The contestant in control chooses six of 24 shuffled face-down number tiles, arranged into two groups: 20 "small numbers" (two each of 1 to 10), and four "large numbers" of 25, 50, 75, and 100. Some special episodes replace the large numbers with 12, 37, 62, and 87.
Number of characters: 548 482 425 421 416 413 408
from operator import *
n=len
def C(N,T):
R=range(1<<n(N));M=[{}for i in R];p=1
for i in range(n(N)):M[1<<i][1.*N[i]]="%d"%N[i]
while p:
p=0
for i in R:
for j in R:
m=M[i|j];l=n(m)
if not i&j:m.update((f(x,y),"("+s+o+t+")")for(y,t)in M[j].items()if y for(x,s)in M[i].items() for(o,f)in zip('+-*/',(add,sub,mul,div)))
p|=l<n(m)
return min((abs(x-T),e)for t in M for(x,e)in t.items())[1]
you can call it like this:
>>> print C([50, 100, 4, 2, 2, 4], 203)
((((4+2)*(2+100))/4)+50)
Takes about half a minute on the given examples on an oldish PC.
Here's the commented version:
def countdown(N,T):
# M is a map: (bitmask of used input numbers -> (expression value -> expression text))
M=[{} for i in range(1<<len(N))]
# initialize M with single-number expressions
for i in range(len(N)):
M[1<<i][1.0*N[i]] = "%d" % N[i]
# allowed operators
ops = (("+",lambda x,y:x+y),("-",lambda x,y:x-y),("*",lambda x,y:x*y),("/",lambda x,y:x/y))
# enumerate all expressions
n=0
while 1:
# test to see if we're done (last iteration didn't change anything)
c=0
for x in M: c +=len(x)
if c==n: break
n=c
# loop over all values we have so far, indexed by bitmask of used input numbers
for i in range(len(M)):
for j in range(len(M)):
if i & j: continue # skip if both expressions used the same input number
for (x,s) in M[i].items():
for (y,t) in M[j].items():
if y: # avoid /0 (and +0,-0,*0 while we're at it)
for (o,f) in ops:
M[i|j][f(x,y)]="(%s%s%s)"%(s,o,t)
# pick best expression
L=[]
for t in M:
for(x,e) in t.items():
L+=[(abs(x-T),e)]
L.sort();return L[0][1]
It works through exhaustive enumeration of all possibilities. It is a bit smart in that if there are two expressions with the same value that use the same input numbers, it discards one of them. It is also smart in how it considers new combinations, using the index into M to prune quickly all the potential combinations that share input numbers.
Number of characters: 361 350 338 322
Fully obfuscated function:
m=map
f=toRational
a%w=m(\(b,v)->(b,a:v))w
p[]=[];p(a:w)=(a,w):a%p w
q[]=[];q(a:w)=[((a,b),v)|(b,v)<-p w]++a%q w
z(o,p)(a,w)(b,v)=[(a`o`b,'(':w++p:v++")")|b/=0]
y=m z(zip[(-),(/),(+),(*)]"-/+*")++m flip(take 2 y)
r w=do{((a,b),v)<-q w;o<-y;c<-o a b;c:r(c:v)}
c t=snd.minimum.m(\a->(abs(fst a-f t),a)).r.m(\a->(f a,show a))
Clear function:
-- | add an element on to the front of the remainder list
onRemainder :: a -> [(b,[a])] -> [(b,[a])]
a`onRemainder`w = map (\(b,as)->(b,a:as)) w
-- | all ways to pick one item from a list, returns item and remainder of list
pick :: [a] -> [(a,[a])]
pick [] = []
pick (a:as) = (a,as) : a `onRemainder` (pick as)
-- | all ways to pick two items from a list, returns items and remainder of list
pick2 :: [a] -> [((a,a),[a])]
pick2 [] = []
pick2 (a:as) = [((a,b),cs) | (b,cs) <- pick as] ++ a `onRemainder` (pick2 as)
-- | a value, and how it was computed
type Item = (Rational, String)
-- | a specification of a binary operation
type OpSpec = (Rational -> Rational -> Rational, String)
-- | a binary operation on Items
