I have the following programm calculating the binomial coefficient of two integers. But I want to change the programm, that it calculates and saves only the necessary coefficients for the solution.
The problem is that I have really no idea how to it, right now.
The Code
public static long binomialIteration(int n, int k)
{
if(k<0 || n<k)
{
return 0;
}
long[][] h= new long[n+1][n+1];
for(int i=0; i<=n; i++)
{
h[i][0]=h[i][i]=1;
}
for(int i=1;i<=n;i++)
{
for(int j=0; j<=i; j++)
{
h[i][j] = (j==0 ? 0: h[i-1][j-1]) + (i == j ? 0 : h[i-1][j]);
}
}
return h[n][k];
}
Do you want to keep your code afterall?
Because you can also compute the binominal coefficient recursively, which would reduce your function to these 4 lines:
static long binomi(int n, int k) {
if ((n == k) || (k == 0))
return 1;
else
return binomi(n - 1, k) + binomi(n - 1, k - 1);
}
What about this Code from this site
private static long binomial(int n, int k)
{
if (k>n-k)
k=n-k;
long b=1;
for (int i=1, m=n; i<=k; i++, m--)
b=b*m/i;
return b;
}
You don't say which coefficients youi need. If you need C(N,n) for some fixed N, you could translate the C code below, which uses a one dimensional array.
After the call, C[n] will hold the binomial coefficient C(N,n) for 0<=m<=N, as long as N is at most 66 -- if you need bigger N you will need to use an integral type with more bits.
static int64_t* pascals_triangle( int N)
{
int n,k;
int64_t* C = calloc( N+1, sizeof *C);
for( n=0; n<=N; ++n)
{ C[n] = 1;
k = n;
while( --k>0)
{ C[k] += C[k-1];
}
}
return C;
}
So I have spent a considerable amount of time struggling to comprehend what is wrong with my code. I have an example program that I compared mine to, which works. My code is structured differently (it's all in one method, as requested by my professor) than the example (which uses two methods). I'm supposed to create a a recursive, divide-and-conquer solution to count inversions in an int array.
I am lost on why the example program maintains the manipulations to the input array throughout the recursion, while mine does not. I know Java is pass-by-value, so I am confused why the example works. Any help with me understanding the differences in these solutions would be greatly appreciated! Thanks!
Example code with two methods - merge and invCounter:
public static long merge(int[] arr, int[] left, int[] right) {
int i = 0, j = 0, count = 0;
while (i < left.length || j < right.length) {
if (i == left.length) {
arr[i+j] = right[j];
j++;
} else if (j == right.length) {
arr[i+j] = left[i];
i++;
} else if (left[i] <= right[j]) {
arr[i+j] = left[i];
i++;
} else {
arr[i+j] = right[j];
count += left.length-i;
j++;
}
}
return count;
}
//the recursive function
public static long invCounter(int[] arr) {
int sum = 0;
if (arr.length < 2)
return 0;
int m = (arr.length + 1) / 2;
int left[] = Arrays.copyOfRange(arr, 0, m);
int right[] = Arrays.copyOfRange(arr, m, arr.length);
sum += invCounter(left);
sum += invCounter(right);
sum += merge(arr, left, right);
return sum;
}
My single-method implementation (attempt):
public static int invCounter(int ranking[]) {
int sum = 0;
int result[] = new int[ranking.length];
int resIndx = 0;
if (ranking.length < 2) {
return 0; //base case
}
//divide
int left[] = Arrays.copyOfRange(ranking, 0, ranking.length/2);
int right[] = Arrays.copyOfRange(ranking, ranking.length/2,
ranking.length);
sum += invCounter(left);
sum += invCounter(right);
int i = 0, j = 0;
while (i < left.length || j < right.length) {
if (i == left.length) {
//i empty, just add j
result[resIndx++] = right[j++];
}
else if (j == right.length) {
//j empty, just add i
result[resIndx++] = left[i++];
}
else if (right[j] < left[i]) {
//inversion
result[resIndx++] = right[j++];
sum += left.length - i;
}
else {
//no inversion
result[resIndx++] = left[i++];
}
}
ranking = Arrays.copyOf(result, result.length);
return sum;
}
Why is the example program able to maintain an updated array through the recursion while mine is not?
UPDATE (10/22/15):
So I discovered that I am able to get the correct results if I replace result with ranking and just modify this array directly. My question now though is why can't I use the result array to temporarily store the results and then copy them into the ranking (argument) array at the end? This seems to me like it would be doing the same exact thing as putting the values in earlier, however the changes to ranking aren't reflected if I change it at the end.
Your method doesn't modify the rankings parameter, instead it creates a new int array (result), and you work on it. Try directly set value on the rankings array, not on result array, or simply set the result variable to the rankings.
public static int invCounter(int ranking[]) {
int sum = 0;
int result[] = ranking;
//other code...
Edit: Or you can copy it's content, but not with Arrays.copyOf, because it first CREATES a new array and then copy into it. Use instead System.arrayCopy which copies into an EXISTING array:
System.arrayCopy(result, 0, rankings, 0, result.length();
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;
}
I'm having trouble figuring out how exactly to make it find the max number and minimum number in the array.
