GaussJordan elimination Algorithm Java - java

I have some trouble with my Gauss Jordan elimination method. It looks a bit oversimplified but on paper it should work. It sets the pivot to 1 considering that in case of 0 it must perform a swap. Then it subtracts that row times the value conindex of the remaing rows with the same index number of the pivot column.
I use these methods in my final algorithm.
Row multiplication:
public static double[] rowMul(double[] row, double scalar) {
BigDecimal[] temp = new BigDecimal[row.length];
BigDecimal s = new BigDecimal(scalar);
double[] newrow = new double[row.length];
for (int i = 0; i < row.length; i++) {
temp[i] = new BigDecimal(row[i]).multiply(s);
newrow[i] = temp[i].doubleValue();
}
return newrow;
}
Dividing rows:
public static double[] rowDiv(double[] row, double divisor) {
BigDecimal[] temp = new BigDecimal[row.length];
BigDecimal s = new BigDecimal(divisor);
double[] newrow = new double[row.length];
for (int i = 0; i < row.length; i++) {
temp[i] = new BigDecimal(row[i]).divide(s);
newrow[i] = temp[i].doubleValue();
}
return newrow;
}
Row subtraction:
public static double[] subtractRow(double[] mat1, double[] mat2) {
double[] c = new double[mat1.length];
for (int i = 0; i < mat1.length; i++) {
c[i] = mat1[i] - mat2[i];
}
return c;
}
Pivot check and row swap:
public static boolean checkPivot(double[][] mat, int row) {
if (mat[row][row] == 0) {
return true;
} else {
return false;
}
}
// Keeps track of the number of swaps performed to secure a finite solution.
private static int swapcount = 0;
// Mind giving the index value. So row starting from 0 up instead of 1!
public static double[][] swapRow(double[][] mat, int row) {
swapcount++;
if (swapcount >= mat.length - row) {
System.out.println("no possible combinations.");
swapcount = 0;
return mat;
}
double[] temp = mat[row];
for (int i = row; i < mat.length - 1; i++) {
mat[i] = mat[i + 1];
}
mat[mat.length - 1] = temp;
if (checkPivot(mat, row) == true) {
mat = swapRow(mat, row);
}
swapcount = 0;
return mat;
}
And then my final Gauss Jordan Algorithm:
public static double[][] gaussJordan(double[][] matrix) {
double[][] mat = matrix;
int m = mat.length;
for (int i = 0; i < m; i++) {
if (checkPivot(mat, i) == true) {
mat = swapRow(mat, i);
}
mat[i] = rowDiv(mat[i], mat[i][i]);
for (int j = 0; j < m; j++) {
if (j == i) {
j++;
} else {
mat[j] = subtractRow(mat[j], rowMul(mat[i], mat[j][i]));
}
}
}
return mat;
}
How ever if I give it this matrix to compute.
private static double[][] elim = {
{-20,-10,10,-10},
{ 0, 10,-5, 10},
{-10, 10,15, 20}
};
It somehow skips the middle column of the square 3 x 3 matrix on the left and returns.
1.0 0.375 0.0 0.625
0.0 1.75 0.0 2.25
0.0 1.5 1.0 2.5
The expected outcome is:
1.0 0.0 0.0 0.14286
0.0 1.0 0.0 1.28571
0.0 0.0 1.0 0.57143
Can somebody help me with finding that what I must have overlooked. I just hope its nothing to obvious! I thank you for your trouble.

mat[j] = subtractRow(mat[j], rowMul(mat[i], mat[j][i]));
seems wrong. With it new value of mat[j][i] is mat[j][i] - (mat[i][i] * mat[j][i]) which is != 0.
I think it should be
mat[j] = subtractRow(mat[j], rowMul(mat[i], mat[j][i] / mat[i][i]));
With it new value of mat[j][i] is mat[j][i] - (mat[i][i] * mat[j][i] / mat[i][i]) which is in fact 0.
Also:
if (mat[row][row] == 0) {
This is risky with doubles. I would advise something like Math.abs(mat[row][row]) < 1e-9
I hope that helps.

Related

Find the max value of the same length nails after hammered

I'm trying to solve this problem:
Given an array of positive integers, and an integer Y, you are allowed to replace at most Y array-elements with lesser values. Your goal is for the array to end up with as large a subset of identical values as possible. Return the size of this largest subset.
The array is originally sorted in increasing order, but you do not need to preserve that property.
So, for example, if the array is [10,20,20,30,30,30,40,40,40] and Y = 3, the result should be 6, because you can get six 30s by replacing the three 40s with 30s. If the array is [20,20,20,40,50,50,50,50] and Y = 2, the result should be 5, because you can get five 20s by replacing two of the 50s with 20s.
