java,sorting,generics,quicksort

Make your entity classes implement Comparable. Thus you'll have v.get(i).compareTo(pivo) instead of v.get(i).toString().compareTo(pivo.toString()); ...

java,c++,sorting,computer-science,quicksort

The quicksort algorithm looks like this: quicksort(A, lo, hi): if lo < hi: p := partition(A, lo, hi) quicksort(A, lo, p - 1) quicksort(A, p + 1, hi) We have a special partition that is 3-way, so let's say it returns the equal range for whatever pivot it picks and...

It would be a terrible idea to modify the code of your sorting algorithm just to adapt to a particular data type whereas your sorting class uses generics. You have already wrapped your data in a Contact class, so all you need to do is to implement the Comparable<Contact> interface....

I the task to finding posivite numbers, there is an algorithm : public static void quickSort(final int size) { int l = 0; int r = size - 1; int q, i = 0; int tmpr = r; while (true) { i--; while (l < tmpr) { q = partition(l,...

Your partition algorithm step is wrong. For example, let's say we start with: [1, 2, 3, 2, 8, 9] ^i ^center ^j We go into the while loop, which will first move i up the first element greater than 3 (the 8), and j down to the first element less...

algorithm,sorting,selection,quicksort

Because it has a better worst-case time complexity. The approximate median-selection algorithm can also be used as a pivot strategy in quicksort, yielding an optimal algorithm, with worst-case complexity O(n log n). Although this approach optimizes quite well, it is typically outperformed in practice by instead choosing random pivots, which...

In run-of-the-mill Pascal, arrays are value types, so in this procedure quickSort(arr: array of integer; left, right:integer); you are passing a copy of the array. Change to this procedure quickSort(var arr: array of integer; left, right:integer); and it should work better....

First thing I would like to add is a shuffle operation before the first call in quicksort. Other than that if you want to take the median of first three elements that would be fine in the case you first shuffle the elements (in other case - especially if the...

This does what you want, I have just added the .tail before partitioning. def quicksortDataByIndex(index: Int, list: MutableList[Array[Double]]) : MutableList[Array[Double]] = { if(list.isEmpty){ list } else { val (smaller, bigger) = list.tail partition (a => a(index) < list.head(index)) quicksortDataByIndex(index, smaller) += list.head ++= quicksortDataByIndex(index, bigger) } } Output : quicksortDataByIndex(1,...

During sorting swaps the value of 'nums[pivotIndex]' can change. Use fixed pivot instead: public static void quickSort(Integer[] nums, int left, int right) { final int pivot = nums[(left + right) / 2]; // <== Fix pivot value. int l = left; int r = right; while (l <= r) {...

if S contains a value d.isEmpty() never returns false. So you run in a infinite loop. If i will bigger the S.size() you get an ArrayIndexOutOfBoundException if you use the get() function. change: while(!S.isEmpty()) { To: while (i<S.size()) { ...

There is no upfront division between the left and the right side. In particular, 6 is not the division. Instead, the division is the result of moving the left and right pointer closer to each other until they meet. The result might be that one side is considerably smaller than...

algorithm,sorting,language-agnostic,quicksort

I claim that m1 <= m2 is necessary and sufficient. If it is the case, after the first we can be sure that m2 smallest numbers from the m1 + 1 ... n part are located inside the 1 ... m1 + m2 prefix. m2 >= m1, thus m1 smallest...

java,string,sorting,arraylist,quicksort

The root of my problem turned out to be in this line of code: for (ndx = (1 + firstIndex); ndx < numberToSort; ndx++) { particularly : ndx < numberToSort this should instead be: ndx < (numberToSort + firstIndex), as we are not necessarily starting at 0. ...

java,quicksort,doubly-linked-list

The reason you are always retrieving the same element in DList.get is that you stop looping after the first iteration. Simply remove the break-statement, and the loop should work as intended. public int get(int pos) { DNode current = new DNode(); for(int i = 0; i <= pos && current...

java,recursion,multidimensional-array,quicksort

In Java, arrays are always one dimensional - although their element type may be an array itself. So a two dimensional array in Java is just an array of arrays. This fact becomes very handy when you want to sort an array so that rows stick together. You treat each...

Your swap method is incorrect. Java is always pass by value, and primitives can't be modified like that. Instead, pass in the array (the value of an array, as an Object instance, is its' reference) and the indexes to swap like private void swap(int[] arr, int l, int r) {...

