I got this problem from an interview with Microsoft.
Given an array of random integers,
write an algorithm in C that removes
duplicated numbers and return the unique numbers in the original
array.
E.g Input: {4, 8, 4, 1, 1, 2, 9} Output: {4, 8, 1, 2, 9, ?, ?}
One caveat is that the expected algorithm should not required the array to be sorted first. And when an element has been removed, the following elements must be shifted forward as well. Anyway, value of elements at the tail of the array where elements were shifted forward are negligible.
Update: The result must be returned in the original array and helper data structure (e.g. hashtable) should not be used. However, I guess order preservation is not necessary.
Update2: For those who wonder why these impractical constraints, this was an interview question and all these constraints are discussed during the thinking process to see how I can come up with different ideas.
A solution suggested by my girlfriend is a variation of merge sort. The only modification is that during the merge step, just disregard duplicated values. This solution would be as well O(n log n). In this approach, the sorting/duplication removal are combined together. However, I'm not sure if that makes any difference, though.
I've posted this once before on SO, but I'll reproduce it here because it's pretty cool. It uses hashing, building something like a hash set in place. It's guaranteed to be O(1) in axillary space (the recursion is a tail call), and is typically O(N) time complexity. The algorithm is as follows:
Take the first element of the array, this will be the sentinel.
Reorder the rest of the array, as much as possible, such that each element is in the position corresponding to its hash. As this step is completed, duplicates will be discovered. Set them equal to sentinel.
Move all elements for which the index is equal to the hash to the beginning of the array.
Move all elements that are equal to sentinel, except the first element of the array, to the end of the array.
What's left between the properly hashed elements and the duplicate elements will be the elements that couldn't be placed in the index corresponding to their hash because of a collision. Recurse to deal with these elements.
This can be shown to be O(N) provided no pathological scenario in the hashing: Even if there are no duplicates, approximately 2/3 of the elements will be eliminated at each recursion. Each level of recursion is O(n) where small n is the amount of elements left. The only problem is that, in practice, it's slower than a quick sort when there are few duplicates, i.e. lots of collisions. However, when there are huge amounts of duplicates, it's amazingly fast.
Edit: In current implementations of D, hash_t is 32 bits. Everything about this algorithm assumes that there will be very few, if any, hash collisions in full 32-bit space. Collisions may, however, occur frequently in the modulus space. However, this assumption will in all likelihood be true for any reasonably sized data set. If the key is less than or equal to 32 bits, it can be its own hash, meaning that a collision in full 32-bit space is impossible. If it is larger, you simply can't fit enough of them into 32-bit memory address space for it to be a problem. I assume hash_t will be increased to 64 bits in 64-bit implementations of D, where datasets can be larger. Furthermore, if this ever did prove to be a problem, one could change the hash function at each level of recursion.
Here's an implementation in the D programming language:
void uniqueInPlace(T)(ref T[] dataIn) {
uniqueInPlaceImpl(dataIn, 0);
}
void uniqueInPlaceImpl(T)(ref T[] dataIn, size_t start) {
if(dataIn.length - start < 2)
return;
invariant T sentinel = dataIn[start];
T[] data = dataIn[start + 1..$];
static hash_t getHash(T elem) {
static if(is(T == uint) || is(T == int)) {
return cast(hash_t) elem;
} else static if(__traits(compiles, elem.toHash)) {
return elem.toHash;
} else {
static auto ti = typeid(typeof(elem));
return ti.getHash(&elem);
}
}
for(size_t index = 0; index < data.length;) {
if(data[index] == sentinel) {
index++;
continue;
}
auto hash = getHash(data[index]) % data.length;
if(index == hash) {
index++;
continue;
}
if(data[index] == data[hash]) {
data[index] = sentinel;
index++;
continue;
}
if(data[hash] == sentinel) {
swap(data[hash], data[index]);
index++;
continue;
}
auto hashHash = getHash(data[hash]) % data.length;
if(hashHash != hash) {
swap(data[index], data[hash]);
if(hash < index)
index++;
} else {
index++;
}
}
size_t swapPos = 0;
foreach(i; 0..data.length) {
if(data[i] != sentinel && i == getHash(data[i]) % data.length) {
swap(data[i], data[swapPos++]);
}
}
size_t sentinelPos = data.length;
for(size_t i = swapPos; i < sentinelPos;) {
if(data[i] == sentinel) {
swap(data[i], data[--sentinelPos]);
} else {
i++;
}
}
dataIn = dataIn[0..sentinelPos + start + 1];
uniqueInPlaceImpl(dataIn, start + swapPos + 1);
}
How about:
void rmdup(int *array, int length)
{
int *current , *end = array + length - 1;
for ( current = array + 1; array < end; array++, current = array + 1 )
{
while ( current <= end )
{
if ( *current == *array )
{
*current = *end--;
}
else
{
current++;
}
}
}
}
Should be O(n^2) or less.
If you are looking for the superior O-notation, then sorting the array with an O(n log n) sort then doing a O(n) traversal may be the best route. Without sorting, you are looking at O(n^2).
Edit: if you are just doing integers, then you can also do radix sort to get O(n).
