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 Source #

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

Eq Outliers Source #
Instance details Defined in Criterion.Types Methods (==) :: Outliers -> Outliers -> Bool (/=) :: Outliers -> Outliers -> Bool
Data Outliers Source #
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 :: (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
Read Outliers Source #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS Outliers readList :: ReadS [Outliers] readPrec :: ReadPrec Outliers readListPrec :: ReadPrec [Outliers]
Show Outliers Source #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> Outliers -> ShowS show :: Outliers -> String showList :: [Outliers] -> ShowS
Generic Outliers Source #
Instance details Defined in Criterion.Types Associated Types type Rep Outliers :: Type -> Type Methods from :: Outliers -> Rep Outliers x to :: Rep Outliers x -> Outliers
Semigroup Outliers Source #
Instance details Defined in Criterion.Types Methods (<>) :: Outliers -> Outliers -> Outliers sconcat :: NonEmpty Outliers -> Outliers stimes :: Integral b => b -> Outliers -> Outliers
Monoid Outliers Source #
Instance details Defined in Criterion.Types Methods mempty :: Outliers mappend :: Outliers -> Outliers -> Outliers mconcat :: [Outliers] -> Outliers
NFData Outliers Source #
Instance details Defined in Criterion.Types Methods rnf :: Outliers -> ()
Binary Outliers Source #
Instance details Defined in Criterion.Types Methods put :: Outliers -> Put get :: Get Outliers putList :: [Outliers] -> Put
FromJSON Outliers Source #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser Outliers parseJSONList :: Value -> Parser [Outliers]
ToJSON Outliers Source #
Instance details Defined in Criterion.Types Methods toJSON :: Outliers -> Value toEncoding :: Outliers -> Encoding toJSONList :: [Outliers] -> Value toEncodingList :: [Outliers] -> Encoding
type Rep Outliers Source #
Instance details Defined in Criterion.Types type Rep Outliers = D1 (MetaData "Outliers" "Criterion.Types" "criterion-1.5.5.0-HGJiAlVpxpHHlZTFWzLBpd" 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 Source #

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

Eq OutlierEffect Source #
Instance details Defined in Criterion.Types Methods (==) :: OutlierEffect -> OutlierEffect -> Bool (/=) :: OutlierEffect -> OutlierEffect -> Bool
Data OutlierEffect Source #
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 :: (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
Ord OutlierEffect Source #
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
Read OutlierEffect Source #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS OutlierEffect readList :: ReadS [OutlierEffect] readPrec :: ReadPrec OutlierEffect readListPrec :: ReadPrec [OutlierEffect]
Show OutlierEffect Source #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> OutlierEffect -> ShowS show :: OutlierEffect -> String showList :: [OutlierEffect] -> ShowS
Generic OutlierEffect Source #
Instance details Defined in Criterion.Types Associated Types type Rep OutlierEffect :: Type -> Type Methods from :: OutlierEffect -> Rep OutlierEffect x to :: Rep OutlierEffect x -> OutlierEffect
NFData OutlierEffect Source #
Instance details Defined in Criterion.Types Methods rnf :: OutlierEffect -> ()
Binary OutlierEffect Source #
Instance details Defined in Criterion.Types Methods put :: OutlierEffect -> Put get :: Get OutlierEffect putList :: [OutlierEffect] -> Put
FromJSON OutlierEffect Source #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser OutlierEffect parseJSONList :: Value -> Parser [OutlierEffect]
ToJSON OutlierEffect Source #
Instance details Defined in Criterion.Types Methods toJSON :: OutlierEffect -> Value toEncoding :: OutlierEffect -> Encoding toJSONList :: [OutlierEffect] -> Value toEncodingList :: [OutlierEffect] -> Encoding
type Rep OutlierEffect Source #
Instance details Defined in Criterion.Types type Rep OutlierEffect = D1 (MetaData "OutlierEffect" "Criterion.Types" "criterion-1.5.5.0-HGJiAlVpxpHHlZTFWzLBpd" 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 Source #

