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

   1 {-|
   2 Module      : Gargantext.Core.Viz.Graph.Tools
   3 Description : Tools to build Graph
   4 Copyright   : (c) CNRS, 2017-Present
   5 License     : AGPL + CECILL v3
   6 Maintainer  : team@gargantext.org
   7 Stability   : experimental
   8 Portability : POSIX
   9
  10 -}
  11
  12 {-# LANGUAGE ScopedTypeVariables #-}
  13
  14 module Gargantext.Core.Viz.Graph.Tools
  15   where
  16
  17 -- import Data.Graph.Clustering.Louvain (hLouvain, {-iLouvainMap-})
  18 import Data.HashMap.Strict (HashMap)
  19 import Data.Map (Map)
  20 import Data.Text (Text)
  21 import Debug.Trace (trace)
  22 import GHC.Float (sin, cos)
  23 import Gargantext.API.Ngrams.Types (NgramsTerm(..))
  24 import Gargantext.Core.Methods.Distances (Distance(..), measure)
  25 import Gargantext.Core.Methods.Graph.BAC.Proxemy (confluence)
  26 import Gargantext.Core.Statistics
  27 import Gargantext.Core.Viz.Graph
  28 import Gargantext.Core.Viz.Graph.Bridgeness (bridgeness, Partitions, ToComId(..))
  29 import Gargantext.Core.Viz.Graph.Index (createIndices, toIndex, map2mat, mat2map, Index, MatrixShape(..))
  30 import Gargantext.Core.Viz.Graph.Tools.IGraph (mkGraphUfromEdges, spinglass, ClusterNode)
  31 import Gargantext.Prelude
  32 import IGraph.Random -- (Gen(..))
  33 import qualified Data.HashMap.Strict      as HashMap
  34 import qualified Data.List                as List
  35 import qualified Data.Map                 as Map
  36 import qualified Data.Set                 as Set
  37 import qualified Data.Vector.Storable     as Vec
  38 import qualified IGraph                   as Igraph
  39 import qualified IGraph.Algorithms.Layout as Layout
  40
  41
  42 -------------------------------------------------------------
  43
  44 defaultClustering :: Map (Int, Int) Double -> IO [ClusterNode]
  45 defaultClustering = spinglass 1
  46
  47 -------------------------------------------------------------
  48
  49 type Threshold = Double
  50
  51 cooc2graph' :: Ord t => Distance
  52                      -> Double
  53                      -> Map (t, t) Int
  54                      -> Map (Index, Index) Double
  55 cooc2graph' distance threshold myCooc
  56     = Map.filter (> threshold)
  57     $ mat2map
  58     $ measure distance
  59     $ case distance of
  60         Conditional    -> map2mat Triangle 0 tiSize
  61         Distributional -> map2mat Square   0 tiSize
  62     $ Map.filter (> 1) myCooc'
  63
  64      where
  65         (ti, _) = createIndices myCooc
  66         tiSize  = Map.size ti
  67         myCooc' = toIndex ti myCooc
  68
  69
  70 data PartitionMethod = Louvain | Spinglass
  71
  72 cooc2graphWith :: PartitionMethod
  73                -> Distance
  74                -> Threshold
  75                -> HashMap (NgramsTerm, NgramsTerm) Int
  76                -> IO Graph
  77 cooc2graphWith Louvain   = undefined -- TODO use IGraph bindings
  78 cooc2graphWith Spinglass = cooc2graphWith' (spinglass 1)
  79
  80 cooc2graph'' :: Ord t => Distance
  81                       -> Double
  82                       -> Map (t, t) Int
  83                       -> Map (Index, Index) Double
  84 cooc2graph'' distance threshold myCooc = neighbouMap
  85   where
  86     (ti, _) = createIndices myCooc
  87     myCooc' = toIndex ti myCooc
  88     matCooc = map2mat Triangle 0 (Map.size ti) $ Map.filter (> 1) myCooc'
  89     distanceMat = measure distance matCooc
  90     neighbouMap = filterByNeighbours threshold
  91                 $ mat2map distanceMat
  92
  93
  94 -- Quentin
  95 filterByNeighbours :: Double -> Map (Index, Index) Double -> Map (Index, Index) Double
  96 filterByNeighbours threshold distanceMap = filteredMap
  97   where
  98     indexes :: [Index]
  99     indexes = List.nub $ List.concat $ map (\(idx,idx') -> [idx,idx'] ) $ Map.keys distanceMap
 100     filteredMap :: Map (Index, Index) Double
 101     filteredMap = Map.fromList
 102                 $ List.concat
 103                 $ map (\idx ->
 104                           let selected = List.reverse
 105                                        $ List.sortOn snd
 106                                        $ Map.toList
 107                                        $ Map.filter (> 0)
 108                                        $ Map.filterWithKey (\(from,_) _ -> idx == from) distanceMap
 109                            in List.take (round threshold) selected
 110                       ) indexes
 111
 112 cooc2graphWith' :: ToComId a
 113                => Partitions a
 114                -> Distance
 115                -> Threshold
 116                -> HashMap (NgramsTerm, NgramsTerm) Int
 117                -> IO Graph
 118 cooc2graphWith' doPartitions distance threshold myCooc = do
 119   let
 120     -- TODO remove below
 121     theMatrix = Map.fromList
 122               $ HashMap.toList myCooc
 123
 124     (ti, _) = createIndices theMatrix
 125     tiSize  = Map.size ti
 126     myCooc' = toIndex ti theMatrix
 127     matCooc = case distance of  -- Shape of the Matrix
 128                 Conditional    -> map2mat Triangle 0 tiSize
 129                 Distributional -> map2mat Square     0 tiSize
 130             $ case distance of   -- Removing the Diagonal ?
