Method for common values in two lists - ruby

Does Ruby has a method I could use when I have 2 arrays (lists) and I want to get an array (list) of only the values common to both arrays? Like this..
a = [1,2,3]
b = [3,4,5]
=> the method would return [3]
And the other way around, values that are "unique" in those arrays (lists).
a = [1,2,3]
b = [3,4,5]
=> the method would return [1,2,4,5]

AND : a & b
There are no XOR method for arrays in Ruby, so you may do it via another methods. Here are 2 ways:
XOR : (a | b) - (a & b)
XOR : (a + b) - (a & b) # this result can have duplicates!
XOR : (a - b) | (b - a)
XOR : (a - b) + (b - a) # this result can have duplicates!

The words you are looking for are intersection and symmetric difference. AFAIK it's this in Ruby:
[1,2,3] & [3,4,5] = [3]
[1,2,3] ^ [3,4,5] = [1,2,4,5]

Related

Sort a String list by String length

I want to sort a list of String first by the length of the strings, and if the length is the same then it should sort lexically. I thought I could use the Data.List library and write my own compare function that does that. So the compare function should take a list of String as the argument and compare all the the elements (which are Strings). A compare function for Strings would look like this
comp a b
| length a > length b = GT
| length a < length b = LT
How could I address all the list elements with such a function?
First of all, your cmp function does not handle the case where the lengths are equal: you need to add that. Otherwise you'll get an runtime pattern match error:
comp a b
| length a > length b = GT
| length a < length b = LT
| otherwise = undefined -- TODO
also, note that this implementation sometimes computes the length twice, but it's likely that GHC optimizes this one away on its own, and we'll get to solving this later on more fundamentally anyway.
Then, once you've fixed your comp, all you need to do is pass it to Data.List.sortBy together with the list of strings you want to sort. An ipmplementation like that is provided below (<$> is the operator alias of fmap which works the same as map does on lists).
However, there's a better solution where you first compute the length of all elements in the list, by mapping each of the elements into a pair where the first member is the original string and the second one is its length. You then use a modified comp function that takes 2 pairs instead of just 2 strings, but otherwise behaves the same as your original comp. However, you then need to map the intermediate list back to just containing the strings (which is what the fst <$> is for, which is equivalent to map fst but, again, uses the, IMO nicer looking, <$> opetator).
So the somewhat naive solution would be:
sortByLenOrLex :: [String] -> [String]
sortByLenOrLex as = sortBy cmp as where
cmp a b | n > m = GT
| n < m = LT
| otherwise = compare a b
where n = length a
m = length b
and the more efficient one, as leftaroundabout points out, would be:
sortByLenOrLex' :: [String] -> [String]
sortByLenOrLex' as = fst <$> sortBy cmp (addLen <$> as) where
cmp (a,n) (b,m) | n > m = GT
| n < m = LT
| otherwise = compare a b
addLen x = (x, length x)
where the list is first amended with the lengths of each of its elements, so as to avoid duplicate, expensive length calls.
EDIT: please see chi's answer for a much nicer implementation of this algorithm!
Furthermore:
You can make your functions generic by making them operate on lists of lists of Ord:
sortByLenOrLex'' :: Ord a => [[a]] -> [[a]]
sortByLenOrLex'' as = fst <$> sortBy cmp (addLen <$> as) where
cmp (a,n) (b,m) | n > m = GT
| n < m = LT
| otherwise = compare a b
addLen x = (x, length x)
this gives you:
*Main> sortByLenOrLex'' [[1,2], [1,3], [1,2,3]]
[[1,2],[1,3],[1,2,3]]
...and if you want to make it as generic as possible, you can sort lists of Foldable of Ord:
sortByLenOrLex''' :: (Foldable f, Ord a) => [f a] -> [f a]
sortByLenOrLex''' as = unamend <$> sortBy cmp (amend <$> as) where
cmp (a,n,a') (b,m,b') | n > m = GT
| n < m = LT
| otherwise = compare a' b'
amend x = (x, length x, toList x)
unamend (x,_,_) = x
this gives you:
*Main> sortByLenOrLex''' [Just 3, Just 4, Just 3, Nothing]
[Nothing,Just 3,Just 3,Just 4]
*Main> sortByLenOrLex''' [(4,1),(1,1),(1,2),(1,1),(3,1)]
[(4,1),(1,1),(1,1),(3,1),(1,2)]
*Main> sortByLenOrLex''' [Left "bla", Right "foo", Right "foo", Right "baz"]
[Left "bla",Right "baz",Right "foo",Right "foo"]
*Main> sortByLenOrLex''' [(3,"hello"),(2,"goodbye"),(1,"hello")]
[(2,"goodbye"),(3,"hello"),(1,"hello")]
A variant of #Erik's solution, using some combinators from the library:
import Data.List
import Control.Arrow
sortByLen = map snd . sort . map (length &&& id)
This is essentially a Schwartzian transform.

