{-# LANGUAGE OverloadedStrings #-} {-# LANGUAGE FlexibleContexts #-} {-# LANGUAGE ScopedTypeVariables #-} import Test.Hspec import GEval.Metric import GEval.MetricsMeta (listOfAvailableEvaluationSchemes, isEvaluationSchemeDescribed, expectedScore, outContents) import GEval.Core import GEval.Common import GEval.EvaluationScheme import GEval.OptionsParser import GEval.BLEU import GEval.Clippings import GEval.PrecisionRecall import GEval.ClusteringMetrics import GEval.BIO import GEval.LineByLine import GEval.ParseParams import GEval.Submit import Text.Tokenizer import Text.WordShape import Data.Attoparsec.Text import Options.Applicative import Data.Text import Text.EditDistance import GEval.Annotation import GEval.BlackBoxDebugging import GEval.FeatureExtractor import GEval.Selector import GEval.CreateChallenge import GEval.Validation import Data.Conduit.Bootstrap import Data.Map.Strict import Data.Conduit.List (consume) import System.FilePath import System.Directory import System.Process import System.Exit import System.IO import System.IO.Temp import System.IO.Silently import Data.List (sort) import qualified Test.HUnit as HU import qualified Data.IntSet as IS import qualified Data.Vector as V import Data.Conduit.SmartSource import Data.Conduit.Rank import qualified Data.Conduit.Text as CT import Data.Conduit import Control.Monad.Trans.Resource import qualified Data.Conduit.List as CL import qualified Data.Conduit.Combinators as CC import Statistics.Distribution (cumulative) import Statistics.Distribution.Normal (normalDistr) import Data.Statistics.Kendall (kendall, kendallZ) import qualified Data.Vector.Unboxed as DVU import qualified Statistics.Matrix.Types as SMT import Data.Statistics.Loess (loess) import Data.Statistics.Calibration (calibration) import Data.CartesianStrings (parseCartesianString) import Data.SplitIntoCrossTabs (splitIntoCrossTabs, CrossTab(..), TextFrag(..)) informationRetrievalBookExample :: [(String, Int)] informationRetrievalBookExample = [("o", 2), ("o", 2), ("d", 2), ("x", 3), ("d", 3), ("x", 1), ("o", 1), ("x", 1), ( "x", 1), ("x", 1), ("x", 1), ("x", 2), ("o", 2), ("o", 2), ("x", 3), ("d", 3), ("d", 3)] perfectClustering :: [(Int, Char)] perfectClustering = [(0, 'a'), (2, 'b'), (3, 'c'), (2, 'b'), (2, 'b'), (1, 'd'), (0, 'a')] stupidClusteringOneBigCluster :: [(Int, Int)] stupidClusteringOneBigCluster = [(0, 2), (2, 2), (1, 2), (2, 2), (0, 2), (0, 2), (0, 2), (0, 2), (1, 2), (1, 2)] stupidClusteringManySmallClusters :: [(Int, Int)] stupidClusteringManySmallClusters = [(0, 0), (2, 1), (1, 2), (2, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 8), (1, 9)] main :: IO () main = hspec $ do describe "root mean square error" $ do it "simple test" $ do [(_, ((MetricOutput (SimpleRun val) _):_))] <- geval $ defaultGEvalSpecification {gesExpectedDirectory=Just "test/rmse-simple/rmse-simple", gesOutDirectory="test/rmse-simple/rmse-simple-solution"} val `shouldBeAlmost` 0.64549722436790 describe "mean square error" $ do it "simple test with arguments" $ runGEvalTest "mse-simple" `shouldReturnAlmost` 0.4166666666666667 describe "mean absolute error" $ do it "simple test with arguments" $ runGEvalTest "mae-simple" `shouldReturnAlmost` 1.5 describe "SMAPE" $ do it "simple test" $ runGEvalTest "smape-simple" `shouldReturnAlmost` 45.1851851851852 describe "Spearman's rank correlation coefficient" $ do it "simple test" $ do runGEvalTest "spearman-simple" `shouldReturnAlmost` (- 0.5735) describe "BLEU" $ do it "trivial example from Wikipedia" $ runGEvalTest "bleu-trivial" `shouldReturnAlmost` 0.0 it "complex example" $ runGEvalTest "bleu-complex" `shouldReturnAlmost` 0.6211 it "perfect translation" $ runGEvalTest "bleu-perfect" `shouldReturnAlmost` 1.0000 it "empty translation" $ runGEvalTest "bleu-empty" `shouldReturnAlmost` 0.0000 it "with tokenization" $ runGEvalTest "bleu-with-tokenization" `shouldReturnAlmost` 0.6501914150070065 it "with bootstrap" $ runGEvalTest "bleu-complex-bootstrap" `shouldReturnAlmost` 0.7061420723046241 describe "GLEU" $ do it "simple example" $ runGEvalTest "gleu-simple" `shouldReturnAlmost` 0.462962962962963 it "empty translation" $ runGEvalTest "gleu-empty" `shouldReturnAlmost` 0.0 it "perfect translation" $ runGEvalTest "gleu-perfect" `shouldReturnAlmost` 1.0 describe "WER" $ do it "simple example" $ runGEvalTest "wer-simple" `shouldReturnAlmost` 0.5555555555 describe "CER" $ do it "simple example" $ runGEvalTest "cer-simple" `shouldReturnAlmost` 0.28947368421 it "simple example (Mean/CER)" $ runGEvalTest "cer-mean-simple" `shouldReturnAlmost` 0.277777777777778 it "space escaping" $ runGEvalTest "cer-space-escaping" `shouldReturnAlmost` 0.0555555 describe "Haversine" $ do it "simple example" $ runGEvalTest "haversine" `shouldReturnAlmost` 1951.9351057250876 describe "Accuracy" $ do it "simple example" $ runGEvalTest "accuracy-simple" `shouldReturnAlmost` 0.6 it "with probs" $ runGEvalTest "accuracy-probs" `shouldReturnAlmost` 0.4 it "sorted" $ runGEvalTest "accuracy-on-sorted" `shouldReturnAlmost` 0.75 it "with filtering" $ runGEvalTest "accuracy-filtering" `shouldReturnAlmost` 0.6666 it "with filtering 2" $ runGEvalTest "accuracy-multiple-filtering" `shouldReturnAlmost` 0.5 describe "F-measure" $ do it "simple example" $ runGEvalTest "f-measure-simple" `shouldReturnAlmost` 0.57142857 it "perfect classifier" $ runGEvalTest "f-measure-perfect" `shouldReturnAlmost` 1.0 it "stupid classifier" $ runGEvalTest "f-measure-stupid" `shouldReturnAlmost` 0.0 it "all false" $ runGEvalTest "f-measure-all-false" `shouldReturnAlmost` 1.0 it "F2-measure" $ runGEvalTest "f2-simple" `shouldReturnAlmost` 0.714285714 describe "Macro-F-measure" $ do it "simple example" $ runGEvalTest "macro-f1-simple" `shouldReturnAlmost` 0.266666 it "perfect soltion" $ runGEvalTest "macro-f-measure-perfect" `shouldReturnAlmost` 1.00000 describe "TokenAccuracy" $ do it "simple example" $ do runGEvalTest "token-accuracy-simple" `shouldReturnAlmost` 0.5 describe "SegmentAccuracy" $ do it "simple test" $ do runGEvalTest "segment-accuracy-simple" `shouldReturnAlmost` 0.4444444 describe "precision count" $ do it "simple test" $ do precisionCount [["Alice", "has", "a", "cat" ]] ["Ala", "has", "cat"] `shouldBe` 2 it "none found" $ do precisionCount [["Alice", "has", "a", "cat" ]] ["for", "bar", "baz"] `shouldBe` 0 it "multiple values" $ do precisionCount [["bar", "bar", "bar", "bar", "foo", "xyz", "foo"]] ["foo", "bar", "foo", "baz", "bar", "foo"] `shouldBe` 4 it "multiple refs" $ do precisionCount [["foo", "baz"], ["bar"], ["baz", "xyz"]] ["foo", "bar", "foo"] `shouldBe` 2 describe "purity (in flat clustering)" $ do it "the example from Information Retrieval Book" $ do purity informationRetrievalBookExample `shouldBeAlmost` 0.70588 describe "NMI (in flat clustering)" $ do it "the example from Information Retrieval Book" $ do normalizedMutualInformation informationRetrievalBookExample `shouldBeAlmost` 0.36456 it "perfect clustering" $ do normalizedMutualInformation perfectClustering `shouldBeAlmost` 1.0 it "stupid clustering with one big cluster" $ do normalizedMutualInformation stupidClusteringOneBigCluster `shouldBeAlmost` 0.0 it "stupid clustering with many small clusters" $ do normalizedMutualInformation stupidClusteringManySmallClusters `shouldBeAlmost` 0.61799 describe "NMI challenge" $ do it "complex test" $ do runGEvalTest "nmi-complex" `shouldReturnAlmost` 0.36456 describe "LogLossHashed challenge" $ do it "simple example" $ do runGEvalTest "log-loss-hashed-simple" `shouldReturnAlmost` 2.398479083333333 it "example with unnormalized values" $ do runGEvalTest "log-loss-hashed-not-normalized" `shouldReturnAlmost` 1.0468455186722887 it "with probs instead of log probs" $ do runGEvalTest "log-loss-hashed-probs" `shouldReturnAlmost` 4.11631293099392 it "with probs instead of log probs (with normalization)" $ do runGEvalTest "log-loss-hashed-probs-normalized" `shouldReturnAlmost` 1.55537749098853 it "with log probs whose probs are summing up to less than 1.0" $ do runGEvalTest "log-loss-hashed-normalization" `shouldReturnAlmost` 5.16395069238851 describe "LikelihoodHashed challenge" $ do it "example with unnormalized values" $ do runGEvalTest "likelihood-hashed-not-normalized" `shouldReturnAlmost` 0.351043364110715 describe "reading options" $ do it "can get the metric" $ do extractMetric "bleu-complex" `shouldReturn` (Just BLEU) describe "error handling" $ do it "too few lines are handled" $ do runGEvalTest "error-too-few-lines" `shouldThrow` (== TooFewLines) it "too many lines are handled" $ do runGEvalTest "error-too-many-lines" `shouldThrow` (== TooManyLines) it "empty output is handled" $ do runGEvalTest "empty-output" `shouldThrow` (== EmptyOutput) it "unexpected data is handled" $ runGEvalTest "unexpected-data" `shouldThrow` (== UnexpectedData 3 "input does not start with a digit") it "unwanted data is handled" $ runGEvalTest "unwanted-data" `shouldThrow` (== UnexpectedData 2 "number expected") describe "precision and recall" $ do it "null test" $ do precision neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0 recall neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0 f1Measure neverMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.0 it "basic test" $ do precision testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.3333333333333333 recall testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.66666666666666666 f1Measure testMatchFun ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.444444444444444 it "perfect result" $ do precision alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0 recall alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0 f1Measure alwaysMatch ['a', 'b', 'c'] [0, 1, 2] `shouldBeAlmost` 1.0 it "full match" $ do precision alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 0.5 recall alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3, 4, 5] `shouldBeAlmost` 1.0 f1Measure alwaysMatch ['a', 'b', 'c'] [0, 1, 2, 3 , 4, 