One more efficient implementation
int i, j;
/* new length of modified array */
int NewLength = 1;
for(i=1; i< Length; i++){
for(j=0; j< NewLength ; j++)
{
if(array[i] == array[j])
break;
}
/* if none of the values in index[0..j] of array is not same as array[i],
then copy the current value to corresponding new position in array */
if (j==NewLength )
array[NewLength++] = array[i];
}
In this implementation there is no need for sorting the array.
Also if a duplicate element is found, there is no need for shifting all elements after this by one position.
The output of this code is array[] with size NewLength
Here we are starting from the 2nd elemt in array and comparing it with all the elements in array up to this array.
We are holding an extra index variable 'NewLength' for modifying the input array.
NewLength variabel is initialized to 0.
Element in array[1] will be compared with array[0].
If they are different, then value in array[NewLength] will be modified with array[1] and increment NewLength.
If they are same, NewLength will not be modified.
So if we have an array [1 2 1 3 1],
then
In First pass of 'j' loop, array[1] (2) will be compared with array0, then 2 will be written to array[NewLength] = array[1]
so array will be [1 2] since NewLength = 2
In second pass of 'j' loop, array[2] (1) will be compared with array0 and array1. Here since array[2] (1) and array0 are same loop will break here.
so array will be [1 2] since NewLength = 2
and so on
1. Using O(1) extra space, in O(n log n) time
This is possible, for instance:
first do an in-place O(n log n) sort
then walk through the list once, writing the first instance of every back to the beginning of the list
I believe ejel's partner is correct that the best way to do this would be an in-place merge sort with a simplified merge step, and that that is probably the intent of the question, if you were eg. writing a new library function to do this as efficiently as possible with no ability to improve the inputs, and there would be cases it would be useful to do so without a hash-table, depending on the sorts of inputs. But I haven't actually checked this.
2. Using O(lots) extra space, in O(n) time
declare a zero'd array big enough to hold all integers
walk through the array once
set the corresponding array element to 1 for each integer.
If it was already 1, skip that integer.
This only works if several questionable assumptions hold:
it's possible to zero memory cheaply, or the size of the ints are small compared to the number of them
you're happy to ask your OS for 256^sizepof(int) memory
and it will cache it for you really really efficiently if it's gigantic
It's a bad answer, but if you have LOTS of input elements, but they're all 8-bit integers (or maybe even 16-bit integers) it could be the best way.
3. O(little)-ish extra space, O(n)-ish time
As #2, but use a hash table.
4. The clear way
If the number of elements is small, writing an appropriate algorithm is not useful if other code is quicker to write and quicker to read.
Eg. Walk through the array for each unique elements (ie. the first element, the second element (duplicates of the first having been removed) etc) removing all identical elements. O(1) extra space, O(n^2) time.
Eg. Use library functions which do this. efficiency depends which you have easily available.
Well, it's basic implementation is quite simple. Go through all elements, check whether there are duplicates in the remaining ones and shift the rest over them.
It's terrible inefficient and you could speed it up by a helper-array for the output or sorting/binary trees, but this doesn't seem to be allowed.
If you are allowed to use C++, a call to std::sort followed by a call to std::unique will give you the answer. The time complexity is O(N log N) for the sort and O(N) for the unique traversal.
And if C++ is off the table there isn't anything that keeps these same algorithms from being written in C.
You could do this in a single traversal, if you are willing to sacrifice memory. You can simply tally whether you have seen an integer or not in a hash/associative array. If you have already seen a number, remove it as you go, or better yet, move numbers you have not seen into a new array, avoiding any shifting in the original array.
In Perl:
foreach $i (#myary) {
if(!defined $seen{$i}) {
$seen{$i} = 1;
push #newary, $i;
}
}
The return value of the function should be the number of unique elements and they are all stored at the front of the array. Without this additional information, you won't even know if there were any duplicates.
Each iteration of the outer loop processes one element of the array. If it is unique, it stays in the front of the array and if it is a duplicate, it is overwritten by the last unprocessed element in the array. This solution runs in O(n^2) time.
#include <stdio.h>
#include <stdlib.h>
size_t rmdup(int *arr, size_t len)
{
size_t prev = 0;
size_t curr = 1;
size_t last = len - 1;
while (curr <= last) {
for (prev = 0; prev < curr && arr[curr] != arr[prev]; ++prev);
if (prev == curr) {
++curr;
} else {
arr[curr] = arr[last];
--last;
}
}
return curr;
}
void print_array(int *arr, size_t len)
{
printf("{");
size_t curr = 0;
for (curr = 0; curr < len; ++curr) {
if (curr > 0) printf(", ");
printf("%d", arr[curr]);
}
printf("}");
}
int main()
{
int arr[] = {4, 8, 4, 1, 1, 2, 9};
printf("Before: ");
size_t len = sizeof (arr) / sizeof (arr[0]);
print_array(arr, len);
len = rmdup(arr, len);
printf("\nAfter: ");
print_array(arr, len);
printf("\n");
return 0;
}
Here is a Java Version.
int[] removeDuplicate(int[] input){
int arrayLen = input.length;
for(int i=0;i<arrayLen;i++){
for(int j = i+1; j< arrayLen ; j++){
if(((input[i]^input[j]) == 0)){
input[j] = 0;
}
if((input[j]==0) && j<arrayLen-1){
input[j] = input[j+1];
input[j+1] = 0;
}
}
}
return input;
}
Here is my solution.
