Related
SO,
The problem
I have two integers, which are in first case, positive, and in second case - just any integers. I need to create a map function F from them to some another integer value, which will be:
Result should be integer value. For first case (x>0, y>0), positive integer value
Symmetric. That means F(x, y) = F(y, x)
Unique. That means F(x0, y0) = F(x1, y1) <=> (x0 = x1 ^ y0 = y1) V (y0 = x1 ^ x0 = y1)
My approach
At first glance, for positive integers we could use expression like F(x, y) = x2 + y2, but that will fail - for example, 892 + 232 = 132 + 912 As for second (common) case - that's even more complicated.
Use-case
That may be useful when dealing with some things, which supposed to be order-independent and need to be unique. For example, if we want to find cartesian product of many arrays and we want result to be unique independent of order, i.e. <x,z,y> is equal to <x,y,z>. It may be done with:
function decartProductPair($one, $two, $unique=false)
{
$result = [];
for($i=0; $i<count($one); $i++)
{
for($j=0; $j<count($two); $j++)
{
if($unique)
{
if($i!=$j)
{
$result[$i*$i+$j*$j]=array_merge((array)$one[$i],(array)$two[$j]);
// ^
// |
// +----//this is the place where F(i,j) is needed
}
}
else
{
$result[]=array_merge((array)$one[$i], (array)$two[$j]);
}
}
}
return array_values($result);
}
Another use-case is to properly group sender and receiver in some SQL table, so that different senders/receivers will be differed while they should stay symmetric. Something like:
SELECT
COUNT(1) AS message_count,
sender,
receiver
FROM
test
GROUP BY
-- this is the place where F(sender, receiver) is needed:
sender*sender + receiver*receiver
(By posting samples I wanted to show that issue is certainly related to programming)
The question
As mentioned, the question is - what can be used as F? I want as simple F as it's possible. Keep in mind two cases:
Integer x>0, y>0. F(x,y) > 0
Any integer x, y and so any integer F(x,y) as a result
May be F isn't just an expression - but some algorithm to find desired result for any x,y (so tagging with algorithm too). However, expression is better because it's more like that it will be able to use that expression in SQL or PHP or whatever. Feel free to edit tagging because I'm not sure if two tags here is enough
Most simple solution: f(x,y) = x^5 + y^5
No positive integer is known which can be written as the sum of two fifth powers in more than one way.
As for now, this is unsolved math problem.
You need a MAX_INTEGER constant, and the result will need to hold MAX_INTEGER**2 (say: be a long, if both are int's). In that case, one such function is:
f(x,y) = min(x,y)*MAX_INTEGER + max(x,y)
But I propose a different solution: use a hash function (say md5) of the string resulting from the concatenation of str(min(x,y)), a separator (say ".") and str(max(x,y)). That is:
f(x,y) = md5(str(min(x,y)) + "." + str(max(x,y)))
It is not unique, but collisions are very rare, and probably OK for most use cases. If still worried about collisions, save the actualy {x,y} along with f(x,y), and check if collisions happened.
Sort input numbers and interleave their bits:
x = 5
y = 3
Step 1. Sorting: 3, 5
Step 2. Mixing bits: 11, 101 -> 1_1_, 1_0_1 -> 11011 = 27
So, F(3, 5) = 27
A compact representation is x*(x+3)/2 + y*(x+1) + (y*(y-1))/2, which comes from an arrangement like this:
x->
y 0 1 3 6 10 15
| 2 4 7 11 16
v 5 8 12 17
9 13 18
14 19
20
According to [Stackoverflow:mapping-two-integers-to-one-in-a-unique-and-deterministic-way][1], if we symmetrize the formula we would have the following:
(x + y) * (x + y + 1) / 2 + min(x, y)
This might just work. For
(x + y) * (x + y + 1) / 2 + x
is unique, then the first formula is also unique.
[1]: Mapping two integers to one, in a unique and deterministic way
I'm given a string 2*x + 5 - (3*x-2)=x + 5 and I need to solve for x. My thought process is that I'd convert it to an expression tree, something like,
=
/ \
- +
/\ /\
+ - x 5
/\ /\
* 5 * 2
/\ /\
2 x 3 x
But how do I actually reduce the tree from here? Any other ideas?
You have to reduce it using axioms from algebra
a * (b + c) -> (a * b) + (a * c)
This is done by checking the types of each node in the pass tree. Once the thing is fully expanded into terms, you can then check they are actually linear, etc.
