I am trying to develop a faster way than what I currently have to add an element to a sorted array list. Currently this is my strategy
public void insertSorted(E value) {
add(value);
for (int i = size() - 1; i > 0 && value.compareTo(get(i - 1)) < 0; i--) {
this.swap(i);
}
}
and my add method...
public void add(E element) {
ensureCapacity();
array[size++] = element;
}
So I read that using a binary search algorithm I could more efficiently find the best way to put an element even faster.
I tried developing that, but somehow it always outputs me 0.
private int binarySearch(E value) {
int low = 0;
int high = this.size()-1;
while (low <= high) {
int mid = (low + high) / 2;
E midVal = this.get(mid);
int cmp = midVal.compareTo(value);
if (cmp < 0)
low = mid + 1;
else if (cmp > 0)
high = mid - 1;
else
return mid;
}
return low;
}
public void insertSorted(E value) {
int searchResult = binarySearch(value);
add(value, searchResult);
System.out.println("Value: " + value + ". Position = " + searchResult);
}
Could someone help me out? If necessary I will show full code
Rather than developing your own binary search, use built-in Arrays.binarySearch implementation. However, this wouldn't give you much improvement over your original version in terms of time.
To see why, consider the steps that you take to place the value in the sorted sequence:
Find the insertion position
Move items to the right of insertion position by one
Place the element into insertion position
The first step can be done in O(log2N). The second step takes O(N). The last step takes O(1). Overall, insertion's time complexity is O(log2N + N + 1), which is the same as O(N). The algorithm is dominated by the second step, so you might as well use linear search as you move items to the right by one.
I'm trying to find the average of all even numbers in an array using recursion and I'm stuck.
I realize that n will have to be decremented for each odd number so I divide by the correct value, but I can't wrap my mind around how to do so with recursion.
I don't understand how to keep track of n as I go, considering it will just revert when I return.
Is there a way I'm missing to keep track of n, or am I looking at this the wrong way entirely?
EDIT: I should have specified, I need to use recursion specifically. It's an assignment.
public static int getEvenAverage(int[] A, int i, int n)
{
// first element
if (i == 0)
if (A[i] % 2 == 0)
return A[0];
else
return 0;
// last element
if (i == n - 1)
{
if (A[i] % 2 == 0)
return (A[i] + getEvenAverage(A, i - 1, n)) / n;
else
return (0 + getEvenAverage(A, i - 1, n)) / n;
}
if (A[i] % 2 == 0)
return A[i] + getEvenAverage(A, i - 1, n);
else
return 0 + getEvenAverage(A, i - 1, n);
}
In order to keep track of the number of even numbers you have encountered so far, just pass an extra parameter.
Moreover, you can also pass an extra parameter for the sum of even numbers and when you hit the base case you can return the average, that is, sum of even numbers divided by their count.
One more thing, your code has two base cases for the first as well as last element which is unneeded.
You can either go decrementing n ( start from size of array and go till the first element ), or
You can go incrementing i starting from 0 till you reach size of array, that is, n.
Here, is something I tried.
public static int getEvenAvg(int[] a, int n, int ct, int sum) {
if (n == -1) {
//make sure you handle the case
//when count of even numbers is zero
//otherwise you'll get Runtime Error.
return sum/ct;
}
if (a[n]%2 == 0) {
ct++;
sum+=a[n];
}
return getEvenAvg(a, n - 1, ct, sum);
}
You can call the function like this getEvenAvg(a, size_of_array - 1, 0, 0);
Example
When dealing with recursive operations, it's often useful to start with the terminating conditions. So what are our terminating conditions here?
There are no more elements to process:
if (index >= a.length) {
// To avoid divide-by-zero
return count == 0 ? 0 : sum / count;
}
... okay, now how do we reduce the number of elements to process? We should probably increment index?
index++;
... oh, but only when going to the next level:
getEvenAverage(elements, index++, sum, count);
Well, we're also going to have to add to sum and count, right?