///// find duplicates in an array and remove them
void unique(int* input, int n)
{
merge_sort(input, 0, n) ;
int prev = 0 ;
for(int i = 1 ; i < n ; i++)
{
if(input[i] != input[prev])
if(prev < i-1)
input[prev++] = input[i] ;
}
}
An array should obviously be "traversed" right-to-left to avoid unneccessary copying of values back and forth.
If you have unlimited memory, you can allocate a bit array for sizeof(type-of-element-in-array) / 8 bytes to have each bit signify whether you've already encountered corresponding value or not.
If you don't, I can't think of anything better than traversing an array and comparing each value with values that follow it and then if duplicate is found, remove these values altogether. This is somewhere near O(n^2) (or O((n^2-n)/2)).
IBM has an article on kinda close subject.
Let's see:
O(N) pass to find min/max allocate
bit-array for found
O(N) pass swapping duplicates to end.
This can be done in one pass with an O(N log N) algorithm and no extra storage.
Proceed from element a[1] to a[N]. At each stage i, all of the elements to the left of a[i] comprise a sorted heap of elements a[0] through a[j]. Meanwhile, a second index j, initially 0, keeps track of the size of the heap.
Examine a[i] and insert it into the heap, which now occupies elements a[0] to a[j+1]. As the element is inserted, if a duplicate element a[k] is encountered having the same value, do not insert a[i] into the heap (i.e., discard it); otherwise insert it into the heap, which now grows by one element and now comprises a[0] to a[j+1], and increment j.
Continue in this manner, incrementing i until all of the array elements have been examined and inserted into the heap, which ends up occupying a[0] to a[j]. j is the index of the last element of the heap, and the heap contains only unique element values.
int algorithm(int[] a, int n)
{
int i, j;
for (j = 0, i = 1; i < n; i++)
{
// Insert a[i] into the heap a[0...j]
if (heapInsert(a, j, a[i]))
j++;
}
return j;
}
bool heapInsert(a[], int n, int val)
{
// Insert val into heap a[0...n]
...code omitted for brevity...
if (duplicate element a[k] == val)
return false;
a[k] = val;
return true;
}
Looking at the example, this is not exactly what was asked for since the resulting array preserves the original element order. But if this requirement is relaxed, the algorithm above should do the trick.
In Java I would solve it like this. Don't know how to write this in C.
int length = array.length;
for (int i = 0; i < length; i++)
{
for (int j = i + 1; j < length; j++)
{
if (array[i] == array[j])
{
int k, j;
for (k = j + 1, l = j; k < length; k++, l++)
{
if (array[k] != array[i])
{
array[l] = array[k];
}
else
{
l--;
}
}
length = l;
}
}
}
How about the following?
int* temp = malloc(sizeof(int)*len);
int count = 0;
int x =0;
int y =0;
for(x=0;x<len;x++)
{
for(y=0;y<count;y++)
{
if(*(temp+y)==*(array+x))
{
break;
}
}
if(y==count)
{
*(temp+count) = *(array+x);
count++;
}
}
memcpy(array, temp, sizeof(int)*len);
I try to declare a temp array and put the elements into that before copying everything back to the original array.
After review the problem, here is my delphi way, that may help
var
A: Array of Integer;
I,J,C,K, P: Integer;
begin
C:=10;
SetLength(A,10);
A[0]:=1; A[1]:=4; A[2]:=2; A[3]:=6; A[4]:=3; A[5]:=4;
A[6]:=3; A[7]:=4; A[8]:=2; A[9]:=5;
for I := 0 to C-1 do
begin
for J := I+1 to C-1 do
if A[I]=A[J] then
begin
for K := C-1 Downto J do
if A[J]<>A[k] then
begin
P:=A[K];
A[K]:=0;
A[J]:=P;
C:=K;
break;
end
else
begin
A[K]:=0;
C:=K;
end;
end;
end;
//tructate array
setlength(A,C);
end;
The following example should solve your problem:
def check_dump(x):
if not x in t:
t.append(x)
return True
t=[]
output = filter(check_dump, input)
print(output)
True
import java.util.ArrayList;
public class C {
public static void main(String[] args) {
int arr[] = {2,5,5,5,9,11,11,23,34,34,34,45,45};
ArrayList<Integer> arr1 = new ArrayList<Integer>();
for(int i=0;i<arr.length-1;i++){
if(arr[i] == arr[i+1]){
arr[i] = 99999;
}
}
for(int i=0;i<arr.length;i++){
if(arr[i] != 99999){
arr1.add(arr[i]);
}
}
System.out.println(arr1);
}
}
This is the naive (N*(N-1)/2) solution. It uses constant additional space and maintains the original order. It is similar to the solution by #Byju, but uses no if(){} blocks. It also avoids copying an element onto itself.