The values in the tree will be either variables or numbers. It isn't very neat to represent these as classes inheriting from some AbstractTreeNode class however, because cplusplus doesn't have multiple dispatch. So it is better to do it the 'c' way.
enum NodeType {
Number,
Variable,
Addition //to represent the + and *
}
struct Node {
NodeType type;
//union {char*, int, Node*[2]} //psuedo code, but you need
//something kind of like this for the
//variable name ("x") and numerical value
//and the children
}
Now you can query they types of a node and its children using switch case.
As I said earlier - c++ idiomatic code would use virtual functions but lack the necessary multiple dispatch to solve this cleanly. (You would need to store the type anyway)
Then you group terms, etc and solve the equation.
You can have rules to normalise the tree, for example
constant + variable -> variable + constant
Would put x always on the left of a term. Then x * 2 + x * 4 could be simplified more easily
var * constant + var * constant -> (sum of constants) * var
In your example...
First, simplify the '=' by moving the terms (as per the rule above)
The right hand side will be -1 * (x + 5), becoming -1 * x + -1 * 5. The left hand side will be harder - consider replacing a - b with a + -1 * b.
Eventually,
2x + 5 + -3x + 2 + -x + -5 = 0
Then you can group terms ever which way you want. (By scanning along, etc)
(2 + -3 + -1) x + 5 + 2 + -5 = 0
Sum them up and when you have mx + c, solve it.
Assuming you have a first order equation, check all the leaves on each side. On each side, have two bins: one to add up all the leaves containing a multiple of X and one for all the leaves containing a multiples of a constant. Either add to a bin or multiply each bin as you step up the tree along each branch from the leaves. You will end up with something that is conceptually like
a*x + b = c*x + d
At that point, you can just solve
x = (d - b) / (a - c)
Assuming the equation can reduce to f(x) = 0, and f(x) = a * x + b.
You can transform all the leaves in expression tree to f(x), for example : 2 -> 0 * x + 2, 3 * x -> 3 * x + 0, then you can do arithmetic operations of f(x) in expression tree. finally solve the equation f(x) = 0.
If the function is much more complicated than polynomial, you can do a binary search on x, and using the expression tree to calculate the left and right side of equation.
In my previous post on this subject i have made little progress (not blaming anyone except myself!) so i'll try to approach my problem statement differently.
how do i go about writing the algorithm to generate a list of primitive triples?
all i have to start with is:
a) the basic theorem: a^2 + b^2 = c^2
b) the fact that the small sides of the triple (a and b) need to be smaller than 'n'
(note: 'n' <= 200 for this purpose)
How do i go about building my loops? Do i need 2 or 3 loops?
a professor gave me some hints but alas i am still lost. I don't know where to start with building my loops. Do i need 2 or 3 loops? do i loop through a and b or do i need to introduce the 'n' variable into a loop of its own? This probably looks like obvious hints to experienced programmers but it seems i need more hand holding still...any help will be appreciated!
A Pythagorean triple is group of a,b,c
where a^2 + b^2 = c^2. you need to
find all a,b,c combinations which
satisfy the above rule starting a
0,0,0 up to 200 ,609,641 The first
triple will be [3,4,5] the next will
be [5,12,13] etc.. n is length of the
small side a so if n is 5 you need to
check all triples with
a=1,a=2,a=3,a=4,a=5 and find the two
cases shown above as being
Pythagorean,
EDIT
thanks for all submissions. So this is what i came up with (using python)
import math
for a in range (1,200):
for b in range (a,a*a):
csqrd = a * a + b * b
c = math.sqrt(csqrd)
if math.floor(c) == c:
print (a,b,int(c))
this DOES return the triple (200 ,609,641) where 200 is the upper limit for 'a' but computing the upper limit for 'b' remains tricky. Not sure how i would go about this...suggestions welcome :)
Thanks
Baba
p.s. i'm not looking for a solution but rather help in improving my problem solving skills. (definitely needed :-) )
You only need two loops. Note that n is given, meaning you read it from the keyboard or from a file.
Once you read n, you simply loop a from 1, then in that loop you loop b from a. Then you check if a <= n and if b <= n. If yes, you check if a^2 + b^2 is a square (if it can be writen as c^2 where c is an integer). If yes you output the corresponding triplet. You can stop the first loop once a > n and the second loop once b > n.
To compute the upper limit of b ... certainly we can't go past a^2 + b^2 = (b+1)^2, since the gap between successive squares increases. Now, (b+1)^2 is b^2 + 2b + 1, so we can stop on b when a^2 < 2b + 1. (In fact, for odd a, the biggest triple is when b = (a^2 - 1)/2, and then a^2 + b^2 = (b+1)^2.)
Let's consider even a. Then, we need to consider a^2 + b^2 = (b+2)^2, since 2b+1 is necessarily odd. Now, (b+2)^2 - b^2 = 4b+4, so we're looking at a^2 = 4b+4, or b = (a^2 - 4)/4 as the highest b (and, as before, we know this b works).