type Op = Item -> Item -> Maybe Item
-- | turn an OpSpec into a operation
-- applies the operator to the values, and builds up an expression string
-- in this context there is no point to doing +0, -0, *0, or /0
combine :: OpSpec -> Op
combine (op,os) (ar,as) (br,bs)
| br == 0 = Nothing
| otherwise = Just (ar`op`br,"("++as++os++bs++")")
-- | the operators we can use
ops :: [Op]
ops = map combine [ ((+),"+"), ((-), "-"), ((*), "*"), ((/), "/") ]
++ map (flip . combine) [((-), "-"), ((/), "/")]
-- | recursive reduction of a list of items to a list of all possible values
-- includes values that don't use all the items, includes multiple copies of
-- some results
reduce :: [Item] -> [Item]
reduce is = do
((a,b),js) <- pick2 is
op <- ops
c <- maybe [] (:[]) $ op a b
c : reduce (c : js)
-- | convert a list of real numbers to a list of items
items :: (Real a, Show a) => [a] -> [Item]
items = map (\a -> (toRational a, show a))
-- | return the first reduction of a list of real numbers closest to some target
countDown:: (Real a, Show a) => a -> [a] -> Item
countDown t is = snd $ minimum $ map dist $ reduce $ items is
where dist is = (abs . subtract t' . fst $ is, is)
t' = toRational t
Any notes on the algorithm/clever shortcuts it takes:
z
returns in the list monad, rather than Maybe
as ops
does.reduce
generates some answers multiple times, in order to easily include solutions with fewer terms.y
is defined partially in terms of itself.Rational
values. Golf'd code would be 17 characters shorter, and faster if computed with Double
.onRemainder
factors out the structural similarity between pick
and pick2
.Driver for golf'd version:
main = do
print $ c 203 [50, 100, 4, 2, 2, 4]
print $ c 465 [25, 4, 9, 2, 3, 10]
print $ c 241 [9, 8, 10, 5, 9, 7]
print $ c 824 [3, 7, 6, 2, 1, 7]
Run, with timing (still under one minute per result):
[1076] : time ./Countdown
(203 % 1,"(((((2*4)-2)/100)+4)*50)")
(465 % 1,"(((((10-4)*25)+2)*3)+9)")
(241 % 1,"(((((10*9)/5)+8)*9)+7)")
(826 % 1,"(((((3*7)-1)*6)-2)*7)")
real 2m24.213s
user 2m22.063s
sys 0m 0.913s
I give up for now, it works as long as there is an exact answer. If there isn't it takes way too long to enumerate all possibilities.
def b a,o,c,p,r
o+c==2*p ?r<<a :o<p ?b(a+['('],o+1,c,p,r):0;c<o ?b(a+[')'],o,c+1,p,r):0
end
w=a=%w{+ - * /}
4.times{w=w.product a}
b [],0,0,3,g=[]
*n,l=$<.read.split.map(&:to_f)
h={}
catch(0){w.product(g).each{|c,f|k=f.zip(c.flatten).each{|o|o.reverse! if o[0]=='('};n.permutation{|m|h[x=eval(d=m.zip(k)*'')]=d;throw 0 if x==l}}}
c=h[k=h.keys.min_by{|i|(i-l).abs}]
puts c.gsub(/(\d*)\.\d*/,'\1')+"=#{k}"
Coming soon
#!/usr/bin/env ruby
[
[[50,100,4,2,2,4],203],
[[25,4,9,2,3,10],465],
[[9,8,10,5,9,7],241],
[[3,7,6,2,1,7],824]
].each do |b|
start = Time.now
puts "{[#{b[0]*', '}] #{b[1]}} gives #{`echo "#{b[0]*' '} #{b[1]}" | ruby count-golf.rb`.strip} in #{Time.now-start}"
end
→ ./test.rb
{[50, 100, 4, 2, 2, 4] 203} gives 100+(4+(50-(2)/4)*2)=203.0 in 3.968534736
{[25, 4, 9, 2, 3, 10] 465} gives 2+(3+(25+(9)*10)*4)=465.0 in 1.430715549
{[9, 8, 10, 5, 9, 7] 241} gives 5+(9+(8)+10)*9-(7)=241.0 in 1.20045702
{[3, 7, 6, 2, 1, 7] 824} gives 7*(6*(7*(3)-1)-2)=826.0 in 193.040054095
The function used for generating the bracket pairs (b
) is based off this one: Finding all combinations of well-formed brackets
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