Below is my solution with O(nlogn) time complexity. (is that right?) I wonder if I can further optimize this solution?
Thanks in advance.
public class Nails {
public static int Solutions(int[] A, int Y) {
int N = A.length;
TreeMap < Integer, Integer > nailMap = new TreeMap < Integer, Integer > (Collections.reverseOrder());
for (int i = 0; i < N; i++) {
if (!nailMap.containsKey(A[i])) {
nailMap.put(A[i], 1);
} else {
nailMap.put(A[i], nailMap.get(A[i]) + 1);
}
}
List < Integer > nums = nailMap.values().stream().collect(Collectors.toList());
if (nums.size() == 1) {
return nums.get(0);
}
//else
int max = nums.get(0);
int longer = 0;
for (int j = 0; j < nums.size(); j++) {
int count = 0;
if (Y < longer) {
count = Y + nums.get(j);
} else {
count = longer + nums.get(j);
}
if (max < count) {
max = count;
}
longer += nums.get(j);
}
return max;
}
public static void main(String[] args) {
Scanner scanner = new Scanner(System.in);
while (scanner.hasNext()) {
String[] input = scanner.nextLine().replaceAll("\\[|\\]", "").split(",");
System.out.println(Arrays.toString(input));
int[] A = new int[input.length - 1];
int Y = Integer.parseInt(input[input.length - 1]);
for (int i = 0; i < input.length; i++) {
if (i < input.length - 1) {
A[i] = Integer.parseInt(input[i]);
} else {
break;
}
}
int result = Solutions(A, Y);
System.out.println(result);
}
}
}
A C++ implementation would like the following where A is the sorted pin size array and K is the number of times the pins can be hammered.
{1,1,3,3,4,4,4,5,5}, K=2 should give 5 as the answer
{1,1,3,3,4,4,4,5,5,6,6,6,6,6,6}, K=2 should give 6 as the answer
int maxCount(vector<int>& A, int K) {
int n = A.size();
int best = 0;
int count = 1;
for (int i = 0; i < n-K-1; i++) {
if (A[i] == A[i + 1])
count = count + 1;
else
count = 1;
if (count > best)
best = count;
}
int result = max(best+K, min(K+1, n));
return result;
}
Since the array is sorted to begin with, a reasonably straightforward O(n) solution is, for each distinct value, to count how many elements have that value (by iteration) and how many elements have a greater value (by subtraction).
public static int doIt(final int[] array, final int y) {
int best = 0;
int start = 0;
while (start < array.length) {
int end = start;
while (end < array.length && array[end] == array[start]) {
++end;
}
// array[start .. (end-1)] is now the subarray consisting of a
// single value repeated (end-start) times.
best = Math.max(best, end - start + Math.min(y, array.length - end));
start = end; // skip to the next distinct value
}
assert best >= Math.min(y + 1, array.length); // sanity-check
return best;
}
First, iterate through all the nails and create a hash H that stores the number of nails for each size. For [1,2,2,3,3,3,4,4,4], H should be:
size count
1 : 1
2 : 2
3 : 3
4 : 3
Now create an little algorithm to evaluate the maximum sum for each size S, given Y:
BestForSize(S, Y){
total = H[S]
while(Y > 0){
S++
if(Y >= H[S] and S < biggestNailSize){
total += H[S]
Y -= H[S]
}
else{
total += Y
Y = 0
}
}
return total;
}
Your answer should be max(BestForSize(0, Y), BestForSize(1, Y), ..., BestForSize(maxSizeOfNail, Y)).
The complexity is O(n²). A tip to optimize is to start from the end. For example, after you have the maximum value of nails in the size 4, how can you use your answer to find the maximum number of size 3?
Here is my java implementation: First I build a reversed map of each integer and its occurence for example {1,1,1,1,3,3,4,4,5,5} would give {5=2, 4=2, 3=2, 1=4}, then for each integer I calculate the max occurence that we can get of it regarding the K and the occurences of the highest integers in the array.
public static int ourFunction(final int[] A, final int K) {
int length = A.length;
int a = 0;
int result = 0;
int b = 0;
int previousValue = 0;
TreeMap < Integer, Integer > ourMap = new TreeMap < Integer, Integer > (Collections.reverseOrder());
for (int i = 0; i < length; i++) {
if (!ourMap.containsKey(A[i])) {
ourMap.put(A[i], 1);
} else {
ourMap.put(A[i], ourMap.get(A[i]) + 1);
}
}
for (Map.Entry<Integer, Integer> entry : ourMap.entrySet()) {
if( a == 0) {
a++;
result = entry.getValue();
previousValue = entry.getValue();
} else {
if( K < previousValue)
b = K;
else
b = previousValue;
if ( b + entry.getValue() > result )
result = b + entry.getValue();
previousValue += entry.getValue();
}
}
return result;
}
Since the array is sorted, we can have an O(n) solution by iterating and checking if current element is equals to previous element and keeping track of the max length.
