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@JulianBirch
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Revised version of Kris Jenkin's Markov Generator
{-# OPTIONS_GHC -Wall #-}
{-# LANGUAGE RankNTypes #-}
module Main where
-- Lots more imports
import Control.Applicative
import Data.List
import qualified Data.Map as Map
import System.Random
-- No longer have an End here. This is because I'm using the absence of an entry
-- in the graph to indicate termination. More further down
data Node a = Node a | Start | End deriving (Eq, Ord, Show)
-- Redefined definition of Graph so that it doesn't depend on Node
-- This, in turn, allows subsequent functions to be node-independent
newtype Graph a = Graph (Map.Map a [a])
-- oneOf moved close to usage
-- addHeadAndTail collapsed with lineToSentence
-- addPair renamed since the old name made no sense
-- Replaced the pairs logic with something that just destructures the head of the list
-- Then swapped the parameters to make it pointfree
addSuccessor :: Ord a => Graph a -> [a] -> Graph a
-- Use insertWith instead. My feeling is that insertWith isn't as nice as
-- Clojure's update-in,
-- in that it requires the inserted value to be the same type as the storage representation
addSuccessor (Graph t) (x:y:_) = Graph $ Map.insertWith (++) x [y] t
addSuccessor t _ = t
-- Used infix
-- flipped the arguments around to facilitate currying
oneOf :: RandomGen g => g -> [a] -> (a,g)
oneOf g xs = (xs !! n, g')
where (n,g') = randomR (0, length xs - 1) g
-- readChainStep modified to work with unfoldr
-- unfoldr is more useful than clojure's iterate function because it's got
-- termination built in.
-- Also modified to use the fact that Maybe is a Functor and so you can just
-- fmap everything
-- Since unfoldr expects a Maybe and lookup generates one, we lose a lot
-- of type rewriting book-keeping
-- Finally, removed the logic from this function that destructured Node, making it
-- Node independent
nextStep :: (Node a, g) -> Maybe (a, (Node a, g))
nextStep p@(Node a, _) = Just (a, p)
nextStep _ = Nothing
-- Fixed the bug. Also discoved the first time I needed a monad
readChainStep :: (Ord a, RandomGen g) => Graph (Node a) -> ((Node a),g) -> Maybe (a,(Node a, g))
readChainStep (Graph t) (p,g) = nextStep =<< oneOf g <$> Map.lookup p t
-- readChain folded into main
-- No longer adds end,
lineToSentence :: [a] -> [Node a]
lineToSentence xs = [Start] ++ fmap Node xs ++ [End]
-- Now uses unfoldr instead of readChain
main :: IO ()
main = do
text <- readFile "corpus.txt"
g <- getStdGen
let productions = tails =<< lineToSentence <$> words <$> lines text
-- Instead of passing the sentences in and tearing them down, we concatMap
-- to tails to just get a list of productions. Then we only need one word
-- This basically makes the whole thing
-- file -> unfold to productions -> fold to graph -> unfold to output -> print output
tree = foldl addSuccessor (Graph Map.empty) productions
newChain = unfoldr (readChainStep tree) (Start,g)
print $ unwords newChain
@pyrtsa
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pyrtsa commented Jun 8, 2014

You probably meant something like

lineToSentence = (Start :) . fmap Node . words

on line 65.

And it probably makes sense to include a data constructor like Stop marking the end of the sentence to allow the Markov chain to stop when picking a word that can appear both in the middle of a sentence as well as in the end.

PS. Btw, found out about Pointfree when fixing it. Here's a nice setup for GHCi:

$ cabal install pointfree
$ echo echo ':def pf \str -> return $ ":! pointfree " ++ show str ++ ""' >> ~/.ghci
$ cabal repl
...
λ> :pf \line -> Start : (fmap Node $ words line)
(Start :) . fmap Node . words

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