- Split Instance into its own file, change it to use arrays, and implement Show.
- Add random InstanceGenerator using RandomizedMonad.
- Make Test export more stuff for use from GHCi.
--- /dev/null
+module ArrayStuff where
+import Data.Ix
+import Data.Array.IArray
+
+funcArray lohi f = listArray lohi $ map f $ range lohi
+
+transposeArray arr =
+ let swap (x, y) = (y, x) in
+ let (lo, hi) = bounds arr in
+ ixmap (swap lo, swap hi) swap arr
+
+array2DtoListOfLists arr =
+ let ((xlo, ylo), (xhi, yhi)) = bounds arr in
+ map (\x -> map (\y -> arr ! (x, y)) $ range (ylo, yhi)) $ range (xlo, xhi)
+
+-- Use instead of amap when the array implementation needs to change.
+-- E.g., mapping an unboxed array to an array whose elements must be boxed.
+amap2 f arr = funcArray (bounds arr) (\i -> f (arr ! i))
--- /dev/null
+module Formatter where
+import Data.List
+
+padWith :: a -> Int -> [a] -> [a]
+padWith _ 0 l = l
+padWith e n [] = replicate n e
+padWith e (n+1) (h:t) = h:(padWith e n t)
+
+formatTable :: [[String]] -> String
+formatTable cells =
+ let columnWidths = map (\col -> maximum $ map length col)
+ $ transpose cells in
+ intercalate "\n" $
+ map (\row ->
+ let rowCells = zipWith (padWith ' ') columnWidths row in
+ intercalate " " rowCells
+ ) cells
--- /dev/null
+module Instance where
+import Data.Array.IArray
+import Data.Array.Unboxed
+import ArrayStuff
+import Formatter
+
+type Wt = Double -- must implement RealFrac
+
+data Instance = Instance
+ Int -- numReviewers
+ Int -- numProposals
+ (UArray Int Wt) -- ! reviewer -> relative load
+ (UArray (Int, Int) Wt) -- ! (reviewer, proposal) -> pref
+ deriving Eq
+
+instance Show Instance where
+ show (Instance numRvrs numProps loadA prefA) =
+ "Instance: " ++ show numRvrs ++ " reviewers, " ++ show numProps ++ " proposals\n"
+ ++ "Reviewer relative load: " ++ show loadA ++ "\n"
+ ++ "Preferences:\n"
+ ++ formatTable (array2DtoListOfLists (amap2 show prefA :: Array (Int, Int) String))
--- /dev/null
+module InstanceGenerator where
+import Instance
+import System.Random
+import RandomizedMonad
+import Data.Array.IArray
+import ArrayStuff
+
+randomMap :: RandomGen g => g -> (g -> a -> b) -> [a] -> [b]
+randomMap g f l = case l of
+ [] -> []
+ h:t -> let (g1, g2) = split g in (f g1 h):(randomMap g2 f t)
+randomRep :: RandomGen g => g -> (g -> a) -> Int -> [a]
+randomRep g f n = if n == 0 then []
+ else let (g1, g2) = split g in (f g1):(randomRep g2 f (n-1))
+
+numTopics = 20
+
+-- Expertise on each of the topics
+type ReviewerInfo = Array Int Double
+
+randomReviewerInfo = do
+ list <- sequence $ replicate numTopics $
+ withProb [(0.15, return 2), (0.4, return 1)] (return 0)
+ return $ listArray (0, numTopics-1) list
+
+-- One topic or two different topics
+data ProposalTopics = PTopic1 Int | PTopic2 Int Int
+
+--type ProposalAuthors = Maybe Int
+
+type ProposalInfo = (ProposalTopics, Wt)
+
+randomProposalTopics = do
+ t1 <- mrandomR (0, numTopics-1)
+ withProb [(0.5, return $ PTopic1 t1)] (do
+ t2 <- filterRandomized (/= t1) $ mrandomR (0, numTopics-1)
+ return $ PTopic2 t1 t2
+ )
+
+-- Add conflict of interest later.
