Related
I was going through the code of KMP when I noticed the Longest Prefix which is also suffix calculation part of KMP. Here is how it goes,
void computeLPSArray(char* pat, int M, int* lps)
{
int len = 0;
lps[0] = 0;
int i = 1;
while (i < M) {
if (pat[i] == pat[len]) {
len++;
lps[i] = len;
i++;
}
else
{
if (len != 0) {
len = lps[len - 1]; //<----I am referring to this part
}
else
{
lps[i] = 0;
i++;
}
}
}
}
Now the part where I got confused was the one which I have shown in comments in the above code. Now we do know that when a code contains a loop like the following
int a[m];
memset(a, 0, sizeof(a));
for(int i = 0; i<m; i++){
for(int j = i; j>=0; j--){
a[j] = a[j]*2;//This inner loop is causing the same cells in the 1
//dimensional array to be visited more than once.
}
}
The complexity comes out to be O(m*m).
Similarly if we write the above LPS computation in the following format
while(i<M){
if{....}
else{
if(len != 0){
//doesn't this part cause the code to again go back a few elements
//in the LPS array the same way as the inner loop in my above
//written nested for loop does? Shouldn't that mean the same cell
//in the array is getting visited more than once and hence the
//complexity should increase to O(M^2)?
}
}
}
It might be that the way I think complexities are calculated is wrong. So please clarify.
If expressions do not take time that grows with len.
Len is an integer. Reading it takes O(1) time.
Array indexing is O(1).
Visiting something more than once does not mean you are higher O notation wise. Only if the visit count grows faster than kn for some k.
If you carefully analyze the algorithm of creating prefix table, you may notice that the total number of rollbacked positions could be m at most, so the upper bound for total number of iterations is 2*m which yields O(m)
Value of len grows alongside the main iterator i and whenever there is a mismatch, len drops back to zero value but this "drop" cannot exceed the interval passed by the main iterator i since the start of match.
For example, let's say, the main iterator i started matching with len at position 5 and mismatched at position 20.
So,
LPS[5]=1
LPS[6]=2
...
LPS[19]=15
At the moment of mismatch, len has a value of 15. Hence it may rollback at most 15 positions down to zero, which is equivalent to the interval passed by i while matching. In other words, on every mismatch, len travels back no more than i has traveled forward since the start of match
I have two integer arrays
int A[] = {2, 4, 3, 5, 6, 7};
int B[] = {9, 2, 7, 6};
And i have to get intersection of these array.
i.e. output will be - 2,6,7
I am thinking to sove it by saving array A in a data strcture and then i want to compare all the element till size A or B and then i will get intersection.
Now i have a problem i need to first store the element of Array A in a container.
shall i follow like -
int size = sizeof(A)/sizeof(int);
To get the size but by doing this i will get size after that i want to access all the elemts too and store in a container.
Here i the code which i am using to find Intersection ->
#include"iostream"
using namespace std;
int A[] = {2, 4, 3, 5, 6, 7};
int B[] = {9, 2, 7, 6};
int main()
{
int sizeA = sizeof(A)/sizeof(int);
int sizeB = sizeof(B)/sizeof(int);
int big = (sizeA > sizeB) ? sizeA : sizeB;
int small = (sizeA > sizeB) ? sizeB : sizeA;
for (int i = 0; i <big ;++i)
{
for (int j = 0; j <small ; ++j)
{
if(A[i] == B[j])
{
cout<<"Element is -->"<<A[i]<<endl;
}
}
}
return 0;
}
Just use a hash table:
#include <unordered_set> // needs C++11 or TR1
// ...
unordered_set<int> setOfA(A, A + sizeA);
Then you can just check for every element in B, whether it's also in A:
for (int i = 0; i < sizeB; ++i) {
if (setOfA.find(B[i]) != setOfA.end()) {
cout << B[i] << endl;
}
}
Runtime is expected O(sizeA + sizeB).
