Discover long patterns

Question

Given a sorted list of numbers, I would like to find the longest subsequence where the differences between successive elements are geometrically increasing. So if the list is <

Answer 1

Update

I have made an improvement of the algorithm that it takes an average of O(M + N^2) and memory needs of O(M+N). Mainly is the same that the protocol described below, but to calculate the possible factors A,K for ech diference D, I preload a table. This table takes less than a second to be constructed for M=10^7.

I have made a C implementation that takes less than 10minutes to solve N=10^5 diferent random integer elements.

Here is the source code in C: To execute just do: gcc -O3 -o findgeo findgeo.c

#include 
#include 
#include 
#include 
#include 

struct Factor {
    int a;
    int k;
    struct Factor *next;
};

struct Factor *factors = 0;
int factorsL=0;

void ConstructFactors(int R) {
    int a,k,C;
    int R2;
    struct Factor *f;
    float seconds;
    clock_t end;
    clock_t start = clock();

    if (factors) free(factors);
    factors = malloc (sizeof(struct Factor) *((R>>1) + 1));
    R2 = R>>1 ;
    for (a=0;a<=R2;a++) {
        factors[a].a= a;
        factors[a].k=1;
        factors[a].next=NULL;
    }
    factorsL=R2+1;
    R2 = floor(sqrt(R));
    for (k=2; k<=R2; k++) {
        a=1;
        C=a*k*(k+1);
        while (C>= 1;
            f=malloc(sizeof(struct Factor));
            *f=factors[C];
            factors[C].a=a;
            factors[C].k=k;
            factors[C].next=f;
            a++;
            C=a*k*(k+1);
        }
    }

    end = clock();
    seconds = (float)(end - start) / CLOCKS_PER_SEC;
    printf("Construct Table: %f\n",seconds);
}

void DestructFactors() {
    int i;
    struct Factor *f;
    for (i=0;inext;
            free(factors[i].next);
            factors[i].next=f;
        }
    }
    free(factors);
    factors=NULL;
    factorsL=0;
}

int ipow(int base, int exp)
{
    int result = 1;
    while (exp)
    {
        if (exp & 1)
            result *= base;
        exp >>= 1;
        base *= base;
    }

    return result;
}

void findGeo(int **bestSolution, int *bestSolutionL,int *Arr, int L) {
    int i,j,D;
    int mustExistToBeBetter;
    int R=Arr[L-1]-Arr[0];
    int *possibleSolution;
    int possibleSolutionL=0;
    int exp;
    int NextVal;
    int idx;
    int kMax,aMax;
    float seconds;
    clock_t end;
    clock_t start = clock();


    kMax = floor(sqrt(R));
    aMax = floor(R/2);
    ConstructFactors(R);
    *bestSolutionL=2;
    *bestSolution=malloc(0);

    possibleSolution = malloc(sizeof(int)*(R+1));

    struct Factor *f;
    int *H=malloc(sizeof(int)*(R+1));
    memset(H,0, sizeof(int)*(R+1));
    for (i=0;i>1);
            while (f) {
                idx=Arr[i] + f->a * f->k  - Arr[0];
                if ((f->k <= kMax)&& (f->ak ==1) {
                        mustExistToBeBetter = Arr[i] + f->a * (*bestSolutionL);
                    } else {
                        mustExistToBeBetter = Arr[i] + f->a * f->k * (ipow(f->k,*bestSolutionL) - 1)/(f->k-1);
                    }
                    if (mustExistToBeBetter< Arr[L-1]+1) {
                        idx=  floor(mustExistToBeBetter - Arr[0]);
                    } else {
                        idx = R+1;
                    }
                    if ((idx<=R)&&H[idx]) {
                        possibleSolution[0]=Arr[i];
                        possibleSolution[1]=Arr[i] + f->a*f->k;
                        possibleSolution[2]=Arr[j];
                        possibleSolutionL=3;
                        exp = f->k * f->k * f->k;
                        NextVal = Arr[j] + f->a * exp;
                        idx=NextVal - Arr[0];
                        while ( (idx<=R) && H[idx]) {
                            possibleSolution[possibleSolutionL]=NextVal;
                            possibleSolutionL++;
                            exp = exp * f->k;
                            NextVal = NextVal + f->a * exp;
                            idx=NextVal - Arr[0];
                        }

                        if (possibleSolutionL > *bestSolutionL) {
                            free(*bestSolution);
                            *bestSolution = possibleSolution;
                            possibleSolution = malloc(sizeof(int)*(R+1));
                            *bestSolutionL=possibleSolutionL;
                            kMax= floor( pow (R, 1/ (*bestSolutionL) ));
                            aMax= floor(R /  (*bestSolutionL));
                        }
                    }
                }
                f=f->next;
            }
        }
    }

    if (*bestSolutionL == 2) {
        free(*bestSolution);
        possibleSolutionL=0;
        for (i=0; (i<2)&&(i0) printf(",");
        printf("%d",Sol[i]);
    }
    printf("]\n");
    printf("Size: %d\n",SolL);

    free(Sol);
    free(A);
    return EXIT_SUCCESS;
}

Demostration

I will try to demonstrate that the algorithm that I proposed is in average for an equally distributed random sequence. I’m not a mathematician and I am not used to do this kind of demonstrations, so please fill free to correct me any error that you can see.

There are 4 indented loops, the two firsts are the N^2 factor. The M is for the calculation of the possible factors table).