Therefore, for given a, you need to check bs up to
(a^2 - 1)/2 (a odd)
(a ^2 - 4)/4 (a even)
Given any a and b, you can compute what c should be. You can also check if the c you get is a whole number. With that in mind, you need to check all the a and b values and find the ones that give you a whole c number.
This should take just two loops (one for a and one for b). Leave comments if you want more help, and let me know what problems you have.
So Pythagorean tripes luckily have two properties that make this not so bad to solve:
First, all the numbers in a triple have to be integers (that means, you can calculate a^2 + b^2 and you have a triple if c^2 is an integer and not a float). Additionally, c is bounded by what a and b are.
So this should inform you how many variables you really have (which will guide your algorithm design - specifically how many for loops you need). The latter piece of information will inform you as to how long of a range you need to iterate over. I've tried to be vague as per your request, but let me know if you'd like anything more specific.
Break the problem into sub problems. The first clue is that you have an upper bound n on the value of c. Let's start with c=1 --- so, let's see how many triplets can be formed with:
a^2 + b^2 = 1
Now, let's set a = 1 to c-1. So that means we have to check if b is an integer such that b^2 = c^2 - a^2 and b^2 = int(b)^2.
leaving the formula and the language alone, you're trying to find every combination of two variables, a and b so...
foreach A
foreach B
foreach C
do something with B and A and eval with c
end foreach C
end foreach B
end foreach A
for ($x = 1; $x <= 200; $x++) {
for ($y = 1; $y <= 200; $y++) {
for ($z = 1; $z <= 200; $z++) {
if ($x < $y) {
if (pow($x, 2) + pow($y, 2) == pow($z, 2)) {
echo "$x, $y , $z<br/>";
}
}
}
}
}
3, 4 , 5
5, 12 , 13
6, 8 , 10
...
81, 108 , 135
84, 112 , 140
84, 135 , 159
Consider the problem in which you have a value of N and you need to calculate how many ways you can sum up to N dollars using [1,2,5,10,20,50,100] Dollar bills.
Consider the classic DP solution:
C = [1,2,5,10,20,50,100]
def comb(p):
if p==0:
return 1
c = 0
for x in C:
if x <= p:
c += comb(p-x)
return c
It does not take into effect the order of the summed parts. For example, comb(4) will yield 5 results: [1,1,1,1],[2,1,1],[1,2,1],[1,1,2],[2,2] whereas there are actually 3 results ([2,1,1],[1,2,1],[1,1,2] are all the same).
What is the DP idiom for calculating this problem? (non-elegant solutions such as generating all possible solutions and removing duplicates are not welcome)
Not sure about any DP idioms, but you could try using Generating Functions.
What we need to find is the coefficient of x^N in
(1 + x + x^2 + ...)(1+x^5 + x^10 + ...)(1+x^10 + x^20 + ...)...(1+x^100 + x^200 + ...)
(number of times 1 appears*1 + number of times 5 appears * 5 + ... )
Which is same as the reciprocal of
(1-x)(1-x^5)(1-x^10)(1-x^20)(1-x^50)(1-x^100).
You can now factorize each in terms of products of roots of unity, split the reciprocal in terms of Partial Fractions (which is a one time step) and find the coefficient of x^N in each (which will be of the form Polynomial/(x-w)) and add them up.
You could do some DP in calculating the roots of unity.
You should not go from begining each time, but at max from were you came from at each depth.
That mean that you have to pass two parameters, start and remaining total.
C = [1,5,10,20,50,100]
def comb(p,start=0):
if p==0:
return 1
c = 0
for i,x in enumerate(C[start:]):
if x <= p:
c += comb(p-x,i+start)
return c
or equivalent (it might be more readable)
C = [1,5,10,20,50,100]
def comb(p,start=0):
if p==0:
return 1
c = 0
for i in range(start,len(C)):
x=C[i]
if x <= p:
c += comb(p-x,i)
return c
Terminology: What you are looking for is the "integer partitions"
into prescibed parts (you should replace "combinations" in the title).
Ignoring the "dynamic programming" part of the question, a routine
for your problem is given in the first section of chapter 16
("Integer partitions", p.339ff) of the fxtbook, online at
http://www.jjj.de/fxt/#fxtbook
At Google Code Jam 2008 round 1A, there is problem:
Calculate last three digits before the
decimal point for the number
(3+sqrt(5))^n
n can be big number up to 1000000.
For example: if n = 2 then (3+sqrt(5))^2 = 27.4164079... answer is 027.
For n = 3: (3+sqrt(5))^3 = 3935.73982... answer is 935.
