[TestFlow] seems good, need to add tests on it and fix distributional distance.

package.yaml

@@ -50,8 +50,12 @@ library:
   - Gargantext.Text.Parsers.WOS
   - Gargantext.Text.Search
   - Gargantext.Text.Terms
+  - Gargantext.Text.Terms.Mono
+  - Gargantext.Text.Terms.Multi.Lang.En
+  - Gargantext.Text.Terms.Multi.Lang.Fr
   - Gargantext.Text.Terms.WithList
   - Gargantext.TextFlow
+  - Gargantext.Viz.Graph
   - Gargantext.Viz.Graph.Distances.Matrice
   - Gargantext.Viz.Graph.Index
   dependencies:

src/Gargantext/API/Settings.hs

-{-|PI/Application.hs
-API/Count.hs
-API/FrontEnd.hs
-API/Node.hs
-API/Auth.hs
-API.hs
-Database/NodeNodeNgram.hs
-Database/User.hs
-Database/Queries.hs
-
+{-| 
 Module      : Gargantext.API.Settings
 Description : Settings of the API (Server and Client)
 Copyright   : (c) CNRS, 2017-Present

src/Gargantext/Database.hs

 {-|
 Module      : Gargantext.Database
-Description : Main commands of BASHQL a Domain Specific Language to deal with Gargantext Database.
+Description : BASHQL to deal with Gargantext Database.
 Copyright   : (c) CNRS, 2017-Present
 License     : AGPL + CECILL v3
 Maintainer  : team@gargantext.org
 Stability   : experimental
 Portability : POSIX
 
+* BASHQL is a Domain Specific Language to deal with the Database
+
 * BASHQL = functional (Bash * SQL)
 
 * Which language to chose when working with a database ? To make it
@@ -42,6 +44,7 @@ write Haskell bash translations.
 - FileSystem is now a NodeSystem where each File is a Node in a Directed Graph (DG).
 
 * References
+
 [0] MIT Press has published "Category theory for the sciences". The book
 can also be purchased on Amazon. Here are reviews by the MAA, by the
 AMS, and by SIAM.
@@ -64,6 +67,7 @@ module Gargantext.Database ( module Gargantext.Database.Utils
                            , del , del'
                            , tree, tree'
                            , postCorpus, postAnnuaire
+                           , Connection
                            )
     where
 

src/Gargantext/Database/Node.hs

@@ -59,6 +59,9 @@ import qualified Data.Profunctor.Product as PP
 -- | Types for Node Database Management
 data PGTSVector
 
+------------------------------------------------------------------------
+type CorpusId = Int
+------------------------------------------------------------------------
 
 instance FromField HyperdataCorpus where
     fromField = fromField'

src/Gargantext/Text/Examples.hs

@@ -11,9 +11,9 @@ This file is intended for these purposes:
 
 - documentation for teaching and research
 - learn basics of Haskell which is a scientific programming language
-- behavioral tests (that should be completed with uni-tests and scale-tests
+- behavioral tests (that should be completed with uni-tests and scale-tests)
 
-This documents defines basic of Text definitions according to Gargantext..
+This document defines basic of Text definitions according to Gargantext..
 
 - What is a term ?
 - What is a sentence ?
@@ -104,7 +104,18 @@ ex_occ = occurrences <$> L.concat <$> ex_terms
 ex_cooc :: IO (Map (Label, Label) Int)
 ex_cooc = cooc <$> ex_terms
 
--- | Tests 
+-- | Tests the specificity and genericity
+--
+-- >>> ex_cooc_mat
+-- (fromList [(["glass"],0),(["spoon"],1),(["table"],2),(["wine"],3)],Matrix (Z :. 4 :. 4) 
+--   [ 4, 0, 0, 0,
+--     1, 2, 0, 0,
+--     3, 2, 4, 0,
+--     3, 1, 2, 3],Matrix (Z :. 4 :. 4) 
+--   [ 1.0, 0.25, 0.75, 0.75,
+--     0.0,  1.0,  1.0,  0.5,
+--     0.0,  0.0,  1.0,  0.5,
+--     0.0,  0.0,  0.0,  1.0],(Vector (Z :. 4) [0.5833333333333334,0.5833333333333334,0.75,0.5833333333333334],Vector (Z :. 4) [-0.5833333333333334,-0.4166666666666667,0.41666666666666674,0.5833333333333334]))
 ex_cooc_mat :: IO (Map Label Index, Matrix Int, Matrix Double, (DAA.Vector InclusionExclusion, DAA.Vector SpecificityGenericity))
 ex_cooc_mat = do
   m <- ex_cooc

src/Gargantext/Text/Metrics.hs

@@ -36,7 +36,7 @@ import qualified Data.Array.Accelerate as DAA
 
 import GHC.Real (round)
 
