231 lines
11 KiB
Haskell
231 lines
11 KiB
Haskell
{-# LANGUAGE OverloadedStrings #-}
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import Test.Hspec
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import GEval.Core
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import GEval.OptionsParser
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import GEval.BLEU
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import GEval.ClippEU
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import GEval.PrecisionRecall
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import GEval.ClusteringMetrics
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import Data.Attoparsec.Text
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import Options.Applicative
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import Data.Text
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import Text.EditDistance
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import qualified Test.HUnit as HU
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informationRetrievalBookExample :: [(String, Int)]
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informationRetrievalBookExample = [("o", 2), ("o", 2), ("d", 2), ("x", 3), ("d", 3),
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("x", 1), ("o", 1), ("x", 1), ( "x", 1), ("x", 1), ("x", 1),
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("x", 2), ("o", 2), ("o", 2),
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("x", 3), ("d", 3), ("d", 3)]
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perfectClustering :: [(Int, Char)]
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perfectClustering = [(0, 'a'), (2, 'b'), (3, 'c'), (2, 'b'), (2, 'b'), (1, 'd'), (0, 'a')]
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stupidClusteringOneBigCluster :: [(Int, Int)]
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stupidClusteringOneBigCluster = [(0, 2), (2, 2), (1, 2), (2, 2), (0, 2), (0, 2), (0, 2), (0, 2), (1, 2), (1, 2)]
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stupidClusteringManySmallClusters :: [(Int, Int)]
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stupidClusteringManySmallClusters = [(0, 0), (2, 1), (1, 2), (2, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 8), (1, 9)]
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main :: IO ()
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main = hspec $ do
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describe "root mean square error" $ do
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it "simple test" $ do
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geval (defaultGEvalSpecification {gesExpectedDirectory=Just "test/rmse-simple/rmse-simple", gesOutDirectory="test/rmse-simple/rmse-simple-solution"}) `shouldReturnAlmost` 0.64549722436790
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describe "mean square error" $ do
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it "simple test with arguments" $
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runGEvalTest "mse-simple" `shouldReturnAlmost` 0.4166666666666667
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describe "BLEU" $ do
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it "trivial example from Wikipedia" $
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runGEvalTest "bleu-trivial" `shouldReturnAlmost` 0.0
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it "complex example" $
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runGEvalTest "bleu-complex" `shouldReturnAlmost` 0.6211
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it "perfect translation" $
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runGEvalTest "bleu-perfect" `shouldReturnAlmost` 1.0000
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it "empty translation" $
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runGEvalTest "bleu-empty" `shouldReturnAlmost` 0.0000
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describe "Accuracy" $ do
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it "simple example" $
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runGEvalTest "accuracy-simple" `shouldReturnAlmost` 0.6
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describe "F-measure" $ do
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it "simple example" $
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runGEvalTest "f-measure-simple" `shouldReturnAlmost` 0.57142857
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it "perfect classifier" $
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runGEvalTest "f-measure-perfect" `shouldReturnAlmost` 1.0
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it "stupid classifier" $
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runGEvalTest "f-measure-stupid" `shouldReturnAlmost` 0.0
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it "all false" $
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runGEvalTest "f-measure-all-false" `shouldReturnAlmost` 1.0
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it "F2-measure" $
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runGEvalTest "f2-simple" `shouldReturnAlmost` 0.714285714
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describe "precision count" $ do
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it "simple test" $ do
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precisionCount [["Alice", "has", "a", "cat" ]] ["Ala", "has", "cat"] `shouldBe` 2
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it "none found" $ do
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precisionCount [["Alice", "has", "a", "cat" ]] ["for", "bar", "baz"] `shouldBe` 0
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it "multiple values" $ do
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precisionCount [["bar", "bar", "bar", "bar", "foo", "xyz", "foo"]] ["foo", "bar", "foo", "baz", "bar", "foo"] `shouldBe` 4
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it "multiple refs" $ do
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precisionCount [["foo", "baz"], ["bar"], ["baz", "xyz"]] ["foo", "bar", "foo"] `shouldBe` 2
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describe "purity (in flat clustering)" $ do
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it "the example from Information Retrieval Book" $ do
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purity informationRetrievalBookExample `shouldBeAlmost` 0.70588
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describe "NMI (in flat clustering)" $ do
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it "the example from Information Retrieval Book" $ do
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normalizedMutualInformation informationRetrievalBookExample `shouldBeAlmost` 0.36456