The solution to your problem is to change int a[] into vector<int> a in definitions of both partition and quickSort functions. So int partiton(vector<int> a, int low, int up) and void quickSort(vector<int> a, int low, int up) should be sufficient for compilation-error-free code. Compiler expects functions to be called with...

java,android,sorting,quicksort,mergesort

The key issue is sort stability - if two elements are equal from the point of view of the sort order, do they appear in the result in the same order as in the input. It does not matter for e.g. long. All instances of 3 in the input will...

Based on your code the qsort function is fine even the partition which is a little bit complicated to understand ! I guess your problem is with the swap function ! Here is a working code which uses an easy-to-understand implementation of partition function : void swap(int *a, int *b)...

You are sorting new slices: partition(arr[left:], len(arr[left:])) Those slices are new lists, not the original list object. Anything you do to those won't be visible in the original value of arr. If you want to do the sorting in-place, you'll need to pass along start and stop values of what...

c,algorithm,pivot,quicksort,partitioning

The modified partitioning procedure gets into an infinite loop when the subarray contains at least two other values that are equal to the pivot. Let's consider a case where we have: int A[] = { 3, 3, 1, 3 }; And we call: partition(A, 0, 3); On the first iteration...

c++,algorithm,sorting,segmentation-fault,quicksort

One thing that looks odd is the line: int middle = (right / 2); This does not always return an element between left and right. Perhaps try instead: int middle = left + ( (right-left) / 2); The current code might result in a pivot value that doesn't reduce the...

algorithm,sorting,time-complexity,quicksort

It may be more suited to English (or some other etymology-related) SO site, but pathological comes from Greek, and means the study of ailments or suffering (also emotions, since ancient Greeks were famous for correlating the two...), and in this context - all sorts of disruptions to the normal order...

java,algorithm,sorting,quicksort

Can anyone explain with that intuition why it is necessary to swap if right>= left? right and left are indexes - not the items themselves (which is probably the source of your confusion). If a number to the "right" of the pivot is smaller than the pivot it should...

java,algorithm,sorting,quicksort

I did two things to your code to get it to work: at beginning of method set j = right +1 and move v = arr.get(right) to after first if statement. Should look something like this: public static void sort(ArrayList<Integer> arr, int left, int right) { int i = left...

When you get to the point of swapping, the comparisions with the pivot you've mentioned have already been done. The first while loop ends when it has found a value greater than the pivot & the second loop ends when it has found a value lesser than the pivot. This...

If the sentence is absent, there is no problem if the array V[ ] is random data. However, if V[ ] is sorted data, no swap is encountered, and the variable last is not changed. Thus, last qsort() is equivalent to qsort(v, left+1, right, comp). It means that only one...

if(first < Last) quickSort(v, first, Last); if(First < last) quickSort(v, First, last); v is the complete array. It never will reach a length smaller than 2. Either partition v, or adjust the base case condition to last - first < 2 ...

python,recursion,stack-trace,quicksort

Your quicksort algorithm is very bad at sorting sorted lists. Your pivot_val is the first number, so a sorted list is partitioned in one number and the rest. For random lists, the recursion needed is something like log_2 N, that means for 20000 elements the depth is about 15. In...

You've got a couple of errors, the main one being that I don't think you've quite understood what the median of three bit should be doing and where to use it. In particular - it should be used to select the pivot, not to do any swapping on the array....

Your partition function is incorrect. There are two primary methods for partitioning a sequence during quicksort: the squeeze and the sweep. The former of these is the one you're attempting and has a high likelihood of fewer swaps than the latter method at the price of a more complicated algorithm....

python,algorithm,list,counter,quicksort

Here's what I would do, if I'm understanding you right. def quicksort(lista,izq,der): i = izq j = der swap_count = 0 compare_count = 0 pivote = lista[(izq + der)//2] while i <= j: while lista[i] < pivote: i += 1 while pivote < lista[j]: j -= 1 if i <=...

int arrayIndex = 0; must be replaced by int arrayIndex = start; ...

Remove i=0, j=0 , k=0; and what follows, and try the following while(k--){ ar[k+j] = a2[k]; } while(j--){ ar[j] = a1[j]; } ...

After seeing several permutations of your code I think what you are trying to do needs to look a little something like this. quickSort(arrayToSort, attributeToSortOn, left, right) { ... } ... function partition(arrayToSort, attributeToSortOn, left, right) { var pivot = student[Math.floor((right + left) / 2)][attributeToSortOn] ... while (arrayToSort[i][attributeToSortOn] < pivot)...

Figured out what I was doing wrong. I really needed to use the Lomuto Partitioning method in order to satisfy the requirements of the print statements. Code for anyone searching for this in the future def partition(array, lo, hi): pivot_index = hi pivot_value = array[pivot_index] store_index = lo for i...

