{-| Module : Gargantext.Core.Text.Ngrams.Lists Description : Tools to build lists Copyright : (c) CNRS, 2017-Present License : AGPL + CECILL v3 Maintainer : team@gargantext.org Stability : experimental Portability : POSIX -} {-# LANGUAGE ScopedTypeVariables #-} {-# LANGUAGE TemplateHaskell #-} {-# LANGUAGE BangPatterns #-} module Gargantext.Core.Text.List where import Control.Lens hiding (both) -- ((^.), view, over, set, (_1), (_2)) import Data.HashMap.Strict (HashMap) import Data.HashSet (HashSet) import Data.Map (Map) import Data.Monoid (mempty) import Data.Ord (Down(..)) import Data.Set (Set) import Data.Text (Text) import Data.Tuple.Extra (both) import Gargantext.API.Ngrams.Types (NgramsElement, NgramsTerm(..)) import Gargantext.Core.NodeStory import Gargantext.Core.Text (size) import Gargantext.Core.Text.List.Group import Gargantext.Core.Text.List.Group.Prelude import Gargantext.Core.Text.List.Group.WithStem import Gargantext.Core.Text.List.Social import Gargantext.Core.Text.List.Social.Prelude import Gargantext.Core.Text.Metrics (scored', Scored(..), scored_speExc, scored_genInc, normalizeGlobal, normalizeLocal, scored_terms) import Gargantext.Core.Types (ListType(..), MasterCorpusId, UserCorpusId) import Gargantext.Core.Types.Individu (User(..)) import Gargantext.Database.Action.Metrics.NgramsByContext (getContextsByNgramsUser, getContextsByNgramsOnlyUser) import Gargantext.Database.Action.Metrics.TFICF (getTficf_withSample) import Gargantext.Database.Admin.Types.Node (NodeId) import Gargantext.Database.Prelude (CmdM) import Gargantext.Database.Query.Table.Ngrams (text2ngrams) import Gargantext.Database.Query.Table.NgramsPostag (selectLems) import Gargantext.Database.Query.Table.Node (defaultList) import Gargantext.Database.Query.Table.Node.Error (HasNodeError()) import Gargantext.Database.Query.Tree.Error (HasTreeError) import Gargantext.Database.Schema.Ngrams (NgramsType(..), Ngrams(..)) import Gargantext.Prelude import qualified Data.HashMap.Strict as HashMap import qualified Data.HashSet as HashSet import qualified Data.List as List import qualified Data.Map as Map import qualified Data.Set as Set import qualified Gargantext.Data.HashMap.Strict.Utils as HashMap {- -- TODO maybe useful for later isStopTerm :: StopSize -> Text -> Bool isStopTerm (StopSize n) x = Text.length x < n || any isStopChar (Text.unpack x) where isStopChar c = not (c `elem` ("- /()%" :: [Char]) || Char.isAlpha c) -} -- | TODO improve grouping functions of Authors, Sources, Institutes.. buildNgramsLists :: ( HasNodeStory env err m , CmdM env err m , HasTreeError err , HasNodeError err ) => User -> UserCorpusId -> MasterCorpusId -> Maybe FlowSocialListWith -> GroupParams -> m (Map NgramsType [NgramsElement]) buildNgramsLists user uCid mCid mfslw gp = do ngTerms <- buildNgramsTermsList user uCid mCid mfslw gp (NgramsTerms, MapListSize 350) othersTerms <- mapM (buildNgramsOthersList user uCid mfslw GroupIdentity) [ (Authors , MapListSize 9, MaxListSize 1000) , (Sources , MapListSize 9, MaxListSize 1000) , (Institutes, MapListSize 9, MaxListSize 1000) ] pure $ Map.unions $ [ngTerms] <> othersTerms data MapListSize = MapListSize { unMapListSize :: !Int } data MaxListSize = MaxListSize { unMaxListSize :: !Int } buildNgramsOthersList :: ( HasNodeError err , CmdM env err m , HasNodeStory env err m , HasTreeError err ) => User -> UserCorpusId -> Maybe FlowSocialListWith -> GroupParams -> (NgramsType, MapListSize, MaxListSize) -> m (Map NgramsType [NgramsElement]) buildNgramsOthersList user uCid mfslw _groupParams (nt, MapListSize mapListSize, MaxListSize maxListSize) = do allTerms :: HashMap NgramsTerm (Set NodeId) <- getContextsByNgramsUser uCid nt -- PrivateFirst for first developments since Public NodeMode is not implemented yet socialLists :: FlowCont NgramsTerm FlowListScores <- flowSocialList mfslw user