 131                 Conditional     -> Map.filterWithKey (\(a,b) _ -> a /= b)
 132                 Distributional  -> identity
 133             $ Map.filter (>1) myCooc'
 134
 135     similarities = measure distance matCooc
 136     links = round (let n :: Double = fromIntegral tiSize in n * log n)
 137     distanceMap  = Map.fromList
 138                  $ List.take links
 139                  $ List.sortOn snd
 140                  $ Map.toList
 141                  $ case distance of
 142                      Conditional    -> Map.filter (> threshold)
 143                      Distributional -> Map.filter (> 0)
 144                  $ mat2map similarities
 145
 146     nodesApprox :: Int
 147     nodesApprox = n'
 148       where
 149         (as, bs) = List.unzip $ Map.keys distanceMap
 150         n' = Set.size $ Set.fromList $ as <> bs
 151     ClustersParams rivers _level = clustersParams nodesApprox
 152
 153   printDebug "similarities" similarities
 154
 155   partitions <- if (Map.size distanceMap > 0)
 156       then doPartitions distanceMap
 157       else panic "Text.Flow: DistanceMap is empty"
 158
 159   let
 160     -- bridgeness' = distanceMap
 161     bridgeness' = trace ("Rivers: " <> show rivers)
 162                 $ bridgeness rivers partitions distanceMap
 163
 164     confluence' = confluence (Map.keys bridgeness') 3 True False
 165
 166   pure $ data2graph (Map.toList $ Map.mapKeys unNgramsTerm ti)
 167                     myCooc' bridgeness' confluence' partitions
 168
 169
 170
 171 -- cooc2graph :: Distance
 172 --            -> Threshold
 173 --            -> (Map (Text, Text) Int)
 174 --            -> IO Graph
 175 -- cooc2graph distance threshold myCooc = do
 176 --   printDebug "cooc2graph" distance
 177 --   let
 178 --     -- TODO remove below
 179 --     theMatrix = Map.fromList $ HashMap.toList myCooc
 180 --     (ti, _) = createIndices theMatrix
 181 --     myCooc' = toIndex ti theMatrix
 182 --     matCooc = map2mat 0 (Map.size ti)
 183 --             $ Map.filterWithKey (\(a,b) _ -> a /= b)
 184 --             $ Map.filter (> 1) myCooc'
 185 --     distanceMat = measure distance matCooc
 186 --     distanceMap = Map.filter (> threshold) $ mat2map distanceMat
 187
 188 --     nodesApprox :: Int
 189 --     nodesApprox = n'
 190 --       where
 191 --         (as, bs) = List.unzip $ Map.keys distanceMap
 192 --         n' = Set.size $ Set.fromList $ as <> bs
 193 --     ClustersParams rivers _level = clustersParams nodesApprox
 194
 195 --   printDebug "Start" ("partitions" :: Text)
 196 --   partitions <- if (Map.size distanceMap > 0)
 197 --       -- then iLouvainMap 100 10 distanceMap
 198 --       -- then hLouvain distanceMap
 199 --       then doPartitions distanceMap
 200 --       else panic "Text.Flow: DistanceMap is empty"
 201 --   printDebug "End" ("partitions" :: Text)
 202
 203 --   let
 204 --     -- bridgeness' = distanceMap
 205 --     bridgeness' = trace ("Rivers: " <> show rivers)
 206 --                 $ bridgeness rivers partitions distanceMap
 207 --     confluence' = confluence (Map.keys bridgeness') 3 True False
 208
 209 --   pure $ data2graph (Map.toList $ Map.mapKeys unNgramsTerm ti)
 210 --                     myCooc' bridgeness' confluence' partitions
 211
 212 ------------------------------------------------------------------------
 213 ------------------------------------------------------------------------
 214 data ClustersParams = ClustersParams { bridgness :: Double
 215                                      , louvain   :: Text
