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Can you please help me to solve this problem ( Using VBA Excel )
We need to find the numbers X and Y such that:
3*X = Y
X is a 4-digit number and Y is a 5-digit number
We find all the digits (from 0 to 9) in the equation.
digits must used one time in the equation
for example : 3 * 4321 = 567890
Facts we know:
X must be in range 3334 <= X <= 9999
Y must be in range 10000 <= Y <= 29997
Y must be a multiple of 3
Thus, the sum of the digits of Y must be a multiple of three
In turn, since (1+2+4..9) mod 3 == 0, X must also be a multiple of three
The least significant digit of neither number can be 0, i.e. neither can be a multiple of 10
The least significant digit of the X cannot be 1
The least significant digit of the Y cannot be 9
Y must be a multiple of 9, so the sum of its digits must be divisible by 9
Thus, X must be congruent to 6 mod 9
In turn, Y must be congruent to 18 mod 27
The most significant digit of Y must be either 1 or 2 (assuming no leading zeros allowed)
There are 9 choose 4 == 126 ways to construct a 4-digit number, as well as a 5-digit number, without repeating digits (but not checking bounds).
With all of this in mind, your best bet is to probably brute force for Y, constructing numbers from combinations of 5 distinct digits, trying only numbers leading with 1|2 and performing a quick modulus check before checking if the equation itself is satisfied.
So there was a puzzle:
This equation is incomplete: 1 2 3 4 5 6 7 8 9 = 100. One way to make
it accurate is by adding seven plus and minus signs, like so: 1 + 2 +
3 – 4 + 5 + 6 + 78 + 9 = 100.
How can you do it using only 3 plus or minus signs?
I'm quite new to Prolog, solved the puzzle, but i wonder how to optimize it
makeInt(S,F,FinInt):-
getInt(S,F,0,FinInt).
getInt(Start, Finish, Acc, FinInt):-
0 =< Finish - Start,
NewAcc is Acc*10 + Start,
NewStart is Start +1,
getInt(NewStart, Finish, NewAcc, FinInt).
getInt(Start, Finish, A, A):-
0 > Finish - Start.
itCounts(X,Y,Z,Q):-
member(XLastDigit,[1,2,3,4,5,6]),
FromY is XLastDigit+1,
numlist(FromY, 7, ListYLastDigit),
member(YLastDigit, ListYLastDigit),
FromZ is YLastDigit+1,
numlist(FromZ, 8, ListZLastDigit),
member(ZLastDigit,ListZLastDigit),
FromQ is ZLastDigit+1,
member(YSign,[-1,1]),
member(ZSign,[-1,1]),
member(QSign,[-1,1]),
0 is XLastDigit + YSign*YLastDigit + ZSign*ZLastDigit + QSign*9,
makeInt(1, XLastDigit, FirstNumber),
makeInt(FromY, YLastDigit, SecondNumber),
makeInt(FromZ, ZLastDigit, ThirdNumber),
makeInt(FromQ, 9, FourthNumber),
X is FirstNumber,
Y is YSign*SecondNumber,
Z is ZSign*ThirdNumber,
Q is QSign*FourthNumber,
100 =:= X + Y + Z + Q.
Not sure this stands for an optimization. The code is just shorter:
sum_123456789_eq_100_with_3_sum_or_sub(L) :-
append([G1,G2,G3,G4], [0'1,0'2,0'3,0'4,0'5,0'6,0'7,0'8,0'9]),
maplist([X]>>(length(X,N), N>0), [G1,G2,G3,G4]),
maplist([G,F]>>(member(Op, [0'+,0'-]),F=[Op|G]), [G2,G3,G4], [F2,F3,F4]),
append([G1,F2,F3,F4], L),
read_term_from_codes(L, T, []),
100 is T.
It took me a while, but I got what your code is doing. It's something like this:
itCounts(X,Y,Z,Q) :- % generate X, Y, Z, and Q s.t. X+Y+Z+Q=100, etc.
generate X as a list of digits
do the same for Y, Z, and Q
pick the signs for Y, Z, and Q
convert all those lists of digits into numbers
verify that, with the signs, they add to 100.