You can sort the two arrays
sort(A, A+sizeA);
sort(B, B+sizeB);
and use a merge-like algorithm to find their intersection:
#include <vector>
...
std::vector<int> intersection;
int idA=0, idB=0;
while(idA < sizeA && idB < sizeB) {
if (A[idA] < B[idB]) idA ++;
else if (B[idB] < A[idA]) idB ++;
else { // => A[idA] = B[idB], we have a common element
intersection.push_back(A[idA]);
idA ++;
idB ++;
}
}
The time complexity of this part of the code is linear. However, due to the sorting of the arrays, the overall complexity becomes O(n * log n), where n = max(sizeA, sizeB).
The additional memory required for this algorithm is optimal (equal to the size of the intersection).
saving array A in a data strcture
Arrays are data structures; there's no need to save A into one.
i want to compare all the element till size A or B and then i will get intersection
This is extremely vague but isn't likely to yield the intersection; notice that you must examine every element in both A and B but "till size A or B" will ignore elements.
What approach i should follow to get size of an unkown size array and store it in a container??
It isn't possible to deal with arrays of unknown size in C unless they have some end-of-array sentinel that allows counting the number of elements (as is the case with NUL-terminated character arrays, commonly referred to in C as "strings"). However, the sizes of your arrays are known because their compile-time sizes are known. You can calculate the number of elements in such arrays with a macro:
#define ARRAY_ELEMENT_COUNT(a) (sizeof(a)/sizeof *(a))
...
int *ptr = new sizeof(A);
[Your question was originally tagged [C], and my comments below refer to that]
This isn't valid C -- new is a C++ keyword.
If you wanted to make copies of your arrays, you could simply do it with, e.g.,
int Acopy[ARRAY_ELEMENT_COUNT(A)];
memcpy(Acopy, A, sizeof A);
or, if for some reason you want to put the copy on the heap,
int* pa = malloc(sizeof A);
if (!pa) /* handle out-of-memory */
memcpy(pa, A, sizeof A);
/* After you're done using pa: */
free(pa);
[In C++ you would used new and delete]
However, there's no need to make copies of your arrays in order to find the intersection, unless you need to sort them (see below) but also need to preserve the original order.
There are a few ways to find the intersection of two arrays. If the values fall within the range of 0-63, you can use two unsigned longs and set the bits corresponding to the values in each array, then use & (bitwise "and") to find the intersection. If the values aren't in that range but the difference between the largest and smallest is < 64, you can use the same method but subtract the smallest value from each value to get the bit number. If the range is not that small but the number of distinct values is <= 64, you can maintain a lookup table (array, binary tree, hash table, etc.) that maps the values to bit numbers and a 64-element array that maps bit numbers back to values.
If your arrays may contain more than 64 distinct values, there are two effective approaches:
1) Sort each array and then compare them element by element to find the common values -- this algorithm resembles a merge sort.
2) Insert the elements of one array into a fast lookup table (hash table, balanced binary tree, etc.), and then look up each element of the other array in the lookup table.
Sort both arrays (e.g., qsort()) and then walk through both arrays one element at a time.
Where there is a match, add it to a third array, which is sized to match the larger of the two input arrays (your result array can be no larger than the largest of the two arrays). Use a negative or other "dummy" value as your terminator.
When walking through input arrays, where one value in the first array is larger than the other, move the index of the second array, and vice versa.
When you're done walking through both arrays, your third array has your answer, up to the terminator value.
I got this question at an interview and at the end was told there was a more efficient way to do this but have still not been able to figure it out. You are passing into a function an array of integers and an integer for size of array. In the array you have a lot of numbers, some that repeat for example 1,7,4,8,2,6,8,3,7,9,10. You want to take that array and return an array where all the repeated numbers are put at the end of the array so the above array would turn into 1,7,4,8,2,6,3,9,10,8,7. The numbers I used are not important and I could not use a buffer array. I was going to use a BST, but the order of the numbers must be maintained(except for the duplicate numbers). I could not figure out how to use a hash table so I ended up using a double for loop(n^2 horrible I know). How would I do this more efficiently using c++. Not looking for code, just an idea of how to do it better.
