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Sorting Neighborhoods by Population Using Heap

I am trying to sort the neighborhoods by their populations. I used heap sorting algorithm in C#. I created an Array which keeps the population of the neighborhoods named "arr". And created an array which keeps the name of the hoods . It works good but how can I get output of sorting with name of the neighborhoods?
My code is here:
using System;
using System.Collections.Generic;
using System.Collections.ObjectModel;
namespace HoodSorting
{
public class example
{
static void heapSort(int[] arr, int n)
{
for (int i = n / 2 - 1; i >= 0; i--)
heapify(arr, n, i);
for (int i = n - 1; i >= 0; i--)
{
int temp = arr[0];
arr[0] = arr[i];
arr[i] = temp;
heapify(arr, i, 0);
}
}
static void heapify(int[] arr, int n, int i)
{
int largest = i;
int left = 2 * i + 1;
int right = 2 * i + 2;
if (left < n && arr[left] > arr[largest])
largest = left;
if (right < n && arr[right] > arr[largest])
largest = right;
if (largest != i)
{
int swap = arr[i];
arr[i] = arr[largest];
arr[largest] = swap;
heapify(arr, n, largest);
}
}
public static void Main()
{// arr REPRESENTS THE POUPLATION OF THE NEIGHBORHOODS
string[] neighborhoods = { "Bornova" ,"Westriver","Paradise","Goodman","McMountain","Rocker","Summerlin","Northcity","Greenhill","Sevenwaves"};
int[] arr = { 55, 25, 89, 34, 12, 19, 78, 95, 1, 100 };
int n = 10, i;
Console.WriteLine("Heap Sort");
Console.Write("Initial array is: ");
for (i = 0; i < n; i++)
{
Console.Write(arr[i] + " ");
}
heapSort(arr, 10);
Console.Write("\nSorted Array is: ");
for (i = 0; i < n; i++)
{
Console.Write(arr[i] + " ");
}
}
}
}
How can I get output like this:
Sorted Array is: Greenhill, McMountain,....,........, Northcity, Sevenwaves
Thanks a lot for the help

From an OOP perspective you would keep the two properties (name and population of a neighborhood) together in one object. Then when you sort the objects, you'll still have the associated data right there.
There are several ways to do this. For instance, you could create tuples.
Here is how that is applied to your code:
static void heapSort(Tuple<int, string>[] arr)
{
int n = arr.Length;
for (int i = n / 2 - 1; i >= 0; i--)
heapify(arr, n, i);
for (int i = n - 1; i >= 0; i--)
{
(arr[0], arr[i]) = (arr[i], arr[0]);
heapify(arr, i, 0);
}
}
static void heapify(Tuple<int, string>[] arr, int n, int i)
{
int largest = i;
int left = 2 * i + 1;
int right = 2 * i + 2;
if (left < n && arr[left].Item1 > arr[largest].Item1)
largest = left;
if (right < n && arr[right].Item1 > arr[largest].Item1)
largest = right;
if (largest != i)
{
(arr[i], arr[largest]) = (arr[largest], arr[i]);
heapify(arr, n, largest);
}
}
public static void Main()
{
Tuple<int, string>[] arr = {
Tuple.Create(55, "Bornova"),
Tuple.Create(25, "Westriver"),
Tuple.Create(89, "Paradise"),
Tuple.Create(34, "Goodman"),
Tuple.Create(12, "McMountain"),
Tuple.Create(19, "Rocker"),
Tuple.Create(78, "Summerlin"),
Tuple.Create(95, "Northcity"),
Tuple.Create(1, "Greenhill"),
Tuple.Create(100, "Sevenwaves")
};
Console.WriteLine("Initial array is: ");
foreach (var pair in arr)
{
Console.Write(pair.Item2 + " ");
}
Console.WriteLine();
heapSort(arr);
Console.WriteLine("Sorted Array is: ");
foreach (var pair in arr)
{
Console.Write(pair.Item2 + " ");
}
Console.WriteLine();
}

returns the smallest positive integer (greater than 0) that does not occur in Array

