[REST] Adding Graph api end point.

src/Gargantext/API.hs

@@ -68,6 +68,7 @@ import Gargantext.API.FrontEnd (FrontEndAPI, frontEndServer)
 import Gargantext.API.Node ( Roots    , roots
                            , NodeAPI  , nodeAPI
                            , NodesAPI , nodesAPI
+                           , GraphAPI, graphAPI
                            )
 import Gargantext.API.Count  ( CountAPI, count, Query)
 import Gargantext.API.Search ( SearchAPI, search, SearchQuery)
@@ -215,6 +216,9 @@ type GargAPI =
            -- Corpus endpoint
            :<|> "search":> Summary "Search endpoint"
                         :> ReqBody '[JSON] SearchQuery :> SearchAPI
+           
+           :<|> "graph" :> Summary "Graph endpoint"
+                        :> Capture "id" Int         :> GraphAPI
 
        --    :<|> "scraper" :> WithCallbacks ScraperAPI
 
@@ -242,6 +246,7 @@ server env = do
      :<|> nodesAPI conn
      :<|> count
      :<|> search conn
+     :<|> graphAPI conn
   --   :<|> orchestrator
   where
     conn = env ^. env_conn

src/Gargantext/API/Node.hs

@@ -45,6 +45,11 @@ import Gargantext.Database.Node ( getNodesWithParentId
 import Gargantext.Database.Facet (FacetDoc, getDocFacet
                                  ,FacetChart)
 
+-- Graph
+import Gargantext.TextFlow
+import Gargantext.Viz.Graph (Graph)
+import Gargantext.Core (Lang(..))
+import Gargantext.Text.Terms (TermType(..))
 -------------------------------------------------------------------
 -------------------------------------------------------------------
 -- | Node API Types management
@@ -101,6 +106,12 @@ roots conn = liftIO (putStrLn ( "/user" :: Text) >> getNodesWithParentId conn 0
           :<|> pure (panic "not implemented yet")
           :<|> pure (panic "not implemented yet")
 
+
+type GraphAPI   = Get '[JSON] Graph
+graphAPI :: Connection -> NodeId -> Server GraphAPI
+graphAPI _ _ = liftIO $ textFlow (Mono EN) (Contexts contextText)
+
+
 nodeAPI :: Connection -> NodeId -> Server NodeAPI
 nodeAPI conn id =  liftIO (putStrLn ("/node" :: Text) >> getNode              conn id )
               :<|> deleteNode'   conn id
@@ -110,6 +121,8 @@ nodeAPI conn id =  liftIO (putStrLn ("/node" :: Text) >> getNode              co
               -- :<|> upload
               -- :<|> query
 
+
+
 nodesAPI :: Connection -> [NodeId] -> Server NodesAPI
 nodesAPI conn ids = deleteNodes' conn ids
 

src/Gargantext/Viz/Graph.hs

@@ -16,6 +16,7 @@ Portability : POSIX
 module Gargantext.Viz.Graph
   where
 
+------------------------------------------------------------------------
 import GHC.IO (FilePath)
 import GHC.Generics (Generic)
 import Data.Aeson.TH (deriveJSON)
@@ -23,19 +24,26 @@ import qualified Data.Aeson as DA
 
 import Data.ByteString.Lazy as DBL (readFile, writeFile)
 
-import Data.Text (Text)
+import Data.Text (Text, pack)
 import qualified Text.Read as T
 import qualified Data.Text as T
 
 import Data.Map.Strict (Map)
 import qualified Data.Map.Strict as M
 
+import Data.Swagger (ToSchema)
+
 import Gargantext.Prelude
 import Gargantext.Core.Types (Label)
 import Gargantext.Core.Utils.Prefix (unPrefix)
 
 import Data.Graph.Clustering.Louvain.CplusPlus (LouvainNode(..))
 
+import Test.QuickCheck.Arbitrary (Arbitrary, arbitrary)
+import Test.QuickCheck (elements)
+
+------------------------------------------------------------------------
+
 data TypeNode = Terms | Unknown
   deriving (Show, Generic)
 