The inefficiency here is that the testing is all done at the last minute. You can improve the efficiency if you can throw out some possible solutions as soon as you pick one of your numbers, that is, testing earlier.
itCounts(X,Y,Z,Q) :- % generate X, Y, Z, and Q s.t. X+Y+Z+Q=100, etc.
generate X as a list of digits, and convert it to a number
if it's so big or small the rest can't possibly bring the sum back to 100, fail
generate Y as a list of digits, convert to number, and pick it sign
if it's so big or so small the rest can't possibly bring the sum to 100, fail
do the same for Z
do the same for Q
Your function is running pretty fast already, even if I search all possible solutions. It only picks 6 X's; 42 Y's; 224 Z's; and 15 Q's. I don't think optimizing will be worth your while.
But if you really wanted to: I tested this by putting a testing function immediately after selecting an X. It reduced the 6 X's to 3 (all before finding the solution); 42 Y's to 30; 224 Z's to 184; and 15 Q's to 11. I believe we could reduce it further by testing immediately after a Y is picked, to see whether X YSign Y is already so large or small there can be no solution.
In PROLOG programs that are more computationally intensive, putting parts of the 'test' earlier in 'generate and test' algorithms can help a lot.
The outer loop executes n times while the inner loop executes ? So the total time is n*something.
Do i need to learn summation,if yes then any book to refer?
for(int i=1;i<=n;i++)
for(int j=1;j<=n;j+=i)
printf("*");
This question can be approached by inspection:
n = 16
i | j values | # terms
1 | 1, 2, ..., 16 | n
2 | 1, 3, 5, ..., 16 | n / 2
.. | .. | n / 3
16 | 16 | n / n
In the above table, i is the outer loop value, and j values show the iterations of the inner loop. By inspection, we can see that the loops will take n * (1 + 1/2 + 1/3 + ... + 1/n) steps. This is a bounded harmonic series. As this Math Stack Exchange article shows, there is no closed form for the above expression in terms of n. However, as this SO article shows, there is an upper bound of O(n*ln(n)).
So, the running time for your two loops is O(n*ln(n)).
I believe the time complexity of that is O(n*log(n)). Here is why:
Let us pick some arbitrary natural number i and see how many steps the inner loop takes for this given i. Well for this i, you are going from j=1 to j<=n with a jump of i in between. So basically you are doing this summation many steps:
summation = 1 + (1+i) + (1+2i) + ... (1+ki)
where k is the largest integer such that 1+ki <= n. That is, k is the number of steps and this is what we want to solve for. Well we can solve for k in the equality resulting in k <= (n-1)/i and thus k = ⌊(n-1)/i⌋. That is, k is the floor function/integer division of (n-1)/i. Since we are dealing with time complexities, this floor function doesn't matter so we will just say k = n/i for simplicity. This is the number of steps that the inner loop will take for a given i. So we basically need to add all these for i = 1 to i <= n.
So numsteps will be this addition:
numsteps = n/1 + n/2 + n/3 + ... n/n
= n(1 + 1/2 + 1/3 + ... 1+n)
So we need to find the sum of 1 + 1/2 + ... 1/n to finish this. There is actually no good closed form for this sum but it is on the order of ln(n). You can read more about this here. You can also guess this since the integral from 1 to n of 1/x is ln(n). Again, since we are dealing with time complexity, we can just use ln(n) to represent its complexity. Thus we have:
numsteps = n(ln(n))
And so the time complexity is O(n*log(n)).
Edit: My bad, i was calculating the sum :P
I would like to know where I can read about algorithms for solving this problem efficiently:
Four directions allowed: up, down, left, right
Cells containing zero can't be visited.
Visiting the same cell twice is illegal.
Moves wraps around the edges:
(first row is connected with last row)
(first col is connected with last col)
Example, 5x5 and 5 steps:
9 1 3 1 9
6 3 2 4 1
0 7 * 7 7
5 4 9 4 9
7 9 1 5 5
Starting point: *
Solution: down,left,down,left,down. That is 9 + 4 + 9 + 7 + 9 = 38
[9] 1 3 1 9
6 3 2 4 1
0 7 * 7 7
5 [4][9] 4 9
[7][9] 1 5 5
This problem is probably not related to:
Finding the maximum sub matrix
Dynamic programming
You specified in comments that you wanted a sub-second way of finding the best value 20-step path out of a 5x5 matrix. I've implemented a basic recursive search tree that does this. Ultimately, the difficulty of this is still O(3^k), but highly saturated cases like yours (21 out of 24 allowed nodes visited) will solve much faster because the problem simplifies to "skip the n*n-z-k-1 lowest value cells" (in this case, n=5, z=1 and k+1 = 21; the winning path skips three 1's).