In what follows:
arr is the input array;
seen is a hash set of numbers already encountered;
l is the index where the next unique element will be placed;
r is the index of the next element to be considered.
Since you're not looking for code, here is a pseudo-code solution (which happens to be valid Python):
arr = [1,7,4,8,2,6,8,3,7,9,10]
seen = set()
l = 0
r = 0
while True:
# advance `r` to the next not-yet-seen number
while r < len(arr) and arr[r] in seen:
r += 1
if r == len(arr): break
# add the number to the set
seen.add(arr[r])
# swap arr[l] with arr[r]
arr[l], arr[r] = arr[r], arr[l]
# advance `l`
l += 1
print arr
On your test case, this produces
[1, 7, 4, 8, 2, 6, 3, 9, 10, 8, 7]
I would use an additional map, where the key is the integer value from the array and the value is an integer set to 0 in the beginning. Now I would go through the array and increase the values in the map if the key is already in the map.
In the end I would go again through the array. When the integer from the array has a value of one in the map, I would not change anything. When it has a value of 2 or more in the map I would swap the integer from the array with the last one.
This should result in a runtime of O(n*log(n))
The way I would do this would be to create an array twice the size of the original and create a set of integers.
Then Loop through the original array, add each element to the set, if it already exists add it to the 2nd half of the new array, else add it to the first half of the new array.
In the end you would get an array that looks like: (using your example)
1,7,4,8,2,6,3,9,10,-,-,8,7,-,-,-,-,-,-,-,-,-
Then I would loop through the original array again and make each spot equal to the next non-null position (or 0'd or whatever you decided)
That would make the original array turn into your solution...
This ends up being O(n) which is about as efficient as I can think of
Edit: since you can not use another array, when you find a value that is already in the
set you can move every value after it forward one and set the last value equal to the
number you just checked, this would in effect do the same thing but with a lot more operations.
I have been out of touch for a while, but I'd probably start out with something like this and see how it scales with larger input. I know you didn't ask for code but in some cases it's easier to understand than an explanation.
Edit: Sorry I missed the requirement that you cannot use a buffer array.
// returns new vector with dupes a the end
std::vector<int> move_dupes_to_end(std::vector<int> input)
{
std::set<int> counter;
std::vector<int> result;
std::vector<int> repeats;
for (std::vector<int>::iterator i = input.begin(); i < input.end(); i++)
{
if (counter.find(*i) == counter.end())
result.push_back(*i);
else
repeats.push_back(*i);
counter.insert(*i);
}
result.insert(result.end(), repeats.begin(), repeats.end());
return result;
}
#include <algorithm>
T * array = [your array];
size_t size = [array size];
// Complexity:
sort( array, array + size ); // n * log(n) and could be threaded
// (if merge sort)
T * last = unique( array, array + size ); // n, but the elements after the last
// unique element are not defined
Check sort and unique.
void remove_dup(int* data, int count) {
int* L=data; //place to put next unique number
int* R=data+count; //place to place next repeat number
std::unordered_set<int> found(count); //keep track of what's been seen
for(int* cur=data; cur<R; ++cur) { //until we reach repeats
if(found.insert(*cur).second == false) { //if we've seen it
std::swap(*cur,*--R); //put at the beginning of the repeats
} else //or else
std::swap(*cur,*L++); //put it next in the unique list
}
std::reverse(R, data+count); //reverse the repeats to be in origional order
}
http://ideone.com/3choA
Not that I would turn in code this poorly commented. Also note that unordered_set probably uses it's own array internally, bigger than data. (This has been rewritten based on aix's answer, to be much faster)
If you know the bounds on what the integer values are, B, and the size of the integer array, SZ, then you can do something like the following:
Create an array of booleans seen_before with B elements, initialized to 0.