sum += a[index];
count++;
.... except, only if the element is even:
if (a[index] % 2 == 0) {
sum += a[index];
count++;
}
... and that's about it:
static int getEvenAverage(int[] elements, int index, int sum, int count) {
if (index >= a.length) {
// To avoid divide-by-zero
return count == 0 ? 0 : sum / count;
}
if (a[index] % 2 == 0) {
sum += a[index];
count++;
}
return getEvenAverage(elements, index + 1, sum, count);
}
... although you likely want a wrapper function to make calling it prettier:
static int getEvenAverage(int[] elements) {
return getEvenAverage(elements, 0, 0, 0);
}
Java is not a good language for this kind of thing but here we go:
public class EvenAverageCalculation {
public static void main(String[] args) {
int[] array = {1,2,3,4,5,6,7,8,9,10};
System.out.println(getEvenAverage(array));
}
public static double getEvenAverage(int[] values) {
return getEvenAverage(values, 0, 0);
}
private static double getEvenAverage(int[] values, double currentAverage, int nrEvenValues) {
if (values.length == 0) {
return currentAverage;
}
int head = values[0];
int[] tail = new int[values.length - 1];
System.arraycopy(values, 1, tail, 0, tail.length);
if (head % 2 != 0) {
return getEvenAverage(tail, currentAverage, nrEvenValues);
}
double newAverage = currentAverage * nrEvenValues + head;
nrEvenValues++;
newAverage = newAverage / nrEvenValues;
return getEvenAverage(tail, newAverage, nrEvenValues);
}
}
You pass the current average and the number of even elements so far to each the recursive call. The new average is calculated by multiplying the average again with the number of elements so far, add the new single value and divide it by the new number of elements before passing it to the next recursive call.
The way of recreating new arrays for each recursive call is the part that is not that good with Java. There are other languages that have syntax for splitting head and tail of an array which comes with a much smaller memory footprint as well (each recursive call leads to the creation of a new int-array with n-1 elements). But the way I implemented that is the classical way of functional programming (at least how I learned it in 1994 when I had similar assignments with the programming language Gofer ;-)
Explanation
The difficulties here are that you need to memorize two values:
the amount of even numbers and
the total value accumulated by the even numbers.
And you need to return a final value for an average.
This means that you need to memorize three values at once while only being able to return one element.
Outline
For a clean design you need some kind of container that holds those intermediate results, for example a class like this:
public class Results {
public int totalValueOfEvens;
public int amountOfEvens;
public double getAverage() {
return totalValueOfEvens + 0.0 / amountOfEvens;
}
}
Of course you could also use something like an int[] with two entries.
After that the recursion is very simple. You just need to recursively traverse the array, like:
public void method(int[] values, int index) {
// Abort if last element
if (index == values.length - 1) {
return;
}
method(array, index + 1);
}
And while doing so, update the container with the current values.
Collecting backwards
When collecting backwards you need to store all information in the return value.
As you have multiple things to remember, you should use a container as return type (Results or a 2-entry int[]). Then simply traverse to the end, collect and return.
Here is how it could look like:
public static Results getEvenAverage(int[] values, int curIndex) {
// Traverse to the end
if (curIndex != values.length - 1) {
results = getEvenAverage(values, curIndex + 1);
}
// Update container
int myValue = values[curIndex];
// Whether this element contributes
if (myValue % 2 == 0) {
// Update the result container
results.totalValueOfEvens += myValue;
results.amountOfEvens++;
}
// Return accumulated results
return results;
}
Collecting forwards
The advantage of this method is that the caller does not need to call results.getAverage() by himself. You store the information in the parameters and thus be able to freely choose the return type.
We get our current value and update the container. Then we call the next element and pass him the current container.
After the last element was called, the information saved in the container is final. We now simply need to end the recursion and return to the first element. When again visiting the first element, it will compute the final output based on the information in the container and return.
public static double getEvenAverage(int[] values, int curIndex, Results results) {
// First element in recursion
if (curIndex == 0) {
// Setup the result container
results = new Results();
}
int myValue = values[curIndex];
// Whether this element contributes
if (myValue % 2 == 0) {
// Update the result container
results.totalValueOfEvens += myValue;
results.amountOfEvens++;
}
int returnValue = 0;
// Not the last element in recursion
if (curIndex != values.length - 1) {
getEvenAverage(values, curIndex + 1, results);
}
// Return current intermediate average,
// which is the correct result if current element
// is the first of the recursion
return results.getAverage();
}
Usage by end-user
The backward method is used like:
Results results = getEvenAverage(values, 0);
double average results.getAverage();
Whereas the forward method is used like:
double average = getEvenAverage(values, 0, null);
Of course you can hide that from the user using a helper method:
public double computeEvenAverageBackward(int[] values) {
return getEvenAverage(values, 0).getAverage();
}
public double computeEvenAverageForward(int[] values) {
return getEvenAverage(values, 0, null);
}
Then, for the end-user, it is just this call:
double average = computeEvenAverageBackward(values);
Here's another variant, which uses a (moderately) well known recurrence relationship for averages:
avg0 = 0
avgn = avgn-1 + (xn - avgn-1) / n
where avgn refers to the average of n observations, and xn is the nth observation.
This leads to:
/*
* a is the array of values to process
* i is the current index under consideration
* n is a counter which is incremented only if the current value gets used
* avg is the running average
*/
private static double getEvenAverage(int[] a, int i, int n, double avg) {
if (i >= a.length) {
return avg;
}
if (a[i] % 2 == 0) { // only do updates for even values
avg += (a[i] - avg) / n; // calculate delta and update the average
n += 1;
}
return getEvenAverage(a, i + 1, n, avg);
}
which can be invoked using the following front-end method to protect users from needing to know about the parameter initialization:
public static double getEvenAverage(int[] a) {
return getEvenAverage(a, 0, 1, 0.0);
}
And now for a completely different approach.