Is there a fast algorithm to determine the godel number of a term of a context free language?

Suppose we have a simple grammar specification. There is a way to enumerate terms of that grammar that guarantees that any finite term will have a finite position, by iterating it diagonally. For example, for the following grammar:
S ::= add
add ::= mul | add + mul
mul ::= term | mul * term
term ::= number | ( S )
number ::= digit | digit number
digit ::= 0 | 1 | ... | 9
You can enumerate terms like that:
0
1
0+0
0*0
0+1
(0)
1+0
0*1
0+0*0
00
... etc
My question is: is there a way to do the opposite? That is, to take a valid term of that grammar, say, 0+0*0, and find its position on such enumeration - in that case, 9?
For this specific problem, we can cook up something fairly simple, if we allow ourselves to choose a different enumeration ordering. The idea is basically the one in Every Bit Counts, which I also mentioned in the comments. First, some preliminaries: some imports/extensions, a data type representing the grammar, and a pretty-printer. For the sake of simplicity, my digits only go up to 2 (big enough to not be binary any more, but small enough not to wear out my fingers and your eyes).
{-# LANGUAGE TypeSynonymInstances #-}
import Control.Applicative
import Data.Universe.Helpers
type S = Add
data Add = Mul Mul | Add :+ Mul deriving (Eq, Ord, Show, Read)
data Mul = Term Term | Mul :* Term deriving (Eq, Ord, Show, Read)
data Term = Number Number | Parentheses S deriving (Eq, Ord, Show, Read)
data Number = Digit Digit | Digit ::: Number deriving (Eq, Ord, Show, Read)
data Digit = D0 | D1 | D2 deriving (Eq, Ord, Show, Read, Bounded, Enum)
class PP a where pp :: a -> String
instance PP Add where
pp (Mul m) = pp m
pp (a :+ m) = pp a ++ "+" ++ pp m
instance PP Mul where
pp (Term t) = pp t
pp (m :* t) = pp m ++ "*" ++ pp t
instance PP Term where
pp (Number n) = pp n
pp (Parentheses s) = "(" ++ pp s ++ ")"
instance PP Number where
pp (Digit d) = pp d
pp (d ::: n) = pp d ++ pp n
instance PP Digit where pp = show . fromEnum
Now let's define the enumeration order. We'll use two basic combinators, +++ for interleaving two lists (mnemonic: the middle character is a sum, so we're taking elements from either the first argument or the second) and +*+ for the diagonalization (mnemonic: the middle character is a product, so we're taking elements from both the first and second arguments). More information on these in the universe documentation. One invariant we'll maintain is that our lists -- with the exception of digits -- are always infinite. This will be important later.
ss = adds
adds = (Mul <$> muls ) +++ (uncurry (:+) <$> adds +*+ muls)
muls = (Term <$> terms ) +++ (uncurry (:*) <$> muls +*+ terms)
terms = (Number <$> numbers) +++ (Parentheses <$> ss)
numbers = (Digit <$> digits) ++ interleave [[d ::: n | n <- numbers] | d <- digits]
digits = [D0, D1, D2]
Let's see a few terms:
*Main> mapM_ (putStrLn . pp) (take 15 ss)
0
0+0
0*0
0+0*0
(0)
0+0+0
0*(0)
0+(0)
1
0+0+0*0
0*0*0
0*0+0
(0+0)
0+0*(0)
0*1