Create a result array result of integers with SZ elements.
Create two integers, one for front_pos = 0, one for back_pos = SZ - 1.
Iterate across the original list:
Set an integer variable val to the value of the current element
If seen_before[val] is set to 1, put the number at result[back_pos] then decrement back_pos
If seen_before[val] is not set to 1, put the number at result[front_pos] then increment front_pos and set seen_before[val] to 1.
Once you finish iterating across the main list, all the unique numbers will be at the front of the list while the duplicate numbers will be at the back. Fun part is that the entire process is done in one pass. Note that this only works if you know the bounds of the values appearing in the original array.
Edit: It was pointed out that there's no bounds on the integers used, so instead of initializing seen_before as an array with B elements, initialize it as a map<int, bool>, then continue as usual. That should get you n*log(n) performance.
This can be done by iterating the array & marking index of the first change.
later on swaping that mark index value with next unique value
& then incrementing that mark index for next swap
Java Implementation:
public static void solve() {
Integer[] arr = new Integer[] { 1, 7, 4, 8, 2, 6, 8, 3, 7, 9, 10 };
final HashSet<Integer> seen = new HashSet<Integer>();
int l = -1;
for (int i = 0; i < arr.length; i++) {
if (seen.contains(arr[i])) {
if (l == -1) {
l = i;
}
continue;
}
if (l > -1) {
final int temp = arr[i];
arr[i] = arr[l];
arr[l] = temp;
l++;
}
seen.add(arr[i]);
}
}
output is 1 7 4 8 2 6 3 9 10 8 7
It's ugly, but it meets the requirements of moving the duplicates to the end in place (no buffer array)
// warning, some light C++11
void dup2end(int* arr, size_t cnt)
{
std::set<int> k;
auto end = arr + cnt-1;
auto max = arr + cnt;
auto curr = arr;
while(curr < max)
{
auto res = k.insert(*curr);
// first time encountered
if(res.second)
{
++curr;
}
else
{
// duplicate:
std::swap(*curr, *end);
--end;
--max;
}
}
}
void move_duplicates_to_end(vector<int> &A) {
if(A.empty()) return;
int i = 0, tail = A.size()-1;
while(i <= tail) {
bool is_first = true; // check of current number is first-shown
for(int k=0; k<i; k++) { // always compare with numbers before A[i]
if(A[k] == A[i]) {
is_first = false;
break;
}
}
if(is_first == true) i++;
else {
int tmp = A[i]; // swap with tail
A[i] = A[tail];
A[tail] = tmp;
tail--;
}
}
If the input array is {1,7,4,8,2,6,8,3,7,9,10}, then the output is {1,7,4,8,2,6,10,3,9,7,8}. Comparing with your answer {1,7,4,8,2,6,3,9,10,8,7}, the first half is the same, while the right half is different, because I swap all duplicates with the tail of the array. As you mentioned, the order of the duplicates can be arbitrary.
Goal here is to merge multiple arrays which are already sorted into a resultant array.
I've written the following solution and wondering if there is a way to improve the solution
/*
Goal is to merge all sorted arrays
*/
void mergeAll(const vector< vector<int> >& listOfIntegers, vector<int>& result)
{
int totalNumbers = listOfIntegers.size();
vector<int> curpos;
int currow = 0 , minElement , foundMinAt = 0;
curpos.reserve(totalNumbers);
// Set the current position that was travered to 0 in all the array elements
for ( int i = 0; i < totalNumbers; ++i)
{
curpos.push_back(0);
}
for ( ; ; )
{
/* Find the first minimum
Which is basically the first element in the array that hasn't been fully traversed
*/
for ( currow = 0 ; currow < totalNumbers ; ++currow)
{
if ( curpos[currow] < listOfIntegers[currow].size() )
{
minElement = listOfIntegers[currow][curpos[currow] ];
foundMinAt = currow;
break;
}
}
/* If all the elements were traversed in all the arrays, then no further work needs to be done */
if ( !(currow < totalNumbers ) )
break;
/*
Traverse each of the array and find out the first available minimum value
*/
for ( ;currow < totalNumbers; ++currow)
{
if ( listOfIntegers[currow][curpos[currow] ] < minElement )
{
minElement = listOfIntegers[currow][curpos[currow] ];
foundMinAt = currow;
}
}
/*
Store the minimum into the resultant array
and increment the element traversed
*/
result.push_back(minElement);
++curpos[foundMinAt];
}
}
The corresponding main goes like this.
