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https://gitlab.com/sheaf/metabrush.git
synced 2024-11-27 09:24:08 +00:00
Slight refactor of bisection dimension choosing logic
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sheaf
parent
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8009983b37
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@ -182,7 +182,7 @@ benchCases :: [ TestCase ]
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benchCases =
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[ ellipseTestCase opts ("minWidth=" ++ show minWidth ++ ",ε=" ++ show narrowAbs) ( 0, 1 ) pi $ defaultStartBoxes [ 2 ]
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| minWidth <- [ 1e-5 ]
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, narrowAbs <- [ 1e-5, 1e-4, 1e-3, 5e-3, 8e-3, 1e-2, 2e-2, 3e-2, 4e-2, 5e-2, 1e-1 ]
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, narrowAbs <- [ 5e-2 ]
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, let opts =
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RootIsolationOptions
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{ minWidth
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@ -130,6 +130,7 @@ newtype Vec n a = Vec { vecList :: [ a ] }
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universe :: forall n. KnownNat n => Vec n ( Fin n )
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universe = Vec [ Fin i | i <- [ 1 .. fromIntegral ( natVal' @n proxy# ) ] ]
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{-# INLINEABLE universe #-}
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coordinates :: forall r u. ( Representable r u ) => u -> Vec ( RepDim u ) r
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coordinates u = fmap ( index u ) $ universe @( RepDim u )
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@ -160,7 +161,7 @@ zipIndices ( Vec v ) = zipIndices_ 1 v
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--------------------------------------------------------------------------------
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-- | Rotate a vector by the given angle (counter-clockwise),
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-- given the cosine and sine of the angle (in that order)
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-- given the cosine and sine of the angle (in that order).
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rotate :: ( Representable r m, RepDim m ~ 2, Ring r )
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=> r -- \( \cos \theta \)
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-> r -- \( \sin \theta \)
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@ -44,12 +44,14 @@ import Data.Kind
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( Type )
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import Data.Foldable
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( toList )
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import Data.Functor
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( (<&>) )
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import Data.List
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( partition, sort )
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( partition )
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import Data.List.NonEmpty
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( NonEmpty )
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import qualified Data.List.NonEmpty as NE
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( NonEmpty(..), last, singleton )
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( NonEmpty(..), cons, filter, fromList, last, singleton, sort )
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import Data.Semigroup
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( Arg(..), Dual(..) )
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import Numeric
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@ -182,9 +184,17 @@ type BisectionOptions :: Nat -> Nat -> Type
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data BisectionOptions n d =
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BisectionOptions
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{ canHaveSols :: !( ( 𝕀ℝ n -> D 1 ( 𝕀ℝ n ) ( 𝕀ℝ d ) ) -> Box n -> Bool )
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, fallbackBisectionDim :: !( [ ( RootIsolationStep, Box n ) ] -> BoxHistory n -> ( 𝕀ℝ n -> D 1 ( 𝕀ℝ n ) ( 𝕀ℝ d ) ) -> ( Fin n, String ) )
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, fallbackBisectionDim :: !( BisectionDimPicker n d )
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}
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type BisectionDimPicker n d
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= forall r
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. [ ( RootIsolationStep, Box n ) ]
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-> BoxHistory n
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-> ( 𝕀ℝ n -> D 1 ( 𝕀ℝ n ) ( 𝕀ℝ d ) )
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-> NE.NonEmpty ( Fin n, r )
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-> ( r, String )
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-- | Options for the interval Gauss–Seidel method.
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type GaussSeidelOptions :: Nat -> Nat -> Type
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data GaussSeidelOptions n d =
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@ -192,7 +202,7 @@ data GaussSeidelOptions n d =
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{ -- | Which preconditioner to user?
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gsPreconditioner :: !Preconditioner
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-- | Function that projects over the equations we will consider
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-- (the identity for a well-determined problem, or a project for
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-- (the identity for a well-determined problem, or a projection for
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-- an overdetermined system).
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, gsDims :: ( 𝕀ℝ d -> 𝕀ℝ n ) }
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@ -246,7 +256,7 @@ defaultRootIsolationAlgorithms minWidth narrowAbs box history
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-> NE.singleton $ Bisection ( defaultBisectionOptions minWidth narrowAbs box )
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-- Otherwise, do a normal round.
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-- Currently: we try an interval Gauss–Seidel step followed by box(1)-consistency.
