there are sorted in descending order of an array, it is necessary that two identical elements disappear, and instead enter a single 1 more
like this:
[12 8 8 6 4 3 3] => [12 9 6 5 ]
I tried to like this but goes completely nonsense:
vector<int> v(c, c + mn);
for ( i = 0; i < mn; i++)
{
if (v[i] == v[i + 1])
{
v[i]++;
v.erase(v.begin() + i + 1);
i = 0;
}
for (auto&x : v)std::cout << x << ".";
}
P.S.:sorry for bad english
You have to make sure that you do not go out of bounds:
do not go until the last element to compare it with the non existing next one
take into consideration that the removal of an item shrinks the size of the vector.
So some minor corrections get it to work:
vector<int> v{12,8,8,6,4,3,3};
for (int i = 0; i < v.size()-1; i++)
{
if (v[i] == v[i + 1])
{
v[i]++;
v.erase(v.begin() + i + 1);
i = 0;
}
}
for (auto&x : v)std::cout << x << ".";
Online demo
To avoid the multiple passes, you could also start from the end:
for (int i = v.size()-2; i >=0; i--)
{
if (v[i] == v[i + 1])
{
v[i]++;
v.erase(v.begin() + i + 1);
}
}
EDIT:
#knivil's comment pointed out that more than 2 identical elements (for example 3 consecutive 8 instead of 2) could lead to inconsistencies in the vector (the final result being no longer sorted). Here a modified version if these multiple repetitions would be a valid case here a modified version (assuming that for n repetitions, it's still 1 more and not n-1 more):
for (int i = 0; i < v.size()-1; i++)
{
if (v[i] == v[i + 1])
{
while (i+1<v.size() && v[i+1]==v[i])
v.erase(v.begin() + i + 1);
v[i]++;
i = 0;
}
}
for (auto&x : v)std::cout << x << ".";
With a new online demo.
I leave you as an exercise to make the single pass reverse version ;-)
One route is to use a hash map to basically look at the frequency of each element. Then use the frequency information to increment data.
std::vector<int> result;
std::unordered_map<int, int> hashMap;
bool update = false;
for(auto cur : v) {
hashMap[cur]++; // intialize hash map with data
}
do {
update = false;
for (auto cur : hashMap) {
if (cur.second == 2) { // Process duplicate case
hashMap[cur.first + 1]++; // add the +1 element
hashMap.erase(cur.first); // remove the original
update = true; // set flag to perform another pass
}
}
} while(update);
for (auto cur : hashMap)
result.push_back(cur.first);
std::sort(result.begin(), result.end(), std::greater<int>());
v = result;
Try it here.
Here is another approach to the problem.
I have one std::vector incremented holding the values that are incremented if duplicates are found.
The while loop runs as long as there are duplicates to be removed, increments the found duplicate and adds it to the incremented vector.
The vector is being sorted after each run to ensure the values are being removed properly and so that the output shows correctly.
#include <iostream> // std::cout
#include <vector> // std::vector
#include <functional> // std::greater
#include <algorithm> // std::sort
bool remove_duplicates(std::vector<int>& vec, std::vector<int>& incremented)
{ // return true if there is work, false otherwise
bool work_done { false };
for (int i = 1; i < vec.size(); ++i) {
if (vec[i] == vec[i - 1]) {
incremented.push_back(vec[i] + 1);
auto it = vec.begin() + i;
vec.erase(it - 1, it + 1);
work_done = true;
}
}
return work_done;
}
auto main() -> int
{
std::vector<int> v { 12, 8, 8, 6, 4, 3, 3 };
std::vector<int> incremented;
while (remove_duplicates(v, incremented)) {
for (const auto& i : incremented)
v.push_back(i);
std::sort(v.begin(), v.end(), std::greater<int>());
incremented.clear();
}
// print result
for (const auto& i : v)
std::cout << i << " ";
}
Output: 12 9 6 5
Hope this appears useful.
Related
Suppose I have a given sum, say sum = 4. I am also given a vector = {2,4}. There are two ways to generate the given sum from the given vector (elements may be reused).
One way is just {4} cause 4 = 4.
Second way is {2,2} cause 2 + 2 = 4.
I have to find the shortest possible combination, therefore in this particular case the answer is {4}.