Okay, now let's get to the good bit. Let's assume we have two infinite lists a and b. There's two things to notice. First, in a +++ b, all the even indices come from a, and all the odd indices come from b. So we can look at the last bit of an index to see which list to look in, and the remaining bits to pick an index in that list. Second, in a +*+ b, we can use the standard bijection between pairs of numbers and single numbers to translate between indices in the big list and pairs of indices in the a and b lists. Nice! Let's get to it. We'll define a class for Godel-able things that can be translated back and forth between numbers -- indices into the infinite list of inhabitants. Later we'll check that this translation matches the enumeration we defined above.
type Nat = Integer -- bear with me here
class Godel a where
to :: a -> Nat
from :: Nat -> a
instance Godel Nat where to = id; from = id
instance (Godel a, Godel b) => Godel (a, b) where
to (m_, n_) = (m + n) * (m + n + 1) `quot` 2 + m where
m = to m_
n = to n_
from p = (from m, from n) where
isqrt = floor . sqrt . fromIntegral
base = (isqrt (1 + 8 * p) - 1) `quot` 2
triangle = base * (base + 1) `quot` 2
m = p - triangle
n = base - m
The instance for pairs here is the standard Cantor diagonal. It's just a bit of algebra: use the triangle numbers to figure out where you're going/coming from. Now building up instances for this class is a breeze. Numbers are just represented in base 3:
-- this instance is a lie! there aren't infinitely many Digits
-- but we'll be careful about how we use it
instance Godel Digit where
to = fromIntegral . fromEnum
from = toEnum . fromIntegral
instance Godel Number where
to (Digit d) = to d
to (d ::: n) = 3 + to d + 3 * to n
from n
| n < 3 = Digit (from n)
| otherwise = let (q, r) = quotRem (n-3) 3 in from r ::: from q
For the remaining three types, we will, as suggested above, check the tag bit to decide which constructor to emit, and use the remaining bits as indices into a diagonalized list. All three instances necessarily look very similar.
instance Godel Term where
to (Number n) = 2 * to n
to (Parentheses s) = 1 + 2 * to s
from n = case quotRem n 2 of
(q, 0) -> Number (from q)
(q, 1) -> Parentheses (from q)
instance Godel Mul where
to (Term t) = 2 * to t
to (m :* t) = 1 + 2 * to (m, t)
from n = case quotRem n 2 of
(q, 0) -> Term (from q)
(q, 1) -> uncurry (:*) (from q)
instance Godel Add where
to (Mul m) = 2 * to m
to (m :+ t) = 1 + 2 * to (m, t)
from n = case quotRem n 2 of
(q, 0) -> Mul (from q)
(q, 1) -> uncurry (:+) (from q)
And that's it! We can now "efficiently" translate back and forth between parse trees and their Godel numbering for this grammar. Moreover, this translation matches the above enumeration, as you can verify:
*Main> map from [0..29] == take 30 ss
True
We did abuse many nice properties of this particular grammar -- non-ambiguity, the fact that almost all the nonterminals had infinitely many derivations -- but variations on this technique can get you quite far, especially if you are not too strict on requiring every number to be associated with something unique.
Also, by the way, you might notice that, except for the instance for (Nat, Nat), these Godel numberings are particularly nice in that they look at/produce one bit (or trit) at a time. So you could imagine doing some streaming. But the (Nat, Nat) one is pretty nasty: you have to know the whole number ahead of time to compute the sqrt. You actually can turn this into a streaming guy, too, without losing the property of being dense (every Nat being associated with a unique (Nat, Nat)), but that's a topic for another answer...