static int findMax(int []a,int y) {
int n = a.length,current = 1,max = 0,diff = 0;
for(int i = 1; i< n; i++) {
if(a[i] == a[i-1]) {
current++;
diff = Math.min(y, n-i-1);
max = Math.max(max, current+diff);
}else {
current = 1;
}
}
return max;
}
given int array is not sorted than you should sort
public static int findMax(int []A,int K) {
int current = 1,max = 0,diff = 0;
List<Integer> sorted=Arrays.stream(A).sorted().boxed().collect(Collectors.toList());
for(int i = 1; i< sorted.size(); i++) {
if(sorted.get(i).equals(sorted.get(i-1))) {
current++;
diff = Math.min(K, sorted.size()-i-1);
max = Math.max(max, current+diff);
}else {
current = 1;
}
}
return max;
}
public static void main(String args[]) {
List<Integer> A = Arrays.asList(3,1,5,3,4,4,3,3,5,5,5,1);
int[] Al = A.stream().mapToInt(Integer::intValue).toArray();
int result=findMax(Al, 5);
System.out.println(result);
}

How to DFS a 2D array to record paths from leftmost column to rightmost column?

Here I want to use DFS to traverse in a 2D array from leftmost column to rightmost column, each element can go to its upper right element or right element or lower right element. I need to record each possible path. For example, here I have:
1 2 3
4 5 6
7 8 9
Then the possible paths will be 123, 126, 153, 156, 159, 423, 426, 453, 456, 459, 486, 489, 753, 756, 759, 786, 789
Now my idea is straightforward backtrack:
public int findSolution(int[][] array) {
List<List<Integer>> availablePaths = new ArrayList<List<Integer>>();
for (int i = 0; i < array.length; i++) {
List<Integer> tempList = new ArrayList<Integer>();
dfs(array, availablePaths, tempList, 0, i);
}
int res = 0;
int min = Integer.MAX_VALUE;
for (List<Integer> path : availablePaths) {
min = Integer.MAX_VALUE;
for (Integer cur : path) {
if (cur < min) {
min = cur;
}
}
if (min > res) {
res = min;
}
}
return res;
}
public void dfs(int[][] array, List<List<Integer>> availablePaths, List<Integer> tempList, int curCol, int curRow) {
if (tempList.size() == array[0].length) {
availablePaths.add(new ArrayList<Integer>(tempList));
return;
}
tempList.add(array[curRow][curCol]);
int startRow;
int endRow;
// Next Column
if (curRow == 0) {
startRow = 0;
endRow = curRow+1;
} else if (curRow == array.length-1) {
startRow = curRow - 1;
endRow = curRow;
} else {
startRow = curRow - 1;
endRow = curRow + 1;
}
for (int i = startRow; i <= endRow; i++) {
dfs(array, availablePaths, tempList, curCol + 1, i);
tempList.remove(tempList.size()-1);
}
}
However, this can not work because of ArrayIndexOutOfBoundsException, so I guess my code has wrong idea.
Could someone give a solution to solve this problem?
The following DFS implementation solves your problem. I added your example as a test case as well.Basically, we start a new dfs on each cell on the first column. In each dfs call, as long as the current cell is in bound, we add it to the current path in a list. If the current cell is already the last column, add the path stored in the list to the final result.
The dx, dy arrays are a concise way of implementing the 3 possible moves.