Here is my approach - I go through the tree, and when on the leaf I get a 0, we hit the base case, return {} vector, and fill up the vector while traversing the tree. When I get to a node, I choose the smaller of the two (or more) vectors. This way when I reach the root node, I should get a vector of the shortest combination that can yield me the target sum.
As of yet, I do not care about time constraints as such, I know there's a lot of repetitive computing going on so I will have to memoize it once I can get the basic version correct.
I have been trying to figure why this code is not working. Any insight would be appreciated.
#include <vector>
#include <algorithm>
#include <iostream>
using namespace std;
vector<int> findBestSum(int targetSum, const vector<int> &elements, vector<vector<int>> &temp) {
if (targetSum == 0)
return {};
else if (targetSum < 0)
return {-1};
else {
vector<int> small;
for (auto &i : elements) {
int remainder = targetSum - i;
vector<int> returnedVector = findBestSum(remainder, elements, temp);
if ((!returnedVector.empty() && find(returnedVector.begin(), returnedVector.end(), -1) == returnedVector.end()) || returnedVector.empty()) {
returnedVector.push_back(i);
temp.push_back(returnedVector);
}
int smallestLength = temp[0].size();
for (auto &j : temp)
if (smallestLength >= j.size())
small = j;
}
return small;
}
}
int main() {
int targetSum = 6;
const vector<int> elements{2, 3, 5}; // answer should be [3,3] however I just get a 3...
vector<vector<int>> temp;
vector<int> bestSumVector = findBestSum(targetSum, elements, temp);
for (auto i : bestSumVector)
cout << i << " ";
}
Update (14th of July, 2021):
After a few busy months I have tried to lock horns with this problem and this time my code looks like this:
#include <iostream>
#include <vector>
#include <map>
#include <numeric>
using namespace std;
bool howSum(int &targetSum, vector<int> &elementVector, vector<int> &howSumVector, vector<vector<int>> &allSums) {
static int originaltargetsum = targetSum;
if (targetSum == 0)
return true;
else if (targetSum < 0)
return false;
else {
for (auto i : elementVector) {
int remainder = targetSum - i;
bool flag = howSum(remainder, elementVector, howSumVector, allSums);
if (flag) {
howSumVector.push_back(i);
if (targetSum == originaltargetsum ||
accumulate(howSumVector.begin(), howSumVector.end(), 0) == originaltargetsum) {
allSums.push_back(howSumVector);
howSumVector.clear();
}
return true;
}
}
return false;
}
}
int main() {
int sum = 8;
vector<int> elements = {1, 4, 5};
vector<vector<int>> allSums = {};
vector<int> workingBench = {};
howSum(sum, elements, workingBench, allSums);
for (auto &i : allSums) {
for (auto &j : i) {
cout << j << " ";
}
cout << endl;
}
}
For this I have sum as 8 and elements as {1, 4, 5}.
Also I'm storing and displaying all possible solutions right now (once that is correctly done, finding shortest vector and memoization should be easy). Possible solutions in this case are:
[1, 1, 1, 1, 1, 1, 1, 1]
[4, 4]
[5, 1, 1, 1]
[4, 1, 1, 1, 1]
Currently my code only shows the first possible combination. I'm pretty sure I'm returning true and false incorrectly, please help me out here.
I took a stab at this. I do have a working solution, hopefully it is what you want:
#include <iostream>
#include <vector>
#include <algorithm>
void howSum(int targetSum, const std::vector<int> & elementVector, const std::vector<int> & howSumVector, std::vector<std::vector<int>> & allSums)
{
static int originaltargetsum = targetSum;
if (targetSum == 0)
{
allSums.push_back(howSumVector);
return;
}
else if (targetSum < 0)
{
return;
}
else
{
for (const auto i : elementVector)
{
// an element less than or equal to 0 would cause an infinite loop
if (i <= 0)
continue;
std::vector<int> newSumVector = howSumVector;
newSumVector.push_back(i);
std::vector<int> newElementVector;
std::copy_if(std::begin(elementVector), std::end(elementVector), std::back_inserter(newElementVector), [i](int element){ return element >= i; });
howSum(targetSum - i, newElementVector, newSumVector, allSums);
}
}
}
int main()
{
int sum = 8;
std::vector<int> elements = { 1, 4, 5 };
std::vector<std::vector<int>> allSums = {};
std::vector<int> workingBench = {};
howSum(sum, elements, workingBench, allSums);
for (const auto & i : allSums)
{
for (const auto & j : i)
{
std::cout << j << " ";
}
std::cout << std::endl;
}
return 0;
}
I think, in general, you were over-thinking or over-engineering the problem. Like others have mentioned, your current code is returning true too early, and nothing besides the first element/combination is tested. With recursion, it is important to take care in your return cases - really, you only want a base case or two, and otherwise you want to recur.
