# HG changeset patch
# User IBBoard <dev@ibboard.co.uk>
# Date 1563108253 -3600
# Node ID 98be775c533c96bce1824d365e75f9daec785d2d
# Parent  d3e35dfc6f84b0cbf8a52d94cf3283f01f8302d5
An odd "non-determinism" example from StackOverflow

It is clever, but doesn't make much sense as to how it gets its results

diff -r d3e35dfc6f84 -r 98be775c533c 7-Haskell/cointoss.hs
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/7-Haskell/cointoss.hs	Sun Jul 14 13:44:13 2019 +0100
@@ -0,0 +1,30 @@
+module CoinToss where
+    -- Based on https://stackoverflow.com/questions/20638893/how-can-non-determinism-be-modeled-with-a-list-monad
+    -- Because it only throws "*** Exception: <interactive>:57:1-26: Non-exhaustive patterns in function toss" in gchi
+    import Control.Monad -- Required for guard, but not mentioned in the example
+
+    data CoinType = Fair | Biased deriving (Show)
+    data Coin = Head | Tail deriving (Eq,Show)
+
+    toss Fair   = [Head, Tail]
+    toss Biased = [Head, Head]
+
+    pick = [Fair, Biased]
+
+    experiment = do
+        coin   <- pick         -- Pick a coin at random (Non-determinism takes both coins)
+        result <- toss coin    -- Toss it, to get a result (Non-determinism joins all possible toss results in a single list)
+        guard (result == Head) -- We only care about results that come up Heads (Non-determinism does something weird and inexplicable)
+        return coin            -- Return which coin was used in this case (Magic has happened here and we've suddenly gone from "Head, Tail, Head, Head" to "Fair, Biased, Biased")
+
+    part_experiment = do
+        coin   <- pick         -- Pick a coin at random
+        result <- toss coin    -- Toss it, to get a result
+        return result          -- Return the intermediary results
+
+    part_experiment_2 = do
+        coin   <- pick         -- Pick a coin at random
+        result <- toss coin    -- Toss it, to get a result
+        return guard (result == Head)          -- Return the intermediary results
+    
+    -- Load the module and then run "experiment" and you get [Fair,Biased,Biased], which apparently shows that there's a 2/3 chance it's a biased coin
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