Copyright	(c) 2009-2014 Bryan O'Sullivan
License	BSD-style
Maintainer	bos@serpentine.com
Stability	experimental
Portability	GHC
Safe Haskell	Trustworthy
Language	Haskell2010

Criterion.Analysis

Description

Analysis code for benchmarks.

Synopsis

data Outliers = Outliers {
- samplesSeen :: !Int64
- lowSevere :: !Int64
- lowMild :: !Int64
- highMild :: !Int64
- highSevere :: !Int64
}
data OutlierEffect
- = Unaffected
- | Slight
- | Moderate
- | Severe
data OutlierVariance = OutlierVariance {
- ovEffect :: OutlierEffect
- ovDesc :: String
- ovFraction :: Double
}
data SampleAnalysis = SampleAnalysis {
- anRegress :: [Regression]
- anMean :: Estimate ConfInt Double
- anStdDev :: Estimate ConfInt Double
- anOutlierVar :: OutlierVariance
}
analyseSample :: Int -> String -> Vector Measured -> ExceptT String Criterion Report
scale :: Double -> SampleAnalysis -> SampleAnalysis
analyseMean :: Sample -> Int -> Criterion Double
countOutliers :: Outliers -> Int64
classifyOutliers :: Sample -> Outliers
noteOutliers :: Outliers -> Criterion ()
outlierVariance :: Estimate ConfInt Double -> Estimate ConfInt Double -> Double -> OutlierVariance
resolveAccessors :: [String] -> Either String [(String, Measured -> Maybe Double)]
validateAccessors :: [String] -> String -> Either String [(String, Measured -> Maybe Double)]
regress :: GenIO -> [String] -> String -> Vector Measured -> ExceptT String Criterion Regression

Documentation

data Outliers #

Outliers from sample data, calculated using the boxplot technique.

Constructors

Outliers
Fields samplesSeen :: !Int64 lowSevere :: !Int64 More than 3 times the interquartile range (IQR) below the first quartile. lowMild :: !Int64 Between 1.5 and 3 times the IQR below the first quartile. highMild :: !Int64 Between 1.5 and 3 times the IQR above the third quartile. highSevere :: !Int64 More than 3 times the IQR above the third quartile.

Instances

Instances details

FromJSON Outliers #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser Outliers # parseJSONList :: Value -> Parser [Outliers] # omittedField :: Maybe Outliers #
ToJSON Outliers #
Instance details Defined in Criterion.Types Methods toJSON :: Outliers -> Value # toEncoding :: Outliers -> Encoding # toJSONList :: [Outliers] -> Value # toEncodingList :: [Outliers] -> Encoding # omitField :: Outliers -> Bool #
Data Outliers #
Instance details Defined in Criterion.Types Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Outliers -> c Outliers gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Outliers toConstr :: Outliers -> Constr dataTypeOf :: Outliers -> DataType dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Outliers) dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Outliers) gmapT :: (forall b. Data b => b -> b) -> Outliers -> Outliers gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Outliers -> r gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Outliers -> r gmapQ :: (forall d. Data d => d -> u) -> Outliers -> [u] gmapQi :: Int -> (forall d. Data d => d -> u) -> Outliers -> u gmapM :: Monad m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers
Monoid Outliers #
Instance details Defined in Criterion.Types Methods mempty :: Outliers # mappend :: Outliers -> Outliers -> Outliers # mconcat :: [Outliers] -> Outliers #
Semigroup Outliers #
Instance details Defined in Criterion.Types Methods (<>) :: Outliers -> Outliers -> Outliers # sconcat :: NonEmpty Outliers -> Outliers # stimes :: Integral b => b -> Outliers -> Outliers #
Generic Outliers #
Instance details Defined in Criterion.Types Associated Types type Rep Outliers :: Type -> Type Methods from :: Outliers -> Rep Outliers x to :: Rep Outliers x -> Outliers
Read Outliers #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS Outliers # readList :: ReadS [Outliers] # readPrec :: ReadPrec Outliers # readListPrec :: ReadPrec [Outliers] #
Show Outliers #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> Outliers -> ShowS show :: Outliers -> String showList :: [Outliers] -> ShowS
Binary Outliers #
Instance details Defined in Criterion.Types Methods put :: Outliers -> Put get :: Get Outliers putList :: [Outliers] -> Put
NFData Outliers #
Instance details Defined in Criterion.Types Methods rnf :: Outliers -> ()
Eq Outliers #
Instance details Defined in Criterion.Types Methods (==) :: Outliers -> Outliers -> Bool (/=) :: Outliers -> Outliers -> Bool
type Rep Outliers #
Instance details Defined in Criterion.Types type Rep Outliers = D1 ('MetaData "Outliers" "Criterion.Types" "criterion-1.6.3.0-3MAySUZ0Pe96o6F7Cg4hB7" 'False) (C1 ('MetaCons "Outliers" 'PrefixI 'True) ((S1 ('MetaSel ('Just "samplesSeen") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :: S1 ('MetaSel ('Just "lowSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)) :: (S1 ('MetaSel ('Just "lowMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :: (S1 ('MetaSel ('Just "highMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :: S1 ('MetaSel ('Just "highSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)))))