This one draws on the fact that if you have two averages, avg1 based on n1 observations and avg2 based on n2 observations, you can combine them to produce a pooled average:
avgpooled = (n1 * avg1 + n2 * avg2) / (n1 + n2).
The only issue here is that the recursive function should return two values, the average and the number of observations on which that average is based. In many other languages, that's not a problem. In Java, it requires some hackery in the form of a trivial, albeit slightly annoying, helper class:
// private helper class because Java doesn't allow multiple returns
private static class Pair {
public double avg;
public int n;
public Pair(double avg, int n) {
super();
this.avg = avg;
this.n = n;
}
}
Applying a divide and conquer strategy yields the following recursion:
private static Pair getEvenAverage(int[] a, int first, int last) {
if (first == last) {
if (a[first] % 2 == 0) {
return new Pair(a[first], 1);
}
} else {
int mid = (first + last) / 2;
Pair p1 = getEvenAverage(a, first, mid);
Pair p2 = getEvenAverage(a, mid + 1, last);
int total = p1.n + p2.n;
if (total > 0) {
return new Pair((p1.n * p1.avg + p2.n * p2.avg) / total, total);
}
}
return new Pair(0.0, 0);
}
We can deal with empty arrays, protect the end-user from having to know about the book-keeping arguments, and return just the average by using the following public front-end:
public static double getEvenAverage(int[] a) {
return a.length > 0 ? getEvenAverage(a, 0, a.length - 1).avg : 0.0;
}
This solution has the benefit of O(log n) stack growth for an array of n items, versus O(n) for the various other solutions that have been proposed. As a result, it can deal with much larger arrays without fear of a stack overflow.
This is my current search method:
public static int search(int[] array, int numero) {
int start = 0;
int end = array.length - 1;
int center;
while (start <= end) {
center = (start + end) / 2;
if (array[center] == numero) {
return center;
} else if (array[center] < numero) {
start = center + 1;
} else {
end = center - 1;
}
}
return -1;
}
It searches from user input numero into a previously bubble sorted Array that's found in the Main method.
What I'm trying to figure out is how to print ALL of the coincidences found in the array, and not just the first one found.
I was thinking about adding results to a List and then returning that to Main, but as I tried that an endless loop happened at the first result found, causing it to add itself to the List repeatedly until the program crashes.
Assuming that you know the basic theory behind binary searches, separate it into 3 steps.
Search using binary search methods.
once a match is found, scan up from that point, until you find a non matching element.
Scan down, adding to a result list, until you find a non
matching element.
If you don't need to care about occurrence order, you could combine steps 2 and 3 and just scan up adding to the list, and scan down adding to the list, since due to the sorting, everything you hit is guaranteed to match until it doesn't.
If you do care about occurrence order, step 2 could be optimised by jumping ahead and checking, and writing a modified binary search that searches for a transition of matching/notmatching instead of a match.
This could be further optimised by keeping statistics or profiling, to find the perfect jump distance, or basing it off of the last up-most check.
actually it's easy because the list is already sorted, the numbers you expect to find are adjacent.
just like Ryan's answer, I'll put some code
public static List<Integer> searchAll (int[] array, int numero){
int firstMatchIndex = search( array, numero);
List<Integer> results = new ArrayList<Integer>():
results.add(firstMatchIndex);
boolean left = true;
while( left){
int i = firstMatchIndex - 1;
if(i<0 || array[i] != numero){
left = false;
}else{
results.add(i);
}
}
boolean right = true;
while( right){
int i = firstMatchIndex + 1;
if(i>array.length || array[i] != numero){
right = false;
}else{
results.add(i);
}
}
}
I work on a genetic algorithm for a robotic assembly line balancing problem (assigning assembly operations and robots to stations to minimize the cycle time for a given number of stations). The solution is represented by an ArrayList (configuration) which holds all the operations in the sequence assigned to different stations. Furthermore, I have two more ArrayLists (robotAssignment, operationPartition) which indicate where a new station starts and which robot is assigned to a station. For example, a solution candidate looks like this (configuration, robotAssignment, operationPartition from top to bottom):
Initial cycle time: 50.0
|2|7|3|9|1|5|4|6|8|10|
|2|1|3|2|
|0|2|5|7|
From this solution representation we know that operations 3, 9, and 1 are assigned to the second sation and robot 1 is used.
I need to keep track of the station an operation is assigned to. I tried a lot to store this in the Object Operation itself but I always ended up in problems and therefore I want to write a method that gives me the stations index of an operation.
