src/Gargantext/Text/Metrics.hs

   1 {-|
   2 Module      : Gargantext.Text.Metrics
   3 Description : All parsers of Gargantext in one file.
   4 Copyright   : (c) CNRS, 2017 - present
   5 License     : AGPL + CECILL v3
   6 Maintainer  : team@gargantext.org
   7 Stability   : experimental
   8 Portability : POSIX
   9
  10 Mainly reexport functions in @Data.Text.Metrics@
  11
  12
  13 TODO
  14 noApax :: Ord a => Map a Occ -> Map a Occ
  15 noApax m = M.filter (>1) m
  16
  17 -}
  18
  19 {-# LANGUAGE BangPatterns      #-}
  20 {-# LANGUAGE NoImplicitPrelude #-}
  21 {-# LANGUAGE OverloadedStrings #-}
  22
  23 module Gargantext.Text.Metrics
  24   where
  25
  26 import Data.Text (Text, pack)
  27 import Data.Map (Map)
  28 import qualified Data.List as L
  29 import qualified Data.Map  as M
  30 import qualified Data.Set  as S
  31 import qualified Data.Text as T
  32 import qualified Data.Vector as V
  33 import qualified Data.Vector.Unboxed as VU
  34 import Data.Tuple.Extra (both)
  35 --import GHC.Real (Ratio)
  36 --import qualified Data.Text.Metrics as DTM
  37 import Data.Array.Accelerate (toList)
  38 import Math.KMeans (kmeans, euclidSq, elements)
  39
  40
  41 import Gargantext.Prelude
  42
  43 import Gargantext.Text.Metrics.Count (occurrences, cooc)
  44 import Gargantext.Text.Terms (TermType(MonoMulti), terms)
  45 import Gargantext.Core (Lang(EN))
  46 import Gargantext.Core.Types (Terms(..))
  47 import Gargantext.Text.Context (splitBy, SplitContext(Sentences))
  48
  49 import Gargantext.Viz.Graph.Distances.Matrice
  50 import Gargantext.Viz.Graph.Index
  51
  52 import qualified Data.Array.Accelerate.Interpreter as DAA
  53 import qualified Data.Array.Accelerate as DAA
  54 -- import Data.Array.Accelerate ((:.)(..), Z(..))
  55
  56 import GHC.Real (round)
  57
  58 import Debug.Trace
  59 import Prelude (seq)
  60
  61 data MapListSize   = MapListSize   Int
  62 data InclusionSize = InclusionSize Int
  63 data SampleBins    = SampleBins    Double
  64 data Clusters      = Clusters      Int
  65 data DefaultValue  = DefaultValue  Int
  66
  67 data FilterConfig = FilterConfig { fc_mapListSize   :: MapListSize
  68                                  , fc_inclusionSize :: InclusionSize
  69                                  , fc_sampleBins    :: SampleBins
  70                                  , fc_clusters      :: Clusters
  71                                  , fc_defaultValue  :: DefaultValue
  72                              }
  73
  74 filterCooc :: Ord t => FilterConfig -> Map (t, t) Int -> Map (t, t) Int
  75 filterCooc fc cc = (filterCooc' fc) ts cc
  76   where
  77     ts     = map _scored_terms $ takeSome fc $ coocScored cc
  78
  79
  80 filterCooc' :: Ord t => FilterConfig -> [t] -> Map (t, t) Int -> Map (t, t) Int
  81 filterCooc' (FilterConfig _ _ _ _ (DefaultValue dv)) ts m = -- trace ("coocScored " <> show (length ts)) $
  82   foldl' (\m' k -> M.insert k (maybe dv identity $ M.lookup k m) m')
  83     M.empty selection
  84   where
  85     selection  = [(x,y) | x <- ts, y <- ts, x > y]
  86
  87
  88 -- | Map list creation
  89 -- Kmeans split into (Clusters::Int) main clusters with Inclusion/Exclusion (relevance score)
  90 -- Sample the main cluster ordered by specificity/genericity in (SampleBins::Double) parts
  91 -- each parts is then ordered by Inclusion/Exclusion
  92 -- take n scored terms in each parts where n * SampleBins = MapListSize.