data OutlierEffect #

A description of the extent to which outliers in the sample data affect the sample mean and standard deviation.

Constructors

Unaffected	Less than 1% effect.
Slight	Between 1% and 10%.
Moderate	Between 10% and 50%.
Severe	Above 50% (i.e. measurements are useless).

Instances

Instances details

FromJSON OutlierEffect #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser OutlierEffect # parseJSONList :: Value -> Parser [OutlierEffect] # omittedField :: Maybe OutlierEffect #
ToJSON OutlierEffect #
Instance details Defined in Criterion.Types Methods toJSON :: OutlierEffect -> Value # toEncoding :: OutlierEffect -> Encoding # toJSONList :: [OutlierEffect] -> Value # toEncodingList :: [OutlierEffect] -> Encoding # omitField :: OutlierEffect -> Bool #
Data OutlierEffect #
Instance details Defined in Criterion.Types Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> OutlierEffect -> c OutlierEffect gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c OutlierEffect toConstr :: OutlierEffect -> Constr dataTypeOf :: OutlierEffect -> DataType dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c OutlierEffect) dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c OutlierEffect) gmapT :: (forall b. Data b => b -> b) -> OutlierEffect -> OutlierEffect gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> OutlierEffect -> r gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> OutlierEffect -> r gmapQ :: (forall d. Data d => d -> u) -> OutlierEffect -> [u] gmapQi :: Int -> (forall d. Data d => d -> u) -> OutlierEffect -> u gmapM :: Monad m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect
Generic OutlierEffect #
Instance details Defined in Criterion.Types Associated Types type Rep OutlierEffect :: Type -> Type Methods from :: OutlierEffect -> Rep OutlierEffect x to :: Rep OutlierEffect x -> OutlierEffect
Read OutlierEffect #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS OutlierEffect # readList :: ReadS [OutlierEffect] # readPrec :: ReadPrec OutlierEffect # readListPrec :: ReadPrec [OutlierEffect] #
Show OutlierEffect #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> OutlierEffect -> ShowS show :: OutlierEffect -> String showList :: [OutlierEffect] -> ShowS
Binary OutlierEffect #
Instance details Defined in Criterion.Types Methods put :: OutlierEffect -> Put get :: Get OutlierEffect putList :: [OutlierEffect] -> Put
NFData OutlierEffect #
Instance details Defined in Criterion.Types Methods rnf :: OutlierEffect -> ()
Eq OutlierEffect #
Instance details Defined in Criterion.Types Methods (==) :: OutlierEffect -> OutlierEffect -> Bool (/=) :: OutlierEffect -> OutlierEffect -> Bool
Ord OutlierEffect #
Instance details Defined in Criterion.Types Methods compare :: OutlierEffect -> OutlierEffect -> Ordering (<) :: OutlierEffect -> OutlierEffect -> Bool (<=) :: OutlierEffect -> OutlierEffect -> Bool (>) :: OutlierEffect -> OutlierEffect -> Bool (>=) :: OutlierEffect -> OutlierEffect -> Bool max :: OutlierEffect -> OutlierEffect -> OutlierEffect min :: OutlierEffect -> OutlierEffect -> OutlierEffect
type Rep OutlierEffect #
Instance details Defined in Criterion.Types type Rep OutlierEffect = D1 ('MetaData "OutlierEffect" "Criterion.Types" "criterion-1.6.3.0-3MAySUZ0Pe96o6F7Cg4hB7" 'False) ((C1 ('MetaCons "Unaffected" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Slight" 'PrefixI 'False) (U1 :: Type -> Type)) :+: (C1 ('MetaCons "Moderate" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Severe" 'PrefixI 'False) (U1 :: Type -> Type)))

data OutlierVariance #

Analysis of the extent to which outliers in a sample affect its standard deviation (and to some extent, its mean).

