Data.TDigest.Postprocess

Histogram

class Affine f => HasHistogram a f | a -> f where

Types from which we can extract histogram.

Minimal complete definition

histogram, totalWeight

Methods

histogram :: a -> f (NonEmpty HistBin)

totalWeight :: a -> Weight

Instances

HistBin ~ e => HasHistogram [HistBin] Maybe

Defined in Data.TDigest.Postprocess.Internal

Methods

histogram :: [HistBin] -> Maybe (NonEmpty HistBin)

totalWeight :: [HistBin] -> Weight

HistBin ~ e => HasHistogram (NonEmpty HistBin) Identity

Defined in Data.TDigest.Postprocess.Internal

Methods

histogram :: NonEmpty HistBin -> Identity (NonEmpty HistBin)

totalWeight :: NonEmpty HistBin -> Weight

HasHistogram (TDigest comp) Maybe

Defined in Data.TDigest.Tree.Internal

Methods

histogram :: TDigest comp -> Maybe (NonEmpty HistBin)

totalWeight :: TDigest comp -> Weight

HasHistogram (TDigest comp) Identity

Defined in Data.TDigest.Tree.NonEmpty

Methods

histogram :: TDigest comp -> Identity (NonEmpty HistBin)

totalWeight :: TDigest comp -> Weight

KnownNat comp => HasHistogram (TDigest comp) Maybe

Defined in Data.TDigest.Vector.Internal

Methods

histogram :: TDigest comp -> Maybe (NonEmpty HistBin)

totalWeight :: TDigest comp -> Weight

data HistBin

Histogram bin

Constructors

HistBin

Fields

• hbMin :: !Mean

  lower bound

• hbMax :: !Mean

  upper bound

• hbValue :: !Mean

  original value: (mi + ma) / 2

• hbWeight :: !Weight

  weight ("area" of the bar)

• hbCumWeight :: !Weight

  weight from the right, excludes this bin

Instances

Show HistBin

Defined in Data.TDigest.Postprocess.Internal

Methods

showsPrec :: Int -> HistBin -> ShowS

show :: HistBin -> String

showList :: [HistBin] -> ShowS

HistBin ~ e => HasHistogram [HistBin] Maybe

Defined in Data.TDigest.Postprocess.Internal

Methods

histogram :: [HistBin] -> Maybe (NonEmpty HistBin)

totalWeight :: [HistBin] -> Weight

HistBin ~ e => HasHistogram (NonEmpty HistBin) Identity

Defined in Data.TDigest.Postprocess.Internal

Methods

histogram :: NonEmpty HistBin -> Identity (NonEmpty HistBin)

totalWeight :: NonEmpty HistBin -> Weight

Quantiles

median :: HasHistogram a f => a -> f Double

Median, i.e. quantile 0.5.

quantile :: HasHistogram a f => Double -> a -> f Double

Calculate quantile of a specific value.

Mean & variance

As we have "full" histogram, we can calculate other statistical variables.

mean :: HasHistogram a f => a -> f Double

Mean.

>>> mean (Tree.tdigest [1..100] :: Tree.TDigest 10)
Just 50.5

Note: if you only need the mean, calculate it directly.

variance :: HasHistogram a f => a -> f Double

Variance.

stddev :: HasHistogram a f => a -> f Double

Standard deviation, square root of variance.

CDF

cdf :: HasHistogram a f => Double -> a -> Double

Cumulative distribution function.

Note: if this is the only thing you need, it's more efficient to count this directly.

icdf :: HasHistogram a f => Double -> a -> f Double

An alias for quantile.

Affine

class Traversable t => Affine t where

Affine containers, i.e. containing at most 1 element

This class doesn't have traverse analogie as it would require using Pointed which is disputed type class.

traverseAff :: Pointed f => (a -> f b) -> t a -> f (t b)

Minimal complete definition

fromAffine | affine

Methods

affine :: b -> (a -> b) -> t a -> b

Like foldMap

fromAffine :: a -> t a -> a

Instances

Affine Maybe

Defined in Data.TDigest.Postprocess.Internal

Methods

affine :: b -> (a -> b) -> Maybe a -> b

fromAffine :: a -> Maybe a -> a

Affine Identity

Defined in Data.TDigest.Postprocess.Internal

Methods

affine :: b -> (a -> b) -> Identity a -> b

fromAffine :: a -> Identity a -> a

Affine (Proxy :: * -> *)

Defined in Data.TDigest.Postprocess.Internal

Methods

affine :: b -> (a -> b) -> Proxy a -> b

fromAffine :: a -> Proxy a -> a

(Affine f, Affine g) => Affine (Compose f g)

Composition of Affine containers is Affine

Defined in Data.TDigest.Postprocess.Internal

Methods

affine :: b -> (a -> b) -> Compose f g a -> b

fromAffine :: a -> Compose f g a -> a