One of the solution is to create matrix M 2x2 : [[0, 1], [-4, 6]] than calculate matrix P = M^n, Where calculation preformed by modulo 1000.
and the result is (6*P[0,0] + 28*P[0,1] - 1) mod 1000.
Who can explain me this solution?
I'll present a method to solve this problem without even understanding the solution.
Assuming that you are familiar with the fibonacci numbers:
ghci> let fib = 0 : 1 : zipWith (+) fib (tail fib)
ghci> take 16 fib
[0,1,1,2,3,5,8,13,21,34,55,89,144,233,377,610]
And are also familiar with its closed form expression:
ghci> let calcFib i = round (((1 + sqrt 5) / 2) ^ i / sqrt 5)
ghci> map calcFib [0..15]
[0,1,1,2,3,5,8,13,21,34,55,89,144,233,377,610]
And you notice the similarity of ((1 + sqrt 5) / 2)n and (3 + sqrt 5)n.
From here one can guess that there is probably a series similar to fibonacci to calculate this.
But what series? So you calculate the first few items:
ghci> let calcThing i = floor ((3 + sqrt 5) ^ i)
ghci> map calcThing [0..5]
[1,5,27,143,751,3935]
Guessing that the formula is of the form:
thingn = a*thingn-1 + b*thingn-2
We have:
27 = a*5 + b*1
143 = a*27 + b*5
We solve the linear equations set and get:
thingn = 4*thingn-1 + 7*thingn-2 (a = 4, b = 7)
We check:
ghci> let thing = 1 : 5 : zipWith (+) (map (* 4) (tail thing)) (map (* 7) thing)
ghci> take 10 thing
[1,5,27,143,761,4045,21507,114343,607921,3232085]
ghci> map calcThing [0..9]
[1,5,27,143,751,3935,20607,107903,564991,2958335]
Then we find out that sadly this does not compute our function. But then we get cheered by the fact that it gets the right-most digit right. Not understanding why, but encouraged by this fact, we try to something similar. To find the parameters for a modified formula:
thingn = a*thingn-1 + b*thingn-2 + c
We then arrive at:
thingn = 6*thingn-1 - 4*thingn-2 + 1
We check it:
ghci> let thing =
1 : 5 : map (+1) (zipWith (+)
(map (*6) (tail thing))
(map (* negate 4) thing))
ghci> take 16 thing == map calcThing [0..15]
True
Just to give an answer to a very old question:
Thanks to yairchu i've got the idea to reread the prove of Binet's formula on the wikipedia page. It's there not really that clear, but we can work with it.
We see on the wikipedia page there is a closed form with 'computation by rounding': Fn = ⌊φ/√5⌋n.
If we could replace the φ/√5 with 3 + √5 (call the latter x). We could compute the floor of xn fairly easily, especially mod 1000, by finding the nth term in our freshly constructed sequence (this is the analogon of F (later we will call this analogon U)).
What sequence are we looking for? Well, we'll try following the prove for the Binet's formula. We need a quadratic equation with x as a root. Let's say x2 = 6 x-4 this one has roots x and y := 3 - √5. The handy part is now:
Define Un (for every a and b) such:
Un = a xn + b yn
by definition of x and y you can see that
Un = 6 Un-1 - 4 Un-2
Now we can choose a and b freely. We need Un to be integers so I propose choosing a=b=1. Now is U0 = 2, U1 = 6, U2 = 28...
We still need to get our 'computation by rounding'. You can see that yn < 1 for every n (because y ≅ 0.76 < 1) so Un = xn + yn = ⌈xn⌉.
If we can compute Un we can find ⌊xn⌋, just subtract 1.
We could compute Un by it's recursive formula but that would require O(n) computation time. We can do better!
For computing such a recursive formula we can use matrices:
⌈ 0 1⌉ ⌈ U(n-1) ⌉ ⌈ U(n) ⌉
⌊-4 6⌋ ⌊ U(n) ⌋ = ⌊U(n+1)⌋
Call this matrix M. Now does M*(U(1), U(2)) compute (U(2), U(3)).
Now we can compute P = Mn-1 (notice that I use one less than n, you can see that this is right if you test the small cases: n=0, n=1, n=2) P*(6,28) gives us now the nth and (n+1)th term of our sequence so:
(P*(6,28))0 - 1 = ⌊xn⌋
Now we can take everything mod 1000 (this is simplifying the calculations (a lot)) and we get the desired result in computation time O(log(n)) (or even better with the computational wonders of powers of matrices (over a cyclic finite field)). This explains the very weird looking solution, I guess.
I don't know how to explain that, but the auther of the problem have compose this analysis.