Write a method range that accepts an ArrayList of integers as a parameter and that returns the range of values contained in the list, which is defined as 1 more than the difference between the largest and smallest elements. For example if a variable called list stores the following values:
[18, 14, 29, 12, 7, 25]
The call of range(list) should return 23, because this is one more than the largest difference between any pair of values (29 - 7 + 1 = 23). An empty list is defined to have a range of 0.
So far I have this:
public static int range(ArrayList<Integer> list)
{
int min = 0;
int max = 0;
int range = 0;
for (int i: list)
{
if (list.size() > 0)
{
range = max - min + 1;
}
}
return range;
}
Thank you VERY MUCH!
You have more than method to achive this goal.
Using Collections (more compact but expensive because it iterates two times on the list, one to find the max and one to find the min):
public static int range(final ArrayList<Integer> list) {
if (list.isEmpty()) {
return 0;
} else {
return (Collections.max(list) - Collections.min(list)) + 1;
}
}
Or using your own algorithm like this (more code but finds min and max with just one loop):
public static int range(final ArrayList<Integer> list) {
if (list.isEmpty()) {
return 0;
} else {
int max = list.get(0);
int min = list.get(0);
for (final int i : list) {
if (i > max) {
max = i;
} else if (i < min) {
min = i;
}
}
return (max - min) + 1;
}
}
Why not use Collections.min and Collections.max
int difference = Collections.max(list) - Collections.min(list);
You never calculate the max and the min value in your loop.
Hint : In this loop, find the max and the min value. Then calculate the range and return it.
int min = 0;
int max = 0;
for (int i: list){
//find max and min here
}
return max - min + 1;
This task only needs two lines:
Collections.sort(list);
return list.isEmpty() ? 0 : list.get(list.size() - 1) - list.get(0);
Use the java JDK's API to do the heavy lifting for you
It's how you look at a problem that's important
Less code is good (as long as it's legible
You could sort it and then peek fist and last item.
public static int range(List<Integer> input)
{
if(input == null || input.size() == 0) throw new IllegalArgumentException("");
if(input.size() == 1) return 0;
List<Integer> copy = new ArrayList(input);
Collections.sort(copy);
int min = copy.get(0);
int max = copy.get(copy.lenght-1);
return max - min;
}
This is not a perfect solution as list may contain nulls.
You can start with simple comparison.
int min = Integer.MAX_VALUE;
int max = Integer.MIN_VALUE;
for(Integer integer : input) {
if(i == null) continue;
int i = integer.intValue();
if(i < min) {
min = i;
}
if(i > max) {
max = i;
}
}
return max - min;
public static int range(ArrayList<Integer> list){
int min = list.get(0);
int max = list.get(0);
for (int i = 0; i < list.size(); i++){
if (list.get(i) > max)
max = list.get(i);
if ((list.get(i) < min))
min = list.get(i);
}
return max-min+1;
}
I have another solution that works. Let me explain how it works.
The first if statement checks for the empty list case.
Afterwards, I declared an integer variable int diff to return at the end. Two numbers are selected by the two for loops where the first one starts at index 0 while the nested loop starts at index 1 so that no same numbers are considered when looping through. The difference between two numbers are obtained using the formula declared as int calc. Since we're looking for the biggest difference between two numbers, we set diff = calc and keep it updating.
Lastly, we return diff + 1 as the problem stated.
public int range(ArrayList<Integer> list) {
if (list.size() == 0) {
return 0;
}
int diff = 0;
for (int i = 0; i < list.size(); i++) {
for (int j = 1; j < list.size(); j++) {
int calc = Math.abs(list.get(i) - list.get(j));
if (diff < calc) {
diff = calc;
}
}
}
return diff + 1;
}
I'm having trouble combining these two algorithms together. I've been asked to modify Binary Search to return the index that an element should be inserted into an array. I've been then asked to implement a Binary Insertion Sort that uses my Binary Search to sort an array of randomly generated ints.
My Binary Search works the way it's supposed to, returning the correct index whenever I test it alone. I wrote out Binary Insertion Sort to get a feel for how it works, and got that to work as well. As soon as I combine the two together, it breaks. I know I'm implementing them incorrectly together, but I'm not sure where my problem lays.
Here's what I've got:
public class Assignment3
{
public static void main(String[] args)
{
int[] binary = { 1, 7, 4, 9, 10, 2, 6, 12, 3, 8, 5 };
ModifiedBinaryInsertionSort(binary);
}
static int ModifiedBinarySearch(int[] theArray, int theElement)
{
int leftIndex = 0;
int rightIndex = theArray.length - 1;
int middleIndex = 0;
while(leftIndex <= rightIndex)
{
middleIndex = (leftIndex + rightIndex) / 2;
if (theElement == theArray[middleIndex])
return middleIndex;
else if (theElement < theArray[middleIndex])
rightIndex = middleIndex - 1;
else
leftIndex = middleIndex + 1;
}
return middleIndex - 1;
}
static void ModifiedBinaryInsertionSort(int[] theArray)
{
int i = 0;
int[] returnArray = new int[theArray.length + 1];
for(i = 0; i < theArray.length; i++)
{
returnArray[ModifiedBinarySearch(theArray, theArray[i])] = theArray[i];
}
for(i = 0; i < theArray.length; i++)
{
System.out.print(returnArray[i] + " ");
}
}
}
The return value I get for this when I run it is 1 0 0 0 0 2 0 0 3 5 12. Any suggestions?