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it "perfect clustering" $ do
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normalizedMutualInformation perfectClustering `shouldBeAlmost` 1.0
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it "stupid clustering with one big cluster" $ do
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normalizedMutualInformation stupidClusteringOneBigCluster `shouldBeAlmost` 0.0
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it "stupid clustering with many small clusters" $ do
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normalizedMutualInformation stupidClusteringManySmallClusters `shouldBeAlmost` 0.61799
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describe "NMI challenge" $ do
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it "complex test" $ do
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runGEvalTest "nmi-complex" `shouldReturnAlmost` 0.36456
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describe "LogLossHashed challenge" $ do
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it "simple example" $ do
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runGEvalTest "log-loss-hashed-simple" `shouldReturnAlmost` 2.398479083333333
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it "example with unnormalized values" $ do
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runGEvalTest "log-loss-hashed-not-normalized" `shouldReturnAlmost` 1.0468455186722887
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describe "reading options" $ do
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it "can get the metric" $ do
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extractMetric "bleu-complex" `shouldReturn` (Just BLEU)
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describe "error handling" $ do
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it "too few lines are handled" $ do
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runGEvalTest "error-too-few-lines" `shouldThrow` (== TooFewLines)
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it "too many lines are handled" $ do
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runGEvalTest "error-too-many-lines" `shouldThrow` (== TooManyLines)
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it "empty output is handled" $ do
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runGEvalTest "empty-output" `shouldThrow` (== EmptyOutput)
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it "unexpected data is handled" $
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runGEvalTest "unexpected-data" `shouldThrow` (== UnexpectedData 3 "input does not start with a digit")
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it "unwanted data is handled" $
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runGEvalTest "unwanted-data" `shouldThrow` (== UnexpectedData 2 "number expected")
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describe "precision and recall" $ do
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it "null test" $ do
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precision neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0
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recall neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0
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f1Measure neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0
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it "basic test" $ do
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precision testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.3333333333333333
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recall testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.66666666666666666
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f1Measure testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.444444444444444
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it "perfect result" $ do
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precision alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0
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recall alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0
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f1Measure alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0
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it "full match" $ do
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precision alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.5
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recall alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 1.0
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f1Measure alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3 , 4, 5] `shouldBeAlmost` 0.66666666666666
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describe "ClippEU" $ do
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it "parsing rectangles" $ do
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let (Right r) = parseOnly (lineClippingsParser <* endOfInput) "2/0,0,2,3 10/20,30,40,50 18/0,1,500,3 "
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r `shouldBe` [Clipping (PageNumber 2) (Rectangle (Point 0 0) (Point 2 3)),
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Clipping (PageNumber 10) (Rectangle (Point 20 30) (Point 40 50)),
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Clipping (PageNumber 18) (Rectangle (Point 0 1) (Point 500 3))]
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it "no rectangles" $ do
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let (Right r) = parseOnly (lineClippingsParser <* endOfInput) ""
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r `shouldBe` []
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it "just spaces" $ do
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let (Right r) = parseOnly lineClippingsParser " "
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r `shouldBe` []
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it "parsing specs" $ do
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let (Right r) = parseOnly lineClippingSpecsParser " 2/0,0,2,3/5 10/20,30,40,50/10"
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r `shouldBe` [ClippingSpec (PageNumber 2) (Rectangle (Point 5 5) (Point 0 0))
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(Rectangle (Point 0 0) (Point 7 8)),
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ClippingSpec (PageNumber 10) (Rectangle (Point 30 40) (Point 30 40))
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(Rectangle (Point 10 20) (Point 50 60))]
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it "full test" $ do
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runGEvalTest "clippeu-simple" `shouldReturnAlmost` 0.399999999999