nt ( FlowCont HashMap.empty $ HashMap.fromList $ List.zip (HashMap.keys allTerms) (List.cycle [mempty]) ) let groupedWithList = toGroupedTree {- groupParams -} socialLists allTerms (stopTerms, tailTerms) = HashMap.partition ((== Just StopTerm) . viewListType) $ view flc_scores groupedWithList (mapTerms, tailTerms') = HashMap.partition ((== Just MapTerm) . viewListType) tailTerms listSize = mapListSize - (List.length mapTerms) (mapTerms', candiTerms) = both HashMap.fromList $ List.splitAt listSize $ List.take maxListSize $ List.sortOn (Down . viewScore . snd) $ HashMap.toList tailTerms' pure $ Map.fromList [( nt, List.take maxListSize $ (toNgramsElement stopTerms) <> (toNgramsElement mapTerms ) <> (toNgramsElement $ setListType (Just MapTerm ) mapTerms' ) <> (toNgramsElement $ setListType (Just CandidateTerm) candiTerms) )] getGroupParams :: ( HasNodeError err , CmdM env err m , HasNodeStory env err m , HasTreeError err ) => GroupParams -> HashSet Ngrams -> m GroupParams getGroupParams gp@(GroupWithPosTag l a _m) ng = do !hashMap <- HashMap.fromList <$> selectLems l a (HashSet.toList ng) -- printDebug "hashMap" hashMap pure $ over gwl_map (\x -> x <> hashMap) gp getGroupParams gp _ = pure gp -- TODO use ListIds buildNgramsTermsList :: ( HasNodeError err , CmdM env err m , HasNodeStory env err m , HasTreeError err ) => User -> UserCorpusId -> MasterCorpusId -> Maybe FlowSocialListWith -> GroupParams -> (NgramsType, MapListSize) -> m (Map NgramsType [NgramsElement]) buildNgramsTermsList user uCid mCid mfslw groupParams (nt, _mapListSize)= do -- Filter 0 With Double -- Computing global speGen score printDebug "[buildNgramsTermsList: Sample List] / start" nt !(allTerms :: HashMap NgramsTerm Double) <- getTficf_withSample uCid mCid nt printDebug "[buildNgramsTermsList: Sample List / end]" (nt, HashMap.size allTerms) printDebug "[buildNgramsTermsList: Flow Social List / start]" nt -- PrivateFirst for first developments since Public NodeMode is not implemented yet !(socialLists :: FlowCont NgramsTerm FlowListScores) <- flowSocialList mfslw user nt ( FlowCont HashMap.empty $ HashMap.fromList $ List.zip (HashMap.keys allTerms) (List.cycle [mempty]) ) printDebug "[buildNgramsTermsList: Flow Social List / end]" nt let !ngramsKeys = HashSet.fromList $ List.take 1000 $ HashSet.toList $ HashMap.keysSet allTerms printDebug "[buildNgramsTermsList: ngramsKeys]" (HashSet.size ngramsKeys) !groupParams' <- getGroupParams groupParams (HashSet.map (text2ngrams . unNgramsTerm) ngramsKeys) printDebug "[buildNgramsTermsList: groupParams']" (""::Text) let !socialLists_Stemmed = addScoreStem groupParams' ngramsKeys socialLists --printDebug "socialLists_Stemmed" socialLists_Stemmed !groupedWithList = toGroupedTree socialLists_Stemmed allTerms !(stopTerms, candidateTerms) = HashMap.partition ((== Just StopTerm) . viewListType) $ HashMap.filter (\g -> (view gts'_score g) > 1) $ view flc_scores groupedWithList !(groupedMono, groupedMult) = HashMap.partitionWithKey (\(NgramsTerm t) _v -> size t < 2) candidateTerms printDebug "[buildNgramsTermsList] stopTerms" stopTerms -- splitting monterms and multiterms to take proportional candidates -- use % of list if to big, or Int if too small let !listSizeGlobal = 2000 :: Double !monoSize = 0.4 :: Double !multSize = 1 - monoSize splitAt n' ns = both (HashMap.fromListWith (<>)) $ List.splitAt (round $ n' * listSizeGlobal) $ List.sortOn (viewScore . snd) $ HashMap.toList ns !(groupedMonoHead, _groupedMonoTail) = splitAt monoSize groupedMono !