Safe Haskell	None
Language	Haskell2010

DataFrame.SymbolicRegression.Expr

Description

The symbolic-regression expression tree: a small first-order ADT with vectorized evaluation and a total translation to a dataframe 'Expr Double'. Division, log, and sqrt are protected so evaluation never produces NaN.

Synopsis

data SRExpr
- = SVar !Int
- | SConst !Double
- | SUn !UnOp SRExpr
- | SBin !BinOp SRExpr SRExpr
data BinOp
- = SAdd
- | SSub
- | SMul
- | SDiv
data UnOp
- = SNeg
- | SSin
- | SCos
- | SExp
- | SLog
- | SSqrt
evalSR :: Vector (Vector Double) -> Int -> SRExpr -> Vector Double
toDataFrameExpr :: Vector Text -> SRExpr -> Expr Double
srSize :: SRExpr -> Int
constants :: SRExpr -> [Double]
setConstants :: [Double] -> SRExpr -> SRExpr
allBinOps :: [BinOp]
allUnOps :: [UnOp]

Documentation

data SRExpr Source #

A symbolic-regression expression over feature variables and constants.

Constructors

SVar !Int
SConst !Double
SUn !UnOp SRExpr
SBin !BinOp SRExpr SRExpr

Instances

Instances details

Show SRExpr Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods showsPrec :: Int -> SRExpr -> ShowS # show :: SRExpr -> String # showList :: [SRExpr] -> ShowS #
Eq SRExpr Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods (==) :: SRExpr -> SRExpr -> Bool # (/=) :: SRExpr -> SRExpr -> Bool #
Ord SRExpr Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods compare :: SRExpr -> SRExpr -> Ordering # (<) :: SRExpr -> SRExpr -> Bool # (<=) :: SRExpr -> SRExpr -> Bool # (>) :: SRExpr -> SRExpr -> Bool # (>=) :: SRExpr -> SRExpr -> Bool # max :: SRExpr -> SRExpr -> SRExpr # min :: SRExpr -> SRExpr -> SRExpr #

data BinOp Source #

Constructors

SAdd
SSub
SMul
SDiv

Instances

Instances details

Bounded BinOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods minBound :: BinOp # maxBound :: BinOp #
Enum BinOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods succ :: BinOp -> BinOp # pred :: BinOp -> BinOp # toEnum :: Int -> BinOp # fromEnum :: BinOp -> Int # enumFrom :: BinOp -> [BinOp] # enumFromThen :: BinOp -> BinOp -> [BinOp] # enumFromTo :: BinOp -> BinOp -> [BinOp] # enumFromThenTo :: BinOp -> BinOp -> BinOp -> [BinOp] #
Show BinOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods showsPrec :: Int -> BinOp -> ShowS # show :: BinOp -> String # showList :: [BinOp] -> ShowS #
Eq BinOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods (==) :: BinOp -> BinOp -> Bool # (/=) :: BinOp -> BinOp -> Bool #
Ord BinOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods compare :: BinOp -> BinOp -> Ordering # (<) :: BinOp -> BinOp -> Bool # (<=) :: BinOp -> BinOp -> Bool # (>) :: BinOp -> BinOp -> Bool # (>=) :: BinOp -> BinOp -> Bool # max :: BinOp -> BinOp -> BinOp # min :: BinOp -> BinOp -> BinOp #

data UnOp Source #

Constructors

SNeg
SSin
SCos
SExp
SLog
SSqrt

Instances

Instances details

Bounded UnOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods minBound :: UnOp # maxBound :: UnOp #
Enum UnOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods succ :: UnOp -> UnOp # pred :: UnOp -> UnOp # toEnum :: Int -> UnOp # fromEnum :: UnOp -> Int # enumFrom :: UnOp -> [UnOp] # enumFromThen :: UnOp -> UnOp -> [UnOp] # enumFromTo :: UnOp -> UnOp -> [UnOp] # enumFromThenTo :: UnOp -> UnOp -> UnOp -> [UnOp] #
Show UnOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods showsPrec :: Int -> UnOp -> ShowS # show :: UnOp -> String # showList :: [UnOp] -> ShowS #
Eq UnOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods (==) :: UnOp -> UnOp -> Bool # (/=) :: UnOp -> UnOp -> Bool #
Ord UnOp Source #
Instance details Defined in DataFrame.SymbolicRegression.Expr Methods compare :: UnOp -> UnOp -> Ordering # (<) :: UnOp -> UnOp -> Bool # (<=) :: UnOp -> UnOp -> Bool # (>) :: UnOp -> UnOp -> Bool # (>=) :: UnOp -> UnOp -> Bool # max :: UnOp -> UnOp -> UnOp # min :: UnOp -> UnOp -> UnOp #

evalSR :: Vector (Vector Double) -> Int -> SRExpr -> Vector Double Source #

Evaluate over a feature matrix given column-major (feats ! j is feature j across all rows). Protected operators keep results finite.

toDataFrameExpr :: Vector Text -> SRExpr -> Expr Double Source #

Translate to a dataframe expression over the named feature columns.

srSize :: SRExpr -> Int Source #

constants :: SRExpr -> [Double] Source #

The constant values in left-to-right traversal order.

setConstants :: [Double] -> SRExpr -> SRExpr Source #

Replace the constants in traversal order; extra values are ignored.

allBinOps :: [BinOp] Source #

allUnOps :: [UnOp] Source #