+{--
+randomProposalAuthors = do
+ withProb [(0.5, return [])] (do
+ a1 <- mrandomR (0, numRvrs-1)
+ withProb [(0.5, return [a1])] (do
+ a2 <- filterRandomized (/= a1) $ mrandomR (0, numRvrs-1)
+ return [a1,a2]
+ )
+ )
+--}
+
+randomProposalInfo = do
+ topics <- randomProposalTopics
+ diff <- mrandomR (3, 5)
+ return (topics, fromInteger diff)
+
+expertnessToPref expertness = if expertness == 0 then 7
+ else if expertness == 1 then 5
+ else 3
+
+randomInstance :: Int -> Int -> Randomized Instance
+randomInstance numRvrs numProps = do
+ reviewerInfosList <- sequence $ replicate numRvrs $ randomReviewerInfo
+ -- reviewerProfs is an array of arrays.
+ -- A pair-indexed array might be better...
+ let reviewerInfos = listArray (0, numRvrs-1) reviewerInfosList :: Array Int ReviewerInfo
+ proposalInfosList <- sequence $ replicate numProps $ randomProposalInfo
+ let proposalInfos = listArray (0, numProps-1) proposalInfosList :: Array Int ProposalInfo
+ let loadA = funcArray (0, numRvrs-1) $ const 1
+ let prefA = funcArray ((0, 0), (numRvrs-1, numProps-1)) (\(i,j) ->
+ let
+ ii = reviewerInfos ! i
+ jj = proposalInfos ! j
+ topicPref = case fst jj of
+ PTopic1 t1 -> expertnessToPref (ii ! t1)
+ PTopic2 t1 t2 -> (expertnessToPref (ii ! t1) + expertnessToPref (ii ! t2)) / 2
+ in topicPref * snd jj - 4)
+ return $ Instance numRvrs numProps loadA prefA
# Let's keep it simple for now.
all:
- ghc --make -c *.hs
+ ghc -fglasgow-exts --make -c *.hs
clean:
rm -f *.hi *.o
-module ProposalMatch where
+module ProposalMatcher where
import UnitMinCostFlow
import Data.Array.IArray
import Data.Graph.Inductive.Graph
import Data.Graph.Inductive.Tree
import Data.List
-import ProposalMatchConfig
-
-data Instance = Instance
- Int -- numReviewers
- Int -- numProposals
- (Int -> Wt) -- reviewer -> relative load
- (Int -> Int -> Wt) -- reviewer -> proposal -> pref
+import Instance
+import ProposalMatcherConfig
prefBoringness p = if prefIsVeryBoring p then 2
else if prefIsBoring p then 1 else 0
else if prefIsKnowledgeable p then 1 else 0
doReduction :: Instance -> Gr () Wt
-doReduction (Instance numRvrs numProps rloadF prefF) =
+doReduction (Instance numRvrs numProps rloadA prefA) =
let
source = 0
sink = 1
in
let
totalReviews = reviewsEachProposal * numProps
- totalRelativeLoad = foldl (+) 0 (map rloadF [0 .. numRvrs - 1])
- targetLoad i = ceiling (numAsWt totalReviews * rloadF i / totalRelativeLoad)
+ totalRelativeLoad = foldl (+) 0 (map (rloadA !) [0 .. numRvrs - 1])
+ targetLoad i = ceiling (numAsWt totalReviews * (rloadA ! i) / totalRelativeLoad)
-- A...H refer to idea book p.429
edgesABC = do
i <- [0 .. numRvrs - 1]
edgesD = do
i <- [0 .. numRvrs - 1]
j <- [0 .. numProps - 1]
- let pref = prefF i j
+ let pref = prefA ! (i, j)
if prefIsConflict pref
then []
else [(rvrNode i (prefBoringness pref),
todo = undefined
-- Returns a list of reviews as ordered pairs (reviewer#, proposal#).
doMatching :: Instance -> [(Int, Int)]
-doMatching inst@(Instance numRvrs numProps rloadF prefF) =
+doMatching inst@(Instance numRvrs numProps _ _) =
-- Copied from doReduction. There should be a better way to get these here.
let
source = 0
-module ProposalMatchConfig where
+module ProposalMatcherConfig where
+import Instance
type Pref = Int
-type Wt = Double -- must implement RealFrac
numAsWt x = fromInteger (toInteger x) :: Wt
--- /dev/null
+module RandomizedMonad (
+ Randomized,
+ runRandom, runRandomStd, runRandomNewStd,
+ mrandomR, mrandom,
+ withProb,
+ filterRandomized
+) where
+import System.Random
+
+-- Needs -XRank2Types
+newtype Randomized a = Randomized (forall g. RandomGen g => (g -> a))
+
+-- This implementation splits the RandomGen over and over.
+-- It would also be possible to serialize everything and use a single RandomGen.