With the solution I have here, the main thing I have added is copying the current combination of elements for each element you need to test. That solves your main issue of not testing every combination of numbers. In addition to that, it seemed better to append to allSums when the targetSum was reached. With those changes, I was able to do away with the bool return value and simplify the code a bit. Running the code above gives these solutions:
1 1 1 1 1 1 1 1
1 1 1 1 4
1 1 1 4 1
1 1 1 5
1 1 4 1 1
1 1 5 1
1 4 1 1 1
1 5 1 1
4 1 1 1 1
4 4
5 1 1 1
This does have some duplicates (because of the order things are tested) but I felt like it is good enough since you only want the smallest solution, 4 4. To find this, you would just need to sort the allSums vector by inner vector size and then take the first entry.
I think you need to change the implementation to correctly process elements of the vector.
In your implementation it doesn't go over all vector items, just the first one.
This is one way to do it if you use vector elements as the first parameter in your function.
vector<int> findBestSum(int element, int targetSum, const vector<int>& elements,
vector<vector<int>>& temp) {
if (targetSum == 0)
return {};
else if (targetSum < 0)
return { -1 };
else {
int remainder = targetSum - element;
vector<int> returnedVector = findBestSum(element, remainder, elements, temp);
if ((!returnedVector.empty() && find(returnedVector.begin(), returnedVector.end(), -1) == returnedVector.end()) || returnedVector.empty()) {
returnedVector.push_back(element);
return returnedVector;
}
return returnedVector;
}
}
int main() {
const int targetSum = 6;
const vector<int> elements{ 2, 3, 5 }; // answer should be [3,3] however I just get a 3...
vector<vector<int>> temp;
for (auto i : elements) {
vector<int> returnedVector = findBestSum(i, targetSum, elements, temp);
if ((!returnedVector.empty() && find(returnedVector.begin(), returnedVector.end(), -1) == returnedVector.end()) || returnedVector.empty())
temp.push_back(returnedVector);
}
if (temp.size() > 0) {
vector<int> bestSum = {};
size_t small = 0;
size_t smallestLength = temp[0].size();
for (auto& j : temp)
if (smallestLength >= j.size()) {
small = j.size();
bestSum = j;
}
for (auto i : bestSum)
cout << i << " ";
}
else
cout << " sum not found" << endl;
}
I tried to solve this exercise
I got 66 percent
I can not understand why
can you help?
The exercise is:
Write a function:
int solution(vector &A);
that, given an array A of N integers, returns the smallest positive integer (greater than 0) that does not occur in A.
For example, given A = [1, 3, 6, 4, 1, 2], the function should return 5.
Given A = [1, 2, 3], the function should return 4.
Given A = [−1, −3], the function should return 1.
The solution I wrote is:
#include <algorithm>
#include<cmath>
using namespace std;
int solution(vector<int> &A) {
if (A.size() == 0 || (A.size() == 1 && A.at(0) <= 0))
return 1;
if (A.size() == 1)
return A.at(0) + 1;
sort(A.begin(), A.end());
if (A.at(A.size() - 1) <= 0)
return 1;
auto ip = std::unique(A.begin(), A.end());
A.resize(distance(A.begin(), ip));
A.erase(remove_if(A.begin(), A.end(), [](const int i) { return i < 0; }),A.end());
if (A.at(0) != 1)
return 1;
if (A.size() == 1)
return (A.at(0) != 1 ? 1 : 2);
int i = 0;
for (; i < A.size(); ++i) {
if (A.at(i) != i + 1)
return A.at(i - 1) + 1;
}
return A.at(A.size()) + 1;
}
The following algorithm has a complexity O(n). No need to sort or to erase.
We know that the first missing value is less or equal to n+1, if n is the array size.