import java.util.ArrayList;
import java.util.List;
public class Solution {
private static int[] dx = {-1,0,1}, dy = {1,1,1};
public static List<List<Integer>> dfsForAllPaths(int[][] grid) {
List<List<Integer>> res = new ArrayList<>();
if(grid == null) {
return res;
}
for(int i = 0; i < grid[0].length; i++) {
dfsHelper(grid, i, 0, res, new ArrayList<>());
}
return res;
}
private static void dfsHelper(int[][] grid, int x, int y, List<List<Integer>> res, List<Integer> list) {
if(!isInBound(grid, x, y)) {
return;
}
list.add(grid[x][y]);
if(y == grid[0].length - 1) {
res.add(new ArrayList<>(list));
}
for(int dir = 0; dir < 3; dir++) {
int newX = x + dx[dir], newY = y + dy[dir];
dfsHelper(grid, newX, newY, res, list);
}
list.remove(list.size() - 1);
}
private static boolean isInBound(int[][] grid, int x, int y) {
return x >= 0 && x < grid.length && y >= 0 && y < grid[0].length;
}
public static void main(String[] args) {
int[][] grid = {{1,2,3},{4,5,6},{7,8,9}};
List<List<Integer>> res = dfsForAllPaths(grid);
for(int i = 0; i < res.size(); i++) {
System.out.println(res.get(i));
}
}
}

Returning the index of the n-th highest value of an unsorted list

I have written the following code and am now trying to figure out the best way to achieve what is explained in the four comments:
Integer[] expectedValues = new Integer[4];
for (int i = 0; i <= 3; i++) {
expectedValues[i] = getExpectedValue(i);
}
int choice = randomNumGenerator.nextInt(100) + 1;
if (choice <= intelligence) {
// return index of highest value in expectedValues
} else if (choice <= intelligence * 2) {
// return index of 2nd highest value in expectedValues
} else if (choice <= intelligence * 3) {
// return index of 3rd highest value in expectedValues
} else {
// return index of lowest value in expectedValues
}
What would be an elegant way o doing so? I do not need to keep expected values as an array - I am happy to use any data structure.
You could create a new array containing the indices and sort on the values - in semi-pseudo code it could look like this (to be adapted):
int[][] valueAndIndex = new int[n][2];
//fill array:
valueAndIndex[i][0] = i;
valueAndIndex[i][1] = expectedValues[i];
//sort on values in descending order
Arrays.sort(valueAndIndex, (a, b) -> Integer.compare(b[1], a[1]));
//find n-th index
int n = 3; //3rd largest number
int index = valueAndIndex[n - 1][0];
If you want to work with simple arrays, maybe this might be a solution:
public static void main(String[] args) {
int[] arr = new int[] { 1, 4, 2, 3 };
int[] sorted = sortedCopy(arr);
int choice = randomNumGenerator.nextInt(100) + 1;
if (choice <= intelligence) {
System.out.println(findIndex(arr, sorted[3])); // 1
} else if (choice <= intelligence * 2) {
System.out.println(findIndex(arr, sorted[2])); // 3
} else if (choice <= intelligence * 3) {
System.out.println(findIndex(arr, sorted[1])); // 2
} else {
System.out.println(findIndex(arr, sorted[0])); // 0
}
}
static int[] sortedCopy(int[] arr) {
int[] copy = new int[arr.length];
System.arraycopy(arr, 0, copy, 0, arr.length);
Arrays.sort(copy);
return copy;
}
static int findIndex(int[] arr, int val) {
int index = -1;
for (int i = 0; i < arr.length; ++i) {
if (arr[i] == val) {
index = i;
break;
}
}
return index;
}
You can "wipe out" the highest value n-1 times. After this the highest value is the n-th highest value of the original array:
public static void main(String[] args) {
int[] numbers = new int[]{5, 9, 1, 4};
int n = 2; // n-th index
for (int i = 0; i < n - 1; ++i) {
int maxIndex = findMaxIndex(numbers);
numbers[maxIndex] = Integer.MIN_VALUE;
}
int maxIndex = findMaxIndex(numbers);
System.out.println(maxIndex + " -> " + numbers[maxIndex]);
}
public static int findMaxIndex(int[] numbers) {
int maxIndex = 0;
for (int j = 1; j < numbers.length; ++j) {
if (numbers[j] > numbers[maxIndex]) {
maxIndex = j;
}
}
return maxIndex;
}
The complexity is O(n * numbers.length).

java codility Frog-River-One

I have been trying to solve a Java exercise on a Codility web page.
Below is the link to the mentioned exercise and my solution.
https://codility.com/demo/results/demoH5GMV3-PV8
Can anyone tell what can I correct in my code in order to improve the score?
Just in case here is the task description:
A small frog wants to get to the other side of a river. The frog is currently located at position 0, and wants to get to position X. Leaves fall from a tree onto the surface of the river.
You are given a non-empty zero-indexed array A consisting of N integers representing the falling leaves. A[K] represents the position where one leaf falls at time K, measured in minutes.
The goal is to find the earliest time when the frog can jump to the other side of the river. The frog can cross only when leaves appear at every position across the river from 1 to X.
For example, you are given integer X = 5 and array A such that:
A[0] = 1
A[1] = 3
A[2] = 1
A[3] = 4
A[4] = 2
A[5] = 3
A[6] = 5
A[7] = 4
In minute 6, a leaf falls into position 5. This is the earliest time when leaves appear in every position across the river.
Write a function:
class Solution { public int solution(int X, int[] A); }
that, given a non-empty zero-indexed array A consisting of N integers and integer X, returns the earliest time when the frog can jump to the other side of the river.
If the frog is never able to jump to the other side of the river, the function should return −1.