int main()
{
vector< vector<int> > myInt;
vector<int> result;
myInt.push_back(vector<int>() );
myInt.push_back(vector<int>() );
myInt.push_back(vector<int>() );
myInt[0].push_back(10);
myInt[0].push_back(12);
myInt[0].push_back(15);
myInt[1].push_back(20);
myInt[1].push_back(21);
myInt[1].push_back(22);
myInt[2].push_back(14);
myInt[2].push_back(17);
myInt[2].push_back(30);
mergeAll(myInt,result);
for ( int i = 0; i < result.size() ; ++i)
{
cout << result[i] << endl;
}
}
You can generalize Merge Sort algorithm and work with multiple pointers. Initially, all of them are pointing to the beginning of each array. You maintain these pointers sorted (by the values they point to) in a priority queue. In each step, you remove the smallest element in the heap in O(log n) (n is the number of arrays). You then output the element pointed by the extracted pointer. Now you increment this pointer in one position and if you didn't reach the end of the array, reinsert in the priority queue in O(log n). Proceed this way until the heap is not empty. If there are a total of m elements, the complexity is O(m log n). The elements are output in sorted order this way.
Perhaps I'm misunderstanding the question...and I feel like I'm misunderstanding your solution.
That said, maybe this answer is totally off-base and not helpful.
But, especially with the number of vectors and push_back's you're already using, why do you not just use std::sort?
#include <algorithm>
void mergeAll(const vector<vector<int>> &origList, vector<int> &resultList)
{
for(int i = 0; i < origList.size(); ++i)
{
resultList.insert(resultList.end(), origList[i].begin(), origList[i].end());
}
std::sort(resultList.begin(), resultList.end());
}
I apologize if this is totally off from what you're looking for. But it's how I understood the problem and the solution.
std::sort runs in O(N log (N)) http://www.cppreference.com/wiki/stl/algorithm/sort
I've seen some solution on the internet to merge two sorted arrays, but most of them were quite cumbersome. I changed some of the logic to provide the shortest version I can come up with:
void merge(const int list1[], int size1, const int list2[], int size2, int list3[]) {
// Declaration & Initialization
int index1 = 0, index2 = 0, index3 = 0;
// Loop untill both arrays have reached their upper bound.
while (index1 < size1 || index2 < size2) {
// Make sure the first array hasn't reached
// its upper bound already and make sure we
// don't compare outside bounds of the second
// array.
if ((list1[index1] <= list2[index2] && index1 < size1) || index2 >= size2) {
list3[index3] = list1[index1];
index1++;
}
else {
list3[index3] = list2[index2];
index2++;
}
index3++;
}
}
If you want to take advantage of multi-threading then a fairly good solution would be to just merge 2 lists at a time.
ie suppose you have 9 lists.
merge list 0 with 1.
merge list 2 with 3.
merge list 4 with 5.
merge list 6 with 7.
These can be performed concurrently.
Then:
merge list 0&1 with 2&3
merge list 4&5 with 6&7
Again these can be performed concurrently.
then merge list 0,1,2&3 with list 4,5,6&7
finally merge list 0,1,2,3,4,5,6&7 with list 8.
Job done.