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

Eq OutlierVariance Source #
Instance details Defined in Criterion.Types Methods (==) :: OutlierVariance -> OutlierVariance -> Bool (/=) :: OutlierVariance -> OutlierVariance -> Bool
Data OutlierVariance Source #
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 :: (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
Read OutlierVariance Source #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS OutlierVariance readList :: ReadS [OutlierVariance] readPrec :: ReadPrec OutlierVariance readListPrec :: ReadPrec [OutlierVariance]
Show OutlierVariance Source #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> OutlierVariance -> ShowS show :: OutlierVariance -> String showList :: [OutlierVariance] -> ShowS
Generic OutlierVariance Source #
Instance details Defined in Criterion.Types Associated Types type Rep OutlierVariance :: Type -> Type Methods from :: OutlierVariance -> Rep OutlierVariance x to :: Rep OutlierVariance x -> OutlierVariance
NFData OutlierVariance Source #
Instance details Defined in Criterion.Types Methods rnf :: OutlierVariance -> ()
Binary OutlierVariance Source #
Instance details Defined in Criterion.Types Methods put :: OutlierVariance -> Put get :: Get OutlierVariance putList :: [OutlierVariance] -> Put
FromJSON OutlierVariance Source #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser OutlierVariance parseJSONList :: Value -> Parser [OutlierVariance]
ToJSON OutlierVariance Source #
Instance details Defined in Criterion.Types Methods toJSON :: OutlierVariance -> Value toEncoding :: OutlierVariance -> Encoding toJSONList :: [OutlierVariance] -> Value toEncodingList :: [OutlierVariance] -> Encoding
type Rep OutlierVariance Source #
Instance details Defined in Criterion.Types type Rep OutlierVariance = D1 (MetaData "OutlierVariance" "Criterion.Types" "criterion-1.5.5.0-HGJiAlVpxpHHlZTFWzLBpd" 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 Source #

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

Eq SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods (==) :: SampleAnalysis -> SampleAnalysis -> Bool (/=) :: SampleAnalysis -> SampleAnalysis -> Bool
Read SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods readsPrec :: Int -> ReadS SampleAnalysis readList :: ReadS [SampleAnalysis] readPrec :: ReadPrec SampleAnalysis readListPrec :: ReadPrec [SampleAnalysis]
Show SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods showsPrec :: Int -> SampleAnalysis -> ShowS show :: SampleAnalysis -> String showList :: [SampleAnalysis] -> ShowS
Generic SampleAnalysis Source #
Instance details Defined in Criterion.Types Associated Types type Rep SampleAnalysis :: Type -> Type Methods from :: SampleAnalysis -> Rep SampleAnalysis x to :: Rep SampleAnalysis x -> SampleAnalysis
NFData SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods rnf :: SampleAnalysis -> ()
Binary SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods put :: SampleAnalysis -> Put get :: Get SampleAnalysis putList :: [SampleAnalysis] -> Put
FromJSON SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods parseJSON :: Value -> Parser SampleAnalysis parseJSONList :: Value -> Parser [SampleAnalysis]
ToJSON SampleAnalysis Source #
Instance details Defined in Criterion.Types Methods toJSON :: SampleAnalysis -> Value toEncoding :: SampleAnalysis -> Encoding toJSONList :: [SampleAnalysis] -> Value toEncodingList :: [SampleAnalysis] -> Encoding
type Rep SampleAnalysis Source #
Instance details Defined in Criterion.Types type Rep SampleAnalysis = D1 (MetaData "SampleAnalysis" "Criterion.Types" "criterion-1.5.5.0-HGJiAlVpxpHHlZTFWzLBpd" 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 Source #

Arguments

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

Perform an analysis of a measurement.

scale Source #

Arguments

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

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

analyseMean Source #

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 Source #

Count the total number of outliers in a sample.

classifyOutliers :: Sample -> Outliers Source #

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

noteOutliers :: Outliers -> Criterion () Source #

Display a report of the Outliers present in a Sample.

outlierVariance Source #

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)] Source #

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 Source #

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 Source #

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.