Your problem starts in read_data(): you allocate memofry for only one single list_element (temp) and overwrite its content with every record you read from the data file. You need to allocate seperate list_elements for each one.

algorithm,sorting,data-structures,quicksort,hoare-logic

The algorithm is correct. You're partitioning the subarray A[p..r] using A[p] as the pivot. So the pivot is 1 and not 5. Hoare-Partition(A=[1,3,9,8,2,7,5], p=0, r=6) results in: x = A[p] = 1 i = -1 j = 7 repeat: j = j - 1 = 6; A[j] = 5 j...

In Quick sort, if the first element is chosen as the pivot element for partitioning..then Quick sort exhibits its worst cast complexity - O(n^2) in this case. More precisely, Quick sort's worst case complexity of O(n^2) is observed when the input to be sorted is in decreasing order or increasing...

There are several mistakes in your code - firstly, your right += 1 is wrong, since right is the highest index. You need to decrease the value, not increase. Secondly, why are you increasing c in input? You are using range, so it does it automatically. Also, you don't need...

Your code doesn't even looks like a python code, you are still trying to translate from something to python and that's not a good idea. Usually you would have something like this in Python: def quickSort(arr): #Leftside less = [] #pivot pivotList = [] #rightside more = [] #if the...

time-complexity,quicksort,quickselect,median-of-medians

According to Wiki, The approximate median-selection algorithm can also be used as a pivot strategy in quicksort, yielding an optimal algorithm, with worst-case complexity O(n log n). This is because the median of medians algorithm prevents the bad partitioning that would occur in naive quicksort on an already sorted array....

There were only small errors in your partition function as you already guessed: 1) Your for loop was not processing the last element because you used range(lower, upper-1) instead of range(lower, upper) 2) You should finally return i instead of i+1 def partition(Array,lower,upper): ... for j in range(lower,upper): ... return...

This is in-place assignment, without replacing the list object with a new object. This way, the output is placed in the original list and can be read by the caller.

The proper way of using recursion in QuickSort is to use start, pivot and end. You appear to be using inclusive-end indexing; then you will want to recurse into quicksort(data, start, pivot - 1) quicksort(data, pivot + 1, end) The pivot element is already in its final position....

Here: partition(arr[left:], len(arr[left:]) ↑ You're missing one ). Using an IDE will really help you to find little problem like this one. Note that your code suffers from more problems, they are unrelated to the syntax error you're getting. General note: Please make more efforts next time when you post...

c++,struct,quicksort,boolean-operations

Try the following #include <algorithm> //... struct type{ int a,b,w; bool operator<(const type& A) const{ return w<A.w; }; }; type edge[6]; //... std::sort( edge, edge + 6 ); Or #include <algorithm> #include <iterator> //... struct type{ int a,b,w; bool operator<(const type& A) const{ return w<A.w; }; }; type edge[6]; //......

I made a few changes to fix the range issue, but the parsing of the strings worked well My changes: I moved the main procedure to a new module I changed it to sort sheet "Master of Masters" specifically Renamed most of your variables to be a bit more intuitive...

Just put the call to var v = a[right]; after the line if (right <= left) return; ...

Nothing seems wrong with your code but bear in mind that this is a recursive function and most languages have a limited-depth stack which you are bound to get to if you have an input large enough. For Java, see: What is the maximum depth of the java call stack?...

sorting,quicksort,binary-search,mergesort

After some Googling and testing, I finally got the answer: In case of Binary Search, when I tried it for the input 20,21 and 30, searching for the element 20, I finally landed upon a typical case wherein p=r=0. If the base condition included here is p>=r, then the result...

There is no problem with implementing this same algorithm using a List rather than an array. You can use a List just like an array: using set and get methods. It also has convenient methods such as subList that are useful for quicksort. A sublist is a view of the...

c#,parallel-processing,quicksort

static void Main(string[] args) { string[] unsorted = { "z", "e", "x", "c", "m", "q", "a" }; // Print the unsorted array. for (int i = 0; i < unsorted.Length; i++) Console.Write(unsorted[i] + " "); Console.WriteLine(); // Get a copy of the array, as a list. List<string> list = unsorted.ToList();...

c++,optimization,quicksort,partitioning

Some problems with your version: 1) Neither loop triggers if both values are equal to pivot (one should) 2) You don't move high and low after the swap (you could forgo retesting those) Your code will work if you fix just one of those...

Worst-case The worst-case behavior for quicksort occurs when the partitioning routine produces one subproblem with n -1 elements and one with 0 elements.The partitioning costs θ(n) time. If the partitioning is maximally unbalanced at every recursive level of the algorithm, then the depth of the tree is n and the...