I have the following question:-
Write a function:
class Solution { public int solution(int[] A); }
that, given an array A of N integers, returns the smallest positive integer (greater than 0) that does not occur in A.
For example, given A = [1, 3, 6, 4, 1, 2], the function should return 5.
Given A = [1, 2, 3], the function should return 4.
Given A = [−1, −3], the function should return 1.
Write an efficient algorithm for the following assumptions:
N is an integer within the range [1..100,000];
each element of array A is an integer within the range [−1,000,000..1,000,000].
now i tried this code:-
using System;
// you can also use other imports, for example:
// using System.Collections.Generic;
// you can write to stdout for debugging purposes, e.g.
// Console.WriteLine("this is a debug message");
class Solution
{
public int solution(int[] A)
{
// write your code in C# 6.0 with .NET 4.5 (Mono)
int n = 1;
Array.Sort(A);
for (int i = 1; i <= 100000; i++)
{
for (int i2 = 0; i2 <= A.Length - 1; i2++)
{
if (A[i2] == i)
{
n = A[i2] + 1;
break;
}
}
}
return n;
}
}
where my code worked well for these test data:-
A = [1, 2, 3]
A = [−1, −3]
while failed for this one:-
A = [1, 3, 6, 4, 1, 2] where it return 7 instead of 5.
any advice why my code failed on the 3rd test?
Thanks

using System.Linq;
int smallestNumber = Enumerable.Range(1, 100000).Except(A).Min();

I would use following approach that uses a HashSet<int> to check if a given integer is missing:
public static int? SmallestMissing(int[] A, int rangeStart = 1, int rangeEnd = 100_000)
{
HashSet<int> hs = new HashSet<int>(A);
for (int i = rangeStart; i <= rangeEnd; i++)
if(!hs.Contains(i)) return i;
return null;
}
A HashSet is a collection if unique values and it's very efficient in lookup items(complexity is O(1)). So you get a very readable and efficient algorithm at the cost of some memory.
Maybe you could optimize it by providing another algorithm in case the array is very large, you don't want to risk an OutOfMemoryException:
public static int? SmallestMissing(int[] A, int rangeStart = 1, int rangeEnd = 100_000)
{
if(A.Length > 1_000_000)
{
Array.Sort(A);
for (int i = rangeStart; i <= rangeEnd; i++)
{
int index = Array.BinarySearch(A, i);
if(index < 0) return i;
}
return null;
}
HashSet<int> hs = new HashSet<int>(A);
for (int i = rangeStart; i <= rangeEnd; i++)
if(!hs.Contains(i)) return i;
return null;
}

If you're allowed to sort the array in-place, which means modifying the input parameter value, here's a simple linear probe for the missing value (on top of the sort of course).
Here's the pseudo-code:
Sort the array
Skip all negatives and 0's at the start
Loopify the following:
Expect 1, if not found at current location return 1
Skip all 1's
Expect 2, if not found at current location return 2
Skip all 2's
Expect 3, if not found at current location return 3
Skip all 3's
... and so on for 4, 5, 6, etc. until end of array
If we get here, return currently expected value which should've been at the end
Here's the code:
public static int FirstMissingValue(int[] input)
{
Array.Sort(input);
int index = 0;
// Skip negatives
while (index < input.Length && input[index] < 1)
index++;
int expected = 1;
while (index < input.Length)
{
if (input[index] > expected)
return expected;
// Skip number and all duplicates
while (index < input.Length && input[index] == expected)
index++;
expected++;
}
return expected;
}
Test-cases:
Console.WriteLine(FirstMissingValue(new[] { 1, 3, 6, 4, 1, 2 }));
Console.WriteLine(FirstMissingValue(new[] { 1, 2, 3 }));
Console.WriteLine(FirstMissingValue(new[] { -1, -3 }));
output:
5
4
1

Your alg won't work in case input array becomes like this: [1,2-1,1,3,5]. I did this based on your alg. Give it a try:
int[] a = new int[] { -1, -2};
IEnumerable<int> uniqueItems = a.Distinct<int>().Where(x => x > 0);
if (uniqueItems.Count() == 0)
{
Console.WriteLine("result: 1");
}
else
{
Array asList = uniqueItems.ToArray();
Array.Sort(asList);
for (int i = 1; i <= 100000; i++)
{
if ((int)asList.GetValue(i - 1) != i)
{
Console.WriteLine("result: " + i);
break;
}
}
}

you can try like this.
public static int solution(int[] A)
{
int smallest = -1;
Array.Sort(A);
if(A[0] > 1)
return 1;
for(int i = 0; i < A.Length; i++)
{
if(A.Length != i+1 && A[i] + 1 != A[i + 1] && A[i+1] > 0)
{
smallest = A[i]+1;
break;
}
else if(A[i] > 0 && A.Length == i+1)
{
smallest = A[i] + 1;
}
}
return smallest > 0 ? smallest:1;
}