 216                                      } deriving (Show)
 217
 218 clustersParams :: Int -> ClustersParams
 219 clustersParams x = ClustersParams (fromIntegral x) "0.00000001" -- y
 220   {- where
 221     y | x < 100  = "0.000001"
 222       | x < 350  = "0.000001"
 223       | x < 500  = "0.000001"
 224       | x < 1000 = "0.000001"
 225       | otherwise = "1"
 226  -}
 227
 228 ----------------------------------------------------------
 229 -- | From data to Graph
 230 data2graph :: ToComId a
 231            => [(Text, Int)]
 232            -> Map (Int, Int) Int
 233            -> Map (Int, Int) Double
 234            -> Map (Int, Int) Double
 235            -> [a]
 236            -> Graph
 237 data2graph labels coocs bridge conf partitions = Graph nodes edges Nothing
 238   where
 239
 240     community_id_by_node_id = Map.fromList $ map nodeId2comId partitions
 241
 242     nodes = map (setCoord ForceAtlas labels bridge)
 243           [ (n, Node { node_size = maybe 0 identity (Map.lookup (n,n) coocs)
 244                    , node_type = Terms -- or Unknown
 245                    , node_id    = cs (show n)
 246                    , node_label = l
 247                    , node_x_coord = 0
 248                    , node_y_coord = 0
 249                    , node_attributes =
 250                      Attributes { clust_default = maybe 0 identity
 251                                 (Map.lookup n community_id_by_node_id) } }
 252                )
 253             | (l, n) <- labels
 254             , Set.member n $ Set.fromList
 255                            $ List.concat
 256                            $ map (\((s,t),d) -> if d > 0 && s /=t then [s,t] else [])
 257                            $ Map.toList bridge
 258             ]
 259
 260     edges = [ Edge { edge_source = cs (show s)
 261                        , edge_target = cs (show t)
 262                        , edge_weight =  d
 263                        , edge_confluence = maybe 0 identity $ Map.lookup (s,t) conf
 264                    -- , edge_confluence = maybe (panic "E: data2graph edges") identity $ Map.lookup (s,t) conf
 265                        , edge_id     = cs (show i)
 266                    }
 267                    | (i, ((s,t), d)) <- zip ([0..]::[Integer] )
 268                                             (Map.toList bridge)
 269                    , s /= t, d > 0
 270                    ]
 271
 272
 273 ------------------------------------------------------------------------
 274
 275 data Layout = KamadaKawai | ACP | ForceAtlas
 276
 277
 278 setCoord' :: (Int -> (Double, Double)) -> (Int, Node) -> Node
 279 setCoord' f (i,n) = n { node_x_coord = x, node_y_coord = y }
 280   where
 281     (x,y) = f i
 282
 283
 284 -- | ACP
 285 setCoord :: Ord a => Layout -> [(a, Int)] -> Map (Int, Int) Double -> (Int, Node) -> Node
 286 setCoord l labels m (n,node) = node { node_x_coord = x
 287                                     , node_y_coord = y
 288                                     }
 289   where
 290     (x,y) = getCoord l labels m n
 291
 292
 293 getCoord :: Ord a
 294          => Layout
 295          -> [(a, Int)]
 296          -> Map (Int, Int) Double
 297          -> Int
 298          -> (Double, Double)
 299 getCoord KamadaKawai _ _m _n = undefined -- layout m n
 300
 301 getCoord ForceAtlas _ _ n = (sin d, cos d)
 302   where
 303     d = fromIntegral n
 304
 305 getCoord ACP labels m n = to2d $ maybe (panic "Graph.Tools no coordinate") identity
 306              $ Map.lookup n
 307              $ pcaReduceTo (Dimension 2)
 308              $ mapArray labels m