Then we simply have to use an array of size n+2, present[n+2], initialised to 0, and then to look at all values A[i]:
if (A[i] <= 1+n && A[i] > 0) present[A[i]] = 1;
Finally, in a second step we simply have to examine the array present[.], and search for the first index k such that present[k]==0.
#include <iostream>
#include <vector>
int find_missing (const std::vector<int> &A) {
int n = A.size();
std::vector<int> present (n+2, 0);
int vmax = n+1;
for (int i = 0; i < n; ++i) {
if (A[i] <= vmax && A[i] > 0) {
present[A[i]] = 1;
}
}
for (int k = 1; k <= vmax; ++k) {
if (present[k] == 0) return k;
}
return -1;
}
int main() {
std::vector<int> A = {1, 2, 0, 3, -3, 5, 6, 8};
int missing = find_missing (A);
std::cout << "First missing element = " << missing << std::endl;
return 0;
}
Well this is wrong
if(A.size()==1)
return A.at(0)+1;
If A is {2} that code will return 3 when the correct answer is 1
Also
A.erase(remove_if(A.begin(), A.end(),[](const int i) {return i < 0; }),A.end());
should be
A.erase(remove_if(A.begin(), A.end(),[](const int i) {return i <= 0; }),A.end());
Also
return A.at(A.size()) + 1;
is a guaranteed vector out of bounds error.
Even a small amount of testing and debugging would have caught these errors. It's a habit you should get into.
I think there are far too many special cases in the code, which only serve to complicate the code and increase the chance of bugs.
This answer is the implementation of the proposal given in the comment by PaulMcKenzie.
So, all credits go to PaulMcKenzie
It is not the fastest solution, but compact. The idea is basically.
Sort the data
Then compare the adjacent values, if the next value is equal to the previous value+1.
If not, then we found a gap. This can be implemented by using the function std::adjacent_find. Description can be found here.
We put all the side conditions into the lambda. If std::adjacent_find cannot find a value, then we take the next possible positive value.
I am not sure, what I could describe more. Please see the below example:
#include <iostream>
#include <vector>
#include <algorithm>
int solution(std::vector<int>& data) {
// Sort
std::sort(data.begin(), data.end());
// Check if there is a gap in the positive values
const auto gap = std::adjacent_find(data.begin(), data.end(), [](const int p, const int n) { return (n !=p) && (n != (p + 1) && p>0); });
// If there is no gap, the take the next positive value
return (gap == data.end()) ? (data.back() > 0 ? data.back() + 1 : 1) : *gap + 1;
}
int main() {
//Some test cases
std::vector<std::vector<int>> testCases{
{1,3,6,4,1,2},
{1,2,3},
{-1,-3}
};
for (auto& testCase : testCases)
std::cout << solution(testCase) << '\n';
return 0;
}
others have already pointed out what are the main errors, but I would like to invite you to try a different solution instead of trying to fix all the bugs and spend much time on debugging, because your solution seems a little overcomplicated.
Here I propose a way you can think about the problem:
What is the minimum number the function can return? Since it returns a positive integer, it is 1, in the case 1 is not in the array. Since that we can use any number <=0 to see if we found our result scanning the vector (see next);
In case one is not in the array, how do I find the wanted number? Your intuition is correct, if your vector is sorted it is easier: you can iterate over your data, and when you find an "hole" between two subsequent elements, then the value of the first element of the hole + 1 is you result
What do I do if the array contains 1 and has no holes? Well, you return the smallest element that is not in the array, so the last element + 1. You may notice that by checking if your "candidate" value (that is a number that shouldn't be returned, so <=0) has changed during the scanning;
Let's go to the code:
int solution(std::vector<int>& v){
int retVal=0;
std::sort(v.begin(), v.end());
for(int i=0; i<v.size()-1; i++){
if(v[i]>0 && v[i+1]>v[i]+1){
retVal=v[i]+1;
break;
}
}
if(retVal==0) {
if (v.back() > 0)
retVal = v.back() + 1;
else
retVal = 1;
}
return retVal;
}
As suggested you can use the standard library a little bit more, but I think this is reasonably simple and efficient.
Other note:
I think your assignment does not bother you with this, but I mention just for completeness. Most of the times you don't want a function to modify your parameters: you can pass the vector "by value" meaning that actually you pass a complete copy of your data, without touching the original one, or you can pass a const reference and create a copy inside the function.