For example, given X = 5 and array A such that:
A[0] = 1
A[1] = 3
A[2] = 1
A[3] = 4
A[4] = 2
A[5] = 3
A[6] = 5
A[7] = 4
the function should return 6, as explained above. Assume that:
N and X are integers within the range [1..100,000];
each element of array A is an integer within the range [1..X].
Complexity:
expected worst-case time complexity is O(N);
expected worst-case space complexity is O(X), beyond input storage (not counting the storage required for input arguments).
Elements of input arrays can be modified.
And here is my solution:
import java.util.ArrayList;
import java.util.List;
class Solution {
public int solution(int X, int[] A) {
int list[] = A;
int sum = 0;
int searchedValue = X;
List<Integer> arrayList = new ArrayList<Integer>();
for (int iii = 0; iii < list.length; iii++) {
if (list[iii] <= searchedValue && !arrayList.contains(list[iii])) {
sum += list[iii];
arrayList.add(list[iii]);
}
if (list[iii] == searchedValue) {
if (sum == searchedValue * (searchedValue + 1) / 2) {
return iii;
}
}
}
return -1;
}
}
You are using arrayList.contains inside a loop, which will traverse the whole list unnecessarily.
Here is my solution (I wrote it some time ago, but I believe it scores 100/100):
public int frog(int X, int[] A) {
int steps = X;
boolean[] bitmap = new boolean[steps+1];
for(int i = 0; i < A.length; i++){
if(!bitmap[A[i]]){
bitmap[A[i]] = true;
steps--;
if(steps == 0) return i;
}
}
return -1;
}
Here is my solution. It got me 100/100:
public int solution(int X, int[] A)
{
int[] B = A.Distinct().ToArray();
return (B.Length != X) ? -1 : Array.IndexOf<int>(A, B[B.Length - 1]);
}
100/100
public static int solution (int X, int[] A){
int[]counter = new int[X+1];
int ans = -1;
int x = 0;
for (int i=0; i<A.length; i++){
if (counter[A[i]] == 0){
counter[A[i]] = A[i];
x += 1;
if (x == X){
return i;
}
}
}
return ans;
}
A Java solution using Sets (Collections Framework) Got a 100%
import java.util.Set;
import java.util.TreeSet;
public class Froggy {
public static int solution(int X, int[] A){
int steps=-1;
Set<Integer> values = new TreeSet<Integer>();
for(int i=0; i<A.length;i++){
if(A[i]<=X){
values.add(A[i]);
}
if(values.size()==X){
steps=i;
break;
}
}
return steps;
}
Better approach would be to use Set, because it only adds unique values to the list. Just add values to the Set and decrement X every time a new value is added, (Set#add() returns true if value is added, false otherwise);
have a look,
public static int solution(int X, int[] A) {
Set<Integer> values = new HashSet<Integer>();
for (int i = 0; i < A.length; i++) {
if (values.add(A[i])) X--;
if (X == 0) return i;
}
return -1;
}
do not forget to import,
import java.util.HashSet;
import java.util.Set;
Here's my solution, scored 100/100:
import java.util.HashSet;
class Solution {
public int solution(int X, int[] A) {
HashSet<Integer> hset = new HashSet<Integer>();
for (int i = 0 ; i < A.length; i++) {
if (A[i] <= X)
hset.add(A[i]);
if (hset.size() == X)
return i;
}
return -1;
}
}
Simple solution 100%
public int solution(final int X, final int[] A) {
Set<Integer> emptyPosition = new HashSet<Integer>();
for (int i = 1; i <= X; i++) {
emptyPosition.add(i);
}
// Once all the numbers are covered for position, that would be the
// moment when the frog will jump
for (int i = 0; i < A.length; i++) {
emptyPosition.remove(A[i]);
if (emptyPosition.size() == 0) {
return i;
}
}
return -1;
}
Here's my solution.
It isn't perfect, but it's good enough to score 100/100.
(I think that it shouldn't have passed a test with a big A and small X)
Anyway, it fills a new counter array with each leaf that falls
counter has the size of X because I don't care for leafs that fall farther than X, therefore the try-catch block.
AFTER X leafs fell (because it's the minimum amount of leafs) I begin checking whether I have a complete way - I'm checking that every int in count is greater than 0.