Constructors

OutlierVariance
Fields ovEffect :: OutlierEffect Qualitative description of effect. ovDesc :: String Brief textual description of effect. ovFraction :: Double Quantitative description of effect (a fraction between 0 and 1).

Instances

Instances details

FromJSON OutlierVariance #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser OutlierVariance # parseJSONList :: Value -> Parser [OutlierVariance] # omittedField :: Maybe OutlierVariance #
ToJSON OutlierVariance #
Instance details Defined in Criterion.Types Methods toJSON :: OutlierVariance -> Value # toEncoding :: OutlierVariance -> Encoding # toJSONList :: [OutlierVariance] -> Value # toEncodingList :: [OutlierVariance] -> Encoding # omitField :: OutlierVariance -> Bool #
Data OutlierVariance #
Instance details Defined in Criterion.Types Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> OutlierVariance -> c OutlierVariance gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c OutlierVariance toConstr :: OutlierVariance -> Constr dataTypeOf :: OutlierVariance -> DataType dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c OutlierVariance) dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c OutlierVariance) gmapT :: (forall b. Data b => b -> b) -> OutlierVariance -> OutlierVariance gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> OutlierVariance -> r gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> OutlierVariance -> r gmapQ :: (forall d. Data d => d -> u) -> OutlierVariance -> [u] gmapQi :: Int -> (forall d. Data d => d -> u) -> OutlierVariance -> u gmapM :: Monad m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance
Generic OutlierVariance #
Instance details Defined in Criterion.Types Associated Types type Rep OutlierVariance :: Type -> Type Methods from :: OutlierVariance -> Rep OutlierVariance x to :: Rep OutlierVariance x -> OutlierVariance
Read OutlierVariance #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS OutlierVariance # readList :: ReadS [OutlierVariance] # readPrec :: ReadPrec OutlierVariance # readListPrec :: ReadPrec [OutlierVariance] #
Show OutlierVariance #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> OutlierVariance -> ShowS show :: OutlierVariance -> String showList :: [OutlierVariance] -> ShowS
Binary OutlierVariance #
Instance details Defined in Criterion.Types Methods put :: OutlierVariance -> Put get :: Get OutlierVariance putList :: [OutlierVariance] -> Put
NFData OutlierVariance #
Instance details Defined in Criterion.Types Methods rnf :: OutlierVariance -> ()
Eq OutlierVariance #
Instance details Defined in Criterion.Types Methods (==) :: OutlierVariance -> OutlierVariance -> Bool (/=) :: OutlierVariance -> OutlierVariance -> Bool
type Rep OutlierVariance #
Instance details Defined in Criterion.Types type Rep OutlierVariance = D1 ('MetaData "OutlierVariance" "Criterion.Types" "criterion-1.6.3.0-3MAySUZ0Pe96o6F7Cg4hB7" 'False) (C1 ('MetaCons "OutlierVariance" 'PrefixI 'True) (S1 ('MetaSel ('Just "ovEffect") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierEffect) :: (S1 ('MetaSel ('Just "ovDesc") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 String) :: S1 ('MetaSel ('Just "ovFraction") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Double))))

data SampleAnalysis #

Result of a bootstrap analysis of a non-parametric sample.

Constructors

SampleAnalysis
Fields anRegress :: [Regression] Estimates calculated via linear regression. anMean :: Estimate ConfInt Double Estimated mean. anStdDev :: Estimate ConfInt Double Estimated standard deviation. anOutlierVar :: OutlierVariance Description of the effects of outliers on the estimated variance.