5] `shouldBeAlmost` 0.66666666666666 describe "max match" $ do it "simple" $ do maxMatch (==) [1,2,2] [3,2] `shouldBe` 1 maxMatch (==) [3,2] [1,2,2] `shouldBe` 1 describe "ClippEU" $ do it "parsing rectangles" $ do let (Right r) = parseOnly (lineClippingsParser <* endOfInput) "2/0,0,2,3 10/20,30,40,50 18/0,1,500,3 " r `shouldBe` [Clipping (PageNumber 2) (Rectangle (Point 0 0) (Point 2 3)), Clipping (PageNumber 10) (Rectangle (Point 20 30) (Point 40 50)), Clipping (PageNumber 18) (Rectangle (Point 0 1) (Point 500 3))] it "parsing labeled rectangles" $ do let (Right r) = parseOnly (lineLabeledClippingsParser <* endOfInput) "2/0,0,2,3 foo:5/10,10,20,20 " r `shouldBe` [LabeledClipping Nothing $ Clipping (PageNumber 2) (Rectangle (Point 0 0) (Point 2 3)), LabeledClipping (Just "foo") $ Clipping (PageNumber 5) (Rectangle (Point 10 10) (Point 20 20))] it "check partition" $ do partitionClippings (LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 0 0) (Point 100 50))) (LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 10 20) (Point 200 300))) `shouldBe` Just (Rectangle (Point 10 20) (Point 100 50), [LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 10 0) (Point 100 19)), LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 0 0) (Point 9 50))], [LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 10 51) (Point 100 300)), LabeledClipping Nothing (Clipping (PageNumber 5) $ Rectangle (Point 101 20) (Point 200 300))]) partitionClippings (LabeledClipping (Just "bar") (Clipping (PageNumber 10) (Rectangle (Point 100 100) (Point 200 149)))) (LabeledClipping (Just "bar") (Clipping (PageNumber 10) (Rectangle (Point 100 201) (Point 200 300)))) `shouldBe` Nothing it "no rectangles" $ do let (Right r) = parseOnly (lineClippingsParser <* endOfInput) "" r `shouldBe` [] it "just spaces" $ do let (Right r) = parseOnly lineClippingsParser " " r `shouldBe` [] it "parsing specs" $ do let (Right r) = parseOnly lineClippingSpecsParser " 2/0,0,2,3/5 10/20,30,40,50/10" r `shouldBe` [ClippingSpec (PageNumber 2) (Rectangle (Point 5 5) (Point 0 0)) (Rectangle (Point 0 0) (Point 7 8)), ClippingSpec (PageNumber 10) (Rectangle (Point 30 40) (Point 30 40)) (Rectangle (Point 10 20) (Point 50 60))] it "full test" $ do runGEvalTest "clippeu-simple" `shouldReturnAlmost` 0.399999999999 describe "evaluation metric specification is parsed" $ do it "for simple names" $ do let metrics = [RMSE, MSE, BLEU, Accuracy, ClippEU] let parsedMetrics = Prelude.map (read . show) metrics metrics `shouldBe` parsedMetrics it "for F-Measure" $ do read "F2" `shouldBe` (FMeasure 2.0) read "F1" `shouldBe` (FMeasure 1.0) read "F0.5" `shouldBe` (FMeasure 0.5) describe "Probabilistic-F1" $ do it "simple test" $ do runGEvalTest "probabilistic-f1-simple" `shouldReturnAlmost` 0.5 it "with probs" $ do runGEvalTest "probabilistic-f1-probs" `shouldReturnAlmost` 0.5451223333805993 describe "Soft-F1" $ do it "simple test" $ do runGEvalTest "soft-f1-simple" `shouldReturnAlmost` 0.33333333333333 it "perfect test" $ do runGEvalTest "soft-f1-perfect" `shouldReturnAlmost` 1.0 describe "FLC-F1" $ do it "simple test" $ do runGEvalTest "flc-f1-simple" `shouldReturnAlmost` 0.394231 it "test with multi overlap" $ do runGEvalTest "flc-f1-multi-overlap" `shouldReturnAlmost` 0.588364 describe "Probabilistic-Soft-F1" $ do it "simple test" $ do runGEvalTest "probabilistic-soft-f1-simple" `shouldReturnAlmost` 0.33333333333333 it "simple test with perfect calibration" $ do runGEvalTest "probabilistic-soft-f1-calibrated" `shouldReturnAlmost` 0.88888888888 describe "Soft2D-F1" $ do it "simple test" $ do runGEvalTest "soft2d-f1-simple" `shouldReturnAlmost` 0.22053934201995676 it "very narrow rectangles" $ do runGEvalTest "soft2d-f1-one-pixel" `shouldReturnAlmost` 0.281992045358382 describe "test edit-distance library" $ do it "for handling UTF8" $ do levenshteinDistance defaultEditCosts "źdźbło" "źd好bło" `shouldBe` 1 levenshteinDistance defaultEditCosts "źdźbło" "źdźcło" `shouldBe` 1 describe "CharMatch" $ do it "simple test" $ do runGEvalTest "charmatch-simple" `shouldReturnAlmost` 0.3571428571428571 it "perfect solution" $ do runGEvalTest "charmatch-perfect" `shouldReturnAlmost` 1.0 it "more complex test" $ do runGEvalTest "charmatch-complex" `shouldReturnAlmost` 0.1923076923076923 it "broken test without input" $ do runGEvalTest "charmatch-no-input" `shouldThrow` (== NoInputFile "test/charmatch-no-input/charmatch-no-input/test-A/in.tsv") describe "MAP" $ do it "one result" $ do (calculateMAPForOneResult ["Berlin", "London", "Warsaw"] ["Warsaw", "Moscow", "Berlin", "Prague"]) `shouldBeAlmost` 0.55555555 it "check whether you cannot cheat with duplicated results" $ do (calculateMAPForOneResult ["one", "two"] ["one", "one"]) `shouldBeAlmost` 0.5 it "simple test" $ do runGEvalTest "map-simple" `shouldReturnAlmost` 0.444444444 describe "LogLoss" $ do it "simple" $ do runGEvalTest "logloss-simple" `shouldReturnAlmost` 0.31824 it "perfect" $ do runGEvalTest "logloss-perfect" `shouldReturnAlmost` 