@@ -67,6 +75,19 @@ data Graph = Graph { graph_nodes :: [Node]
                    }
   deriving (Show, Generic)
 $(deriveJSON (unPrefix "graph_") ''Graph)
+
+-- | Intances for Swagger documentation
+instance ToSchema Node
+instance ToSchema TypeNode
+instance ToSchema Attributes
+instance ToSchema Edge
+instance ToSchema Graph
+
+-- | Intances for the mack
+instance Arbitrary Graph where
+  arbitrary = elements $ [Graph {graph_nodes = [Node {node_size = 4, node_type = Terms, node_id = pack "0", node_label = pack "animal", node_attributes = Attributes {clust_default = 0}},Node {node_size = 3, node_type = Terms, node_id = pack "1", node_label = pack "bird", node_attributes = Attributes {clust_default = 0}},Node {node_size = 2, node_type = Terms, node_id = pack "2", node_label = pack "boy", node_attributes = Attributes {clust_default = 1}},Node {node_size = 2, node_type = Terms, node_id = pack "3", node_label = pack "dog", node_attributes = Attributes {clust_default = 0}},Node {node_size = 2, node_type = Terms, node_id = pack "4", node_label = pack "girl", node_attributes = Attributes {clust_default = 1}},Node {node_size = 4, node_type = Terms, node_id = pack "5", node_label = pack "human body", node_attributes = Attributes {clust_default = 1}},Node {node_size = 3, node_type = Terms, node_id = pack "6", node_label = pack "object", node_attributes = Attributes {clust_default = 2}},Node {node_size = 2, node_type = Terms, node_id = pack "7", node_label = pack "pen", node_attributes = Attributes {clust_default = 2}},Node {node_size = 2, node_type = Terms, node_id = pack "8", node_label = pack "table", node_attributes = Attributes {clust_default = 2}}], graph_edges = [Edge {edge_source = pack "0", edge_target = pack "0", edge_weight = 1.0, edge_id = pack "0"},Edge {edge_source = pack "1", edge_target = pack "0", edge_weight = 1.0, edge_id = pack "1"},Edge {edge_source = pack "1", edge_target = pack "1", edge_weight = 1.0, edge_id = pack "2"},Edge {edge_source = pack "2", edge_target = pack "2", edge_weight = 1.0, edge_id = pack "3"},Edge {edge_source = pack "2", edge_target = pack "5", edge_weight = 1.0, edge_id = pack "4"},Edge {edge_source = pack "3", edge_target = pack "0", edge_weight = 1.0, edge_id = pack "5"},Edge {edge_source = pack "3", edge_target = pack "1", edge_weight = 1.0, edge_id = pack "6"},Edge {edge_source = pack "3", edge_target = pack "3", edge_weight = 1.0, edge_id = pack "7"},Edge {edge_source = pack "4", edge_target = pack "4", edge_weight = 1.0, edge_id = pack "8"},Edge {edge_source = pack "4", edge_target = pack "5", edge_weight = 1.0, edge_id = pack "9"},Edge {edge_source = pack "5", edge_target = pack "5", edge_weight = 1.0, edge_id = pack "10"},Edge {edge_source = pack "6", edge_target = pack "6", edge_weight = 1.0, edge_id = pack "11"},Edge {edge_source = pack "7", edge_target = pack "6", edge_weight = 1.0, edge_id = pack "12"},Edge {edge_source = pack "7", edge_target = pack "7", edge_weight = 1.0, edge_id = pack "13"},Edge {edge_source = pack "8", edge_target = pack "6", edge_weight = 1.0, edge_id = pack "14"},Edge {edge_source = pack "8", edge_target = pack "7", edge_weight = 1.0, edge_id = pack "15"},Edge {edge_source = pack "8", edge_target = pack "8", edge_weight = 1.0, edge_id = pack "16"}]}]
+
+
 -----------------------------------------------------------
 -- Old Gargantext Version
 

src/Gargantext/Viz/Graph/Distances/Matrice.hs

@@ -117,7 +117,6 @@ matProba r mat = zipWith (/) mat (matSum r mat)
 diag :: Elt e => Acc (Matrix e) -> Acc (Vector e)
 diag m = backpermute (indexTail (shape m)) (lift1 (\(Z :. x) -> (Z :. x :. (x :: Exp Int)))) m
 
-
 -- | Divide by the Diagonal of the matrix
 --
 -- >>> run $ divByDiag 3 (use $ matrix 3 ([1..] :: [Double]))
@@ -209,21 +208,25 @@ conditional' m = (run $ ie $ map fromIntegral $ use m, run $ sg $ map fromIntegr
 -- Distributional measure is a relative measure which depends on the
 -- selected list, it represents structural equivalence.
 --
--- The distributional measure \[P_c\] of @i@ and @j@ terms is: \[
+-- The distributional measure P(c) of @i@ and @j@ terms is: \[
 -- S_{MI} = \frac {\sum_{k \neq i,j ; MI_{ik} >0}^{} \min(MI_{ik},
 -- MI_{jk})}{\sum_{k \neq i,j ; MI_{ik}}^{}} \]
 --
 -- Mutual information
--- \[S{MI}({i},{j}) = \log(\frac{C{ij}}{E{ij}})\]
+-- \[S_{MI}({i},{j}) = \log(\frac{C{ij}}{E{ij}})\]
 --
 -- Number of cooccurrences of @i@ and @j@ in the same context of text
 --                        \[C{ij}\]
 --
--- The expected value of the cooccurrences
---            \[E_{ij} = \frac {S_{i} S_{j}} {N}\]
+-- The expected value of the cooccurrences @i@ and @j@ (given a map list of size @n@)
+--            \[E_{ij}^{m} = \frac {S_{i} S_{j}} {N_{m}}\]
+--
+-- Total cooccurrences of term @i@ given a map list of size @m@
+--            \[S_{i} = \sum_{j, j \neq i}^{m} S_{ij}\]
+--
+-- Total cooccurrences of terms given a map list of size @m@
+--            \[N_{m} = \sum_{i,i \neq i}^{m} \sum_{j, j \neq j}^{m} S_{ij}\]
 --
--- Total cooccurrences of @i@ term
---            \[N_{i} = \sum_{i}^{} S_{i}\]
 distributional :: Matrix Int -> Matrix Double
 distributional m = run $ matMiniMax $ ri (map fromIntegral $ use m)
   where
@@ -232,17 +235,17 @@ distributional m = run $ matMiniMax $ ri (map fromIntegral $ use m)
     
     ri mat = zipWith (/) mat1 mat2
       where
-        mat1 = matSum n $ zipWith min (mi mat) (mi $ transpose mat)
+        mat1 = matSum n $ zipWith min (s_mi mat) (s_mi $ transpose mat)
         mat2 = matSum n mat
     
-    mi    m'  = zipWith (\a b -> max (log $ a/b) 0)  m'
+    s_mi    m'  = zipWith (\a b -> log (a/b))  m'
               $ zipWith (/) (crossProduct m') (total m')
 
     total m'' = replicate (constant (Z :. n :. n)) $ fold (+) 0 $ fold (+) 0 m''
-    n    = dim m
+    n         = dim m
     
     crossProduct m''' = zipWith (*) (cross m'''  ) (cross (transpose m'''))
-    cross mat      = zipWith (-) (matSum n mat) (mat)
+    cross mat         = zipWith (-) (matSum n mat) (mat)
 
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