There are many possible variations of the quicksort algorithm. In this one it is OK for the pivot to be not in its correct place in its iteration. The defining feature of every variation of the quicksort algorithm is that after the partition step, we have a part in the...

Your program fails because you operate on copies of the array, rather than operating in-place. So consider the declaration of quicksort: Procedure quicksort(links, rechts: integer; localIntArray: iArray); The array is passed by value. You pass the array into the procedure, but any changes made to the array are never seen...

java,arrays,recursion,quicksort

Quicksort is known to be O(n^2) worst case, which is when you give it sorted input and choose the worst pivot (the highest or lowest element). That will also have the effect of causing very deep recursion, as you have seen. You don't include your pivot selection mechanism, so I...

javascript,algorithm,sorting,quicksort

So as you stated the first element of the array will be used as a temporary variable which will be only useful for the execution of the algorithm and which wasn't clear at first ! Your algorithm works fine but you have problem in printing the result ! To get...

c,infinite-loop,quicksort,gcc4.9

Your partitioning code looks weird and there's at least a few things wrong with it: for (; a[i] < p; i++) is not guaranteed to terminate. And then if j is the final position of pivot element, your left array should be sorted by quicksort(array, j) and not j-1....

Your quicksort algorithm is wrong. While (tmp_low_file.file_mod_date < pivot.file_mod_date And tmpLow < inHighBound) tmpLow = tmpLow + 1 Wend You only update your index counter, but you don't update your comparison values "tmp_low_file.file_mod_date < pivot.file_mod_date" alway stay the same, and you tmpLow will go up until inHighBound. Run this test...

java,data-structures,quicksort

Here is what happens: At first, your list is: ┌──┬──┬──┬──┬──┬──┐ │50│30│10│40│20│60│ └──┴──┴──┴──┴──┴──┘ ↑ pivot The pivot is 10 in this case. Scanning from the left, x points to 50, so it stops there. y, on the other hand, stops at the 10. Good, so we swap them. We get: x=0...

Use left and right in the for loop declaration: public static void insertionSort(int a[], int left, int right) { int j; for (int p = left; p < right; p++) { int tmp = a[p]; for(j = p; j > 0 && tmp < a[j - 1]; j--) { a[j]...

java,arrays,algorithm,sorting,quicksort

I think the confusion I had was the whole idea of quicksort. If anyone else is struggling, with this, here's how I would explain it now. int index = partition(arr, left, right);  Will partition the array with regards to a pivot, which would be index in this case. It is...

The logic error is that qsrt takes the minimum element of l and then skips x, but x would only be the minimum element of l by accident so you're usually skipping the wrong element.

It's a problem with your test code. The third parameter should be the index of the last element, not the number of elements: quickSort(tarr, 0, 9); You're reading past the end of the array. For more information about Hoare partitioning, Quicksort and Cormen etc, see this question. The simple fix...

python,list,optimization,quicksort

It is best if you ask one question per question. The first part is answered by Python quicksort - List comprehension vs Recursion (partition routine) Then second part of your question can be expressed as a += 3 if condition else 1 but I find that hard to read and...

I'm pretty sure I fixed it now. You were increasing the left and right pointers within the partition method before you wanted to (outside of the "checks"). Change your partition method as follows: public static int partition(int[] array, int left, int right) { if(array.length == 1) return right; int pivot...

int cmpfunc (const void * a, const void * b) //what is it returning? { return ( *(int*)a - *(int*)b ); //What is a and b? } Is equivalent to: int cmpfunc (const void * a, const void * b) //what is it returning? { // qsort() passes in `void*`...

algorithm,sorting,debugging,quicksort

You don't consider the case when i == j and also, as @MK said in a comment, the pivot should be a value and not an index (pivot = (a1+b1)/2; should be something like pivot = a[(a1+b1)/2]). For example, if you start the array a = {2, 45, 56, 3,...

The block of code that swaps, also needs to increment l and decrement r once the swap is complete: if (l <= r) then begin temp := iArray[l]; iArray[l] := iArray[r]; iArray[r] := temp; inc(l); // <-- this was missing dec(r); // <-- as was this end; The complete program,...

java,algorithm,sorting,quicksort

Two problems: You need to choose pivot value from partition, not just take first element of an array Last swap should be outside of the loop, you are putting pivot element to it's place after traversing partition. See last two lines: Fixed partition method: public static int partition(int[] a, int...