---import Debug.Trace
+import Debug.Trace (trace)
 
 data MapListSize   = MapListSize   Int
 data InclusionSize = InclusionSize Int
@@ -51,13 +51,13 @@ data FilterConfig = FilterConfig { fc_mapListSize   :: MapListSize
                                  , fc_defaultValue  :: DefaultValue
                              }
 
-filterCooc :: Ord t => FilterConfig -> Map (t, t) Int -> Map (t, t) Int
+filterCooc :: (Show t, Ord t) => FilterConfig -> Map (t, t) Int -> Map (t, t) Int
 filterCooc fc cc = (filterCooc' fc) ts cc
   where
     ts     = map _scored_terms $ takeSome fc $ coocScored cc
 
-filterCooc' :: Ord t => FilterConfig -> [t] -> Map (t, t) Int -> Map (t, t) Int
-filterCooc' (FilterConfig _ _ _ _ (DefaultValue dv)) ts m = -- trace ("coocScored " <> show (length ts)) $
+filterCooc' :: (Show t, Ord t) => FilterConfig -> [t] -> Map (t, t) Int -> Map (t, t) Int
+filterCooc' (FilterConfig _ _ _ _ (DefaultValue dv)) ts m = trace ("coocScored " <> show ts) $
   foldl' (\m' k -> M.insert k (maybe dv identity $ M.lookup k m) m')
     M.empty selection
   where
@@ -75,7 +75,7 @@ filterCooc' (FilterConfig _ _ _ _ (DefaultValue dv)) ts m = -- trace ("coocScore
 takeSome :: Ord t => FilterConfig -> [Scored t] -> [Scored t]
 takeSome (FilterConfig (MapListSize l) (InclusionSize l') (SampleBins s) (Clusters _) _) scores = L.take l
                     $ takeSample n m
-                    $ L.take l' $ sortWith (Down . _scored_incExc) scores
+                    $ L.take l' $ reverse $ sortWith (Down . _scored_incExc) scores
                     -- splitKmeans k scores
   where
     -- TODO: benchmark with accelerate-example kmeans version
@@ -95,7 +95,7 @@ takeSome (FilterConfig (MapListSize l) (InclusionSize l') (SampleBins s) (Cluste
                                  $ sortWith (Down . _scored_speGen) xs
 
 
-data Scored t = Scored { _scored_terms  :: !t
+data Scored ts = Scored { _scored_terms :: !ts
                         , _scored_incExc :: !InclusionExclusion
                         , _scored_speGen :: !SpecificityGenericity
                         } deriving (Show)

src/Gargantext/Text/Terms/Mono/Token/En.hs

@@ -17,7 +17,6 @@ module Gargantext.Text.Terms.Mono.Token.En
     ( EitherList(..)
     , Tokenizer
     , tokenize
-    , run
     , defaultTokenizer
     , whitespace
     , uris
@@ -64,8 +63,6 @@ import Gargantext.Prelude
 --    ,"Hyphen-words"
 --    ,"Yes/No questions"
 --    ]
----
-
 type Tokenizer =  Text -> EitherList Text Text
 
 -- | The EitherList is a newtype-wrapped list of Eithers.

src/Gargantext/TextFlow.hs

@@ -21,15 +21,22 @@ import GHC.IO (FilePath)
 import qualified Data.Text as T
 import Data.Text.IO (readFile)
 
+import Data.Maybe (catMaybes)
+import qualified Data.Set as DS
 
 import qualified Data.Array.Accelerate as A
 import qualified Data.Map.Strict as M
 ----------------------------------------------
+import Gargantext.Database (Connection)
+
+import Gargantext.Database.Node
+import Gargantext.Core.Types.Node
+
 import Gargantext.Core (Lang)
 import Gargantext.Prelude
 
 import Gargantext.Viz.Graph.Index (createIndices, toIndex, map2mat, mat2map)
-import Gargantext.Viz.Graph.Distances.Matrice (distributional)
+import Gargantext.Viz.Graph.Distances.Matrice (distributional, measureConditional)
 import Gargantext.Viz.Graph (Graph(..), data2graph)
 import Gargantext.Text.Metrics.Count (cooc)
 import Gargantext.Text.Metrics (filterCooc, FilterConfig(..), Clusters(..), SampleBins(..), DefaultValue(..), MapListSize(..), InclusionSize(..))
@@ -38,7 +45,7 @@ import Gargantext.Text.Context (splitBy, SplitContext(Sentences))
 
 import Gargantext.Text.Parsers.CSV
 
-import Data.Graph.Clustering.Louvain.CplusPlus (cLouvain)
+import Data.Graph.Clustering.Louvain.CplusPlus (cLouvain, l_community_id)
 
 {-
   ____                             _            _
@@ -50,11 +57,27 @@ import Data.Graph.Clustering.Louvain.CplusPlus (cLouvain)
 -}
 