#include <stdio.h>
#include <stdlib.h>
int numbers[] = {4, 8, 4, 1, 1, 2, 9};
#define COUNT (sizeof numbers / sizeof numbers[0])
size_t undup_it(int array[], size_t len)
{
size_t src,dst;
/* an array of size=1 cannot contain duplicate values */
if (len <2) return len;
/* an array of size>1 will cannot at least one unique value */
for (src=dst=1; src < len; src++) {
size_t cur;
for (cur=0; cur < dst; cur++ ) {
if (array[cur] == array[src]) break;
}
if (cur != dst) continue; /* found a duplicate */
/* array[src] must be new: add it to the list of non-duplicates */
if (dst < src) array[dst] = array[src]; /* avoid copy-to-self */
dst++;
}
return dst; /* number of valid alements in new array */
}
void print_it(int array[], size_t len)
{
size_t idx;
for (idx=0; idx < len; idx++) {
printf("%c %d", (idx) ? ',' :'{' , array[idx] );
}
printf("}\n" );
}
int main(void) {
size_t cnt = COUNT;
printf("Before undup:" );
print_it(numbers, cnt);
cnt = undup_it(numbers,cnt);
printf("After undup:" );
print_it(numbers, cnt);
return 0;
}
This can be done in a single pass, in O(N) time in the number of integers in the input
list, and O(N) storage in the number of unique integers.
Walk through the list from front to back, with two pointers "dst" and
"src" initialized to the first item. Start with an empty hash table
of "integers seen". If the integer at src is not present in the hash,
write it to the slot at dst and increment dst. Add the integer at src
to the hash, then increment src. Repeat until src passes the end of
the input list.
Insert all the elements in a binary tree the disregards duplicates - O(nlog(n)). Then extract all of them back in the array by doing a traversal - O(n). I am assuming that you don't need order preservation.
Use bloom filter for hashing. This will reduce the memory overhead very significantly.
In JAVA,
Integer[] arrayInteger = {1,2,3,4,3,2,4,6,7,8,9,9,10};
String value ="";
for(Integer i:arrayInteger)
{
if(!value.contains(Integer.toString(i))){
value +=Integer.toString(i)+",";
}
}
String[] arraySplitToString = value.split(",");
Integer[] arrayIntResult = new Integer[arraySplitToString.length];
for(int i = 0 ; i < arraySplitToString.length ; i++){
arrayIntResult[i] = Integer.parseInt(arraySplitToString[i]);
}
output:
{ 1, 2, 3, 4, 6, 7, 8, 9, 10}
hope this will help
Create a BinarySearchTree which has O(n) complexity.
First, you should create an array check[n] where n is the number of elements of the array you want to make duplicate-free and set the value of every element(of the check array) equal to 1. Using a for loop traverse the array with the duplicates, say its name is arr, and in the for-loop write this :
{
if (check[arr[i]] != 1) {
arr[i] = 0;
}
else {
check[arr[i]] = 0;
}
}
With that, you set every duplicate equal to zero. So the only thing is left to do is to traverse the arr array and print everything it's not equal to zero. The order stays and it takes linear time (3*n).
Given an array of n elements, write an algorithm to remove all duplicates from the array in time O(nlogn)
Algorithm delete_duplicates (a[1....n])
//Remove duplicates from the given array
//input parameters :a[1:n], an array of n elements.
{
temp[1:n]; //an array of n elements.
temp[i]=a[i];for i=1 to n
temp[i].value=a[i]
temp[i].key=i
//based on 'value' sort the array temp.
//based on 'value' delete duplicate elements from temp.
//based on 'key' sort the array temp.//construct an array p using temp.
p[i]=temp[i]value
return p.
In other of elements is maintained in the output array using the 'key'. Consider the key is of length O(n), the time taken for performing sorting on the key and value is O(nlogn). So the time taken to delete all duplicates from the array is O(nlogn).
this is what i've got, though it misplaces the order we can sort in ascending or descending to fix it up.
#include <stdio.h>
int main(void){
int x,n,myvar=0;
printf("Enter a number: \t");
scanf("%d",&n);
int arr[n],changedarr[n];
for(x=0;x<n;x++){
printf("Enter a number for array[%d]: ",x);
scanf("%d",&arr[x]);
}
printf("\nOriginal Number in an array\n");
for(x=0;x<n;x++){
printf("%d\t",arr[x]);
}
int i=0,j=0;
// printf("i\tj\tarr\tchanged\n");
for (int i = 0; i < n; i++)
{
// printf("%d\t%d\t%d\t%d\n",i,j,arr[i],changedarr[i] );
for (int j = 0; j <n; j++)
{
if (i==j)
{
continue;
}
else if(arr[i]==arr[j]){
changedarr[j]=0;
}
else{
changedarr[i]=arr[i];
}
// printf("%d\t%d\t%d\t%d\n",i,j,arr[i],changedarr[i] );
}
myvar+=1;
}
// printf("\n\nmyvar=%d\n",myvar);
int count=0;
printf("\nThe unique items:\n");
for (int i = 0; i < myvar; i++)
{
if(changedarr[i]!=0){
count+=1;
printf("%d\t",changedarr[i]);
}
}
printf("\n");
}
It'd be cool if you had a good DataStructure that could quickly tell if it contains an integer. Perhaps a tree of some sort.
DataStructure elementsSeen = new DataStructure();
int elementsRemoved = 0;
for(int i=0;i<array.Length;i++){
if(elementsSeen.Contains(array[i])
elementsRemoved++;
else
array[i-elementsRemoved] = array[i];
}
array.Length = array.Length - elementsRemoved;
Related
I was doing selection sort yesterday. I wondered if I could replace the min and max values to begining and end of the unsorted array every time I iterated. I am just a beginner at programming, so its obvious that this wouldn't work. However, suprisingly, the code below does sort a larger array (~ 30k - 40k) in size. I experimented by generating random values from rand()%2000 and the function sorted the array successfully 28 times in 30 experiments.