I'm not sure on the complexity of that but it seems the obvious solution and DOES have the bonus of being multi-threadable to some extent.
Consider the priority-queue implementation in this answer linked in a comment above: Merging 8 sorted lists in c++, which algorithm should I use
It's O(n lg m) time (where n = total number of items and m = number of lists).
All you need is two pointers (or just int index counters), checking for minimum between array A and B, copying the value over to the resultant list, and incrementing the pointer of the array the minimum came from. If you run out of elements on one source array, copy the remainder of the second to the resultant and you're done.
Edit:
You can trivially expand this to N arrays.
Edit:
Don't trivially expand this to N arrays :-). Do two at a time. Silly me.
If you are merging very many vector together, then you could speed up performance by using a sort of tree to determine which vector contains the smallest element. This is probably not necessary for your application, but comment if it is and I'll try to work it out.
You could just stick them all into a multiset. That will handle the sorting for you.
There are N values in the array, and one of them is the smallest value. How can I find the smallest value most efficiently?
If they are unsorted, you can't do much but look at each one, which is O(N), and when you're done you'll know the minimum.
Pseudo-code:
small = <biggest value> // such as std::numerical_limits<int>::max
for each element in array:
if (element < small)
small = element
A better way reminded by Ben to me was to just initialize small with the first element:
small = element[0]
for each element in array, starting from 1 (not 0):
if (element < small)
small = element
The above is wrapped in the algorithm header as std::min_element.
If you can keep your array sorted as items are added, then finding it will be O(1), since you can keep the smallest at front.
That's as good as it gets with arrays.
You need too loop through the array, remembering the smallest value you've seen so far. Like this:
int smallest = INT_MAX;
for (int i = 0; i < array_length; i++) {
if (array[i] < smallest) {
smallest = array[i];
}
}
The stl contains a bunch of methods that should be used dependent to the problem.
std::find
std::find_if
std::count
std::find
std::binary_search
std::equal_range
std::lower_bound
std::upper_bound
Now it contains on your data what algorithm to use.
This Artikel contains a perfect table to help choosing the right algorithm.
In the special case where min max should be determined and you are using std::vector or ???* array
std::min_element
std::max_element
can be used.
If you want to be really efficient and you have enough time to spent, use SIMD instruction.
You can compare several pairs in one instruction:
r0 := min(a0, b0)
r1 := min(a1, b1)
r2 := min(a2, b2)
r3 := min(a3, b3)
__m64 _mm_min_pu8(__m64 a , __m64 b );
Today every computer supports it. Other already have written min function for you:
http://smartdata.usbid.com/datasheets/usbid/2001/2001-q1/i_minmax.pdf
or use already ready library.
If the array is sorted in ascending or descending order then you can find it with complexity O(1).
For an array of ascending order the first element is the smallest element, you can get it by arr[0] (0 based indexing).
If the array is sorted in descending order then the last element is the smallest element,you can get it by arr[sizeOfArray-1].
If the array is not sorted then you have to iterate over the array to get the smallest element.In this case time complexity is O(n), here n is the size of array.
int arr[] = {5,7,9,0,-3,2,3,4,56,-7};
int smallest_element=arr[0] //let, first element is the smallest one
for(int i =1;i<sizeOfArray;i++)
{
if(arr[i]<smallest_element)
{
smallest_element=arr[i];
}
}
You can calculate it in input section (when you have to find smallest element from a given array)
int smallest_element;
int arr[100],n;
cin>>n;
for(int i = 0;i<n;i++)
{
cin>>arr[i];
if(i==0)
{
smallest_element=arr[i]; //smallest_element=arr[0];
}
else if(arr[i]<smallest_element)
{
smallest_element = arr[i];
}
}
Also you can get smallest element by built in function
#inclue<algorithm>
int smallest_element = *min_element(arr,arr+n); //here n is the size of array
You can get smallest element of any range by using this function
such as,
int arr[] = {3,2,1,-1,-2,-3};
cout<<*min_element(arr,arr+3); //this will print 1,smallest element of first three element
cout<<*min_element(arr+2,arr+5); // -2, smallest element between third and fifth element (inclusive)
I have used asterisk (*), before min_element() function. Because it returns pointer of smallest element.
