Data.Histogram.Bin.Classes

Type classes for binning algorithms. This is mapping from set of interest to integer indices and approximate reverse.

Bin type class

class Bin b where

This type represent some abstract data binning algorithms. It maps sets/intervals of values of type 'BinValue b' to integer indices.

Following invariant is expected to hold:

toIndex . fromIndex == id

Minimal complete definition

toIndex, fromIndex, nBins

Associated Types

type BinValue b

Type of value to bin

Methods

toIndex :: b -> BinValue b -> Int

Convert from value to index. Function must not fail for any input and should produce out of range indices for invalid input.

fromIndex :: b -> Int -> BinValue b

Convert from index to value. Returned value should correspond to center of bin. Definition of center is left for definition of instance. Funtion may fail for invalid indices but encouraged not to do so.

nBins :: b -> Int

Total number of bins. Must be non-negative.

inRange :: b -> BinValue b -> Bool

Check whether value in range. Have default implementation. Should satisfy: inRange b x ⇔ toIndex b x ∈ [0,nBins b)

Instances

Bin BinI

Bin BinInt

Bin BinD

Bin LogBinD

Enum a => Bin (BinEnum a)

RealFrac f => Bin (BinF f)

Bin bin => Bin (MaybeBin bin)

Bin b => Bin (BinPermute b)

Enum2D i => Bin (BinEnum2D i)

(Bin binX, Bin binY) => Bin (Bin2D binX binY)

binsCenters :: (Bin b, Vector v (BinValue b)) => b -> v (BinValue b)

Return vector of bin centers

Approximate equality

class Bin b => BinEq b where

Approximate equality for bins. It's nessesary to define approximate equality since exact equality is ill defined for bins which work with floating point data. It's not safe to compare floating point numbers for exact equality

Methods

binEq :: b -> b -> Bool

Approximate equality

Instances

BinEq BinI

BinEq BinInt

BinEq BinD

Equality is up to 3e-11 (2/3th of digits)

BinEq LogBinD

Enum a => BinEq (BinEnum a)

RealFloat f => BinEq (BinF f)

Equality is up to 2/3th of digits

BinEq bin => BinEq (MaybeBin bin)

(BinEq bx, BinEq by) => BinEq (Bin2D bx by)

1D bins

class (Bin b, Ord (BinValue b)) => IntervalBin b where

For binning algorithms which work with bin values which have some natural ordering and every bin is continous interval.

Minimal complete definition

binInterval

Methods

binInterval :: b -> Int -> (BinValue b, BinValue b)

Interval for n'th bin

binsList :: Vector v (BinValue b, BinValue b) => b -> v (BinValue b, BinValue b)

List of all bins. Could be overridden for efficiency.

Instances

IntervalBin BinI

IntervalBin BinInt

IntervalBin BinD

IntervalBin LogBinD

(Enum a, Ord a) => IntervalBin (BinEnum a)

RealFrac f => IntervalBin (BinF f)

IntervalBin b => IntervalBin (BinPermute b)

class IntervalBin b => Bin1D b where

IntervalBin which domain is single finite interval

Methods

lowerLimit :: b -> BinValue b

Minimal accepted value of histogram

upperLimit :: b -> BinValue b

Maximal accepted value of histogram

Instances

Bin1D BinI

Bin1D BinInt

Bin1D BinD

Bin1D LogBinD

(Enum a, Ord a) => Bin1D (BinEnum a)

RealFrac f => Bin1D (BinF f)

class Bin b => SliceableBin b where

Binning algorithm which support slicing.

Methods

unsafeSliceBin :: Int -> Int -> b -> b

Slice bin by indices. This function doesn't perform any checks and may produce invalid bin. Use sliceBin instead.

Instances

SliceableBin BinI

SliceableBin BinInt

SliceableBin BinD

SliceableBin LogBinD

(Enum a, Ord a) => SliceableBin (BinEnum a)

RealFrac f => SliceableBin (BinF f)

sliceBin

Arguments

:: SliceableBin b

=> Int

Index of first bin

-> Int

Index of last bin

-> b

-> b

Slice bin using indices

class Bin b => MergeableBin b where

Bin which support rebinning.

Methods

unsafeMergeBins :: CutDirection -> Int -> b -> b

N consecutive bins are joined into single bin. If number of bins isn't multiple of N remaining bins with highest or lowest index are dropped. This function doesn't do any checks. Use mergeBins instead.

Instances

MergeableBin BinInt

MergeableBin BinD

MergeableBin LogBinD

RealFrac f => MergeableBin (BinF f)

data CutDirection

How index should be dropped

Constructors

CutLower

Drop bins with smallest index

CutHigher

Drop bins with bigger index

mergeBins :: MergeableBin b => CutDirection -> Int -> b -> b

N consecutive bins are joined into single bin. If number of bins isn't multiple of N remaining bins with highest or lowest index are dropped. If N is larger than number of bins all bins are merged into single one.

Sizes of bin

class Bin b => VariableBin b where

1D binning algorithms with variable bin size

Methods

binSizeN :: b -> Int -> BinValue b

Size of n'th bin.

Instances

VariableBin BinI

VariableBin BinInt

VariableBin BinD

VariableBin LogBinD

RealFrac f => VariableBin (BinF f)

VariableBin bin => VariableBin (MaybeBin bin)

VariableBin b => VariableBin (BinPermute b)

class VariableBin b => UniformBin b where

1D binning algorithms with constant size bins. Constant sized bins could be thought as specialization of variable-sized bins therefore a superclass constraint.

Minimal complete definition

Nothing

Methods

binSize :: b -> BinValue b

Size of bin. Default implementation just uses 0th bin.

Instances

UniformBin BinI

UniformBin BinInt

UniformBin BinD

RealFrac f => UniformBin (BinF f)

UniformBin b => UniformBin (BinPermute b)

Conversion

class (Bin b, Bin b') => ConvertBin b b' where

Class for conversion between binning algorithms.

Methods

convertBin :: b -> b'

Convert bins

Instances

ConvertBin BinI BinInt

ConvertBin BinI BinD

ConvertBin BinInt BinD

RealFrac f => ConvertBin BinI (BinF f)

RealFrac f => ConvertBin BinInt (BinF f)

(ConvertBin bx bx', ConvertBin by by') => ConvertBin (Bin2D bx by) (Bin2D bx' by')

(ConvertBin by by', Bin bx) => ConvertBin (Bin2D bx by) (Bin2D bx by')

(ConvertBin bx bx', Bin by) => ConvertBin (Bin2D bx by) (Bin2D bx' by)