{-# LANGUAGE OverloadedLists #-}

module Clustering.FrequentItemSet.AprioriSpec where

import Control.Monad (Monad (..))
import Data.List qualified as List
import Test.Syd
import Test.Syd.Validity

import Clustering.FrequentItemSet.Apriori

spec = do
  describe "frequentItemSets" do
    it "solves Takeaki Uno example" do
      -- From https://research.nii.ac.jp/~uno/code/lcm.html#IntroductionstoFrequentItemsetMining
      ( frequentItemSets
          [ [1, 2, 5, 6, 7]
          , [2, 3, 4, 5]
          , [1, 2, 7, 8, 9]
          , [1, 7, 9]
          , [2, 7, 9]
          , [2, 7, 9] -- Copy-paste typo on the original example
          , [1, 9] -- Add this to increase the support of [1,9] because the original example is wrong…
          , [2]
          ]
          3
        )
        `shouldBe` [ []
                   , [1]
                   , [1, 7]
                   , [1, 9]
                   , [2]
                   , [2, 7]
                   , [2, 7, 9]
                   , [2, 9]
                   , [7]
                   , [7, 9]
                   , [9]
                   ]

{-
it "solves a singleton transaction" do
  naiveClosedFrequentItemSets
    [ [1]
    ] 1 `shouldBe`
    [ [1]
    ]
it "solves a basic example" do
  naiveClosedFrequentItemSets
    [ [1]
    , [1,2]
    ] 1 `shouldBe`
    [ [1]
    , [1, 2]
    ]
it "solves a another basic example" do
  naiveClosedFrequentItemSets
    [ [1]
    , [1,2]
    , [1,2]
    ] 1 `shouldBe`
    [ [1]
    , [1, 2]
    ]
it "" do
  naiveClosedFrequentItemSets
    [ [1,2,3,4,5,6]
    , [2,3,5]
    , [2,5]
    , [1,2,4,5,6]
    , [2,4]
    , [1,4,6]
    , [3,4,6]
    ] 3 `shouldBe`
    [ [4]
    , [2]
    , [2,4]
    , [4,6]
    , [2,5]
    , [3]
    , [1,4,6]
    ]
-}