But it can't sort something as simple as {4,2,3}
I think there's a bug somewhere, I couldn't figure it out so I've come here.
I'm also curious about the fact that it sorted such large arrays successfully. How?
int *zigzag_sort(int arr[])
{
// loop through array
// find min and max
// replace min at begining and max at end
// keep doing until sorted
int f_idx = 0, l_idx = n-1;
int min_pos, max_pos;
while( f_idx < l_idx ) {
min_pos = f_idx;
max_pos = l_idx;
for(int i = f_idx+1; i <= l_idx; i++)
{
if(arr[i] < arr[min_pos])
min_pos = i;
else if(arr[i] > arr[max_pos])
max_pos = i;
}
swap(&arr[f_idx], &arr[min_pos]);
swap(&arr[l_idx], &arr[max_pos]);
f_idx++;
l_idx--;
}
return arr;
}
void swap(int *a, int *b)
{
int temp = *a;
*a = *b;
*b = temp;
}
Your swaps are not as simple as you think, and there is a hole in your position starting points going in to the inner loop iterations.
First, there are there situations that must be accounted after completing a segment enumeration and finding the segment min-index and max-index locations. They all deal with where you're reading data from, and where you'r'e trying to write it to. There can be partial, or in one case, full, overlap.
After each inner iteration, one of several conditions can transpire...
(min_pos == l_idx) && (max_pos == f_idx) . In other words, the minimum and maximum values are each in the places where the other wants to be. If that is the case ONE swap is needed (each other) and you're done for that iteration.
One of (min_pos == l_idx) or (max_pos == f_idx) is true, but not both. The order of the impending two swaps is important, depending on which of those conditions is true. In short, don't swap something into a slot that is about to be swapped again with the second swap. Ex: If the maximum value resides at the low target position, you need to swap it out to the maximum target position before the minimum value is swapped to the low target position. Otherwise you will dislocate something right after you put it home.
Neither of the above are true, in which case two swaps are still required, but order is irrelevant.
The probability of the special cases in (1) and (2) above increase significantly as you squeeze the iteration window down further and further during the outer loop iteration. For a random ordering, sooner or later it is going to happen.
Secondly, both the min_pos and max_pos starting points should be the same location in the segment, f_idx. It may not seem important, but it is so because the inner loop starts a f_idx+1. that means if the maximum value of the iteration was originally at f_idx you never accounted for it, will not discover it, etc.
The fixed routine is below, with notes where appropriate.
int *zigzag_sort(int arr[], int n)
{
int f_idx = 0, l_idx = n - 1;
while (f_idx < l_idx)
{
// both should start at the same location
int min_pos = f_idx;
int max_pos = f_idx;
for (int i = f_idx + 1; i <= l_idx; i++)
{
if (arr[i] < arr[min_pos])
min_pos = i;
else if (arr[i] > arr[max_pos])
max_pos = i;
}
if (max_pos == f_idx)
{
if (min_pos == l_idx)
{
// swap each other
swap(&arr[max_pos], &arr[min_pos]);
}
else
{ // swap the max out before overwritine with min
swap(&arr[l_idx], &arr[max_pos]);
swap(&arr[f_idx], &arr[min_pos]);
}
}
else
{ // also handle the case of l_idx == min_pos
swap(&arr[f_idx], &arr[min_pos]);
swap(&arr[l_idx], &arr[max_pos]);
}
f_idx++;
l_idx--;
}
return arr;
}
Why doesn't it work for { 4, 2, 3 }?
... // f_idx = 0; l_idx = 2; min_pos = 1; max_pos = 0;
swap(&arr[f_idx], &arr[min_pos]); // swap(&arr[0], &arr[1]) ==> { 2, 4, 3 }
// ===> max_pos is "wrong" now <===
swap(&arr[l_idx], &arr[max_pos]); // swap(&arr[2], &arr[0]) ==> { 3, 4, 2 }
How can I use repetitions to check if there aren't any repeated numbers on a n x n matrix?
Using two for's two times wouldn't let me check anything that does not share at least a line or a column
Example: (in the most simplified way possible):
int matrix[n][n];
/*matrix is filled*/
int current, isEqual;
for (int i=0; i<n; i++)
{
for (int j=0; j<n; j++)
{
current = matrix[i][j];
if (current == matrix[i][j+1])
{
isEqual=1;
}
else
{
isEqual=0;
}
}
}
for (int j=0; j<n; j++)
{
for (int i=0; i<n; i++)
{
current = matrix[i][j];
if (current == matrix[i+1][j])
{
isEqual=1;
}
else
{
isEqual=0;
}
}
}
I can't check numbers that don't share lines or columns.
First, think in a NxM matrix as if it were an array with length [N*M]. The only difference is how you access the elements (two fors instead of one, for example).
Then, a simple algorithm would be to iterate every element (first index), and for each one, iterate every other element (second index) to check if it's the same. It's easier to do with an array; in a matrix it's the same, maybe a bit more verbose and complex. But the algorithm is the same.
As a second phase, after you have implemented the basic algorithm, you can improve its performance starting the second index in the element after the first index. This way, you avoid checking the already seen elements multiple times. This algorithm improvement is slightly harder to do in a matrix, if you iterate it with 2 fors, as it's a bit harder to know what's the "next index" (you have a "compound" index, {i,j}).
