Etage-Graph 0.1.4 → 0.1.6
raw patch · 2 files changed
+8/−8 lines, 2 filesdep ~Etagedep ~Etage-Graph
Dependency ranges changed: Etage, Etage-Graph
Files
- Etage-Graph.cabal +5/−5
- lib/Data/Graph/Etage.hs +3/−3
Etage-Graph.cabal view
@@ -1,5 +1,5 @@ Name: Etage-Graph-Version: 0.1.4+Version: 0.1.6 Synopsis: Data-flow based graph algorithms Description: Data-flow based graph algorithms using the "Control.Etage" framework, showcasing its use for data-flow computations. It is meant to be used with the "Data.Graph.Inductive" package which provides graph structures@@ -13,7 +13,7 @@ License-file: LICENSE Author: Mitar Milutinovic Maintainer: mitar.haskell@tnode.com-Copyright: (c) 2011 Mitar Milutinovic+Copyright: (c) 2011-2012 Mitar Milutinovic Category: Data Structures Build-type: Simple Cabal-version: >= 1.8@@ -23,7 +23,7 @@ Library Exposed-modules: Data.Graph.Etage Build-depends: base >= 4.3 && < 5,- Etage >= 0.1.8 && < 0.2,+ Etage >= 0.1.10 && < 0.2, fgl >= 5.4.2 && < 5.5, mtl >= 2.0 && < 3, containers >= 0.4 && < 1@@ -48,7 +48,7 @@ array >= 0.3 && < 1, time >= 1.1 && < 2, parallel >= 3.1 && < 4,- Etage == 0.1.8,- Etage-Graph == 0.1.4+ Etage >= 0.1.10 && < 0.2,+ Etage-Graph == 0.1.6 GHC-options: -Wall -rtsopts -threaded
lib/Data/Graph/Etage.hs view
@@ -17,7 +17,7 @@ import Data.Data import Data.Graph.Inductive hiding (inn, inn', out, out', node', nodes, run) import qualified Data.Map as M-import Data.Map hiding (filter, map, empty, null, lookup)+import Data.Map hiding (filter, map, empty, null, lookup, foldl) import Data.Tuple import System.IO @@ -40,10 +40,10 @@ While shortest paths search is lasting, information about suboptimal paths is already available. This algorithm also allows effective incremental search after graph topology changes (new nodes are added or removed, weights are changed) but this is not yet implemented. -}-shortestPaths :: (DynGraph gr, Show a, Data a, Data b, Real b, Bounded b) => gr a b -> Incubation (M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive))+shortestPaths :: (DynGraph gr, Show a, Show b, Data a, Data b, Real b, Bounded b) => gr a b -> Incubation (M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive)) shortestPaths = ufoldM' growGraph M.empty -growGraph :: forall a b. (Show a, Data a, Data b, Real b, Bounded b) => Context a b -> M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive) -> Incubation (M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive))+growGraph :: forall a b. (Show a, Show b, Data a, Data b, Real b, Bounded b) => Context a b -> M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive) -> Incubation (M.Map Node (Nerve (GraphImpulse a b) AxonConductive (GraphImpulse a b) AxonConductive)) growGraph (inn, node, label, out) nodes = do -- TODO: Sometimes nerve is not connected in both directions, how to fix memory leak then? liftIO $ do