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describe "evaluation metric specification is parsed" $ do
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it "for simple names" $ do
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let metrics = [RMSE, MSE, BLEU, Accuracy, ClippEU]
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let parsedMetrics = Prelude.map (read . show) metrics
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metrics `shouldBe` parsedMetrics
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it "for F-Measure" $ do
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read "F2" `shouldBe` (FMeasure 2.0)
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read "F1" `shouldBe` (FMeasure 1.0)
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read "F0.5" `shouldBe` (FMeasure 0.5)
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describe "test edit-distance library" $ do
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it "for handling UTF8" $ do
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levenshteinDistance defaultEditCosts "źdźbło" "źd好bło" `shouldBe` 1
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levenshteinDistance defaultEditCosts "źdźbło" "źdźcło" `shouldBe` 1
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describe "CharMatch" $ do
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it "simple test" $ do
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runGEvalTest "charmatch-simple" `shouldReturnAlmost` 0.3571428571428571
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it "perfect solution" $ do
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runGEvalTest "charmatch-perfect" `shouldReturnAlmost` 1.0
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it "more complex test" $ do
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runGEvalTest "charmatch-complex" `shouldReturnAlmost` 0.1923076923076923
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it "broken test without input" $ do
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runGEvalTest "charmatch-no-input" `shouldThrow` (== NoInputFile "test/charmatch-no-input/charmatch-no-input/test-A/in.tsv")
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describe "MAP" $ do
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it "one result" $ do
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(calculateMAPForOneResult ["Berlin", "London", "Warsaw"]
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["Warsaw", "Moscow", "Berlin", "Prague"]) `shouldBeAlmost` 0.55555555
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it "check whether you cannot cheat with duplicated results" $ do
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(calculateMAPForOneResult ["one", "two"]
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["one", "one"]) `shouldBeAlmost` 0.5
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it "simple test" $ do
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runGEvalTest "map-simple" `shouldReturnAlmost` 0.444444444
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describe "evaluating single lines" $ do
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it "RMSE" $ do
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gevalCoreOnSingleLines RMSE (LineInFile "stub1" 1 "blabla")
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(LineInFile "stub2" 1 "3.4")
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(LineInFile "stub3" 1 "2.6") `shouldReturnAlmost` 0.8
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neverMatch :: Char -> Int -> Bool
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neverMatch _ _ = False
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alwaysMatch :: Char -> Int -> Bool
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alwaysMatch _ _ = True
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testMatchFun :: Char -> Int -> Bool
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testMatchFun 'a' 1 = True
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testMatchFun 'a' 2 = True
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testMatchFun 'a' 3 = True
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testMatchFun 'b' 1 = True
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testMatchFun 'c' 1 = True
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testMatchFun _ _ = False
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extractVal :: (Either (ParserResult GEvalOptions) (Maybe MetricValue)) -> IO MetricValue
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extractVal (Right (Just val)) = return val
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runGEvalTest testName = (runGEval [
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"--expected-directory",
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"test/" ++ testName ++ "/" ++ testName,
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"--out-directory",
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"test/" ++ testName ++ "/" ++ testName ++ "-solution"]) >>= extractVal
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extractMetric :: String -> IO (Maybe Metric)
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extractMetric testName = do
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result <- getOptions ["--expected-directory", "test/" ++ testName ++ "/" ++ testName]
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return $ case result of
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Left _ -> Nothing
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Right opts -> Just $ gesMetric $ geoSpec opts
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class AEq a where
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(=~) :: a -> a -> Bool
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instance AEq Double where
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x =~ y = abs ( x - y ) < (1.0e-4 :: Double)
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(@=~?) :: (Show a, AEq a) => a -> a -> HU.Assertion
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(@=~?) actual expected = expected =~ actual HU.@? assertionMsg
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where
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assertionMsg = "Expected : " ++ show expected ++
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"\nActual : " ++ show actual
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shouldBeAlmost got expected = got @=~? expected
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shouldReturnAlmost :: (AEq a, Show a, Eq a) => IO a -> a -> Expectation
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shouldReturnAlmost action expected = action >>= (@=~? expected)
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