The problem instance in your question solves in 0.231seconds on a 3 year old i5 laptop and about half a second on ideone.com. I've provided code here http://ideone.com/5kOyxq (note that 'up' and 'down' are reversed because of the way I input the data).
For less saturated problems you may need to add a Bound/Cut method. You can generate a Bound as follows:
First, run over the NxN matrix and collect the K highest value elements (can be done in N² log K) and sort them by max-first. Then, cumulatively calculate the value UB[t] = SUM[i::0->t] SortedElements[i]. So, any t-length path has a UB of UB[t] (max t elements).
At step T, the current Branch's UB is UB[t]. If ValueSoFar[T] + UB[K-T] <= BestPathValue, you can stop that branch.
There may be better ways, but this should be sufficient for reasonably sized matrices and path lengths.
Game or puzzle. Given a matrix, number of steps and a sum, find the path.
Would be nice if there is a real world application for this, but i haven't found it.
Games tend to "burn in" knowledge in young brains, so why not burn in something useful, like addition?
#include<iostream>
#include<climits>
#define R 3
#define C 3
int MAX(int x, int y, int z);
int Max_Cost(int cost[R][C], int m, int n)
{
if (n < 0 || m < 0)
return INT_MIN;
else if (m == 0 && n == 0)
return cost[m][n];
else
return cost[m][n] + MIN( Max_Cost(cost, m-1, n-1),
Max_Cost(cost, m-1, n),
Max_Cost(cost, m, n-1)
);
}
int MAX(int x, int y, int z)
{
return max(max(x, y), z);
}
int main()
{
int cost[R][C] = { {3, 2, 5},
{5, 8, 2},
{9, 7, 1}
};
cout<<Max_Cost(cost, 2, 1);
return 0;
}
I am new to objective C and trying to understand arc4random().
There are so many conflicting explanations on the web. Please clear my confusion, which of the following is correct:
// 1.
arc4random() % (toNumber - fromNumber) + fromNumber;
OR
//2.
arc4random() % ((toNumber - fromNumber) + 1) + fromNumber;
//toNumber-fromNumbers are any range of numbers like random # between 7-90.
This code will get you a random number between 7 and 90.
NSUInteger random = 7 + arc4random_uniform(90 - 7);
Use arc4random_uniform to avoid modulo bias.
Adam's answer is correct. However, just to clarify the difference between the two, the second one raises the possible range by one to make the range inclusive. The important thing to remember is that modulo is remainder division, so while there are toNumber possible outcomes, one of them is zero (if the result of arc4random() is a multiple of toNumber) and toNumber itself can not be the remainder.
// 1.
arc4random() % (10 - 5) + 5;
This results in a range of 0 + 5 to 4 + 5, which is 5 to 9.
//2.
arc4random() % ((10 - 5) + 1) + 5;
This results in a range of 0 + 5 to (4 + 1) + 5, which is 5 to 10.
Neither is correct or incorrect if you wish to use modulo. One is exclusive of the upper range while the other is inclusive of the upper range. However, if you think about how remainder division works and think of the pool of numbers returned by any PRNG in terms of cycles the length of your total range, then you'll realize that if the range does not divide evenly into the maximum range of the pool you'll get biased results. For instance, if arc4random() returned a result from 1 to 5 (it doesn't, obviously) and you wanted a number from 0 to 2, and you used arc4random() % 3, these are the possible results.
1 % 3 = 1
2 % 3 = 2
3 % 3 = 0
4 % 3 = 1
5 % 3 = 2
Note that there are two ones and two twos, but only one zero. This is because our range of 3 does not evenly divide into the PRNG's range of 5. The result is that (humorously enough) PRNG range % desired range numbers at the end of the cycle need to be culled because they are "biased"–the numbers themselves aren't really biased, but it's easier to cull from the end. Failing to do this results in the lower numbers of the range becoming more likely to appear.
We can cull the numbers by calculating the upper range of the numbers we can generate, modulo it with the desired range and then pull those numbers off of the end. By "pull those numbers off of the end" I really mean "loop infinitely until we get a number that isn't one of the end numbers".
Some would say that's bad practice; you could theoretically loop forever. In practice, however, the expected number of retries is always less than one since the modulo bias is never more than half the pool (usually much less than that) of the PRNG's numbers. I once wrote a wrapper for rand using this technique.
You can see an example of this in the source for OpenBSD, where arc4random_uniform calls arc4random in a loop until a number is determined to be clean.