One simple way to do this is to insert each number into a data structure that makes it easy to check for duplicates. This is sort of fun to do in C, and although the following is certainly not super efficient or production ready, it's (IMO) a nice little toy:
/* Check if any integer on the input stream is a dup */
#include <stdio.h>
#include <stdlib.h>
struct node { int data; struct node *child[2]; };
static struct node *
new_node(int data)
{
struct node *e = calloc(1, sizeof *e);
if( e == NULL ){
perror("calloc");
exit(EXIT_FAILURE);
}
e->data = data;
return e;
}
/*
* Insert a value into the tree. Return 1 if already present.
* Note that this tree needs to be rebalanced. In a real
* project, we would use existing libraries. For this toy
* it is not worth the work needed to properly rebalance the
* tree.
*/
int
insert(struct node **table, int data)
{
struct node *t = *table;
if( !t ){
*table = new_node(data);
return 0;
}
if( data == t->data ){
return 1;
}
return insert(&t->child[data < t->data], data);
}
int
main(void)
{
int rv, v;
struct node *table = NULL;
while( (rv = scanf("%d", &v)) == 1 ){
if( insert(&table, v) ){
fprintf(stderr, "%d is duplicated\n", v);
return EXIT_FAILURE;
}
}
if( rv != EOF ){
fprintf(stderr, "Invalid input\n");
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
The basic approach is to loop through the nxn matrix and keeping a list of the numbers in it along with a count of the number of times each number is found in the nxn matrix.
The following is example source code for a 50 x 50 matrix. To extend this to an n x n matrix is fairly straightforward and I leave that as an exercise for you. You may need to do something such as using malloc() to create an arbitrary sized matrix. There are posts on that sort of thing.
I also do not specify how the data is put into the matrix in the first place. That is also up to you.
This is to just show a brute force approach for determining if there are duplicates in the matrix.
I've also taken the liberty of assuming the matrix elements are int but changing the type to something else should be straightforward. If the matrix elements are something other than a simple data value type such as int, long, etc. then the function findAndCount() will need changing for the equality comparison.
Here are the data structures I'm using.
typedef struct {
int nLength; // number of list elements in use
struct {
int iNumber; // number from an element of the nxn matrix
int iCount; // number of times this element was found in the matrix
} list[50 * 50];
} elementList;
elementList matrixList = {
0,
{0, 0}
};
int matrixThing[50][50];
next we need to loop through the matrix and with each element in the matrix to check if it is in the list. If it's not then add it. It does exist then increment the count.
for (unsigned short i = 0; i < 50; i++) {
for (unsigned short j = 0; j < 50; j++) {
findAndCount (matrixThing[i][j], &matrixList);
}
}
And then we need to define our function we use to check matrix values against the list.
void findAndCount (int matrixElement, elementList *matrixList)
{
for (int i = 0; i < matrixList->nLength; i++) {
if (matrixElement == matrixList->list[i].iNumber) {
matrixList->list[i].iCount++;
return;
}
}
// value not found in the list so we add it and set the initial count
// to one.
// we can then determine if there are any duplicates by checking the
// resulting list once we have processed all matrix elements to see
// if any count is greater than one.
// the initial check will be to see if the value of nLength is equal
// to the number of array elements in the matrix, n time n.
// so a 50 x 50 matrix should result in an nLength of 2500 if each
// element is unique.
matrixList->list[matrixList->nLength].iNumber = matrixElement;
matrixList->list[matrixList->nLength].iCount = 1;
matrixList->nLength++;
return;
}
Search algorithms
The above function, findAndCheck(), is a brute force search algorithm that searches through an unsorted list element by element until either the thing being searched for is found or the end of the list is reached.
If the list is sorted then you can use a binary search algorithm which is much quicker than a linear search. However you then run into the overhead needed to keep the list sorted using a sorting algorithm in order to use a binary search.
If you change the data structure used to store the list of found values to a data structure that maintains values in an ordered sequence, you can also cut down on the overhead of searching though there will also be an overhead of inserting new values into the data structure.
One such data structure is a tree and there are several types and algorithms to build a tree by inserting new items as well as searching a tree. See search tree which describes several different kinds of trees and searches.
So there is a kind of balancing between the effort to do searching versus the effort to add items to the data structure.
Here is an example that checks for duplicate values, the way want to do it.
Looping is slow, and we should use a hash set or a tree instead of using loops.
I assume you are not using C++, because the C++ standard library has build-in algorithms and data structures to do it efficiently.
#include <stdio.h>
/* Search the 'array' with the specified 'size' for the value 'key'
starting from 'offset' and return 1 if the value is found, otherwise 0 */
int find(int key, int* array, int size, int offset) {
for (int x = offset; x < size; ++x)
if (key == array[x])
return 1;
return 0;
}
/* Print duplicate values in a matrix */
int main(int argc, char *argv[]) {
int matrix[3][3] = { 1, 2, 3, 4, 3, 6, 2, 8, 2 };
int size = sizeof(matrix) / sizeof(matrix[0][0]);
int *ptr = (int*)matrix;
for (int x = 0; x < size; ++x) {
/* If we already checked the number, then don't check it again */
if (find(ptr[x], ptr, x, 0))
continue;
/* Check if the number repeats and show it in the console if it does */
if (find(ptr[x], ptr, size, x + 1))
printf("%d\n", ptr[x]);
}
return 0;
}
When you become better at C, you should find or implement a "hash set" or a "red-black tree", and use that instead.