0.0 describe "Likelihood" $ do it "simple" $ do runGEvalTest "likelihood-simple" `shouldReturnAlmost` 0.72742818469866 describe "MultiLabel-F" $ do it "simple" $ do runGEvalTest "multilabel-f1-simple" `shouldReturnAlmost` 0.66666666666 it "simple F2" $ do runGEvalTest "multilabel-f2-simple" `shouldReturnAlmost` 0.441176470588235 it "labels given with probs" $ do runGEvalTest "multilabel-f1-with-probs" `shouldReturnAlmost` 0.615384615384615 it "labels given with probs and numbers" $ do runGEvalTest "multilabel-f1-with-probs-and-numbers" `shouldReturnAlmost` 0.6666666666666 it "information extraction" $ do runGEvalTest "multilabel-f1-ie" `shouldReturnAlmost` 0.1111111111 it "information extraction with flags" $ do runGEvalTest "multilabel-f1-ie-flags" `shouldReturnAlmost` 0.444444444444 it "information extraction with fuzzy matching" $ do runGEvalTest "multilabel-f1-ie-fuzzy" `shouldReturnAlmost` 0.681777777777 it "information extraction with smart fuzzy matching" $ do runGEvalTest "multilabel-f1-ie-fuzzy-smart" `shouldReturnAlmost` 0.598444 it "information extraction with smart fuzzy matching hardened" $ do runGEvalTest "multilabel-f1-ie-fuzzy-harden" `shouldReturnAlmost` 0.555555555 describe "Mean/MultiLabel-F" $ do it "simple" $ do runGEvalTest "mean-multilabel-f1-simple" `shouldReturnAlmost` 0.5 describe "MultiLabel-Likelihood" $ do it "simple" $ do runGEvalTest "multilabel-likelihood-simple" `shouldReturnAlmost` 0.115829218528827 describe "Preprocessing operations" $ do it "F1 with preprocessing" $ do runGEvalTest "f1-with-preprocessing" `shouldReturnAlmost` 0.57142857142857 it "Regexp substition" $ do runGEvalTest "accuracy-with-flags" `shouldReturnAlmost` 0.8 let sampleChallenge = GEvalSpecification { gesOutDirectory = "test/accuracy-flags-line-by-line/accuracy-flags-line-by-line-solution", gesExpectedDirectory = Just "test/accuracy-flags-line-by-line/accuracy-flags-line-by-line", gesTestName = "test-A", gesSelector = Nothing, gesOutFile = "out.tsv", gesAltOutFiles = Nothing, gesExpectedFile = "expected.tsv", gesInputFile = "in.tsv", gesMetrics = [read "Accuracy:fs<\\d+><>"], gesFormatting = FormattingOptions Nothing False, gesTokenizer = Just Minimalistic, gesGonitoHost = Nothing, gesToken = Nothing, gesGonitoGitAnnexRemote = Nothing, gesReferences = Nothing, gesBootstrapResampling = Nothing, gesInHeader = Nothing, gesOutHeader = Nothing, gesShowPreprocessed = False } it "In line-by-line mode Accuracy" $ do results <- runLineByLineGeneralized KeepTheOriginalOrder sampleChallenge (const Data.Conduit.List.consume) results `shouldBe` [ LineRecord "foo" "Ala 123 ma kota." "Ala ma 2 kota ." 1 1.0, LineRecord "foo" "Foo bar baz" "Fox bax 456 bax" 2 0.0] it "In line-by-line mode F0" $ do results <- runLineByLineGeneralized KeepTheOriginalOrder sampleChallenge { gesMetrics = [read "MultiLabel-F0:fs<\\d+><>"]} (const Data.Conduit.List.consume) results `shouldBe` [ LineRecord "foo" "Ala 123 ma kota." "Ala ma 2 kota ." 1 1.0, LineRecord "foo" "Foo bar baz" "Fox bax 456 bax" 2 0.0] describe "Flag examples" $ do it "none" $ do runGEvalTest "flags-none" `shouldReturnAlmost` 0.2 it "lower-case" $ do runGEvalTest "flags-lowercase" `shouldReturnAlmost` 0.3 it "upper-case" $ do runGEvalTest "flags-uppercase" `shouldReturnAlmost` 0.4 it "regexp-matching" $ do runGEvalTest "flags-regexp-matching" `shouldReturnAlmost` 0.8 it "regexp-matching-anchor" $ do runGEvalTest "flags-regexp-matching-anchor" `shouldReturnAlmost` 0.8 it "regexp-token-matching" $ do runGEvalTest "flags-regexp-token-matching" `shouldReturnAlmost` 0.7 it "regexp-token-matching-anchor" $ do runGEvalTest "flags-regexp-token-matching-anchor" `shouldReturnAlmost` 0.8 it "regexp-substitution" $ do runGEvalTest "flags-regexp-substitution" `shouldReturnAlmost` 0.3 it "regexp-substitution-ref" $ do runGEvalTest "flags-regexp-substitution-ref" `shouldReturnAlmost` 0.5 it "sort" $ do runGEvalTest "flags-sort" `shouldReturnAlmost` 0.3 it "filtering" $ do runGEvalTest "flags-filtering" `shouldReturnAlmost` 0.25 describe "evaluating single lines" $ do it "RMSE" $ do (MetricOutput (SimpleRun v) _) <- gevalCoreOnSingleLines RMSE id RawItemTarget (LineInFile (FilePathSpec "stub1") 1 "blabla") RawItemTarget (LineInFile (FilePathSpec "stub2") 1 "3.4") RawItemTarget (LineInFile (FilePathSpec "stub3") 1 "2.6") v `shouldBeAlmost` 0.8 describe "Annotation format" $ do it "just parse" $ do parseAnnotations "foo:3,7-10 baz:4-6" `shouldBe` Right [Annotation "foo" (IS.fromList [3,7,8,9,10]), Annotation "baz" (IS.fromList [4,5,6])] it "just parse wit colons" $ do parseSegmentAnnotations "foo:x:3,7-10 baz:4-6" `shouldBe` Right [Annotation "foo:x" (IS.fromList [3,7,8,9,10]), Annotation "baz" (IS.fromList [4,5,6])] it "just parse wit colons" $ do parseSegmentAnnotations "foo:x:3,7-10 baz:2-6" `shouldBe` Left "Overlapping segments" it "just parse 2" $ do parseAnnotations "inwords:1-3 indigits:5" `shouldBe` Right [Annotation "inwords" (IS.fromList [1,2,3]), Annotation "indigits" (IS.fromList [5])] it "empty" $ do parseAnnotations "" `shouldBe` Right [] it "empty (just spaces)" $ do parseAnnotations " " `shouldBe` Right [] it "match score" $ do matchScore (Annotation "x" (IS.fromList [3..6])) (ObtainedAnnotation (Annotation "y" (IS.fromList [3..6])) 1.0) `shouldBeAlmost` 0.0 matchScore (Annotation "x" (IS.fromList [3..6])) (ObtainedAnnotation (Annotation "x" (IS.fromList [3..6])) 1.0) `shouldBeAlmost` 1.0 matchScore (Annotation "x" (IS.fromList [123..140])) (ObtainedAnnotation (Annotation "x" (IS.fromList [125..130])) 1.0) `shouldBeAlmost` 0.33333 matchScore (Annotation "x" (IS.fromList [3..4])) (ObtainedAnnotation (Annotation "x" (IS.fromList [2..13])) 1.0) `shouldBeAlmost` 0.1666666 describe "BIO format" $ do it "just parse" $ do let (Right r) = parseOnly (bioSequenceParser <* endOfInput) "O B-city/NEW_YORK I-city B-city/KALISZ I-city O B-name" r `shouldBe` [Outside, Beginning "city" (Just "NEW_YORK"), Inside "city" Nothing, Beginning "city" (Just "KALISZ"), Inside "city" Nothing, Outside, Beginning "name" Nothing] it "simplest entity" $ do let (Right ents) = parseBioSequenceIntoEntities "B-city" ents `shouldBe` [TaggedEntity (TaggedSpan 1 1) "city" Nothing] it "multi-word entity" $ do let (Right ents) = parseBioSequenceIntoEntities "B-date I-date" ents `shouldBe` [TaggedEntity (TaggedSpan 1 2) "date" Nothing] it "multi-word entity with normalized text" $ do let (Right ents) = parseBioSequenceIntoEntities "B-date/FOO I-date/BAR" ents `shouldBe` [TaggedEntity (TaggedSpan 1 2) "date" (Just "FOO_BAR")] it "simplest entity with something outside" $ do let (Right ents) = parseBioSequenceIntoEntities "O B-city" ents `shouldBe` [TaggedEntity (TaggedSpan 2 2) "city" Nothing] it "another simple case" $ do let (Right ents) = parseBioSequenceIntoEntities "B-city B-city" ents `shouldBe` [TaggedEntity (TaggedSpan 1 1) "city" Nothing, TaggedEntity (TaggedSpan 2 2) "city" Nothing] it "just parse into entities" $ do let (Right ents) = parseBioSequenceIntoEntities "O O B-city/LOS_ANGELES I-city B-city/KLUCZBORK O B-name O B-person/JOHN I-person/VON I-person/NEUMANN" ents `shouldBe` [TaggedEntity (TaggedSpan 3 4) "city" (Just "LOS_ANGELES"), TaggedEntity (TaggedSpan 5 5) "city" (Just "KLUCZBORK"), TaggedEntity (TaggedSpan 7 7) "name" (Nothing), TaggedEntity (TaggedSpan 9 11) "person" (Just "JOHN_VON_NEUMANN")] it "another entity parse" $ do let (Right ents) = parseBioSequenceIntoEntities "B-month/JULY B-month/JULY O O B-foo/bar" ents `shouldBe` [TaggedEntity (TaggedSpan 1 1) "month" (Just "JULY"), TaggedEntity (TaggedSpan 2 2) "month" (Just "JULY"), TaggedEntity (TaggedSpan 5 5) "foo" (Just "bar")] it "another entity parse" $ do let (Right ents) = parseBioSequenceIntoEntities "B-city/LOS I-city/ANGELES O B-city/NEW I-city/YORK" ents `shouldBe` [TaggedEntity (TaggedSpan 1 2) "city" (Just "LOS_ANGELES"), TaggedEntity (TaggedSpan 4 5) "city" (Just "NEW_YORK")] it "parse entity" $ do let (Right ents) = parseBioSequenceIntoEntities "B-surname/BROWN B-surname/SMITH" ents `shouldBe` [TaggedEntity (TaggedSpan 1 1) "surname" (Just "BROWN"), TaggedEntity (TaggedSpan 2 2) "surname" (Just "SMITH")] it "parse entity" $ do let (Right ents) = parseBioSequenceIntoEntities "O B-surname/SMITH" ents `shouldBe` [TaggedEntity (TaggedSpan 2 2) "surname" (Just "SMITH")] it "check counting" $ do gatherCountsForBIO [TaggedEntity (TaggedSpan 2 2) "surname" (Just "SMITH")] [TaggedEntity (TaggedSpan 1 1) "surname" (Just "BROWN"), TaggedEntity (TaggedSpan 2 2) "surname" (Just "SMITH")] `shouldBe` (1, 1, 2) it "check F1 on a more complicated example" $ do runGEvalTest "bio-f1-complex" `shouldReturnAlmost` 0.625 it "check F1 on labels only" $ do runGEvalTest "bio-f1-complex-labels" `shouldReturnAlmost` 0.6666666666 it "calculate F1" $ do runGEvalTest "bio-f1-simple" `shouldReturnAlmost` 0.5 it "calculate F1 with underscores rather than minus signs" $ do runGEvalTest "bio-f1-simple-underscores" `shouldReturnAlmost` 0.5 it "check perfect score" $ do runGEvalTest "bio-f1-perfect" `shouldReturnAlmost` 1.0 it "check inconsistent input" $ do runGEvalTest "bio-f1-error" `shouldThrow` (== UnexpectedData 2 "inconsistent label sequence `B-NAME/JOHN I-FOO/SMITH I-FOO/X`") describe "automatic decompression" $ do it "more complex test" $ do runGEvalTest "charmatch-complex-compressed" `shouldReturnAlmost` 0.1923076923076923 describe "headers" $ do it "simple" $ do runGEvalTest "mse-simple-headers" `shouldReturnAlmost` 0.4166666666666667 describe "handling jsonl format" $ do it "simple test" $ runGEvalTestExtraOptions ["-e", "expected.jsonl" ] "jsonl-simple" `shouldReturnAlmost` 0.571428571428 describe "line by line mode" $ do let sampleChallenge = GEvalSpecification { gesOutDirectory = "test/likelihood-simple/likelihood-simple-solution", gesExpectedDirectory = Just "test/likelihood-simple/likelihood-simple", gesTestName = "test-A", gesSelector = Nothing, gesOutFile = "out.tsv", gesAltOutFiles = Nothing, gesExpectedFile = "expected.tsv", gesInputFile = "in.tsv", gesMetrics = [EvaluationScheme Likelihood []], gesFormatting = FormattingOptions Nothing False, gesTokenizer = Nothing, gesGonitoHost = Nothing, gesToken = Nothing, gesGonitoGitAnnexRemote = Nothing, gesReferences = Nothing, gesBootstrapResampling = Nothing, gesInHeader = Nothing, gesOutHeader = Nothing, gesShowPreprocessed = False } it "simple test" $ do results <- runLineByLineGeneralized KeepTheOriginalOrder sampleChallenge (const Data.Conduit.List.consume) Prelude.map (\(LineRecord inp _ _ _ _) -> inp) results `shouldBe` ["foo", "bar", "baz", "baq"] it "test sorting" $ do results <- runLineByLineGeneralized FirstTheWorst sampleChallenge (const Data.Conduit.List.consume) Prelude.head (Prelude.map (\(LineRecord inp _ _ _ _) -> inp) results) `shouldBe` "baq" describe "handle --alt-metric option" $ do it "accuracy instead of likelihood" $ do runGEvalTestExtraOptions ["--alt-metric", "Accuracy"] "likelihood-simple" `shouldReturnAlmost` 0.75 it "accuracy instead of log loss" $ do runGEvalTestExtraOptions ["--alt-metric", "Accuracy"] "log-loss-hashed-probs" `shouldReturnAlmost` 0.4 describe "smart sources" $ do it "smart specs are obtained" $ do getSmartSourceSpec "foo" "" "" `shouldReturn` Left NoSpecGiven getSmartSourceSpec "foo" "out.tsv" "-" `shouldReturn` Right Stdin getSmartSourceSpec "foo" "out.sv" "http://gonito.net/foo" `shouldReturn` (Right $ Http "http://gonito.net/foo") getSmartSourceSpec "foo" "in.tsv" "https://gonito.net" `shouldReturn` (Right $ Https "https://gonito.net") it "sources are accessed" $ do readFromSmartSource "baz" "out.tsv" "test/files/foo.txt" `shouldReturn` ["foo\n"] readFromSmartSource "" "" "https://httpbin.org/robots.txt" `shouldReturn` ["User-agent: *\nDisallow: /deny\n"] describe "parse model params from filenames" $ do it "no params 1" $ do parseParamsFromFilePath "out.tsv" `shouldBe` OutputFileParsed "out" Data.Map.Strict.empty it "no params 2" $ do parseParamsFromFilePath "out.tsv.xz" `shouldBe` OutputFileParsed "out" Data.Map.Strict.empty it "no params 3" $ do parseParamsFromFilePath "out-test-foo_bar.tsv" `shouldBe` OutputFileParsed "out-test-foo_bar" Data.Map.Strict.empty it "one parameter" $ do parseParamsFromFilePath "out-nb_epochs=123.tsv" `shouldBe` OutputFileParsed "out" (Data.Map.Strict.fromList [("nb_epochs", "123")]) it "complex" $ do parseParamsFromFilePath "out-nb_epochs = 12,foo=off, bar-baz =10.tsv" `shouldBe` OutputFileParsed "out" (Data.Map.Strict.fromList [("nb_epochs", "12"), ("foo", "off"), ("bar-baz", "10")]) it "empty val" $ do parseParamsFromFilePath "out-nb_epochs=1,foo=,bar-baz=8.tsv" `shouldBe` OutputFileParsed "out" (Data.Map.Strict.fromList [("nb_epochs", "1"), ("foo", ""), ("bar-baz", "8")]) describe "ranking" $ do it "simple case" $ do checkConduitPure (rank (\(a,_) (b,_) -> a < b)) [(3.0::Double, "foo"::String), (10.0, "bar"), (12.0, "baz")] [(1.0, (3.0::Double, "foo"::String)), (2.0, (10.0, "bar")), (3.0, (12.0, "baz"))] it "one item" $ do checkConduitPure (rank (\(a,_) (b,_) -> a < b)) [(5.0::Double, "foo"::String)] [(1.0, (5.0::Double, "foo"::String))] it "take between" $ do checkConduitPure (rank (<)) [3.0::Double, 5.0, 5.0, 10.0] [(1.0::Double, 3.0), (2.5, 5.0), (2.5, 5.0), (4.0, 10.0)] it "two sequences" $ do checkConduitPure (rank (<)) [4.5::Double, 4.5, 4.5, 6.1, 6.1] [(2.0::Double, 4.4), (2.0, 4.5), (2.0, 4.5), (4.5, 6.1), (4.5, 6.1)] it "series at the beginning" $ do checkConduitPure (rank (<)) [10.0::Double, 10.0, 13.0, 14.0] [(1.5::Double, 10.0), (1.5, 10.0), (3.0, 13.0), (4.0, 14.0)] it "inverted" $ do checkConduitPure (rank (>)) [3.0::Double, 3.0, 2.0, 1.0] [(1.5::Double, 3.0), (1.5, 3.0), (3.0, 2.0), (4.0, 1.0)] describe "bootstrap conduit" $ do it "sanity test" $ do let nbOfSamples = 1000 let listChecked :: [Int] = [0..10] (runResourceT $ runConduit (CL.sourceList listChecked .| CC.product)) `shouldReturn` 0 results <- runResourceT $ runConduit (CL.sourceList listChecked .| bootstrapC nbOfSamples CC.product) Prelude.length results `shouldBe` nbOfSamples (Prelude.length (Prelude.filter (> 0) results)) `shouldNotBe` 0 it "test gettings bounds" $ do let sample = [3.0, 11.0, 2.0, 4.0, 15.0, 12.0, 2013.5, 19.0, 17.0, -10000.0, 16.0, 13.0, 6.0, 7.0, 8.0, 5.0, 9.0, 10.0, 14.0, 18] getConfidenceBounds defaultConfidenceLevel sample `shouldBe` (-10000.0, 2013.5) getConfidenceBounds 0.9 sample `shouldBe` (2.0, 19.0) describe "tokenizer" $ do it "simple utterance with '13a' tokenizer" $ do tokenize (Just V13a) "To be or not to be, that's the question." `shouldBe` ["To", "be", "or", "not", "to", "be", ",", "that's", "the", "question", "."] it "simple utterance with 'character-by-character' tokenizer" $ do tokenize (Just CharacterByCharacter) "To be or not to be." `shouldBe` ["T", "o", "_", "b", "e", "_", "o", "r", "_", "n", "o", "t", "_", "t", "o", "_", "b", "e", "."] describe "shapify" $ do it "simple tests" $ do shapify "Poznań" `shouldBe` (WordShape "Aa+") shapify "2019" `shouldBe` (WordShape "9999") shapify "Ala ma (czarnego) kota?" `shouldBe` (WordShape "Aa+ a+ (a+( a+.") shapify "" `shouldBe` (WordShape "") shapify "PCMCIA" `shouldBe` (WordShape "A+") shapify "a" `shouldBe` (WordShape "a") shapify "B5" `shouldBe` (WordShape "A9") describe "create challenges and validate them" $ do (flip mapM_) listOfAvailableEvaluationSchemes $ \scheme -> do it (show scheme) $ do withSystemTempDirectory "geval-validation-test" $ \tempDir -> do let spec = defaultGEvalSpecification { gesExpectedDirectory = Just tempDir, gesMetrics = [scheme], gesFormatting = FormattingOptions (Just 4) False } createChallenge True tempDir spec validationChallenge tempDir spec describe "test sample outputs" $ do (flip mapM_ ) (Prelude.filter isEvaluationSchemeDescribed listOfAvailableEvaluationSchemes) $ \scheme@(EvaluationScheme metric _) -> do it (show scheme) $ do withSystemTempDirectory "geval-sample-output-test" $ \tempDir -> do let spec = defaultGEvalSpecification { gesExpectedDirectory = Just tempDir, gesMetrics = [scheme] } createChallenge True tempDir spec let outFile = tempDir "test-A" "out.tsv" writeFile outFile (outContents metric) obtainedScore <- (runGEval ["--expected-directory", tempDir, "--out-directory", tempDir]) >>= extractVal obtainedScore `shouldBeAlmost` (expectedScore scheme) describe "submit" $ do it "current branch" $ do runGitTest "branch-test" (\_ -> getCurrentBranch) `shouldReturn` "develop" it "challengeId" $ do runGitTest "challengeId-test" ( \_ -> do path <- makeAbsolute "challenge01" setCurrentDirectory path getChallengeId) `shouldReturn` "challenge01" it "everything committed - positive" $ do runGitTest "everythingCommitted-test-pos" (\_ -> checkEverythingCommitted) `shouldReturn` () it "everything committed - negative" $ do hSilence [stderr] $ runGitTest "everythingCommitted-test-neg" (\_ -> checkEverythingCommitted) `shouldThrow` (== ExitFailure 1) it "remote synced - positive" $ do runGitTest "remoteSynced-test-pos" (\_ -> checkRemoteSynced) `shouldReturn` () it "remote synced - negative" $ do hSilence [stderr] $ runGitTest "remoteSynced-test-neg" (\_ -> checkRemoteSynced) `shouldThrow` (== ExitFailure 1) it "remote url" $ do runGitTest "remoteUrl-test" (\_ -> getRemoteUrl "origin") `shouldReturn` "git@git.example.com:example/example.git" it "repo root" $ do runGitTest "repoRoot-test" ( \path -> do subpath <- makeAbsolute "A/B" setCurrentDirectory subpath root <- getRepoRoot return $ root == path ) `shouldReturn` True it "no token" $ do runGitTest "token-test-no" (\_ -> readToken) `shouldReturn` Nothing it "read token" $ do runGitTest "token-test-yes" (\_ -> readToken) `shouldReturn` (Just "AAAA") it "write-read token" $ do runGitTest "token-test-no" ( \_ -> do writeToken "BBBB" token <- readToken return $ token == (Just "BBBB") ) `shouldReturn` True describe "extracting features" $ do it "extract factors" $ do let bbdo = BlackBoxDebuggingOptions { bbdoMinFrequency = 1, bbdoWordShapes = False, bbdoBigrams = True, bbdoCartesian = False, bbdoMinCartesianFrequency = Nothing, bbdoConsiderNumericalFeatures = True } (sort $ extractFactorsFromTabbed Nothing bbdo Nothing "in" "I like this\t34.3\ttests" Nothing) `shouldBe` [ PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (SimpleExistentialFactor (SimpleAtomicFactor (TextFactor "I"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (SimpleExistentialFactor (SimpleAtomicFactor (TextFactor "like"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (SimpleExistentialFactor (SimpleAtomicFactor (TextFactor "this"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (SimpleExistentialFactor (BigramFactor (TextFactor "I") (TextFactor "like"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (SimpleExistentialFactor (BigramFactor (TextFactor "like") (TextFactor "this"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 1)) (NumericalFactor Nothing 11), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 2)) (SimpleExistentialFactor (SimpleAtomicFactor (TextFactor "34.3"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 2)) (NumericalFactor (Just 34.3) 4), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 3)) (SimpleExistentialFactor (SimpleAtomicFactor (TextFactor "tests"))), PeggedFactor (FeatureTabbedNamespace "in" (ColumnByNumber 3)) (NumericalFactor Nothing 5) ] describe "Kendall's tau" $ do it "tau" $ do kendall (V.fromList $ Prelude.zip [12, 2, 1, 12, 2] [1, 4, 7, 1, 0]) `shouldBeAlmost` (-0.47140452079103173) it "z" $ do kendallZ (V.fromList $ Prelude.zip [12, 2, 1, 12, 2] [1, 4, 7, 1, 0]) `shouldBeAlmost` (-1.0742) it "p-value" $ do (2 * (cumulative (normalDistr 0.0 1.0) $ kendallZ (V.fromList $ Prelude.zip [12, 2, 1, 12, 2] [1, 4, 7, 1, 0]))) `shouldBeAlmost` 0.2827 describe "Loess" $ do it "simple" $ do loess (DVU.fromList [0.2, 0.6, 1.0]) (DVU.fromList [-0.6, 0.2, 1.0]) 0.4 `shouldBeAlmost` (-0.2) describe "Calibration" $ do it "empty list" $ do calibration [] [] `shouldBeAlmost` 1.0 it "one element" $ do calibration [True] [1.0] `shouldBeAlmost` 1.0 calibration [False] [0.0] `shouldBeAlmost` 1.0 calibration [True] [0.0] `shouldBeAlmost` 0.0 calibration [False] [1.0] `shouldBeAlmost` 0.0 calibration [True] [0.7] `shouldBeAlmost` 0.7 calibration [True] [0.3] `shouldBeAlmost` 0.3 calibration [False] [0.7] `shouldBeAlmost` 0.3 calibration [False] [0.3] `shouldBeAlmost` 0.7 it "perfect calibration" $ do calibration [True, True, False] [0.5, 1.0, 0.5] `shouldBeAlmost` 1.0 it "totally wrong" $ do calibration [True, False] [0.0, 1.0] `shouldBeAlmost` 0.0 calibration [True, False, False, True, False] [0.0, 1.0, 1.0, 0.5, 0.5] `shouldBeAlmost` 0.0 calibration [False, True, True, True, True, False, False, True, False] [0.25, 0.25, 0.0, 0.25, 0.25, 1.0, 1.0, 0.5, 0.5] `shouldBeAlmost` 0.0 describe "Cartesian strings" $ do it "singleton" $ do (parseCartesianString "foo") `shouldBe` ["foo"] it "simple" $ do parseCartesianString "a-{foo,bar,baz}-b" `shouldBe` ["a-foo-b", "a-bar-b", "a-baz-b"] it "3x2" $ do parseCartesianString "a-{foo,bar,baz}-{b,c}" `shouldBe` ["a-foo-b", "a-foo-c", "a-bar-b", "a-bar-c", "a-baz-b", "a-baz-c" ] it "3x2x3" $ do parseCartesianString "{foo,bar,ba}-{b,c}-{0,1,2}x" `shouldBe` ["foo-b-0x", "foo-b-1x", "foo-b-2x", "foo-c-0x", "foo-c-1x", "foo-c-2x", "bar-b-0x", "bar-b-1x", "bar-b-2x", "bar-c-0x", "bar-c-1x", "bar-c-2x", "ba-b-0x", "ba-b-1x", "ba-b-2x", "ba-c-0x", "ba-c-1x", "ba-c-2x" ] describe "cross-tabs" $ do it "tricky" $ do splitIntoCrossTabs ["AAAfoo", "AAAbar", "BBBbar", "CCCbar", "AAAbaz", "BBBbaz", "CCCbaz" ] `shouldBe ` [ SingleItem "AAAfoo", CrossTab [Prefix "AAAba", Prefix "BBBba", Prefix "CCCba"] [Suffix "r", Suffix "z"]] it "singleton" $ do splitIntoCrossTabs ["abababab"] `shouldBe` [SingleItem "abababab"] it "too small" $ do splitIntoCrossTabs ["aabb", "aacc"] `shouldBe` [SingleItem "aabb", SingleItem "aacc"] it "two tables" $ do splitIntoCrossTabs ["yABC", "xx00", "yABD", "ZC", "xx11", "yy00", "yy11", "ZD"] `shouldBe` [ CrossTab [Prefix "yAB", Prefix "Z"] [Suffix "C", Suffix "D"], CrossTab [Prefix "xx", Prefix "yy"] [Suffix "00", Suffix "11"]] it "simple" $ do splitIntoCrossTabs ["aabsolutely", "aaafoo", "other", "aaabaz", "aaabaq", "bbbfoo", "bbbbaz", "bbbbaq"] `shouldBe` [SingleItem "aabsolutely", CrossTab [Suffix "foo", Suffix "baz", Suffix "baq"] [Prefix "aaa", Prefix "bbb"], SingleItem "other"] checkConduitPure conduit inList expList = do let outList = runConduitPure $ CC.yieldMany inList .| conduit .| CC.sinkList mapM_ (\(o,e) -> (fst o) `shouldBeAlmost` (fst e)) $ Prelude.zip outList expList readFromSmartSource :: FilePath -> FilePath -> String -> IO [String] readFromSmartSource defaultDir defaultFile specS = do (Right spec) <- getSmartSourceSpec defaultDir defaultFile specS let source = smartSource spec contents <- runResourceT $ runConduit (source .| CT.decodeUtf8Lenient .| CL.consume) return $ Prelude.map unpack contents neverMatch :: Char -> Int -> Bool neverMatch _ _ = False alwaysMatch :: Char -> Int -> Bool alwaysMatch _ _ = True testMatchFun :: Char -> Int -> Bool testMatchFun 'a' 1 = True testMatchFun 'a' 2 = True testMatchFun 'a' 3 = True testMatchFun 'b' 1 = True testMatchFun 'c' 1 = True testMatchFun _ _ = False extractVal :: (Either (ParserResult GEvalOptions) (Maybe [(SourceSpec, [MetricResult])])) -> IO MetricValue extractVal (Right (Just ([(_, (SimpleRun val):_)]))) = return val extractVal (Right (Just ([(_, (BootstrapResampling vals):_)]))) = return (sum vals / fromIntegral (Prelude.length vals)) extractVal (Right Nothing) = return $ error "no metrics???" extractVal (Right (Just [])) = return $ error "emtpy metric list???" extractVal (Left result) = do handleParseResult result return $ error "something wrong" runGEvalTest = runGEvalTestExtraOptions [] runGEvalTestExtraOptions extraOptions testName = (runGEval ([ "--expected-directory", "test/" ++ testName ++ "/" ++ testName, "--out-directory", "test/" ++ testName ++ "/" ++ testName ++ "-solution"] ++ extraOptions)) >>= extractVal extractMetric :: String -> IO (Maybe Metric) extractMetric testName = do result <- getOptions ["--expected-directory", "test/" ++ testName ++ "/" ++ testName] return $ case result of Left _ -> Nothing Right opts -> Just $ gesMainMetric $ geoSpec opts (@=~?) :: (Show a, AEq a) => a -> a -> HU.Assertion (@=~?) actual expected = expected =~ actual HU.@? assertionMsg where assertionMsg = "Expected : " ++ show expected ++ "\nActual : " ++ show actual shouldBeAlmost got expected = got @=~? expected shouldReturnAlmost :: (AEq a, Show a, Eq a) => IO a -> a -> Expectation shouldReturnAlmost action expected = action >>= (@=~? expected) runGitTest :: String -> (FilePath -> IO a) -> IO a runGitTest name callback = do withSystemTempDirectory "geval-submit-test" $ \temp -> do copyFile ("test/_submit-tests/" ++ name ++ ".tar") (temp ++ "/" ++ name ++ ".tar") withCurrentDirectory temp $ do callCommand $ "tar xf " ++ name ++ ".tar" let testRoot = temp ++ "/" ++ name withCurrentDirectory testRoot $ do callback testRoot