How is this expression evaluated

Can anyone say how ruby evaluates this:
a = 1
b = 2
a, b = b, a + b
a will be 2 and b will be 3, not 4 as you might expect
It seems that instead of working from left to right it does both sides in parallel somehow?
It is expressed as :-
a = 1
b = 2
a, b = b, (a + b)
a # => 2
b # => 3
This is called parallel assignment. Here all RHS expressions will be evaluated first (left to right). After that assignment will be happened from left to right.
It means, the calculation as follows :
a, b = b, a + b
a, b = 2, (2 + 1)
a, b = 2, 3 # now the real assignment will be happened here.
This is called parallel association, and, like name suggests, it works like all the assignments are done in parallel. You can for example write:
a = 1
b = 2
a, b = b, a
a #=> 2
b #=> 1
a = 1
b = 2
a, b = b, a + b
a
#=> 2
b
#=> 3
Here first rvalue is assigned to first lvalue and the result of second rexp is assigned to second lvalue. These assignments are parallel in nature not sequential.
a, b = b, a is a swap operation using parallel assignments. This makes me think Ruby might be using temporary variables to perform parallel assignments. I invite for corrections here.

Writing infinite list to skip every factor of p?

How can I efficiently represent the list [0..] \\ [t+0*p, t+1*p ..]?
I have defined:
Prelude> let factors p t = [t+0*p, t+1*p ..]
I want to efficiently represent an infinite list that is the difference of [0..] and factors p t, but using \\ from Data.List requires too much memory for even medium-sized lists:
Prelude Data.List> [0..10000] \\ (factors 5 0)
<interactive>: out of memory
I know that I can represent the values between t+0*p and t+1*p with:
Prelude> let innerList p1 p2 t = [t+p1+1, t+p1+2 .. t+p2-1]
Prelude> innerList 0 5 0
[1,2,3,4]
However, repeatedly calculating and concatenating innerList for increasing intervals seems clumsy.
Can I efficiently represent [0..] \\ (factors p t) without calculating rem or mod for each element?
For the infinite list [0..] \\ [t,t+p..],
yourlist t p = [0..t-1] ++ [i | m <- [0,p..], i <- [t+m+1..t+m+p-1]]
Of course this approach doesn't scale, at all, if you'd want to remove some other factors, like
[0..] \\ [t,t+p..] \\ [s,s+q..] \\ ...
in which case you'll have to remove them in sequence with minus, mentioned in Daniel Fischer's answer. There is no magic bullet here.
But there's also a union, with which the above becomes
[0..] \\ ( [t,t+p..] `union` [s,s+q..] `union` ... )
the advantage is, we can arrange the unions in a tree, and get algorithmic improvement.
You can't use (\\) for that, because
(\\) :: (Eq a) => [a] -> [a] -> [a]
(\\) = foldl (flip delete)
the list of elements you want to remove is infinite, and a left fold never terminates when the list it folds over is infinite.
If you rather want to use something already written than write it yourself, you can use minus from the data-ordlist package.
The performance should be adequate.
Otherwise,
minus :: Ord a => [a] -> [a] -> [a]
minus xxs#(x:xs) yys#(y:ys)
| x < y = x : minus xs yys
| x == y = minus xs ys
| otherwise = minus xss ys
minus xs _ = xs
You can use a list comprehesion with a predicate, using rem:
>>> let t = 0
>>> let p = 5
>>> take 40 $ [ x | x <- [1..], x `rem` p /= t ]
[1,2,3,4,6,7,8,9,11,12,13,14,16,17,18,19,21,22,23,24,26,27,28,29,31,32,33,34,36,37,38,39,41,42,43,44,46,47,48,49]
If you want efficiency, why does your solution have to use list comprehension syntax?
Why not something like this?
gen' n i p | i == p = gen' (n + p) 1 p
gen' n i p = (n+i) : gen' n (i+1) p
gen = gen' 0 1
and then do
gen 5
Because you have ascending lists, you can simply lazily merge them:
nums = [1..]
nogos = factors p t
result = merge nums (dropWhile (<head nums) nogos) where
merge (a:as) (b:bs)
| a < b = a : merge as (b:bs)
| a == b = merge as bs
| otherwise = error "should not happen"
Writing this in a general way so that we have a function that builds the difference of two infinite lists, provided only that they are in ascending order, is left as exercise. In the end, the following should be possible
[1..] `infiniteDifference` primes `infiniteDifference` squares
For this, make it a left associative operator.

Help with algorithm for compute columns sum of a (quadtree) matrix?