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_ -> GaussSeidel defaultGaussSeidelOptions
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_ -> GaussSeidel _gaussSeidelOptions
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NE.:| [ Box1 _box1Options ]
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where
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@ -254,7 +264,7 @@ defaultRootIsolationAlgorithms minWidth narrowAbs box history
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_box1Options =
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Box1Options
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{ box1EpsEq = narrowAbs
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, box1CoordsToNarrow = toList $ universe @n -- [ Fin 1, Fin 2 ]
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, box1CoordsToNarrow = toList $ universe @n
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, box1EqsToUse = toList $ universe @d
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}
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@ -267,23 +277,27 @@ defaultRootIsolationAlgorithms minWidth narrowAbs box history
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, box2EqsToUse = toList $ universe @d
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}
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_gaussSeidelOptions :: GaussSeidelOptions n d
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_gaussSeidelOptions =
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GaussSeidelOptions
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{ gsPreconditioner = InverseMidJacobian
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, gsDims =
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\ ( 𝕀 ( ℝ3 a_lo b_lo c_lo ) ( ℝ3 a_hi b_hi c_hi ) ) ->
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case length history `mod` 3 of
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0 -> 𝕀 ( ℝ2 a_lo b_lo ) ( ℝ2 a_hi b_hi )
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1 -> 𝕀 ( ℝ2 b_lo c_lo ) ( ℝ2 b_hi c_hi )
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_ -> 𝕀 ( ℝ2 a_lo c_lo ) ( ℝ2 a_hi c_hi )
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}
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-- Did we reduce the box width by at least "narrowAbs" in at least one of the dimensions?
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sufficientlySmallerThan :: Box n -> Box n -> Bool
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b1 `sufficientlySmallerThan` b2 =
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or $
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( \ cd1 cd2 -> width cd2 - width cd1 > narrowAbs )
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( \ cd1 cd2 -> width cd2 - width cd1 >= narrowAbs )
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<$> coordinates b1
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<*> coordinates b2
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{-# INLINEABLE defaultRootIsolationAlgorithms #-}
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defaultGaussSeidelOptions :: GaussSeidelOptions N 3
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defaultGaussSeidelOptions =
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GaussSeidelOptions
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{ gsPreconditioner = InverseMidJacobian
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, gsDims = \ ( 𝕀 ( ℝ3 _a_lo b_lo c_lo ) ( ℝ3 _a_hi b_hi c_hi ) )
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-> 𝕀 ( ℝ2 b_lo c_lo ) ( ℝ2 b_hi c_hi )
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}
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defaultBisectionOptions
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:: forall n d
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. ( 1 <= n, BoxCt n d )
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@ -295,7 +309,7 @@ defaultBisectionOptions minWidth _narrowAbs box =
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\ eqs box' ->
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-- box(0)-consistency
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let iRange' :: Box d
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iRange' = ( `monIndex` zeroMonomial ) $ eqs box'
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iRange' = eqs box' `monIndex` zeroMonomial
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in unT ( origin @Double ) `inside` iRange'
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-- box(1)-consistency
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@ -309,52 +323,52 @@ defaultBisectionOptions minWidth _narrowAbs box =
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-- iRange'' = eqs box'' `monIndex` zeroMonomial
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--in unT ( origin @Double ) `inside` iRange''
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, fallbackBisectionDim =
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\ _roundHist _prevRoundsHist eqs ->
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let df = eqs box
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datPerCoord =
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[ CoordBisectionData
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\ _roundHist _prevRoundsHist eqs possibleCoordChoices ->
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let datPerCoord =
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possibleCoordChoices <&> \ ( i, r ) ->
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CoordBisectionData
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{ coordIndex = i
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, coordInterval = box `index` i
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, coordJacobianColumn = df `monIndex` ( linearMonomial i )
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, coordJacobianColumn = eqs box `monIndex` ( linearMonomial i )
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, coordBisectionData = r
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}
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| i <- toList $ universe @n ]
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-- First, check if the largest dimension is over 10 times larger
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-- First, check if the largest dimension is over 20 times larger
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-- than the smallest dimension; if so bisect along that coordinate.