I happened to write a simple sorting algorithm, but I am not sure what this algorithm is called.
#include<stdio.h>
#include<stdlib.h>
void IDontKnowWhatThisIs(int* arr, int size){
int* minuscount = malloc(size * sizeof(int)); //new location chooser array
int* valarr = malloc(size * sizeof(int)); //value backup array
//compare all elements: size^2
for (int i = 0; i < size; i++){
valarr[i] = arr[i];
minuscount[i] = 0;
for (int j = 0; j < size; j++){
if (i != j){
//the one with the least amount(0) is the smallest value
if (arr[i] - arr[j] > 0){
minuscount[i] += 1;
}
}
}
}
//O(size)
for (int i = 0; i < size; i++){
//place everything back in
arr[minuscount[i]] = valarr[i];
}
free(minuscount);
free(valarr);
//total time complexity: O(size^2)
}
int main(){
int arr[10] = { 50, 2, 13, 33, 62, 11, 30, 66, 1, -101 };
IDontKnowWhatThisIs(arr, 10);
for (int i = 0; i < 10; i++) printf("%d ", arr[i]);
return 0;
}
It is a simple algorithm that compares each elements with one another and counts new location for them.
and then it is copied back to the original array.
I don't think it is one of those generic n^2 algorithms(selection, bubble, insertion), but the concept of it is still very simple, so I am sure this algorithm already exists.
edit: on second thought, I think this is similar to a selection sort, but unoptimized as it compares even more..
I am not aware of a name for this algorithm. It's clever, but unfortunately you need to add an extra step if you want to handle possible duplicates in the array.
For instance, if the array is: [3;4;4;1;2] then minuscount will be [2;3;3;0;1] and the two 4 will be put in the same cell in arr, resulting in the final array [1;2;3;4;2] where that final 2 is leftover from the original array.
I don't known a name either. I would call it RankSort, because it computes the rank of every element, in order to permute them to their sorted location.
This sort is not very attractive because
it takes two extra arrays, one for the ranks and one as a buffer for permutation (the buffer can be avoided by implementing the permutation in-place);
as said by others, possible equal elements require special handling, namely a lexicographical comparison on value then index. This has a cost;
it performs all N² comparisons. (This can be reduced to N(N-1)/2 by updating the rank of the largest element.)
EDIT:
I forgot to mention that I do not want to allocate another temporarily array.
I am trying to solve a problem in C, which is:
Suppose you were given an array a and it's size N. You know that all of the elements in the array are between 0 to n-1. The function is supposed to return 0 if there is a missing number in the range (0 to n-1). Otherwise, it returns 1. As you can understand, duplicates are possible. The thing is that its supposed to run on O(n) runtime.
I think I managed to do it but i'm not sure. From looking at older posts here, it seems almost impossible and the algorithm seems much more complicated then the algorithm I have. Therefore, something feels wrong to me.
I could not find an input that returns the wrong output yet thou.
In any case, I'd appreciate your feedback- or if you can think of an input that this might not work for. Here's the code:
int missingVal(int* a, int size)
{
int i, zero = 0;
for (i = 0; i < size; i++)
//We multiply the element of corresponding index by -1
a[abs(a[i])] *= -1;
for (i = 0; i < size; i++)
{
//If the element inside the corresponding index is positive it means it never got multiplied by -1
//hence doesn't exist in the array
if (a[i] > 0)
return 0;
//to handle the cases for zeros, we will count them
if (a[i] == 0)
zero++;
}
if (zero != 1)
return 0;
return 1;
}
Just copy the values to another array placing each value in its ordinal position. Then walk the copy to see if anything is missing.
your program works and it is in O(N), but it is quite complicated and worst it modify the initial array
can be just that :
int check(int* a, int size)
{
int * b = calloc(size, sizeof(int));
int i;
for (i = 0; i != size; ++i) {
b[a[i]] = 1;
}
for (i = 0; i != size; ++i) {
if (b[i] == 0) {
free(b);
return 0;
}
}
free(b);
return 1;
}
This problem is the same as finding out if your array has duplicates. Here's why
All the numbers in the array are between 0 and n-1
The array has a size of n
If there's a missing number in that range, that can only mean that another number took its place. Which means that the array must have a duplicate number
An algorithm in O(n) time & O(1) space
Iterate through your array
If the sign of the current number is positive, then make it negative
If you found a negative this means that you have a duplicate. Since all items are originally greater (or equal) than 0
Implementation
int missingVal(int arr[], int size)
{
// Increment all the numbers to avoid an array with only 0s
for (int i = 0; i < size; i++) arr[i]++;
for (int i = 0; i < size; i++)
{
if (arr[abs(arr[i])] >= 0)
arr[abs(arr[i])] = -arr[abs(arr[i])];
else
return 0;
}
return 1;
}
Edit
As Bruno mentioned if we have an array with all zeros, we could have run into a problem. This is why I included in this edit an incrementation of all the numbers.
While this add another "pass" into the algorithm, the solution is still in O(n) time & O(1) space
Edit #2
Another great suggestion from Bruno which optimizes this, is to look if there's more than one zero instead of incrementing the array.