Here's the approach that uses O(N) partitioning followed by an O(N) search. This approach does not use any additional storage, but it DOES change the contents of the array.
This code was converted from here. Also see this article.
I've added comments to try to explain how the second stage findSmallestMissing() works. I've not commented the partitioning method, since that's just a variant of a standard partition as might be used in a QuickSort algorithm.
static class Program
{
public static void Main()
{
Console.WriteLine(FindSmallestMissing(1, 3, 6, 4, 1, 2));
Console.WriteLine(FindSmallestMissing(1, 2, 3));
Console.WriteLine(FindSmallestMissing(-1, -3));
}
public static int FindSmallestMissing(params int[] array)
{
return findSmallestMissing(array, partition(array));
}
// Places all the values > 0 before any values <= 0,
// and returns the index of the first value <= 0.
// The values are unordered.
static int partition(int[] arr)
{
void swap(int x, int y)
{
var temp = arr[x];
arr[x] = arr[y];
arr[y] = temp;
}
int pIndex = 0; // Index of pivot.
for (int i = 0; i < arr.Length; i++)
{
if (arr[i] > 0) // pivot is 0, hence "> 0"
swap(i, pIndex++);
}
return pIndex;
}
// This is the clever bit.
// We will use the +ve values in the array as flags to indicate that the number equal to that index is
// present in the array, by making the value negative if it is found in the array.
// This way we can store both the original number AND whether or not the number equal to that index is present
// in a single value.
//
// Given n numbers that are all > 0, find the smallest missing number as follows:
//
// For each array index i in (0..n):
// val = |arr[i]| - 1; // Subtract 1 so val will be between 0 and max +ve value in original array.
// if (val is in range) // If val beyond the end of the array we can ignore it
// and arr[val] is non-negative // If already negative, no need to make it negative.
// make arr[val] negative
//
// After that stage, we just need to find the first positive number in the array, which indicates that
// the number equal to that index + 1 is missing.
// n = number of values at the start of the array that are > 0
static int findSmallestMissing(int[] arr, int n)
{
for (int i = 0; i < n; i++)
{
int val = Math.Abs(arr[i]) - 1;
if (val < n && arr[val] >= 0)
arr[val] = -arr[val];
}
for (int i = 0; i < n; i++)
{
if (arr[i] > 0) // Missing number found.
return i + 1;
}
return n + 1; // No missing number found.
}
}

class Program
{
static void Main(string[] args)
{
int [] A = new int[] {1, 2, 3};
int n = 0;
bool found = false;
Array.Sort(A);
for (int i = 1; i <= 100000; i++) {
for (int x = 0; x <= A.Length - 1; x++) {
int next = (x + 1) < A.Length ? (x + 1): x;
if (A[x] > 0 && (A[next] - A[x]) > 0) {
n = A[x] + 1;
found = true;
break;
}
}
if(found) {
break;
}
}
Console.WriteLine("Smallest number: " + n);
}
}

int smallestNumber=Enumerable.Range(1,(int.Parse(A.Length.ToString())+1)).Except(A).Min();
Array.Sort(A);
for (int number = 1; number <= 100000; number++)
{
for (int num = number; i2 <= A.Length - 1; num++)
{
if (A[num] == number)
{
smallestNumber = A[num] + 1;
break;
}
}
}
return smallestNumber;
}

The easiest one :)
class Solution
{
public int solution(int[] array)
{
int[] onlyPositiveArray = array.Where(a => a > 0).OrderBy(a => a).Distinct().ToArray();
int smallestNumber = 1;
foreach (var number in onlyPositiveArray)
{
if (smallestNumber != number)
{
break;
}
smallestNumber ++;
}
if (!onlyPositiveArray.Contains(smallestNumber ))
{
return smallestNumber;
}
else
{
return smallestNumber + 1;
}
}
}

PHP Solution:
function solution($A) {
// write your code in PHP7.0
// sort array
sort($A);
// get the first
$smallest = $A[0];
// write while
while( in_array(($smallest),$A) || (($smallest) < 1 ) )
{
$smallest++;
}
return $smallest;
}

My solution, also if someone could test how performant it is?
public int solution(int[] N) {
if (N.Length == 0)
return 1;
else if (N.Length == 1)
return N[0] >= 0 ? N[0] + 1 : 1;
Array.Sort(N);
int min = Array.Find(N, IsUnderZero);
if (min ==
default)
return 1;
HashSet < int > hashSet = new HashSet < int > (N);
int max = N[N.Length - 1];
for (int i = min + 1; i <= max + 1; i++) {
if (!hashSet.Contains(i) && i > 0)
return i;
}
return max + 1;
bool IsUnderZero(int i) => i <= 0;
}