I am trying to solve a problem:
You are given an unordered array consisting of consecutive integers [1, 2, 3, ..., n] without any duplicates nor specific order.You are allowed to swap any two elements. You need to find the minimum number of swaps required to sort the array in ascending order.
CONSTRAINTS:
the number of elements must be >= 1
the elements in the array must be <= to the size of the array
My code works when the numbers are not in the right position, but when the element is in the right position it enters an infinite loop, example array: [1 3 5 2 4 6 7] <- My code doesn't work because it gets stuck on 1.
My code:
#include <iostream>
#include <vector>
void swap(int &a, int &b)
{
int temp = a;
a = b;
b = temp;
}
int minimumSwaps(std::vector<int> arr)
{
int numberOfSwaps = 0;
int lastElementIndex = (arr.size() - 1);
bool isSwapping = true;
while (isSwapping)
{
isSwapping = false;
for (int i = 0; i < arr.size(); i++)
{
if (lastElementIndex - (arr.size() - arr[i]) != 0)
{
isSwapping = true;
swap(arr[i], arr[lastElementIndex - (arr.size() - arr[i])]);
numberOfSwaps++;
}
else
{
std::cout << arr[i] << " is already in its perfect position." << std::endl;
}
}
}
return numberOfSwaps;
}
P.S: I've just used the else statement to check what was going wrong.
Replacing lastElementIndex with its value (arr.size() - 1)
in line
if (lastElementIndex - (arr.size() - arr[i]) != 0)
yields
if ((arr.size() - 1) - (arr.size() - arr[i]) != 0)
and this is equivalent to
if (arr[i] != 1)
That's obviously wrong. Replace the line with
if (arr[i] - 1 != i)
I'm writing an operation to find the lowest missing element of a vector, V = 1..N + 1. This has to be performed in O(N) time complexity.
Solution One:
std::vector<int> A {3,4,1,4,6,7};
int main()
{
int max_el = *std::max_element(A.begin(), A.end()); //Find max element
std::vector<int> V(max_el);
std::iota(V.begin(), V.end(), 1) //Populate V with all int's up to max element
for(unsigned into i {0}; i < A.size(); i++)
{
int index = A[i] - 1;
if(A[i] == V[index]) //Search V in O(1)
{
V[index] = max_el; //Set each to max_el, leaving the missing int
}
}
return *std::min_element(V.begin(), V.end()); //Find missing int as its the lowest (hasn't been set to max_el)
}
//Output: 2
This works completely fine.
However, I'm now trying to get this to work with vector containing negative int's.
Solution Two:
My logic is to take the same approach, however 'weight' the indexes given the size of the vector and the number of negative int's in the vector:
std::vector<int> A {-1, -4, -2, 0, 3, 2, 1}
int main()
{
int max_el = *std::max_element(A.begin(), A.end());
int min_el = *std::min_element(A.begin(), A.end());
int min_el_abs = abs(min_el); //Convert min element to absolute
int total = min_el_abs + max_el;
std::vector<int> V(total + 1);
std::iota(V.begin(), V.end(), min_el);
int index;
//Find amount of negative int's
int first_pos;
for(unsigned int i {0}; i < A.size(); i++)
{
if(A[i] >= 0) {first_pos = i; break;}
}
for(unsigned int i {0}; i < A.size(); i++)
{
if(A[i] <= 0) //If negative
{
index = (A.size() - first_pos) - abs(A[i]);
} else
{
index = (A[i] + 1) + first_pos;
}
if(A[i] == V[index])
{
V[index] = 0;
}
}
return *std::min_element(V.begin(), V.end());
}
//Output: -3
Solution Two fails to compare the values of the two vectors (A and V), as calculating the index with the above methods with a positive int doesn't work.
1) How can I get my Solution 2 to work with unordered vector's of negative int's?
2) How can I edit my Solution 2 to work with vectors of positive as well as vectors with negative int's?
Your first solution seems O(max(N,M)), where I consider N the number of elements in vector A and M the size of vector V (or max(Ai)), but you are looping through both vectors multiple times (with std::min_element, std::max_element, the for loop, the allocation of V and std::iota too).
Besides, once corrected a couple of typos (a missing ; and an into instead of int), your program returns the value found... from main(), which is a bit odd.
Your first algorithm always searches for the lowest missing value in the range [1, max value in A], but it can be generalized to find the lowest missing element in the range [min(Ai), max(Ai)], even for negative numbers.