If so, I return i, else I break and try again.
public static int solution(int X, int[] A){
int[] count = new int[X];
for (int i = 0; i < A.length; i++){
try{
count[A[i]-1]++;
} catch (ArrayIndexOutOfBoundsException e){ }
if (i >= X - 1){
for (int j = 0; j< count.length; j++){
if (count[j] == 0){
break;
}
if (j == count.length - 1){
return i;
}
}
}
}
return -1;
}
Here's my solution with 100 / 100.
public int solution(int X, int[] A) {
int len = A.length;
if (X > len) {
return -1;
}
int[] isFilled = new int[X];
int jumped = 0;
Arrays.fill(isFilled, 0);
for (int i = 0; i < len; i++) {
int x = A[i];
if (x <= X) {
if (isFilled[x - 1] == 0) {
isFilled[x - 1] = 1;
jumped += 1;
if (jumped == X) {
return i;
}
}
}
}
return -1;
}
Here's what I have in C#. It can probably still be refactored.
We throw away numbers greater than X, which is where we want to stop, and then we add numbers to an array if they haven't already been added.
When the count of the list has reached the expected number, X, then return the result. 100%
var tempArray = new int[X+1];
var totalNumbers = 0;
for (int i = 0; i < A.Length; i++)
{
if (A[i] > X || tempArray.ElementAt(A[i]) != 0)
continue;
tempArray[A[i]] = A[i];
totalNumbers++;
if (totalNumbers == X)
return i;
}
return -1;
below is my solution. I basically created a set which allows uniques only and then go through the array and add every element to set and keep a counter to get the sum of the set and then using the sum formula of consecutive numbers then I got 100% . Note : if you add up the set using java 8 stream api the solution is becoming quadratic and you get %56 .
public static int solution2(int X, int[] A) {
long sum = X * (X + 1) / 2;
Set<Integer> set = new HashSet<Integer>();
int setSum = 0;
for (int i = 0; i < A.length; i++) {
if (set.add(A[i]))
setSum += A[i];
if (setSum == sum) {
return i;
}
}
return -1;
}
My JavaScript solution that got 100 across the board. Since the numbers are assumed to be in the range of the river width, simply storing booleans in a temporary array that can be checked against duplicates will do. Then, once you have amassed as many numbers as the quantity X, you know you have all the leaves necessary to cross.
function solution(X, A) {
covered = 0;
tempArray = [];
for (let i = 0; i < A.length; i++) {
if (!tempArray[A[i]]) {
tempArray[A[i]] = true;
covered++
if(covered === X) return i;
}
}
return -1;
}
Here is my answer in Python:
def solution(X, A):
# write your code in Python 3.6
values = set()
for i in range (len(A)):
if A[i]<=X :
values.add(A[i])
if len(values)==X:
return i
return -1
Just tried this problem as well and here is my solution. Basically, I just declared an array whose size is equal to position X. Then, I declared a counter to monitor if the necessary leaves have fallen at the particular spots. The loop exits when these leaves have been met and if not, returns -1 as instructed.
class Solution {
public int solution(int X, int[] A) {
int size = A.length;
int[] check = new int[X];
int cmp = 0;
int time = -1;
for (int x = 0; x < size; x++) {
int temp = A[x];
if (temp <= X) {
if (check[temp-1] > 0) {
continue;
}
check[temp - 1]++;
cmp++;
}
if ( cmp == X) {
time = x;
break;
}
}
return time;
}
}
It got a 100/100 on the evaluation but I'm not too sure of its performance. I am still a beginner when it comes to programming so if anybody can critique the code, I would be grateful.
Maybe it is not perfect but its straightforward. Just made a counter Array to track the needed "leaves" and verified on each iteration if the path was complete. Got me 100/100 and O(N).
public static int frogRiver(int X, int[] A)
{
int leaves = A.Length;
int[] counter = new int[X + 1];
int stepsAvailForTravel = 0;
for(int i = 0; i < leaves; i++)
{
//we won't get to that leaf anyway so we shouldnt count it,
if (A[i] > X)
{
continue;
}
else
{
//first hit!, keep a count of the available leaves to jump
if (counter[A[i]] == 0)
stepsAvailForTravel++;
counter[A[i]]++;
}
//We did it!!
if (stepsAvailForTravel == X)
{
return i;
}
}
return -1;
}
This is my solution. I think it's very simple. It gets 100/100 on codibility.
set.contains() let me eliminate duplicate position from table.
The result of first loop get us expected sum. In the second loop we get sum of input values.
class Solution {
public int solution(int X, int[] A) {
Set<Integer> set = new HashSet<Integer>();
int sum1 = 0, sum2 = 0;
for (int i = 0; i <= X; i++){
sum1 += i;
}
for (int i = 0; i < A.length; i++){
if (set.contains(A[i])) continue;
set.add(A[i]);
sum2 += A[i];
if (sum1 == sum2) return i;
}
return -1;
}
}
Your algorithm is perfect except below code
Your code returns value only if list[iii] matches with searchedValue.