If there's 2 or more, we can directly return 0 since we have found a duplicate (and by the same token that not all the numbers in the range are in the array)
To overcome the requirement that excludes any extra memory consumption, the posted algorithm changes the values inside the array by simply negating their value, but that would leave index 0 unchanged.
I propose a different mapping: from [0, size) to (-1 - size, -1], so that e.g. {0, 1, 2, 3, 4, ...} becomes {-1, -2, -3, -4, -5, ...}. Note that, for a two's complement representation of integers, INT_MIN = -INT_MAX - 1.
// The following assumes that every value inside the array is in [0, size-1)
int missingVal(int* a, int size) // OT: I find the name misleading
{
int i = 0;
for (; i < size; i++)
{
int *pos = a[i] < 0
? a + (-a[i] - 1) // A value can already have been changed...
: a + a[i];
if ( *pos < 0 ) // but if the pointed one is negative, there's a duplicate
break;
*pos = -1 - *pos;
}
return i == size; // Returns 1 if there are no duplicates
}
If needed, the original values could be restored, before returning, with a simple loop
if ( i != size ) {
for (int j = 0; j < size; ++j) {
if ( a[j] < 0 )
a[j] = -a[j] - 1;
}
} else { // I already know that ALL the values are changed
for (int j = 0; j < size; ++j)
a[j] = -a[j] - 1;
}
I am writing a program that reads a text file as an input and randomly shuffles the array of strings for the user.
I have written a program that shuffles the string array randomly but I want to do it in a way that no two elements that are the same are beside each other.
Here's an example:
The original array would look like this
{1,2,3,4,5,1,2}
The shuffled array would look like this
{5,3,1,2,4,2,1}
But currently my program creates an output array of this
{5,1,1,3,2,4,2}
Here is my code that shuffles the elements randomly:
int i;
char s[11][100];
char line[100], t[100];
/*Open the text file*/
FILE *fp;
fp = fopen("players.txt", "r");
/*Read each line and put it into an element in an array.
Each line will be in a seperate element in the array.*/
i=0;
while(fgets(line, 100, fp)!= NULL){
strcpy(s[i], line);
i++;
}
/*Generates a random number stored in j and shuffles the order of the array randomly*/
for(i=1; i<10; i++){
j = rand()%(i+1);
strcpy(t, s[j]);
strcpy(s[j], s[i]);
strcpy(s[i], t);
}
As far as I know, there is no better solution than repeatedly running the Fisher-Yates shuffle until you find an arrangement without adjacent duplicates. (That's usually called a rejection strategy.)
The amount of time this will take depends on the probability that a random shuffle has adjacent duplicates, which will be low if there are few duplicates and could be as much as 1.0 if more than half of the set is the same majority element. Since the rejection strategy never terminates if there is no possible qualifying arrangement, it could be worth the trouble to verify that a solution is possible, which means that there is no majority element. There's an O(n) algorithm for that, if necessary, but given the precise details you provided, it shouldn't be necessary (yet).
You can reject immediately rather than continuing to the end of the shuffle, which significantly cuts down on the cost of running the algorithm. So just use your shuffle algorithm, but restart the counter if you place an element beside one of its twins.
By the way, using strcpy to move elements around is really inefficient. Just shuffle the pointers.
Here's some code adapted from this answer. I've assumed that the duplicates are exact, for simplicity; perhaps you have some other way of telling (like looking only at the first word):
void shuffle(const char* names[], size_t n) {
for (size_t i = 0; i < n;) {
size_t j = i + rand() % (n - i);
/* Reject this shuffle if the element we're about to place
* is the same as the previous one
*/
if (i > 0 && strcmp(names[j], names[i-1]) == 0)
i = 0;
else {
/* Otherwise, place element i and move to the next one*/
const char* t = names[i];
names[i] = s[j];
names[j] = t;
++i;
}
}
}
For your use case, where you have 10 objects with frequencies 3, 3, 2, and 2, there are 605,376 valid arrangements, out 3,628,800 (10!) total arrangements, so about five of every six shuffles will be rejected before you find a valid arrangement, on average. However, the early termination means that you will do less than six times as much work as a single shuffle; empirical results indicate that it takes about 33 swaps to produce a valid shuffle of 10 objects with the above frequencies.
Note: rand()%k is not a very good way to generate a uniform distribution of integers from 0 to k-1. You'll find lots of advice about that on this site.
import java.util.Random;
import java.util.Arrays;
public class ShuffleRand
{
static void randomize( int arr[], int n)
{
Random r = new Random();
for (int i = n-1; i > 0; i--) {
int j = r.nextInt(i+1);
int temp = arr[i];
arr[i] = arr[j];
arr[j] = temp;
}
System.out.println(Arrays.toString(arr));
}
public static void main(String[] args)
{
int[] arr = {1, 2, 3, 4, 5, 6, 7, 8};
int n = arr.length;
randomize (arr, n);
}
}
This function will shuffle array of strings randomly:
void shuffle(char *arr[], int size)
{
srand(time(NULL));
for (int i = 0; i < size; i++)
{
int b = rand() % size;
int a = rand() % size;
char *tmp = arr[a];
arr[a] = arr[b];
arr[b] = tmp;
}
}