  93 takeSome :: Ord t => FilterConfig -> [Scored t] -> [Scored t]
  94 takeSome (FilterConfig (MapListSize l) (InclusionSize l') (SampleBins s) (Clusters k) _) scores = L.take l
  95                     $ takeSample n m
  96                     $ L.take l' $ L.reverse $ L.sortOn _scored_incExc scores
  97                     -- $ splitKmeans k scores
  98   where
  99     -- TODO: benchmark with accelerate-example kmeans version
 100     splitKmeans x xs = L.concat $ map elements
 101                      $ V.take (k-1)
 102                      $ kmeans (\i -> VU.fromList ([(_scored_incExc i :: Double)]))
 103                               euclidSq x xs
 104     n = round ((fromIntegral l)/s)
 105     m = round $ (fromIntegral $ length scores) / (s)
 106     takeSample n m xs = -- trace ("splitKmeans " <> show (length xs)) $
 107                         L.concat $ map (L.take n)
 108                                  $ map (reverse . (L.sortOn _scored_incExc))
 109                                  -- TODO use kmeans s instead of splitEvery
 110                                  -- in order to split in s heteregenous parts
 111                                  -- without homogeneous order hypothesis
 112                                  $ splitEvery m
 113                                  $ L.reverse $ L.sortOn _scored_speGen xs
 114
 115
 116 data Scored t = Scored { _scored_terms  :: !t
 117                        , _scored_incExc :: !InclusionExclusion
 118                        , _scored_speGen :: !SpecificityGenericity
 119                      } deriving (Show)
 120
 121 coocScored :: Ord t => Map (t,t) Int -> [Scored t]
 122 coocScored m = zipWith (\(i,t) (inc,spe) -> Scored t inc spe) (M.toList fi) scores
 123   where
 124     (ti,fi) = createIndices m
 125     (is, ss) = incExcSpeGen $ cooc2mat ti m
 126     scores = DAA.toList $ DAA.run $ DAA.zip (DAA.use is) (DAA.use ss)
 127
 128
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 145
 146
 147 incExcSpeGen_sorted :: Ord t => Map (t,t) Int -> ([(t,Double)],[(t,Double)])
 148 incExcSpeGen_sorted m = both ordonne (incExcSpeGen $ cooc2mat ti m)
 149   where
 150     (ti,fi) = createIndices m
 151     ordonne x = L.reverse $ L.sortOn snd $ zip (map snd $ M.toList fi) (toList x)
 152
 153
 154
 155 metrics_text :: Text
 156 metrics_text = T.intercalate " " metrics_sentences
 157
 158 metrics_sentences' :: [Text]
 159 metrics_sentences' = splitBy (Sentences 0) metrics_text
 160
 161 -- | Sentences
 162 metrics_sentences :: [Text]
 163 metrics_sentences = [ "There is a table with a glass of wine and a spoon."
 164                     , "I can see the glass on the table."
 165                     , "There was only a spoon on that table."
 166                     , "The glass just fall from the table, pouring wine everywhere."
 167                     , "I wish the glass did not contain wine."
 168                     ]
 169
 170 metrics_sentences_Test = metrics_sentences == metrics_sentences'
 171
 172 -- | Terms reordered to visually check occurrences
 173 -- >>>
 174 {- [ [["table"],["glass"],["wine"],["spoon"]]
 175    , [["glass"],["table"]]
 176    , [["spoon"],["table"]]
 177    , [["glass"],["table"],["wine"]]
 178    , [["glass"],["wine"]]
 179    ]
 180 -}
 181
 182 metrics_terms :: IO [[Terms]]
 183 metrics_terms = mapM (terms (MonoMulti EN)) $ splitBy (Sentences 0) metrics_text
 184
 185 -- | Occurrences
 186 {-
 187 fromList [ (fromList ["table"] ,fromList [(["table"] , 3 )])]
 188          , (fromList ["object"],fromList [(["object"], 3 )])
 189          , (fromList ["glas"]  ,fromList [(["glas"]  , 2 )])
 190          , (fromList ["spoon"] ,fromList [(["spoon"] , 2 )])
 191 -}
 192 metrics_occ = occurrences <$> L.concat <$> metrics_terms
 193
 194 {-
 195 -- fromList [((["glas"],["object"]),6)
 196             ,((["glas"],["spoon"]),4)
 197             ,((["glas"],["table"]),6),((["object"],["spoon"]),6),((["object"],["table"]),9),((["spoon"],["table"]),6)]
 198
 199 -}
 200 metrics_cooc = cooc <$> metrics_terms
 201
 202 metrics_cooc_mat = do
 203   m <- metrics_cooc
 204   let (ti,_) = createIndices m
 205   let mat_cooc = cooc2mat ti m
 206   pure ( ti
 207        , mat_cooc
 208        , incExcSpeGen_proba  mat_cooc
 209        , incExcSpeGen        mat_cooc
 210        )
 211
 212 metrics_incExcSpeGen = incExcSpeGen_sorted <$> metrics_cooc
 213