2),(0,4),(0,5),(0,3),(0,6)
+                   ,(1,2),(1,3),(2,3),(4,5),(4,6),(5,6)
+                   ,(7,8),(7,3),(7,4),(8,2),(8,5)
+                   ]
+
+        clustering_result =
+          ClusteringIs { parts = Dict.fromList [(0, Set.fromList [0,4,5,6])
+                                               ,(1, Set.fromList [1,2,3])
+                                               ,(7, Set.fromList [7,8])]
+                       , index = Dict.fromList [(0,0),(1,1),(2,1)
+                                               ,(3,1),(4,0),(5,0)
+                                               ,(6,0),(7,7),(8,7)
+                                               ]
+                       , score = 3.0558391780792453
+                       , mode = Part
+                       }
+
+        g :: Graph () ()
+        g = mkGraphUfromEdges edges_test
+
+        result = withG g (identity  . (clusteringOptim 3 Conf))
+    it "Graph Toy test exact result" $ do
+      shouldBe True (result == clustering_result)
+
+{-
+  m <- randomAdjacency
+  describe "Random Matrix of fixed size (TODO dynamic size)" $ do
+    let
+      g :: Graph () ()
+      g = mkGraphUfromEdges
+        $ List.map (\(x,y,_) -> (x,y))
+        $ SMatrix.toList m
+      result = withG g (parts  . (clusteringOptim 3 Conf))
+    it "Random test, checking clustering size" $ do
+      shouldBe True (let n = (Dict.size result) in n > 1 && n < 10)
+-}

test/Spec.hs

-
-{-# LANGUAGE NoImplicitPrelude       #-}
-
-module Spec where
-
-import Data.Set as Set
-import Data.String.Conversions (cs)
-import Data.Text (Text)
-import qualified Eigen.Matrix as Matrix
-import Graph.BAC.ProxemyOptim
-import Graph.FGL
-import Graph.Types
-import Graph.Tools.Random
-import Prelude (String)
-import Protolude
-import Graph.BAC.ProxemyOptim
-import qualified Data.IntMap                       as Dict
-import qualified Eigen.SparseMatrix as SMatrix
-import qualified Prelude as Prelude
-import qualified Data.List as List
-
-
-main :: IO ()
-main = do
-  let 
-
-      edges_test :: [(Int,Int)]
-      edges_test=[(0,1),(0,2),(0,4),(0,5),(0,3),(0,6)
-                 ,(1,2),(1,3),(2,3),(4,5),(4,6),(5,6)
-                 ,(7,8),(7,3),(7,4),(8,2),(8,5)
-                 ]
-
-      clustering_result =
-        ClusteringIs { parts = Dict.fromList [(0, Set.fromList [0,4,5,6])
-                                             ,(1, Set.fromList [1,2,3])
-                                             ,(7, Set.fromList [7,8])]
-                     , index = Dict.fromList [(0,0),(1,1),(2,1)
-                                             ,(3,1),(4,0),(5,0)
-                                             ,(6,0),(7,7),(8,7)
-                                             ]
-                     , score = 3.0558391780792453
-                     , mode = Part
-                     }
-
-      g :: Graph () ()
-      g = mkGraphUfromEdges edges_test
-
-      result = withG g (identity  . (clusteringOptim 3 Conf))
-
-  print $ result == clustering_result
-
-test_random :: IO ()
-test_random = do
-  m <- randomAdjacency
-  let
-    g :: Graph () ()
-    g = mkGraphUfromEdges
-      $ List.map (\(x,y,_) -> (x,y))
-      $ SMatrix.toList m
-    result = withG g (identity  . (clusteringOptim 3 Conf))
-  print (result)