Here is what I have coded so far:
// Get the station of an operation
public int getStation(Operation operation) {
int stationIndex = 0;
int position = configuration.indexOf(operation);
for (int i = 0; i < GA_RALBP.numberOfStations ; i++ ) {
if (i < GA_RALBP.numberOfStations - 1 && operationPartition.get(i) != null) {
if (isBetween(position, (int) operationPartition.get(i), (int) operationPartition.get(i + 1))) {
return stationIndex + 1;
} else {
stationIndex++;
}
}
else if (i >= GA_RALBP.numberOfStations - 1 && operationPartition.get(i) != null) {
if (isBetween(position, (int) operationPartition.get(i), configurationSize())) {
return stationIndex + 1;
}
}
}
return -1;
}
// Check if value x is between values left and right including left
public static boolean isBetween(int x, int left, int right) {
if (left <= x && x < right ) {
return true;
}
else {
return false;
}
}
However, this does not seem to be (a) very elegant and (b) if I have to do this for a large number of operations the runtime could become a problem. Has anoyone an idea how to solve this more efficiently?
Why not make the partitioning explicit (replaces your operationPartition) - something like:
Map<Integer, Integer> operationToStationMapping = new HashMap<>();
operationToStationMapping.put(2,0);
operationToStationMapping.put(7,0);
operationToStationMapping.put(3,2);
operationToStationMapping.put(9,2);
operationToStationMapping.put(1,2);
operationToStationMapping.put(5,5);
operationToStationMapping.put(6,7);
operationToStationMapping.put(8,-1);
operationToStationMapping.put(10,-1);
Then getStation() becomes:
getStation(int operation) {return operationToStationMapping.get(operation);}
I am trying to sort an array via merge sort, and while sorting, remove elements that I have deemed equal. I am recursively calling merge sort and then merging.
I get to this point and find that a and c are duplicates.
a b | c d
I determine which one I want based on certain criteria and I pick c. I increment the right hand counter and and the left hand counter and compare b and d. Say I pick d, then I pick b. I want my final list to only have the elements
c d b
However, what is happening is on the next recursive call, start and end are 0 and 3 so d is listed twice in the array on the next call. The array that the merge procedure works with is:
c d b d
Here is the code. Thanks in advance.
private static void merge(int[] data, int start, int mid, int end)
{
int firstCopied=0;
int secondCopied=0;
int index=0;
int length=end-start+1;
int[] temp = new int[end-start+1];
int firstSize=mid-start+1;
int secondSize=end-mid;
while(firstCopied < firstSize && secondCopied < secondSize)
{
if(data[start+firstCopied] < data[mid+1+secondCopied])
{
temp[index++] = data[start+firstCopied];
firstCopied++;
}
else if(data[start+firstCopied] > data[mid+1+secondCopied])
{
temp[index++] = data[mid+1+secondCopied];
secondCopied++;
}
else if(data[start+firstCopied]==data[mid+1+secondCopied])
{
boolean result = PickOne();
if(result)
{
temp[index++] = data[start+firstCopied];
}
else
{
temp[index++] = data[mid+1+secondCopied];
}
firstCopied++;
secondCopied++;
length--;
}
}
while(firstCopied < firstSize)
{
temp[index++] = data[start+firstCopied];
firstCopied++;
}
while(secondCopied < secondSize)
{
temp[index++] = data[mid+1+secondCopied];
secondCopied++;
}
for(int i=0; i<length; i++)
{
data[start+i]=temp[i];
}
}
The philosophy of the C++ Standard Library is to use algorithms that do one thing well. It's best to follow that approach since it will lead to more reusable code.
E.g. here's a mergesort sketch followed by a call to std::unique
template<typename BiDirIt>
void merge_sort(BiDirIt first, BiDirIt last)
{
auto const N = std::distance(first, last);
if (N < 2) return;
// sort each part individually, then merge back in-place
auto middle = first + N / 2;
merge_sort(first, middle);
merge_sort(middle, last);
std::inplace_merge(first, middle, last);
}
int data[] = { /* your data */ };
merge_sort(std::begin(data), std::end(data));
auto it = std::unique(std::begin(data), std::end(data));
for (auto ut = std::begin(data); ut != it; ++ut) {
// process unique data
}
If your data was in a std::vector instead of a C-array, you could call v.erase(v.begin(), it); to actually erase the non-unique data as well.
Your merge conceptually changes the length of the array. But there is no code to actually truncate data. I suggest you return length (instead of void) and use some final postprocessing step to either truncate the data to the final length, or at least avoid printing those past-the-end elements.
Make sure the elements in [start, mid] and [mid + 1, end] is sorted and unique, first.
Otherwise, duplicates will exists after your code run.