java,algorithm,data-structures,stack-overflow,quicksort

In your partition method you sometimes use a element outside the range: String string1 = data.get(firstIndex); String string2 = data.get((firstIndex + (numberToPartition - 1)) / 2); String string3 = data.get(firstIndex + numberToPartition - 1); (firstIndex + (numberToPartition - 1)) / 2 is not index of the middle element. That would...

c++,c,arrays,parameter-passing,quicksort

l is the function parameter of type int, it hides the global variable with the same name.

c#,arrays,algorithm,sorting,quicksort

Several things: Youre missing the comparisons(while loops) within the do while loop that move the index pointers, and the recursive calls that make quicksort actually work. Remember when you swap your values, increment i and decrement j. Second, for the values i and j, dont add 1 to those indexes...

delphi,pointers,quicksort,delphi-2009

Quicksort is a good choice when you can use O(1) random access. Otherwise it's a not a good choice. You can certainly implement Quicksort with your doubly linked list. It's just that any time you need random access to an element, you need to step through your list. Clearly that...

One problem the implementation has is that it won't work if you have equal numbers (you will keep switching them with each other if it will be chosen as pivot). The other is in the recursion: if(pivot > left + 1) QuickSort_HighLow(arr, left, pivot - 1); if(pivot < right -...

algorithm,sorting,data-structures,time-complexity,quicksort

Intuitively, you can ignore the part about quicksort, because it only happens for small n, and the big-O notation only talks about values of n that are "big enough". So the parts of the algorithm are: Recursive invocation on 1/4 of input: T(1/4 * n) Recursive invocation on 3/4 of...

Since q_sort is recursive, the meaning of its parameters needs to be taken in two contexts: When the function is called externally, and When a recursive invocation is performed. You have adjusted the int right parameter in the external call q_sort(array, 0, 4) to treat the right end as exclusive,...

Use this in your pivot function before return statement. swap(a,++i,high); instead of swap(a,i,high); ...

java,arrays,algorithm,sorting,quicksort

After reading @greybeard's and @Smac89's comments, I realized I needed a stable form of quicksort, stable as in "preserving the original order of the input set, where the comparison algorithm does not distinguish between two or more items"(http://programmers.stackexchange.com/questions/247440/what-does-it-mean-for-a-sorting-algorithm-to-be-stable) To me a stable sort doesn't really make sense for this run...

c,string,algorithm,pointers,quicksort

You are calling quicksort(strings, 0, iteration); which will try to access the element at iteration location for which there might be memory access violation. For array of size of iteration, iteration-1 is the last element. Hence, you should pass iteration-1 rather than iteration. Also, keep a check of iteration as...

c++,algorithm,sorting,quicksort

The answer lies in the Wikipedia article linked in this post.

c,arrays,recursion,quicksort,bubble-sort

Either use a global variable as suggested in the comments : int _SwapCount = 0; void quicksort(int arr[],int first,int last) { ... //whenever you swap _SwapCount++; or take a pointer to an int as a parameter: void quicksort(int arr[],int first,int last, int* swapCount) { ... //whenever you swap (*swapCount)++; //recursion...

c,algorithm,recursion,quicksort

Here's what I did with your outline and it seems to be working and sorting fine. I replaced the void with an int, and declared int's as necessary #include<iostream> using namespace std; int partition(int *A, int p, int r){ int value = A[r]; int i = p-1; int tmp; for...

The fundamental problem is that your recursion has no exit condition. You don't have a single return statement in your partition method. When your while loop exits, it will just make additional call into the partition method again. But there's nothing in the code to say, "stop making recursive calls...

javascript,algorithm,go,quicksort

left++ should be after the swap() function as follow if arr[i] <= v { swap(i, left) left++ } After the fix, output is Unsorted: [20 43 52 -1 43 29 34] Sorted: [-1 20 29 34 43 43 52] ...

Your partition looks odd, try this one private int partition(String[] array, int inicio, int fim) { String pivo = array[(inicio + fim) / 2]; int i = inicio; int j = fim; while (true) { while (array[i].compareTo(pivo) < 0) { i++; } while (array[j].compareTo(pivo) > 0) { j--; } if...

java,indexoutofboundsexception,quicksort

I have fixed your error see below code. static void dog(int i, int b, int c, int array[]) { if (c<array.length-1 && array[i] <= array[c] ) { if (c <(int) array.length-1) { int y = array[i]; array[i] = array[b]; array[b] = y; if (b < array.length) return; else b++; i...

java,arrays,sorting,quicksort,heapsort

So after few weeks of pain I managed to understand what was wrong. Everything seems to work fine with the following moveDownAux method: private static <T extends Comparable<? super T>> void moveDownAux(T[] a, int min, int i, int max) { T e = a[i]; int j; while((j = (2*i)+1 -...