+instance Monad Randomized where
+ ma >>= amb = Randomized (\g -> let
+ (g1, g2) = split g
+ Randomized fa = ma
+ a = fa g1
+ Randomized fb = amb a
+ in fb g2
+ )
+ return x = Randomized (const x)
+
+runRandom :: RandomGen g => g -> Randomized a -> a
+runRandom g (Randomized fa) = fa g
+
+-- Conveniences
+runRandomStd :: Randomized a -> IO a
+runRandomStd ra = do
+ g <- getStdGen
+ return $ runRandom g ra
+
+runRandomNewStd :: Randomized a -> IO a
+runRandomNewStd ra = do
+ g <- newStdGen
+ return $ runRandom g ra
+
+-- Monadic versions of random and randomR (to generate primitive-ish values)
+mrandomR :: Random a => (a, a) -> Randomized a
+mrandomR lohi = Randomized (\g -> fst (randomR lohi g))
+mrandom :: Random a => Randomized a
+mrandom = Randomized (\g -> fst (random g))
+
+chooseCase :: Double -> [(Double, a)] -> a -> a
+chooseCase val ifCs elseR = case ifCs of
+ [] -> elseR
+ (cutoff, theR):ifCt -> if val < cutoff
+ then theR
+ else chooseCase (val - cutoff) ifCt elseR
+
+withProb :: [(Double, Randomized a)] -> Randomized a -> Randomized a
+withProb ifCs elseR = do
+ val <- mrandom
+ chooseCase val ifCs elseR
+
+-- Keep trying until we get what we want.
+filterRandomized :: (a -> Bool) -> Randomized a -> Randomized a
+filterRandomized f ra = do
+ a <- ra
+ if f a then return a else filterRandomized f ra
-module Test where
+module Test (
+ -- Export everything we need to have fun in GHCi:
+
+ -- See the results of examples.
+ module Test,
+
+ -- Generate instances.
+ module Instance,
+ module InstanceGenerator,
+
+ -- Solve instances.
+ module ProposalMatcher,
+ module ProposalMatcherConfig,
+
+ -- Run randomized things.
+ module System.Random,
+ module RandomizedMonad,
+
+ -- Visualize graphs.
+ module Data.Graph.Inductive.Graphviz
+) where
+import Instance
+import InstanceGenerator
+import ProposalMatcher
+import ProposalMatcherConfig
+import System.Random
+import RandomizedMonad
+import Data.Graph.Inductive.Graphviz
+
+-- Other imports we need
import BellmanFord
import UnitMinCostFlow
-import ProposalMatch
-import ProposalMatchConfig
-import Data.Array
+import Data.Array.IArray
+import Data.Array.Unboxed
import Data.Graph.Inductive.Graph
import Data.Graph.Inductive.Tree
-
--- So we can call graphviz' at the GHCi prompt
-import Data.Graph.Inductive.Graphviz
-graphviz' g = Data.Graph.Inductive.Graphviz.graphviz' g
+import ArrayStuff
myGraph = mkGraph [(0, ()), (1, ()), (2, ())]
[(0, 1, 2), (0, 2, 3), (2, 1, -2)] :: Gr () Double
(myNumRvrs, myNumProps) = (5, 3)
-myPrefsArray = array ((0,0), (myNumRvrs-1,myNumProps-1)) [
- ((0, 0), 15), ((1, 0), 10), ((2, 0), 15), ((3, 0), 40), ((4, 0), 20),
- ((0, 1), 30), ((1, 1), 7), ((2, 1), 10), ((3, 1), 15), ((4, 1), 15),
- ((0, 2), 15), ((1, 2), 25), ((2, 2), 20), ((3, 2), 20), ((4, 2), 15)
- ]
+myPrefs = transposeArray $ listArray ((0,0), (myNumProps-1,myNumRvrs-1)) [
+ 15, 10, 15, 40, 20,
+ 30, 7, 10, 15, 15,
+ 15, 25, 20, 20, 15
+ ] :: UArray (Int, Int) Wt
-myPrefs = \i j -> myPrefsArray ! (i, j)
-myInst = Instance myNumRvrs myNumProps (const 1) myPrefs
+myInst = Instance myNumRvrs myNumProps (funcArray (0, myNumRvrs-1) $ const 1) myPrefs
rdnGraph = doReduction myInst
(rdnFlowVal, rdnFlowResid) = umcf 0 1 rdnGraph
Matt McCutchen's Web Site / match / match.git / commitdiff