Try the below:
public static int MinIntegerGreaterThanZeroInArray(int[] A)
{
int minInt;
if (A.Length > 0)
{
Array.Sort(A);
for (minInt = 1; minInt <= A.Length; minInt++)
{
int index = Array.BinarySearch(A, minInt);
if (index < 0) return minInt;
}
return minInt;
}
//Array is empty.
throw new InvalidOperationException();
}

public static int Smallest(int[] A)
{
int maxPositiveInt = 1;
HashSet<int> NumDic = new HashSet<int>();
for (int i = 0; i < A.Length; i++)
{
if (A[i] <= 0)
{
continue;
}
if (!NumDic.Contains(A[i]))
{
NumDic.Add(A[i]);
}
maxPositiveInt = Math.Max(A[i], maxPositiveInt);
}
//All numbers are negative
if (NumDic.Count == 0)
{
return 1;
}
int smallestinteger = 1;
for (int i = 0; i < A.Length; i++)
{
if (A[i] <= 0)
{
continue;
}
if (!NumDic.Contains(smallestinteger))
{
return smallestinteger;
}
else
{
smallestinteger++;
}
}
return maxPositiveInt + 1;
}

static void Main(string[] args)
{
Console.WriteLine(solution(new int[]{1, 3, 6, 4, 1, 2}));
}
public static int solution(int[] A)
{
Array.Sort(A);
int smallest = A[0];
while (A.Contains(smallest+1)|| (smallest+1)<1)
{
smallest++;
}
return smallest +1;
}

Divide an array's element by 2 for k times such that array's sum is minimized

I have an array of n integers and I need to divide any of it's elements by 2 (return the ceiling of the result) for k times such that the sum is minimum. The value of k can be very large as compared to n.
I am using this code:
private static int GetMaxSum(int[] array, int k)
{
int n = array.Length;
for (int i = 0; i < k; i++)
{
var indexAtMax = GetMaxIndex(array);
if (array[indexAtMax] == 1) break;
array[indexAtMax] = array[indexAtMax] / 2 + array[indexAtMax] % 2;
}
return array.Sum();
}
private static int GetMaxIndex(int[] array)
{
int maxIndex = 0;
int max = array[0];
for (int i=1; i<array.Length;i++)
{
if (array[i] > max)
{
max = array[i];
maxIndex = i;
}
}
return maxIndex;
}
How can we improve the performance further probably by using max heap or some other data structure?

Unless I'm misunderstanding your requirements, your solution seens way too complicated (and apparently wrong according to comments).
I can't really think this through right now, but wouldn't it be the case that the global solution is made up of optimal intermediate steps? The order in which you divide is irrelevant and the problem is linear.
If that is the case, you simply have to evaluate the optimal division in each step and that is not very hard to do:
static void Minimize(int[] arr, int k)
{
for (var j = 0; j < k; j++)
{
var maxGainIndex = -1;
var maxGain = int.MinValue;
for (var i = 0; i < arr.Length; i++)
{
var gain = arr[i] - (arr[i]/2 + arr[i] % 2);
if (gain > maxGain)
{
maxGain = gain;
maxGainIndex = i;
}
}
arr[maxGainIndex] -= maxGain;
}
}
If I'm not wrong, the asymptotic behavior of this algorithm is O(k·n).
UPDATE:
Based on claims of posted code being far less optimal, I've taken the liberty of benchmarking both algorithms with these results on my machine:
Input array: 100;120;80;55;75;115;125;150;90;35;65;77;89;10;11;113;200;300
Number of divisions: 20
Running benchmarks in Release mode without debugger attached.
1000000 of GetMimimum finished in 584 ms with result 704.
1000000 of GetMimimum2 finished in 8846 ms with result 704.
Benchmarking code can be found here: https://dotnetfiddle.net/ITx53q
The performance gain of my proposed algorithm is rather staggering (x15), which was expected because your solution is, as evaluated initally, overcomplicated at best for such a simple problem.