UPDATE: updated ModifiedBinaryInsertionSort
static void ModifiedBinaryInsertionSort(int[] theArray)
{
int index = 0;
int element = 0;
int[] returnArray = new int[theArray.length];
for (int i = 1; i < theArray.lenght - 1; i++)
{
element = theArray[i];
index = ModifiedBinarySearch(theArray, 0, i, element);
returnArray[i] = element;
while (index >= 0 && theArray[index] > element)
{
theArray[index + 1] = theArray[index];
index = index - 1;
}
returnArray[index + 1] = element;
}
}
Here is my method to sort an array of integers using binary search.
It modifies the array that is passed as argument.
public static void binaryInsertionSort(int[] a) {
if (a.length < 2)
return;
for (int i = 1; i < a.length; i++) {
int lowIndex = 0;
int highIndex = i;
int b = a[i];
//while loop for binary search
while(lowIndex < highIndex) {
int middle = lowIndex + (highIndex - lowIndex)/2; //avoid int overflow
if (b >= a[middle]) {
lowIndex = middle+1;
}
else {
highIndex = middle;
}
}
//replace elements of array
System.arraycopy(a, lowIndex, a, lowIndex+1, i-lowIndex);
a[lowIndex] = b;
}
}
How an insertion sort works is, it creates a new empty array B and, for each element in the unsorted array A, it binary searches into the section of B that has been built so far (From left to right), shifts all elements to the right of the location in B it choose one right and inserts the element in. So you are building up an at-all-times sorted array in B until it is the full size of B and contains everything in A.
Two things:
One, the binary search should be able to take an int startOfArray and an int endOfArray, and it will only binary search between those two points. This allows you to make it consider only the part of array B that is actually the sorted array.
Two, before inserting, you must move all elements one to the right before inserting into the gap you've made.
I realize this is old, but the answer to the question is that, perhaps a little unintuitively, "Middleindex - 1" will not be your insertion index in all cases.
If you run through a few cases on paper the problem should become apparent.
I have an extension method that solves this problem. To apply it to your situation, you would iterate through the existing list, inserting into an empty starting list.
public static void BinaryInsert<TItem, TKey>(this IList<TItem> list, TItem item, Func<TItem, TKey> sortfFunc)
where TKey : IComparable
{
if (list == null)
throw new ArgumentNullException("list");
int min = 0;
int max = list.Count - 1;
int index = 0;
TKey insertKey = sortfFunc(item);
while (min <= max)
{
index = (max + min) >> 1;
TItem value = list[index];
TKey compKey = sortfFunc(value);
int result = compKey.CompareTo(insertKey);
if (result == 0)
break;
if (result > 0)
max = index - 1;
else
min = index + 1;
}
if (index <= 0)
index = 0;
else if (index >= list.Count)
index = list.Count;
else
if (sortfFunc(list[index]).CompareTo(insertKey) < 0)
++index;
list.Insert(index, item);
}
Dude, I think you have some serious problem with your code. Unfortunately, you are missing the fruit (logic) of this algorithm. Your divine goal here is to get the index first, insertion is a cake walk, but index needs some sweat. Please don't see this algorithm unless you gave your best and desperate for it. Never give up, you already know the logic, your goal is to find it in you. Please let me know for any mistakes, discrepancies etc. Happy coding!!
public class Insertion {
private int[] a;
int n;
int c;
public Insertion()
{
a = new int[10];
n=0;
}
int find(int key)
{
int lowerbound = 0;
int upperbound = n-1;
while(true)
{
c = (lowerbound + upperbound)/2;
if(n==0)
return 0;
if(lowerbound>=upperbound)
{
if(a[c]<key)
return c++;
else
return c;
}
if(a[c]>key && a[c-1]<key)
return c;
else if (a[c]<key && a[c+1]>key)
return c++;
else
{
if(a[c]>key)
upperbound = c-1;
else
lowerbound = c+1;
}
}
}
void insert(int key)
{
find(key);
for(int k=n;k>c;k--)
{
a[k]=a[k-1];
}
a[c]=key;
n++;
}
void display()
{
for(int i=0;i<10;i++)
{
System.out.println(a[i]);
}
}
public static void main(String[] args)
{
Insertion i=new Insertion();
i.insert(56);
i.insert(1);
i.insert(78);
i.insert(3);
i.insert(4);
i.insert(200);
i.insert(6);
i.insert(7);
i.insert(1000);
i.insert(9);
i.display();
}
}