Given this definition and a test matrix:
data (Eq a, Show a) => QT a = C a | Q (QT a) (QT a) (QT a) (QT a)
deriving (Eq, Show)
data (Eq a, Num a, Show a) => Mat a = Mat {nexp :: Int, mat :: QT a}
deriving (Eq, Show)
-- test matrix, exponent is 2, that is matrix is 4 x 4
test = Mat 2 (Q (C 5) (C 6) (Q (C 1) (C 0) (C 2) (C 1)) (C 3))
| | |
| 5 | 6 |
| | |
-------------
|1 | 0| |
|--|--| 3 |
|2 | 1| |
I'm trying to write a function that will output a list of columns sum, like: [13, 11, 18, 18]. The base idea is to sum each sub-quadtree:
If quadtree is (C c), then output the a repeating 2 ^ (n - 1) times the value c * 2 ^ (n - 1). Example: first quadtree is (C 5) so we repeat 5 * 2^(2 - 1) = 10, 2 ^ (n - 1) = 2 times, obtaining [5, 5].
Otherwise, given (Q a b c d), we zipWith the colsum of a and c (and b and d).
Of course this is not working (not even compiling) because after some recursion we have:
zipWith (+) [[10, 10], [12, 12]] [zipWith (+) [[1], [0]] [[2], [1]], [6, 6]]
Because I'm beginning with Haskell I feel I'm missing something, need some advice on function I can use. Not working colsum definition is:
colsum :: (Eq a, Show a, Num a) => Mat a -> [a]
colsum m = csum (mat m)
where
n = nexp m
csum (C c) = take (2 ^ n) $ repeat (c * 2 ^ n)
csum (Q a b c d) = zipWith (+) [colsum $ submat a, colsum $ submat b]
[colsum $ submat c, colsum $ submat d]
submat q = Mat (n - 1) q
Any ideas would be great and much appreciated...
Probably "someone" should have explained to who is worried about the depth of the QuadTree that the nexp field in the Matrix type is exactly meant to be used to determine the real size of a (C _).
About the solution presented in the first answer, ok it works. However it is quite useless to construct and deconstruct Mat, this could be easily avoided. Moreover the call to fromIntegral to "bypass" the type checking problem coming from the use of replicate can be solved without forcing to first going to Integral and then coming back, like
let m = 2^n; k=2^n in replicate k (m*x)
Anyway, the challenge here is to avoid the quadratical behavior due to the ++, that is what I would expect.
Cheers,
Let's consider your colsum:
colsum :: (Eq a, Show a, Num a) => Mat a -> [a]
colsum m = csum (mat m)
where
n = nexp m
csum (C c) = take (2 ^ n) $ repeat (c * 2 ^ n)
csum (Q a b c d) = zipWith (+) [colsum $ submat a, colsum $ submat b]
[colsum $ submat c, colsum $ submat d]
submat q = Mat (n - 1) q
It is almost correct, except the line where you define csum (Q a b c d) = ....
Let think about types. colsum returns a list of numbers. ZipWith (+) sums two lists elementwise:
ghci> :t zipWith (+)
zipWith (+) :: Num a => [a] -> [a] -> [a]
This means that you need to pass two lists of numbers to zipWith (+). Instead you create two lists of lists of numbers, like this:
[colsum $ submat a, colsum $ submat b]
The type of this expression is [[a]], not [a] as you need.
What you need to do is to concatenate two lists of numbers to obtain a single list of numbers (and this is, probably, what you intended to do):
((colsum $ submat a) ++ (colsum $ submat b))
Similarly, you concatenate lists of partial sums for c and d then your function should start working.
Let's go more general, and come back to the goal at hand.
Consider how we would project a quadtree into a 2n×2n matrix. We may not need to create this projection in order to calculate its column sums, but it's a useful notion to work with.
If our quadtree is a single cell, then we'd just fill the entire matrix with that cell's value.
Otherwise, if n ≥ 1, we can divide the matrix up into quadrants, and let the subquadtrees each fill one quadrant (that is, have each subquadtree fill a 2n-1×2n-1 matrix).
Note that there's still a case remaining. What if n = 0 (that is, we have a 1×1 matrix) and the quadtree isn't a single cell? We need to specify some behaviour for this case - maybe we just let one of the subquadtrees populate the entire matrix, or we fill the matrix with some default value.
Now consider the column sums of such a projection.
If our quadtree was a single cell, then the 2n column sums will all be 2n
times the value stored in that cell.
(hint: look at replicate and genericReplicate on hoogle).
Otherwise, if n ≥ 1, then each column overlaps two distinct quadrants.
Half of our columns will be completely determined by the western quadrants,
and the other half by the eastern quadrants, The sum for a particular column
can be defined as the sum of the contribution to that column
from its northern half (that is, the column sum for that column in the northern quadrant),
and its southern half (likewise).
(hint: We'll need to append the western column sums to the eastern column sums
to get all the column sums, and combien the northern and southern demi-column sums
to get the actual sums for each column).
Again, we have a third case, and the column sum here depends on how
you project four subquadtrees onto a 1×1 matrix. Fortunately, a 1×1 matrix means
only a single column sum!
Now, we only care about a particular projection - the projection onto a matrix of size 2dd×2d
where d is the depth of our quadtree. So you'll need to figure the depth too. Since a
single cell fits "naturally" into a matrix of size 1×1, that implies that it has a
depth of 0. A quadbranch must have depth great enough to allow each of its subquads to fit
into their quadrant of the matrix.

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