Clingo.Statistics

Documentation

data StatsTree v

The polymorphic statistics tree.

Constructors

SValue v

SMap [(Text, StatsTree v)]

SArray [(Int, StatsTree v)]

Instances

Functor StatsTree

Methods

fmap :: (a -> b) -> StatsTree a -> StatsTree b

(<$) :: a -> StatsTree b -> StatsTree a

Foldable StatsTree

Methods

fold :: Monoid m => StatsTree m -> m

foldMap :: Monoid m => (a -> m) -> StatsTree a -> m

foldr :: (a -> b -> b) -> b -> StatsTree a -> b

foldr' :: (a -> b -> b) -> b -> StatsTree a -> b

foldl :: (b -> a -> b) -> b -> StatsTree a -> b

foldl' :: (b -> a -> b) -> b -> StatsTree a -> b

foldr1 :: (a -> a -> a) -> StatsTree a -> a

foldl1 :: (a -> a -> a) -> StatsTree a -> a

toList :: StatsTree a -> [a]

null :: StatsTree a -> Bool

length :: StatsTree a -> Int

elem :: Eq a => a -> StatsTree a -> Bool

maximum :: Ord a => StatsTree a -> a

minimum :: Ord a => StatsTree a -> a

sum :: Num a => StatsTree a -> a

product :: Num a => StatsTree a -> a

Traversable StatsTree

Methods

traverse :: Applicative f => (a -> f b) -> StatsTree a -> f (StatsTree b)

sequenceA :: Applicative f => StatsTree (f a) -> f (StatsTree a)

mapM :: Monad m => (a -> m b) -> StatsTree a -> m (StatsTree b)

sequence :: Monad m => StatsTree (m a) -> m (StatsTree a)

AMVTree StatsTree

Methods

atArray :: Int -> StatsTree v -> Maybe (StatsTree v)

atMap :: Text -> StatsTree v -> Maybe (StatsTree v)

value :: StatsTree v -> Maybe v

Eq v => Eq (StatsTree v)

Methods

(==) :: StatsTree v -> StatsTree v -> Bool

(/=) :: StatsTree v -> StatsTree v -> Bool

Ord v => Ord (StatsTree v)

Methods

compare :: StatsTree v -> StatsTree v -> Ordering

(<) :: StatsTree v -> StatsTree v -> Bool

(<=) :: StatsTree v -> StatsTree v -> Bool

(>) :: StatsTree v -> StatsTree v -> Bool

(>=) :: StatsTree v -> StatsTree v -> Bool

max :: StatsTree v -> StatsTree v -> StatsTree v

min :: StatsTree v -> StatsTree v -> StatsTree v

Show v => Show (StatsTree v)

Methods

showsPrec :: Int -> StatsTree v -> ShowS

show :: StatsTree v -> String

showList :: [StatsTree v] -> ShowS

Generic (StatsTree v)

Associated Types

type Rep (StatsTree v) :: * -> *

Methods

from :: StatsTree v -> Rep (StatsTree v) x

to :: Rep (StatsTree v) x -> StatsTree v

NFData v => NFData (StatsTree v)

Methods

rnf :: StatsTree v -> ()

type Rep (StatsTree v)

type Rep (StatsTree v) = D1 (MetaData "StatsTree" "Clingo.Statistics" "clingo-0.2.0.0-DzJnCg9nABaE1yAGw8EIsO" False) ((:+:) (C1 (MetaCons "SValue" PrefixI False) (S1 (MetaSel (Nothing Symbol) NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 v))) ((:+:) (C1 (MetaCons "SMap" PrefixI False) (S1 (MetaSel (Nothing Symbol) NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 [(Text, StatsTree v)]))) (C1 (MetaCons "SArray" PrefixI False) (S1 (MetaSel (Nothing Symbol) NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 [(Int, StatsTree v)])))))

class AMVTree t where

Minimal complete definition

atArray, atMap, value

Methods

atArray :: Int -> t v -> Maybe (t v)

atMap :: Text -> t v -> Maybe (t v)

value :: t v -> Maybe v

Instances

AMVTree StatsTree

Methods

atArray :: Int -> StatsTree v -> Maybe (StatsTree v)

atMap :: Text -> StatsTree v -> Maybe (StatsTree v)

value :: StatsTree v -> Maybe v

AMVTree ConfTree

Methods

atArray :: Int -> ConfTree v -> Maybe (ConfTree v)

atMap :: Text -> ConfTree v -> Maybe (ConfTree v)

value :: ConfTree v -> Maybe v

(>=>) :: Monad m => (a -> m b) -> (b -> m c) -> a -> m c infixr 1

Left-to-right Kleisli composition of monads.

fromStats :: NFData w => Statistics s -> (StatsTree Double -> Maybe w) -> Clingo s (Maybe w)

Get a statistics value from the tree. If any lookup fails, the result will be Nothing. The tree will be traversed lazily, but the result is evaluated before returning!

fromStatsMany :: NFData w => Statistics s -> [StatsTree Double -> Maybe w] -> Clingo s [Maybe w]

Like fromTree but supporting multiple paths.

subStats :: NFData w => Statistics s -> (StatsTree Double -> Maybe (StatsTree w)) -> Clingo s (Maybe (StatsTree w))

Get an entire subtree from the statistics. The entire subtree will be evaluated before returning!