The third loop is executed only once in average for each pair. You can see this checking the size of the pre-calculated factors table. It’s size is M when N->inf. So the average steps for each pair is M/M=1.

So the proof happens to check that the forth loop. (The one that traverses the good made sequences is executed less that or equal O(N^2) for all the pairs.

To demonstrate that, I will consider two cases: one where M>>N and other where M ~= N. Where M is the maximum difference of the initial array: M= S(n)-S(1).

For the first case, (M>>N) the probability to find a coincidence is p=N/M. To start a sequence, it must coincide the second and the b+1 element where b is the length of the best sequence until now. So the loop will enter times. And the average length of this series (supposing an infinite series) is . So the total number of times that the loop will be executed is . And this is close to 0 when M>>N. The problem here is when M~=N.

Now lets consider this case where M~=N. Lets consider that b is the best sequence length until now. For the case A=k=1, then the sequence must start before N-b, so the number of sequences will be N-b, and the times that will go for the loop will be a maximum of (N-b)*b.

For A>1 and k=1 we can extrapolate to where d is M/N (the average distance between numbers). If we add for all A’s from 1 to dN/b then we see a top limit of:

For the cases where k>=2, we see that the sequence must start before , So the loop will enter an average of and adding for all As from 1 to dN/k^b, it gives a limit of

Here, the worst case is when b is minimum. Because we are considering minimum series, lets consider a very worst case of b= 2 so the number of passes for the 4th loop for a given k will be less than

.

And if we add all k’s from 2 to infinite will be:

So adding all the passes for k=1 and k>=2, we have a maximum of:

Note that d=M/N=1/p.

So we have two limits, One that goes to infinite when d=1/p=M/N goes to 1 and other that goes to infinite when d goes to infinite. So our limit is the minimum of both, and the worst case is when both equetions cross. So if we solve the equation:

we see that the maximum is when d=1.353

So it is demonstrated that the forth loops will be processed less than 1.55N^2 times in total.

Of course, this is for the average case. For the worst case I am not able to find a way to generate series whose forth loop are higher than O(N^2), and I strongly believe that they does not exist, but I am not a mathematician to prove it.

Old Answer

Here is a solution in average of O((n^2)*cube_root(M)) where M is the difference between the first and last element of the array. And memory requirements of O(M+N).

1.- Construct an array H of length M so that M[i - S[0]]=true if i exists in the initial array and false if it does not exist.

2.- For each pair in the array S[j], S[i] do:

2.1 Check if it can be the first and third elements of a possible solution. To do so, calculate all possible A,K pairs that meet the equation S(i) = S(j) + AK + AK^2. Check this SO question to see how to solve this problem. And check that exist the second element: S[i]+ A*K

2.2 Check also that exist the element one position further that the best solution that we have. For example, if the best solution that we have until now is 4 elements long then check that exist the element A[j] + AK + AK^2 + AK^3 + AK^4

2.3 If 2.1 and 2.2 are true, then iterate how long is this series and set as the bestSolution until now is is longer that the last.

Here is the code in javascript:

function getAKs(A) {
    if (A / 2 != Math.floor(A / 2)) return [];
    var solution = [];
    var i;
    var SR3 = Math.pow(A, 1 / 3);
    for (i = 1; i <= SR3; i++) {
        var B, C;
        C = i;
        B = A / (C * (C + 1));
        if (B == Math.floor(B)) {
            solution.push([B, C]);
        }

        B = i;
        C = (-1 + Math.sqrt(1 + 4 * A / B)) / 2;
        if (C == Math.floor(C)) {
            solution.push([B, C]);
        }
    }

    return solution;
}

function getBestGeometricSequence(S) {
    var i, j, k;

    var bestSolution = [];

    var H = Array(S[S.length-1]-S[0]);
    for (i = 0; i < S.length; i++) H[S[i] - S[0]] = true;

    for (i = 0; i < S.length; i++) {
        for (j = 0; j < i; j++) {
            var PossibleAKs = getAKs(S[i] - S[j]);
            for (k = 0; k < PossibleAKs.length; k++) {
                var A = PossibleAKs[k][0];
                var K = PossibleAKs[k][17];

                var mustExistToBeBetter;
                if (K==1) {
                    mustExistToBeBetter = S[j] + A * bestSolution.length;
                } else {
                    mustExistToBeBetter = S[j] + A * K * (Math.pow(K,bestSolution.length) - 1)/(K-1);
                }

                if ((H[S[j] + A * K - S[0]]) && (H[mustExistToBeBetter - S[0]])) {
                    var possibleSolution=[S[j],S[j] + A * K,S[i]];
                    exp = K * K * K;
                    var NextVal = S[i] + A * exp;
                    while (H[NextVal - S[0]] === true) {
                        possibleSolution.push(NextVal);
                        exp = exp * K;
                        NextVal = NextVal + A * exp;
                    }

                    if (possibleSolution.length > bestSolution.length) {
                        bestSolution = possibleSolution;
                    }
                }
            }
        }
    }
    return bestSolution;
}

//var A= [ 1, 2, 3,5,7, 15, 27, 30,31, 81];
var A=[];
for (i=1;i<=3000;i++) {
    A.push(i);
}
var sol=getBestGeometricSequence(A);

$("#result").html(JSON.stringify(sol));

You can check the code here: http://jsfiddle.net/6yHyR/1/

I maintain the other solution because I believe that it is still better when M is very big compared to N.