 
+contextText :: [T.Text]
+contextText = ["The dog is an animal."
+              ,"The bird is an animal."
+              ,"The bird is an animal."
+              ,"The bird and the dog are an animal."
+              ,"The table is an object."
+              ,"The pen is an object."
+              ,"This object is a pen or a table?"
+              ,"The girl has a human body."
+              ,"The girl has a human body."
+              ,"The boy has a human body."
+              ,"The boy has a human body."
+              ]
+
+
+
 data TextFlow = CSV FilePath
               | FullText FilePath
               | Contexts [T.Text]
-              | SQL Int
-              | Database T.Text
+              | DB Connection CorpusId
+              | Query T.Text
                 -- ExtDatabase Query
                 -- IntDatabase NodeId
 
@@ -64,6 +87,7 @@ textFlow termType workType = do
                 FullText path -> splitBy (Sentences 5) <$> readFile path
                 CSV      path -> readCsvOn [csv_title, csv_abstract] path
                 Contexts ctxt -> pure ctxt
+                SQL con corpusId -> catMaybes <$> map (\n -> hyperdataDocumentV3_title (node_hyperdata n)  <> hyperdataDocumentV3_abstract (node_hyperdata n))<$> getDocumentsV3WithParentId con corpusId
                 _             -> undefined
 
   textFlow' termType contexts
@@ -78,53 +102,61 @@ textFlow' termType contexts = do
   -- TermsType = Mono | Multi | MonoMulti
   -- myterms # filter (\t -> not . elem t stopList)
   --         # groupBy (Stem|GroupList|Ontology)
+  printDebug "terms" myterms
   printDebug "myterms" (sum $ map length myterms)
 
   -- Bulding the map list
   -- compute copresences of terms, i.e. cooccurrences of terms in same context of text
   -- Cooc = Map (Term, Term) Int
   let myCooc1 = cooc myterms
-  printDebug "myCooc1" (M.size myCooc1)
+  printDebug "myCooc1 size" (M.size myCooc1)
 
   -- Remove Apax: appears one time only => lighting the matrix
-  let myCooc2 = M.filter (>1) myCooc1
-  printDebug "myCooc2" (M.size myCooc2)
+  let myCooc2 = M.filter (>0) myCooc1
+  printDebug "myCooc2 size" (M.size myCooc2)
+  printDebug "myCooc2" myCooc2
+
 
   -- Filtering terms with inclusion/Exclusion and Specificity/Genericity scores
-  let myCooc3 = filterCooc ( FilterConfig (MapListSize    100 )
-                                          (InclusionSize  900 )
+  let myCooc3 = filterCooc ( FilterConfig (MapListSize    350 )
+                                          (InclusionSize  500 )
                                           (SampleBins      10 )
                                           (Clusters         3 )
                                           (DefaultValue     0 )
                            ) myCooc2
-  printDebug "myCooc3" $ M.size myCooc3
-  -- putStrLn $ show myCooc3
+  printDebug "myCooc3 size" $ M.size myCooc3
+  printDebug "myCooc3" myCooc3
 
   -- Cooc -> Matrix
   let (ti, _) = createIndices myCooc3
-  printDebug "ti" $ M.size ti
+  printDebug "ti size" $ M.size ti
+  printDebug "ti" ti
 
   let myCooc4 = toIndex ti myCooc3
-  printDebug "myCooc4" $ M.size myCooc4
+  printDebug "myCooc4 size" $ M.size myCooc4
+  printDebug "myCooc4" myCooc4
 
   let matCooc = map2mat (0) (M.size ti) myCooc4
+  printDebug "matCooc shape" $ A.arrayShape matCooc
   printDebug "matCooc" matCooc
 
   -- Matrix -> Clustering
-  --let distanceMat = conditional' matCooc
-  let distanceMat = distributional matCooc
-  printDebug "distanceMat" $ A.arrayShape distanceMat
+  let distanceMat = measureConditional matCooc
+  --let distanceMat = distributional matCooc
+  printDebug "distanceMat shape" $ A.arrayShape distanceMat
   printDebug "distanceMat" distanceMat
 --
-  let distanceMap = mat2map distanceMat
-  printDebug "distanceMap" $ M.size distanceMap
+  --let distanceMap = M.filter (>0) $ mat2map distanceMat
+  let distanceMap = M.map (\n -> 1) $ M.filter (>0) $ mat2map distanceMat
+  printDebug "distanceMap size" $ M.size distanceMap
+  printDebug "distanceMap" distanceMap
 
 --  let distance = fromIndex fi distanceMap
 --  printDebug "distance" $ M.size distance
 
   partitions <- cLouvain distanceMap
 -- Building : -> Graph -> JSON
-  printDebug "partitions" $ length partitions
+  printDebug "partitions" $ DS.size $ DS.fromList $ map (l_community_id) partitions
   --printDebug "partitions" partitions
   pure $ data2graph (M.toList ti) myCooc4 distanceMap partitions