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in case sortOnArg ( width . coordInterval ) datPerCoord of
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[] -> error "impossible: dimension 0"
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[Arg _ d] -> (coordIndex d, "")
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Arg w0 _ : ds ->
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in case sortOnArgNE ( width . coordInterval ) datPerCoord of
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Arg _ d NE.:| [] -> ( coordBisectionData d, "" )
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Arg w0 _ NE.:| ds ->
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let Arg w1 d1 = last ds
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in if w1 >= 10 * w0
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then ( coordIndex d1, "tooWide" )
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in if w1 >= 20 * w0
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then ( coordBisectionData d1, "tooWide" )
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-- Otherwise, pick the dimension with the largest spread = width * Jacobian column norm
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else case filter ( not . isTooSmall ) $ sortOnArg ( Dual . spread ) datPerCoord of
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[] -> ( coordIndex d1, "tooWide'" )
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Arg _ d : _ -> ( coordIndex d, "spread" )
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else
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let isTooSmall ( Arg ( Dual w ) _ ) = w < minWidth
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in case NE.filter ( not . isTooSmall ) $ sortOnArgNE ( Dual . spread ) datPerCoord of
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[] -> ( coordBisectionData d1, "tooWide'" )
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Arg _ d : _ -> ( coordBisectionData d, "spread" )
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}
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where
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isTooSmall ( Arg ( Dual w ) _ ) = w < minWidth
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{-# INLINEABLE defaultBisectionOptions #-}
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sortOnArg :: Ord b => (a -> b) -> [a] -> [Arg b a]
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sortOnArg f = sort . map ( \ a -> Arg ( f a ) a )
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{-# INLINEABLE sortOnArg #-}
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sortOnArgNE :: Ord b => ( a -> b ) -> NE.NonEmpty a -> NE.NonEmpty ( Arg b a )
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sortOnArgNE f = NE.sort . fmap ( \ a -> Arg ( f a ) a )
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{-# INLINEABLE sortOnArgNE #-}
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type CoordBisectionData :: Nat -> Nat -> Type
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data CoordBisectionData n d =
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type CoordBisectionData :: Nat -> Nat -> Type -> Type
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data CoordBisectionData n d r =
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CoordBisectionData
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{ coordIndex :: !( Fin n )
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, coordInterval :: !( 𝕀 Double )
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, coordJacobianColumn :: !( 𝕀ℝ d )
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, coordBisectionData :: !r
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}
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deriving stock instance Show ( ℝ d )
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=> Show ( CoordBisectionData n d )
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deriving stock instance ( Show ( ℝ d ), Show r )
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=> Show ( CoordBisectionData n d r )
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spread :: ( BoxCt n d, Representable Double ( ℝ d ) )
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=> CoordBisectionData n d -> Double
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=> CoordBisectionData n d r -> Double
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spread ( CoordBisectionData { coordInterval = cd, coordJacobianColumn = j_cd } )
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= width cd * normVI j_cd
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= width cd * normVI j_cd --maxVI j_cd
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{-# INLINEABLE spread #-}
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-- | Use the following algorithms using interval arithmetic in order
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@ -400,13 +414,12 @@ isolateRootsIn
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= case cuspFindingAlgorithms cand history of
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Right strats -> doStrategies history strats cand
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Left whyStop -> do
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-- We are giving up on this box (e.g. because it is too small,
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-- or we have reached an iteration depth).
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-- We are giving up on this box (e.g. because it is too small).
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tell ( [ cand ], [] )
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return [ RootIsolationLeaf whyStop cand ]
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where
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iRange :: Box d
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iRange = ( `monIndex` zeroMonomial ) $ eqs cand
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iRange = eqs cand `monIndex` zeroMonomial
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-- Run a round of cusp finding strategies, then recur.
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doStrategies
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@ -477,56 +490,57 @@ doStrategy roundHistory previousRoundsHistory eqs minWidth algo box =
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-- (The difficult part lies in determining along which dimension to bisect.)
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bisect
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:: forall n
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. ( KnownNat n, Representable Double ( ℝ n ) )
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. ( 1 <= n, KnownNat n, Representable Double ( ℝ n ) )
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=> ( Box n -> Bool )
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-- ^ how to check whether a box contains solutions
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-> ( Fin n, String )
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-- ^ fallback choice of dimension (and "why" we chose it)
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-> ( forall r. NE.NonEmpty ( Fin n, r ) -> ( r, String ) )
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-- ^ heuristic bisection coordinate picker
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-> Box n
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-- ^ the box to bisect
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-> ( [ Box n ], ( String, Double ) )
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bisect canHaveSols ( fallbackDim, why ) box =
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-- We try to bisect along a dimension which eliminates zeros from one of the
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-- sub-regions.
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--
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-- If this fails, we fall back to the provided dimension choice.
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bisect canHaveSols pickFallBackBisCoord box =
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case findFewestSols solsList of
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Just ( Arg _nbSols ( i, mid, oks ) ) ->
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( oks, ("cd = " ++ show i, mid ) )
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Nothing ->
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case bisectInCoord box fallbackDim of
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( mid, ( lo, hi ) ) ->
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( [ lo, hi ], ( why, mid ) )
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-- If there is a coordinate for which bisection results in no solutions,
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-- or in fewer sub-boxes with solutions than any other coordinate choice,
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-- pick that coordinate for bisection.