The algorithm must be corrected in such a way that, it returns the value if sum == n * ( n + 1) / 2.
import java.util.ArrayList;
import java.util.List;
class Solution {
public int solution(int X, int[] A) {
int list[] = A;
int sum = 0;
int searchedValue = X;
int sumV = searchedValue * (searchedValue + 1) / 2;
List<Integer> arrayList = new ArrayList<Integer>();
for (int iii = 0; iii < list.length; iii++) {
if (list[iii] <= searchedValue && !arrayList.contains(list[iii])) {
sum += list[iii];
if (sum == sumV) {
return iii;
}
arrayList.add(list[iii]);
}
}
return -1;
}
}
I think you need to check the performance as well. I just ensured the output only
This solution I've posted today gave 100% on codility, but respectivly #rafalio 's answer it requires K times less memory
public class Solution {
private static final int ARRAY_SIZE_LOWER = 1;
private static final int ARRAY_SIZE_UPPER = 100000;
private static final int NUMBER_LOWER = ARRAY_SIZE_LOWER;
private static final int NUMBER_UPPER = ARRAY_SIZE_UPPER;
public static class Set {
final long[] buckets;
public Set(int size) {
this.buckets = new long[(size % 64 == 0 ? (size/64) : (size/64) + 1)];
}
/**
* number should be greater than zero
* #param number
*/
public void put(int number) {
buckets[getBucketindex(number)] |= getFlag(number);
}
public boolean contains(int number) {
long flag = getFlag(number);
// check if flag is stored
return (buckets[getBucketindex(number)] & flag) == flag;
}
private int getBucketindex(int number) {
if (number <= 64) {
return 0;
} else if (number <= 128) {
return 1;
} else if (number <= 192) {
return 2;
} else if (number <= 256) {
return 3;
} else if (number <= 320) {
return 4;
} else if (number <= 384) {
return 5;
} else
return (number % 64 == 0 ? (number/64) : (number/64) + 1) - 1;
}
private long getFlag(int number) {
if (number <= 64) {
return 1L << number;
} else
return 1L << (number % 64);
}
}
public static final int solution(final int X, final int[] A) {
if (A.length < ARRAY_SIZE_LOWER || A.length > ARRAY_SIZE_UPPER) {
throw new RuntimeException("Array size out of bounds");
}
Set set = new Set(X);
int ai;
int counter = X;
final int NUMBER_REAL_UPPER = min(NUMBER_UPPER, X);
for (int i = 0 ; i < A.length; i++) {
if ((ai = A[i]) < NUMBER_LOWER || ai > NUMBER_REAL_UPPER) {
throw new RuntimeException("Number out of bounds");
} else if (ai <= X && !set.contains(ai)) {
counter--;
if (counter == 0) {
return i;
}
set.put(ai);
}
}
return -1;
}
private static int min(int x, int y) {
return (x < y ? x : y);
}
}
This is my solution it got me 100/100 and O(N).
public int solution(int X, int[] A) {
Map<Integer, Integer> leaves = new HashMap<>();
for (int i = A.length - 1; i >= 0 ; i--)
{
leaves.put(A[i] - 1, i);
}
return leaves.size() != X ? -1 : Collections.max(leaves.values());
}
This is my solution
public func FrogRiverOne(_ X : Int, _ A : inout [Int]) -> Int {
var B = [Int](repeating: 0, count: X+1)
for i in 0..<A.count {
if B[A[i]] == 0 {
B[A[i]] = i+1
}
}
var time = 0
for i in 1...X {
if( B[i] == 0 ) {
return -1
} else {
time = max(time, B[i])
}
}
return time-1
}
A = [1,2,1,4,2,3,5,4]
print("FrogRiverOne: ", FrogRiverOne(5, &A))
Actually I re-wrote this exercise without seeing my last answer and came up with another solution 100/100 and O(N).
public int solution(int X, int[] A) {
Set<Integer> leaves = new HashSet<>();
for(int i=0; i < A.length; i++) {
leaves.add(A[i]);
if (leaves.contains(X) && leaves.size() == X) return i;
}
return -1;
}
I like this one better because it is even simpler.
This one works good on codality 100% out of 100%. It's very similar to the marker array above but uses a map:
public int solution(int X, int[] A) {
int index = -1;
Map<Integer, Integer> map = new HashMap();
for (int i = 0; i < A.length; i++) {
if (!map.containsKey(A[i])) {
map.put(A[i], A[i]);
X--;
if (X == 0) {index = i;break;}
}
}
return index;
}
%100 with js
function solution(X, A) {
let leafSet = new Set();
for (let i = 0; i < A.length; i += 1) {
if(A[i] <= 0)
continue;
if (A[i] <= X )
leafSet.add(A[i]);
if (leafSet.size == X)
return i;
}
return -1;
}
With JavaScript following solution got 100/100.