My approach is similar to that of L.Senioins, but I've used different library functions trying to minimize the number of loops.
#include <iostream>
#include <vector>
#include <utility>
#include <algorithm>
template <class ForwardIt>
typename std::iterator_traits<ForwardIt>::value_type
lowest_missing(ForwardIt first, ForwardIt last)
{
if ( first == last )
throw std::string {"The range is empty"};
// find both min and max element with one function
auto result = std::minmax_element(first, last);
// range is always > 0
auto range = *result.second - *result.first + 1;
if ( range < 2 )
throw std::string {"Min equals max, so there are no missing elements"};
std::vector<bool> vb(range); // the initial value of all elements is false
for (auto i = first; i != last; ++i)
vb[*i - *result.first] = true;
// search the first false
auto pos = std::find(vb.cbegin(), vb.cend(), false);
if ( pos == vb.cend() ) // all the elements are true
throw std::string {"There are no missing elements"};
return std::distance(vb.cbegin(), pos) + *result.first;
}
template <class ForwardIt>
void show_the_first_missing_element(ForwardIt first, ForwardIt last)
{
try
{
std::cout << lowest_missing(first, last) << '\n';
}
catch(const std::string &msg)
{
std::cout << msg << '\n';
}
}
int main() {
std::vector<int> a { 1, 8, 9, 6, 2, 5, 3, 0 };
show_the_first_missing_element(a.cbegin(), a.cend());
std::vector<int> b { -1, -4, 8, 1, -3, -2, 10, 0 };
show_the_first_missing_element(b.cbegin(), b.cend());
show_the_first_missing_element(b.cbegin() + b.size() / 2, b.cend());
std::vector<int> c { -2, -1, 0, 1, 2, 3 };
show_the_first_missing_element(c.cbegin(), c.cend());
std::vector<int> d { 3, 3, 3 };
show_the_first_missing_element(d.cbegin(), d.cend());
std::vector<int> e;
show_the_first_missing_element(e.cbegin(), e.cend());
return 0;
}
The results outputted for my test cases are:
4
2
-1
There are no missing elements
Min equals max, so there are no missing elements
The range is empty
My solution is to make a bool vector (or char vector just to avoid compilation warnings about casting to bool) which has the size of all possible elements. All elements are initialized to 0 and later are assigned to 1 which indicates that the element is not missing. All you need to do then is to find an index of the first 0 element which is the lowest missing element.
#include <vector>
#include <algorithm>
#include <iostream>
std::vector<int> A{ -1, 0, 11, 1, 10, -5 };
int main() {
if (A.size() > 1) {
int max_el = *std::max_element(A.begin(), A.end());
int min_el = *std::min_element(A.begin(), A.end());
int range = abs(max_el - min_el) + 1;
std::vector<int> V(range, 0);
for (size_t i = 0; i < A.size(); i++)
V[A[i] - min_el] = 1;
if (*std::min_element(V.begin(), V.end()) == 0)
std::cout << std::distance(V.begin(), std::find(V.begin(), V.end(), 0)) + min_el;
else
std::cout << "There are no missing elements" << std::endl;
}
else
std::cout << "There are no missing elements" << std::endl;
std::cin.get();
}
I'm going to try give my own question an answer, after spending sometime thinking about this:
int main()
{
std::vector<int> A {-3, -1, 0, 1, 3, 4};
auto relative_pos = std::minmax_elment(A.begin(), A.end());
std::vector<bool> Litmus( *(relative_pos.second) - *(relative_pos.first), false); //Create vector of size max val - min val)
auto lowest_val = *(relative_pos.first);
for(auto x : A)
{
Litmus[i - lowest_val] = true;
}
auto pos = std::find(Litmus.begin(), Litmus.end(), false); //Find the first occurring false value
std::cout<< (pos - Litmus.begin()) + lower<<std::endl; //Print the val in A relative to false value in Litmus
}
This solution works with negative numbers and is linear.