 309   where
 310     to2d :: Vec.Vector Double -> (Double, Double)
 311     to2d v  = (x',y')
 312       where
 313         ds = take 2 $ Vec.toList v
 314         x'  = head' "to2d" ds
 315         y'  = last' "to2d" ds
 316
 317     mapArray :: Ord a => [(a, Int)] -> Map (Int, Int) Double -> Map Int (Vec.Vector Double)
 318     mapArray items m' = Map.fromList [ toVec n' ns m' | n' <- ns ]
 319       where
 320         ns = map snd items
 321
 322     toVec :: Int -> [Int] -> Map (Int,Int) Double -> (Int, Vec.Vector Double)
 323     toVec n' ns' m' = (n', Vec.fromList $ map (\n'' -> maybe 0 identity $ Map.lookup (n',n'') m') ns')
 324 ------------------------------------------------------------------------
 325
 326 -- | KamadaKawai Layout
 327 -- TODO TEST: check labels, nodeId and coordinates
 328 layout :: Map (Int, Int) Double -> Int -> Gen -> (Double, Double)
 329 layout m n gen = maybe (panic "") identity $ Map.lookup n $ coord
 330   where
 331     coord :: (Map Int (Double,Double))
 332     coord = Map.fromList $ List.zip (Igraph.nodes g) $ (Layout.layout g p gen)
 333     --p = Layout.defaultLGL
 334     p = Layout.kamadaKawai
 335     g = mkGraphUfromEdges $ map fst $ List.filter (\e -> snd e > 0) $ Map.toList m
 336 -----------------------------------------------------------------------------
 337 -----------------------------------------------------------------------------
 338 -----------------------------------------------------------------------------
 339 -- Debug
 340 {-
 341 -- measure logDistributional
 342 dataDebug = map2mat Square (0::Int) 19 dataBug'
 343
 344 dataBug' :: Map (Int, Int) Int
 345 dataBug' = Map.fromList [((0,0),28),((0,1),8),((0,2),6),((0,3),2),((0,5),4),((0,6),4),((0,7),2),((0,9),7),((0,10),4),((0,13),4),((0,14),2),((0,15),5),((0,16),8),((0,17),3),((1,1),28),((1,2),6),((1,3),7),((1,4),5),((1,5),7),((1,6),5),((1,7),2),((1,9),6),((1,10),7),((1,11),5),((1,13),6),((1,15),6),((1,16),14),((1,18),4),((2,2),39),((2,3),5),((2,4),4),((2,5),3),((2,6),4),((2,7),4),((2,8),3),((2,9),17),((2,10),4),((2,11),8),((2,12),2),((2,13),15),((2,14),4),((2,15),5),((2,16),21),((2,18),4),((3,3),48),((3,4),10),((3,5),7),((3,6),3),((3,7),7),((3,8),6),((3,9),12),((3,10),9),((3,11),8),((3,12),5),((3,13),15),((3,14),5),((3,15),9),((3,16),17),((3,18),4),((4,4),33),((4,5),2),((4,6),5),((4,7),7),((4,8),4),((4,9),6),((4,10),12),((4,11),8),((4,12),3),((4,13),16),((4,14),4),((4,15),4),((4,16),5),((4,17),2),((4,18),12),((5,5),27),((5,6),2),((5,8),3),((5,9),12),((5,10),6),((5,11),9),((5,13),4),((5,14),2),((5,15),7),((5,16),11),((5,18),4),((6,6),34),((6,7),4),((6,8),3),((6,9),12),((6,10),8),((6,11),2),((6,12),5),((6,13),6),((6,14),6),((6,15),5),((6,16),22),((6,17),8),((6,18),4),((7,7),27),((7,8),2),((7,9),6),((7,10),2),((7,11),4),((7,13),13),((7,15),2),((7,16),8),((7,17),6),((7,18),4),((8,8),30),((8,9),9),((8,10),6),((8,11),9),((8,12),6),((8,13),3),((8,14),3),((8,15),4),((8,16),15),((8,17),3),((8,18),5),((9,9),69),((9,10),9),((9,11),22),((9,12),15),((9,13),18),((9,14),10),((9,15),14),((9,16),48),((9,17),6),((9,18),9),((10,10),39),((10,11),15),((10,12),5),((10,13),11),((10,14),2),((10,15),4),((10,16),19),((10,17),3),((10,18),11),((11,11),48),((11,12),9),((11,13),20),((11,14),2),((11,15),13),((11,16),29),((11,18),13),((12,12),30),((12,13),4),((12,15),5),((12,16),16),((12,17),6),((12,18),2),((13,13),65),((13,14),10),((13,15),14),((13,16),23),((13,17),6),((13,18),10),((14,14),25),((14,16),9),((14,17),3),((14,18),3),((15,15),38),((15,16),17),((15,18),4),((16,16),99),((16,17),11),((16,18),14),((17,17),29),((18,18),23)]
 346 -}