Detected time complexity: O(N)
function solution(X, A) {
let leaves = new Set();
for (let i = 0; i < A.length; i++) {
if (A[i] <= X) {
leaves.add(A[i])
if (leaves.size == X) {
return i;
}
}
}
return -1;
}
100% Solution using Javascript.
function solution(X, A) {
if (A.length === 0) return -1
if (A.length < X) return -1
let steps = X
const leaves = {}
for (let i = 0; i < A.length; i++) {
if (!leaves[A[i]]) {
leaves[A[i]] = true
steps--
}
if (steps === 0) {
return i
}
}
return -1
}
C# Solution with 100% score:
using System;
using System.Collections.Generic;
class Solution {
public int solution(int X, int[] A) {
// go through the array
// fill a hashset, until the size of hashset is X
var set = new HashSet<int>();
int i = 0;
foreach (var a in A)
{
if (a <= X)
{
set.Add(a);
}
if (set.Count == X)
{
return i;
}
i++;
}
return -1;
}
}
https://app.codility.com/demo/results/trainingXE7QFJ-TZ7/
I have a very simple solution (100% / 100%) using HashSet. Lots of people check unnecessarily whether the Value is less than or equal to X. This task cannot be otherwise.
public static int solution(int X, int[] A) {
Set<Integer> availableFields = new HashSet<>();
for (int i = 0; i < A.length; i++) {
availableFields.add(A[i]);
if (availableFields.size() == X){
return i;
}
}
return -1;
}
public static int solutions(int X, int[] A) {
Set<Integer> values = new HashSet<Integer>();
for (int i = 0; i < A.length; i++) {
if (values.add(A[i])) {
X--;
}
if (X == 0) {
return i;
}
}
return -1;
}
This is my solution. It uses 3 loops but is constant time and gets 100/100 on codibility.
class FrogLeap
{
internal int solution(int X, int[] A)
{
int result = -1;
long max = -1;
var B = new int[X + 1];
//initialize all entries in B array with -1
for (int i = 0; i <= X; i++)
{
B[i] = -1;
}
//Go through A and update B with the location where that value appeared
for (int i = 0; i < A.Length; i++)
{
if( B[A[i]] ==-1)//only update if still -1
B[A[i]] = i;
}
//start from 1 because 0 is not valid
for (int i = 1; i <= X; i++)
{
if (B[i] == -1)
return -1;
//The maxValue here is the earliest time we can jump over
if (max < B[i])
max = B[i];
}
result = (int)max;
return result;
}
}
Short and sweet C++ code. Gets perfect 100%... Drum roll ...
#include <set>
int solution(int X, vector<int> &A) {
set<int> final;
for(unsigned int i =0; i< A.size(); i++){
final.insert(A[i]);
if(final.size() == X) return i;
}
return -1;
}

MedianCalc() method give me IndexOutOfBounds Exception

I have this method to get the median value,
public double getMedian(double[] numberList) {
int factor = numberList.length;
double[] first = new double[(int) factor / 2];
double[] last = new double[first.length];
double[] middleNumbers = new double[1];
for (int i = 0; i < first.length; i++) {
first[i] = numberList[i];
}
for (int i = numberList.length; i >= last.length; i--) {
last[i] = numberList[i];
}
for (int i = 0; i <= numberList.length; i++) {
if (numberList[i] != first[i] || numberList[i] != last[i])
middleNumbers[i] = numberList[i];
}
if (numberList.length % 2 == 0) {
double total = middleNumbers[0] + middleNumbers[1];
return total / 2;
} else {
return middleNumbers[0];
}
}
but give me an IndexOutOfBounds Exception.
Could someone help me to fix the error?
You should be using i < numberList.length, not i <= numberList.length; the legal indexes of an array are [0, array.length-1], i.e. array.length is not a legal index
Simplified Answer
If you only want the median value, simply use your if-else on numberList, there is no need for any sub-arrays:
public double getMedian(double[] numberList) {
int middle = numberList.length / 2;
if (numberList.length % 2 == 0) {
double total = numberList[middle - 1] + numberList[middle]
return total / 2;
} else {
return numberList[middle];
}
}
Original Answer
As I stated under Zim-Zam's answer, this loop doesn't use the correct indices either:
for (int i = numberList.length; i >= last.length; i--) {
last[i] = numberList[i];
}
last can only have 0 through numberList.length / 2 (rounded down).
It looks like you want two split numberList into first and last, simply use:
int[] first = Arrays.copyOfRange(numberList, 0, factor);
int[] last = Arrays.copyOfRange(numberList, factor, numberList.length);
Instead of your for-loops.

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