#include <vector>
#include <iostream>
#include <string>
#include <algorithm>
#include <numeric>
int solution(vector<int> &A) {
std::vector<int>::iterator it = std::max_element(A.begin(),A.end());
try
{
sort(A.begin(),A.end());
std::vector<int>::iterator it = std::unique(A.begin(),A.end());
A.resize(std::distance(A.begin(),it));
for(int i = 0, j = 1; i < A.size(); i++)
{
if( A[i] != j)
{
return j;
}
j++;
}
}
catch(exception &e)
{
std::cout<<e.what()<<std::endl;
}
return ++(*it);
}
I have worked out a O(n square) solution to the problem. I was wondering about a better solution to this. (this is not a homework/interview problem but something I do out of my own interest, hence sharing here):
If a=1, b=2, c=3,….z=26. Given a string, find all possible codes that string
can generate. example: "1123" shall give:
aabc //a = 1, a = 1, b = 2, c = 3
kbc // since k is 11, b = 2, c= 3
alc // a = 1, l = 12, c = 3
aaw // a= 1, a =1, w= 23
kw // k = 11, w = 23
Here is my code to the problem:
void alpha(int* a, int sz, vector<vector<int>>& strings) {
for (int i = sz - 1; i >= 0; i--) {
if (i == sz - 1) {
vector<int> t;
t.push_back(a[i]);
strings.push_back(t);
} else {
int k = strings.size();
for (int j = 0; j < k; j++) {
vector<int> t = strings[j];
strings[j].insert(strings[j].begin(), a[i]);
if (t[0] < 10) {
int n = a[i] * 10 + t[0];
if (n <= 26) {
t[0] = n;
strings.push_back(t);
}
}
}
}
}
}
Essentially the vector strings will hold the sets of numbers.
This would run in n square. I am trying my head around at least an nlogn solution.
Intuitively tree should help here, but not getting anywhere post that.
Generally, your problem complexity is more like 2^n, not n^2, since your k can increase with every iteration.
This is an alternative recursive solution (note: recursion is bad for very long codes). I didn't focus on optimization, since I'm not up to date with C++X, but I think the recursive solution could be optimized with some moves.
Recursion also makes the complexity a bit more obvious compared to the iterative solution.
// Add the front element to each trailing code sequence. Create a new sequence if none exists
void update_helper(int front, std::vector<std::deque<int>>& intermediate)
{
if (intermediate.empty())
{
intermediate.push_back(std::deque<int>());
}
for (size_t i = 0; i < intermediate.size(); i++)
{
intermediate[i].push_front(front);
}
}
std::vector<std::deque<int>> decode(int digits[], int count)
{
if (count <= 0)
{
return std::vector<std::deque<int>>();
}
std::vector<std::deque<int>> result1 = decode(digits + 1, count - 1);
update_helper(*digits, result1);
if (count > 1 && (digits[0] * 10 + digits[1]) <= 26)
{
std::vector<std::deque<int>> result2 = decode(digits + 2, count - 2);
update_helper(digits[0] * 10 + digits[1], result2);
result1.insert(result1.end(), result2.begin(), result2.end());
}
return result1;
}
Call:
std::vector<std::deque<int>> strings = decode(codes, size);
Edit:
Regarding the complexity of the original code, I'll try to show what would happen in the worst case scenario, where the code sequence consists only of 1 and 2 values.
void alpha(int* a, int sz, vector<vector<int>>& strings)
{
for (int i = sz - 1;
i >= 0;
i--)
{
if (i == sz - 1)
{
vector<int> t;
t.push_back(a[i]);
strings.push_back(t); // strings.size+1
} // if summary: O(1), ignoring capacity change, strings.size+1
else
{
int k = strings.size();
for (int j = 0; j < k; j++)
{
vector<int> t = strings[j]; // O(strings[j].size) vector copy operation
strings[j].insert(strings[j].begin(), a[i]); // strings[j].size+1
// note: strings[j].insert treated as O(1) because other containers could do better than vector
if (t[0] < 10)
{
int n = a[i] * 10 + t[0];
if (n <= 26)
{
t[0] = n;
strings.push_back(t); // strings.size+1
// O(1), ignoring capacity change and copy operation
} // if summary: O(1), strings.size+1
} // if summary: O(1), ignoring capacity change, strings.size+1
} // for summary: O(k * strings[j].size), strings.size+k, strings[j].size+1
} // else summary: O(k * strings[j].size), strings.size+k, strings[j].size+1
} // for summary: O(sum[i from 1 to sz] of (k * strings[j].size))
// k (same as string.size) doubles each iteration => k ends near 2^sz
// string[j].size increases by 1 each iteration
// k * strings[j].size increases by ?? each iteration (its getting huge)
}
Maybe I made a mistake somewhere and if we want to play nice we can treat a vector copy as O(1) instead of O(n) in order to reduce complexity, but the hard fact remains, that the worst case is doubling outer vector size in each iteration (at least every 2nd iteration, considering the exact structure of the if conditions) of the inner loop and the inner loop depends on that growing vector size, which makes the whole story at least O(2^n).
