{-|
Module      : Gargantext.TextFlow
Description : Server API
Copyright   : (c) CNRS, 2017-Present
License     : AGPL + CECILL v3
Maintainer  : team@gargantext.org
Stability   : experimental
Portability : POSIX

From text to viz, all the flow of texts in Gargantext.

-}

{-# OPTIONS_GHC -fno-warn-name-shadowing #-}
{-# LANGUAGE NoImplicitPrelude           #-}

module Gargantext.TextFlow
  where

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, measureConditional)
import Gargantext.Viz.Graph (Graph(..), data2graph)
import Gargantext.Text.Metrics.Count (cooc)
import Gargantext.Text.Metrics (filterCooc, FilterConfig(..), Clusters(..), SampleBins(..), DefaultValue(..), MapListSize(..), InclusionSize(..))
import Gargantext.Text.Terms (TermType, extractTerms)
import Gargantext.Text.Context (splitBy, SplitContext(Sentences))

import Gargantext.Text.Parsers.CSV

import Data.Graph.Clustering.Louvain.CplusPlus (cLouvain, l_community_id)

{-
  ____                             _            _
 / ___| __ _ _ __ __ _  __ _ _ __ | |_ _____  _| |_
| |  _ / _` | '__/ _` |/ _` | '_ \| __/ _ \ \/ / __|
| |_| | (_| | | | (_| | (_| | | | | ||  __/>  <| |_
 \____|\__,_|_|  \__, |\__,_|_| |_|\__\___/_/\_\\__|
                 |___/
-}


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]
              | DB Connection CorpusId
              | Query T.Text
                -- ExtDatabase Query
                -- IntDatabase NodeId

textFlow :: TermType Lang -> TextFlow -> IO Graph
textFlow termType workType = do
  contexts <- case workType of
                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


textFlow' :: TermType Lang -> [T.Text] -> IO Graph
textFlow' termType contexts = do
  -- Context :: Text -> [Text]
  -- Contexts = Paragraphs n | Sentences n | Chars n

  myterms <- extractTerms termType contexts
  -- 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 size" (M.size myCooc1)

  -- Remove Apax: appears one time only => lighting the matrix
  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    350 )
                                          (InclusionSize  500 )
                                          (SampleBins      10 )
                                          (Clusters         3 )
                                          (DefaultValue     0 )
                           ) myCooc2
  printDebug "myCooc3 size" $ M.size myCooc3
  printDebug "myCooc3" myCooc3

  -- Cooc -> Matrix
  let (ti, _) = createIndices myCooc3
  printDebug "ti size" $ M.size ti
  printDebug "ti" ti

  let myCooc4 = toIndex ti myCooc3
  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 = measureConditional matCooc
  --let distanceMat = distributional matCooc
  printDebug "distanceMat shape" $ A.arrayShape distanceMat
  printDebug "distanceMat" distanceMat
--
  --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" $ DS.size $ DS.fromList $ map (l_community_id) partitions
  --printDebug "partitions" partitions
  pure $ data2graph (M.toList ti) myCooc4 distanceMap partitions