(groupedMultHead, groupedMultTail) = splitAt multSize groupedMult ------------------------- -- Filter 1 With Set NodeId and SpeGen !selectedTerms = Set.toList $ hasTerms (groupedMonoHead <> groupedMultHead) printDebug "[buildNgramsTermsList: selectedTerms]" selectedTerms -- TODO remove (and remove HasNodeError instance) !userListId <- defaultList uCid !masterListId <- defaultList mCid !mapTextDocIds <- getContextsByNgramsOnlyUser uCid [userListId, masterListId] nt selectedTerms printDebug "[buildNgramsTermsList: mapTextDocIds]" mapTextDocIds let groupedTreeScores_SetNodeId :: HashMap NgramsTerm (GroupedTreeScores (Set NodeId)) !groupedTreeScores_SetNodeId = HashMap.filter (\g -> Set.size (view gts'_score g) > 1) -- removing hapax $ setScoresWithMap mapTextDocIds (groupedMonoHead <> groupedMultHead) printDebug "[buildNgramsTermsList: groupedTreeScores_SetNodeId]" groupedTreeScores_SetNodeId -- Coocurrences computation --, t1 >= t2 -- permute byAxis diag -- since matrix symmetric let !mapCooc = HashMap.filter (>1) -- removing cooc of 1 $ HashMap.fromList [ ((t1, t2), Set.size $ Set.intersection s1 s2) | (t1, s1) <- mapStemNodeIds , (t2, s2) <- mapStemNodeIds ] where mapStemNodeIds = HashMap.toList $ HashMap.map viewScores $ groupedTreeScores_SetNodeId let -- computing scores mapScores f = HashMap.fromList $ map (\g -> (view scored_terms g, f g)) $ normalizeGlobal $ map normalizeLocal $ scored' $ Map.fromList -- TODO remove this $ HashMap.toList mapCooc let groupedTreeScores_SpeGen :: HashMap NgramsTerm (GroupedTreeScores (Scored NgramsTerm)) !groupedTreeScores_SpeGen = setScoresWithMap (mapScores identity) groupedTreeScores_SetNodeId let -- sort / partition / split -- filter mono/multi again !(monoScored, multScored) = HashMap.partitionWithKey (\(NgramsTerm t) _v -> size t < 2) groupedTreeScores_SpeGen -- filter with max score partitionWithMaxScore = HashMap.partition (\g -> (view scored_genInc $ view gts'_score g) > (view scored_speExc $ view gts'_score g) ) !(monoScoredIncl, monoScoredExcl) = partitionWithMaxScore monoScored !(multScoredIncl, multScoredExcl) = partitionWithMaxScore multScored -- splitAt let -- use % of list if to big, or Int if to small !mapSize = 1000 :: Double !canSize = mapSize * 2 :: Double !inclSize = 0.4 :: Double !exclSize = 1 - inclSize splitAt' max' n' = (both (HashMap.fromList)) . (List.splitAt (round $ n' * max')) sortOn f = (List.sortOn (Down . (view (gts'_score . f)) . snd)) . HashMap.toList monoInc_size n = splitAt' n $ monoSize * inclSize / 2 multExc_size n = splitAt' n $ multSize * exclSize / 2 !(mapMonoScoredInclHead, monoScoredInclTail) = monoInc_size mapSize $ (sortOn scored_genInc) monoScoredIncl !(mapMonoScoredExclHead, monoScoredExclTail) = monoInc_size mapSize $ (sortOn scored_speExc) monoScoredExcl !(mapMultScoredInclHead, multScoredInclTail) = multExc_size mapSize $ (sortOn scored_genInc) multScoredIncl !(mapMultScoredExclHead, multScoredExclTail) = multExc_size mapSize $ (sortOn scored_speExc) multScoredExcl !(canMonoScoredIncHead , _) = monoInc_size canSize $ (sortOn scored_genInc) monoScoredInclTail !(canMonoScoredExclHead, _) = monoInc_size canSize $ (sortOn scored_speExc) monoScoredExclTail !(canMulScoredInclHead, _) = multExc_size canSize $ (sortOn scored_genInc) multScoredInclTail !(canMultScoredExclHead, _) = multExc_size canSize $ (sortOn scored_speExc) multScoredExclTail ------------------------------------------------------------ -- Final Step building the Typed list -- Candidates Terms need to be filtered let !maps = setListType (Just MapTerm) $ mapMonoScoredInclHead <> mapMonoScoredExclHead <> mapMultScoredInclHead <> mapMultScoredExclHead -- An original way to filter to start with !cands = setListType (Just CandidateTerm) $ canMonoScoredIncHead <> canMonoScoredExclHead <> canMulScoredInclHead <> canMultScoredExclHead -- TODO count it too !cands' = setListType (Just CandidateTerm) {-\$ groupedMonoTail <>-} groupedMultTail -- Quick FIX !candNgramsElement = List.take 1000 $ toNgramsElement cands <> toNgramsElement cands' !result = Map.unionsWith (<>) [ Map.fromList [( nt, toNgramsElement maps <> toNgramsElement stopTerms <> candNgramsElement )] ] pure result