Edit2:
I figured out the result complexity (the best hypothetical algoritm still needs to create every element of the result, so result complexity is like a lower bound to what any algorithm can archieve)
Its actually following the Fibonacci numbers:
For worst case input (like only 1s) of size N+2 you have:
size N has k(N) elements
size N+1 has k(N+1) elements
size N+2 is the combination of codes starting with a followed by the combinations from size N+1 (a takes one element of the source) and the codes starting with k, followed by the combinations from size N (k takes two elements of the source)
size N+2 has k(N) + k(N+1) elements
Starting with size 1 => 1 (a) and size 2 => 2 (aa or k)
Result: still exponential growth ;)
Edit3:
Worked out a dynamic programming solution, somewhat similar to your approach with reverse iteration over the code array and kindof optimized in its vector usage, based on the properties explained in Edit2.
The inner loop (update_helper) is still dominated by the count of results (worst case Fibonacci) and a few outer loop iterations will have a decent count of sub-results, but at least the sub-results are reduced to a pointer to some intermediate node, so copying should be pretty efficient. As a little bonus, I switched the result from numbers to characters.
Another edit: updated code with range 0 - 25 as 'a' - 'z', fixed some errors that led to wrong results.
struct const_node
{
const_node(char content, const_node* next)
: next(next), content(content)
{
}
const_node* const next;
const char content;
};
// put front in front of each existing sub-result
void update_helper(int front, std::vector<const_node*>& intermediate)
{
for (size_t i = 0; i < intermediate.size(); i++)
{
intermediate[i] = new const_node(front + 'a', intermediate[i]);
}
if (intermediate.empty())
{
intermediate.push_back(new const_node(front + 'a', NULL));
}
}
std::vector<const_node*> decode_it(int digits[9], size_t count)
{
int current = 0;
std::vector<const_node*> intermediates[3];
for (size_t i = 0; i < count; i++)
{
current = (current + 1) % 3;
int prev = (current + 2) % 3; // -1
int prevprev = (current + 1) % 3; // -2
size_t index = count - i - 1; // invert direction
// copy from prev
intermediates[current] = intermediates[prev];
// update current (part 1)
update_helper(digits[index], intermediates[current]);
if (index + 1 < count && digits[index] &&
digits[index] * 10 + digits[index + 1] < 26)
{
// update prevprev
update_helper(digits[index] * 10 + digits[index + 1], intermediates[prevprev]);
// add to current (part 2)
intermediates[current].insert(intermediates[current].end(), intermediates[prevprev].begin(), intermediates[prevprev].end());
}
}
return intermediates[current];
}
void cleanupDelete(std::vector<const_node*>& nodes);
int main()
{
int code[] = { 1, 2, 3, 1, 2, 3, 1, 2, 3 };
int size = sizeof(code) / sizeof(int);
std::vector<const_node*> result = decode_it(code, size);
// output
for (size_t i = 0; i < result.size(); i++)
{
std::cout.width(3);
std::cout.flags(std::ios::right);
std::cout << i << ": ";
const_node* item = result[i];
while (item)
{
std::cout << item->content;
item = item->next;
}
std::cout << std::endl;
}
cleanupDelete(result);
}
void fillCleanup(const_node* n, std::set<const_node*>& all_nodes)
{
if (n)
{
all_nodes.insert(n);
fillCleanup(n->next, all_nodes);
}
}
void cleanupDelete(std::vector<const_node*>& nodes)
{
// this is like multiple inverse trees, hard to delete correctly, since multiple next pointers refer to the same target
std::set<const_node*> all_nodes;
for each (auto var in nodes)
{
fillCleanup(var, all_nodes);
}
nodes.clear();
for each (auto var in all_nodes)
{
delete var;
}
all_nodes.clear();
}
A drawback of the dynamically reused structure is the cleanup, since you wanna be careful to delete each node only once.