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( i, ( mid, subBoxesWithSols ) ) NE.:| [] ->
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( subBoxesWithSols, ( "cd = " ++ show i, mid ) )
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-- Otherwise, fall back to the provided heuristic.
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is ->
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let ( ( mid, subBoxesWithSols ), why ) = pickFallBackBisCoord is
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in ( subBoxesWithSols, ( why, mid ) )
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where
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solsList =
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[ Arg ( fromIntegral $ length oks ) ( i, mid, oks )
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NE.fromList -- (n >= 1 so definitely non-empty)
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[ Arg ( fromIntegral $ length subBoxesWithSols ) ( i, ( mid, subBoxesWithSols ) )
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| i <- toList $ universe @n
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, let (mid, (lo, hi)) = bisectInCoord box i
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lo_ok = canHaveSols lo
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hi_ok = canHaveSols hi
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oks = [ lo | lo_ok ] ++ [ hi | hi_ok ]
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, let ( mid, ( loBox, hiBox ) ) = bisectInCoord box i
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loBox_ok = canHaveSols loBox
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hiBox_ok = canHaveSols hiBox
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subBoxesWithSols = [ loBox | loBox_ok ] ++ [ hiBox | hiBox_ok ]
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]
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{-# INLINEABLE bisect #-}
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-- | Find any element with the least argument.
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-- | Return the elements with the least argument.
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--
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-- NB: this function shortcuts as soon as it finds an element with argument 0.
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findFewestSols :: forall a. [ Arg Word a ] -> Maybe ( Arg Word a )
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findFewestSols [] = Nothing
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findFewestSols ( arg@( Arg nbSols _ ) : args )
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findFewestSols :: forall a. NE.NonEmpty ( Arg Word a ) -> NE.NonEmpty a
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findFewestSols ( ( Arg nbSols arg ) NE.:| args )
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| nbSols == 0
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= Just arg
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= NE.singleton arg
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| otherwise
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= Just $ go arg args
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= go nbSols ( NE.singleton arg ) args
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where
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go :: Arg Word a -> [ Arg Word a ] -> Arg Word a
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go bestSoFar [] = bestSoFar
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go bestSoFar@( Arg bestNbSolsSoFar _ ) ( arg'@( Arg nbSols' _ ) : args' )
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go :: Word -> NE.NonEmpty a -> [ Arg Word a ] -> NE.NonEmpty a
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go _ bestSoFar [] = bestSoFar
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go bestNbSolsSoFar bestSoFar ( ( Arg nbSols' arg' ) : args' )
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| nbSols' == 0
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= arg'
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| nbSols' < bestNbSolsSoFar
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= go arg' args'
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= NE.singleton arg'
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| otherwise
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= go bestSoFar args'
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= case compare nbSols' bestNbSolsSoFar of
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LT -> go nbSols' ( NE.singleton arg' ) args'
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GT -> go bestNbSolsSoFar bestSoFar args'
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EQ -> go bestNbSolsSoFar ( arg `NE.cons` bestSoFar ) args'
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bisectInCoord
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:: Representable Double ( ℝ n )
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@ -755,8 +769,8 @@ matMulVec
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-> 𝕀ℝ m -- ^ vector \( v \)
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-> 𝕀ℝ n
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matMulVec as v = tabulate $ \ r ->
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sum [ scaleInterval ( ( as ! c ) `index` r ) ( index v c )
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| c <- toList ( universe @m )
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sum [ scaleInterval ( a `index` r ) ( index v c )
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| ( c, a ) <- toList ( (,) <$> universe @m <*> as )
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]
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{-# INLINEABLE matMulVec #-}
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@ -768,6 +782,14 @@ normVI ( 𝕀 los his ) =
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nm1 lo hi = max ( abs lo ) ( abs hi ) Ring.^ 2
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{-# INLINEABLE normVI #-}
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maxVI :: ( Applicative ( Vec d ), Representable Double ( ℝ d ) ) => 𝕀ℝ d -> Double
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maxVI ( 𝕀 los his ) =
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maximum ( maxAbs <$> coordinates los <*> coordinates his )
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where
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maxAbs :: Double -> Double -> Double
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maxAbs lo hi = max ( abs lo ) ( abs hi )
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{-# INLINEABLE maxVI #-}
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-- Use the univariate interval Newton method to narrow from the left
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-- a candidate interval.
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--
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