All codes are in c++.
You can find the maximum element in opposite way.
Richie's answer is close. It depends upon the language. Here is a good solution for java:
int smallest = Integer.MAX_VALUE;
int array[]; // Assume it is filled.
int array_length = array.length;
for (int i = array_length - 1; i >= 0; i--) {
if (array[i] < smallest) {
smallest = array[i];
}
}
I go through the array in reverse order, because comparing "i" to "array_length" in the loop comparison requires a fetch and a comparison (two operations), whereas comparing "i" to "0" is a single JVM bytecode operation. If the work being done in the loop is negligible, then the loop comparison consumes a sizable fraction of the time.
Of course, others pointed out that encapsulating the array and controlling inserts will help. If getting the minimum was ALL you needed, keeping the list in sorted order is not necessary. Just keep an instance variable that holds the smallest inserted so far, and compare it to each value as it is added to the array. (Of course, this fails if you remove elements. In that case, if you remove the current lowest value, you need to do a scan of the entire array to find the new lowest value.)
An O(1) sollution might be to just guess: The smallest number in your array will often be 0. 0 crops up everywhere. Given that you are only looking at unsigned numbers. But even then: 0 is good enough. Also, looking through all elements for the smallest number is a real pain. Why not just use 0? It could actually be the correct result!
If the interviewer/your teacher doesn't like that answer, try 1, 2 or 3. They also end up being in most homework/interview-scenario numeric arrays...
On a more serious side: How often will you need to perform this operation on the array? Because the sollutions above are all O(n). If you want to do that m times to a list you will be adding new elements to all the time, why not pay some time up front and create a heap? Then finding the smallest element can really be done in O(1), without resulting to cheating.
If finding the minimum is a one time thing, just iterate through the list and find the minimum.
If finding the minimum is a very common thing and you only need to operate on the minimum, use a Heap data structure.
A heap will be faster than doing a sort on the list but the tradeoff is you can only find the minimum.
If you're developing some kind of your own array abstraction, you can get O(1) if you store smallest added value in additional attribute and compare it every time a new item is put into array.
It should look something like this:
class MyArray
{
public:
MyArray() : m_minValue(INT_MAX) {}
void add(int newValue)
{
if (newValue < m_minValue) m_minValue = newValue;
list.push_back( newValue );
}
int min()
{
return m_minValue;
}
private:
int m_minValue;
std::list m_list;
}
//find the min in an array list of #s
$array = array(45,545,134,6735,545,23,434);
$smallest = $array[0];
for($i=1; $i<count($array); $i++){
if($array[$i] < $smallest){
echo $array[$i];
}
}
//smalest number in the array//
double small = x[0];
for(t=0;t<x[t];t++)
{
if(x[t]<small)
{
small=x[t];
}
}
printf("\nThe smallest number is %0.2lf \n",small);
Procedure:
We can use min_element(array, array+size) function . But it iterator
that return the address of minimum element . If we use *min_element(array, array+size) then it will return the minimum value of array.
C++ implementation
#include<bits/stdc++.h>
using namespace std;
int main()
{
int num;
cin>>num;
int arr[10];
for(int i=0; i<num; i++)
{
cin>>arr[i];
}
cout<<*min_element(arr,arr+num)<<endl;
return 0;
}
int small=a[0];
for (int x: a.length)
{
if(a[x]<small)
small=a[x];
}
C++ code
#include <iostream>
using namespace std;
int main() {
int n = 5;
int arr[n] = {12,4,15,6,2};
int min = arr[0];
for (int i=1;i<n;i++){
if (min>arr[i]){
min = arr[i];
}
}
cout << min;
return 0;
}