Instances

Instances details

FromJSON SampleAnalysis #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser SampleAnalysis # parseJSONList :: Value -> Parser [SampleAnalysis] # omittedField :: Maybe SampleAnalysis #
ToJSON SampleAnalysis #
Instance details Defined in Criterion.Types Methods toJSON :: SampleAnalysis -> Value # toEncoding :: SampleAnalysis -> Encoding # toJSONList :: [SampleAnalysis] -> Value # toEncodingList :: [SampleAnalysis] -> Encoding # omitField :: SampleAnalysis -> Bool #
Generic SampleAnalysis #
Instance details Defined in Criterion.Types Associated Types type Rep SampleAnalysis :: Type -> Type Methods from :: SampleAnalysis -> Rep SampleAnalysis x to :: Rep SampleAnalysis x -> SampleAnalysis
Read SampleAnalysis #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS SampleAnalysis # readList :: ReadS [SampleAnalysis] # readPrec :: ReadPrec SampleAnalysis # readListPrec :: ReadPrec [SampleAnalysis] #
Show SampleAnalysis #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> SampleAnalysis -> ShowS show :: SampleAnalysis -> String showList :: [SampleAnalysis] -> ShowS
Binary SampleAnalysis #
Instance details Defined in Criterion.Types Methods put :: SampleAnalysis -> Put get :: Get SampleAnalysis putList :: [SampleAnalysis] -> Put
NFData SampleAnalysis #
Instance details Defined in Criterion.Types Methods rnf :: SampleAnalysis -> ()
Eq SampleAnalysis #
Instance details Defined in Criterion.Types Methods (==) :: SampleAnalysis -> SampleAnalysis -> Bool (/=) :: SampleAnalysis -> SampleAnalysis -> Bool
type Rep SampleAnalysis #
Instance details Defined in Criterion.Types type Rep SampleAnalysis = D1 ('MetaData "SampleAnalysis" "Criterion.Types" "criterion-1.6.3.0-3MAySUZ0Pe96o6F7Cg4hB7" 'False) (C1 ('MetaCons "SampleAnalysis" 'PrefixI 'True) ((S1 ('MetaSel ('Just "anRegress") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 [Regression]) :: S1 ('MetaSel ('Just "anMean") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double))) :: (S1 ('MetaSel ('Just "anStdDev") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double)) :*: S1 ('MetaSel ('Just "anOutlierVar") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierVariance))))

analyseSample #

Arguments

:: Int	Experiment number.
-> String	Experiment name.
-> Vector Measured	Sample data.
-> ExceptT String Criterion Report

Perform an analysis of a measurement.

scale #

Arguments

:: Double	Value to multiply by.
-> SampleAnalysis
-> SampleAnalysis

Multiply the Estimates in an analysis by the given value, using scale.

analyseMean #

Arguments

:: Sample
-> Int	Number of iterations used to compute the sample.
-> Criterion Double

Display the mean of a Sample, and characterise the outliers present in the sample.

countOutliers :: Outliers -> Int64 #

Count the total number of outliers in a sample.

classifyOutliers :: Sample -> Outliers #

Classify outliers in a data set, using the boxplot technique.

noteOutliers :: Outliers -> Criterion () #

Display a report of the Outliers present in a Sample.

outlierVariance #

Arguments

:: Estimate ConfInt Double	Bootstrap estimate of sample mean.
-> Estimate ConfInt Double	Bootstrap estimate of sample standard deviation.
-> Double	Number of original iterations.
-> OutlierVariance

Compute the extent to which outliers in the sample data affect the sample mean and standard deviation.

resolveAccessors :: [String] -> Either String [(String, Measured -> Maybe Double)] #

Given a list of accessor names (see measureKeys), return either a mapping from accessor name to function or an error message if any names are wrong.

validateAccessors #

Arguments

:: [String]	Predictor names.
-> String	Responder name.
-> Either String [(String, Measured -> Maybe Double)]

Given predictor and responder names, do some basic validation, then hand back the relevant accessors.

regress #

Arguments

:: GenIO
-> [String]	Predictor names.
-> String	Responder name.
-> Vector Measured
-> ExceptT String Criterion Regression

Regress the given predictors against the responder.

Errors may be returned under various circumstances, such as invalid names or lack of needed data.

See olsRegress for details of the regression performed.