As the assumption was that k>>n, the simpler algorithms are of the order O(kn) which can be too much of iterations.
I have written this code thinking of the problem and how can I limit sorting or calculating min/max. I have divided the array into subarrays so that the operations can be performed on subarrays without thinking of the order of operations.
private static int GetMinSum(int[] array, int k)
{
int n = array.Length;
var sum = 0;
k = GetOptimizedListAndK(array, n, k, out var lists);
//If more sublists are needed
if (k > 0)
{
var count = lists.CountSum;
var key = lists.Key;
if (key > 0)
{
var poweroftwo = 1 << key;
sum += count * poweroftwo - k * poweroftwo / 2;
var dictionary2 = GetDictionary(array, lists, poweroftwo);
key = dictionary2.Keys.Last();
while (k > 0 && key > 0)
{
var list2 = dictionary2[key];
count = list2.Count;
if (k >= count)
{
list2.ForEach(
index => array[index] = array[index] / 2 + array[index] % 2);
dictionary2.Remove(key);
key = dictionary2.Keys.LastOrDefault();
k -= count;
}
else
{
if (k <= Log2(count))
{
for (int i = 0; i < k; i++)
{
var indexAtMax = GetMaxIndex(list2, array);
array[indexAtMax] = array[indexAtMax] / 2 + array[indexAtMax] % 2;
}
k = 0;
}
if (count - k <= Log2(count))
{
var minIndexes = GetMinIndexes(list2, array, count - k);
foreach (var i in list2)
{
if (!minIndexes.Contains(i))
{
array[i] = array[i] / 2 + array[i] % 2;
}
}
k = 0;
}
if (k > 0)
{
poweroftwo = 1 << key;
sum += list2.Count * poweroftwo - k * poweroftwo / 2;
dictionary2 = GetDictionary(array, list2, poweroftwo);
key = dictionary2.Keys.Last();
}
}
}
}
}
return array.Sum() + sum;
}
private static int GetOptimizedListAndK(int[] array, int n, int k, out Lists lists)
{
lists = null;
Dictionary<int, Lists> dictionary = new Dictionary<int, Lists>();
PopulatePowerBasedDictionary(array, n, dictionary);
var key = dictionary.Keys.Max();
while (key > 0 && k > 0)
{
lists = dictionary[key];
var count = lists.CountSum;
if (k >= count)
{
lists.ForEach(list => list.ForEach(index => array[index] = array[index] / 2 + array[index] % 2));
if (key > 1)
{
if (dictionary.TryGetValue(key - 1, out var lowerlists))
{
lowerlists.AddRange(lists);
lowerlists.CountSum += count;
}
else dictionary.Add((key - 1), lists);
}
dictionary.Remove(key);
key--;
k -= count;
}
else
{
if (k < Log2(count))
{
for (int i = 0; i < k; i++)
{
var indexAtMax = GetMaxIndex(lists, array);
array[indexAtMax] = array[indexAtMax] / 2 + array[indexAtMax] % 2;
}
k = 0;
}
if (count - k < Log2(count))
{
var minIndexes = GetMinIndexes(lists, array, count - k);
foreach (var list in lists)
{
foreach (var i in list)
{
if (!minIndexes.Contains(i))
{
array[i] = array[i] / 2 + array[i] % 2;
}
}
}
k = 0;
}
break;
}
}
return k;
}
private static void PopulatePowerBasedDictionary(int[] array, int n, Dictionary<int, Lists> dictionary)
{
for (int i = 0; i < n; i++)
{
if (array[i] < 2) continue;
var log2 = Log2(array[i]);
if (dictionary.TryGetValue(log2, out var lists))
{
lists[0].Add(i);
lists.CountSum++;
}
else
{
lists = new Lists(1,log2) { new List<int> { i } };
dictionary.Add(log2, lists);
}
}
}
private static int GetMaxIndex(List<int> list, int[] array)
{
var maxIndex = 0;
var max = 0;
foreach (var i in list)
{
if (array[i] > max)
{
maxIndex = i;
max = array[i];
}
}
return maxIndex;
}
private static SortedDictionary<int, List<int>> GetDictionary(int[] array, Lists lists, int poweroftwo)
{
SortedDictionary<int, List<int>> dictionary = new SortedDictionary<int, List<int>>();
foreach (var list in lists)
{
foreach (var i in list)
{
array[i] = array[i] - poweroftwo;
if (array[i] < 2)
{
continue;
}
var log2 = Log2(array[i]);
if (dictionary.TryGetValue(log2, out var list2))
{
list2.Add(i);
}
else
{
list2 = new List<int> { i };
dictionary.Add(log2, list2);
}
}
}
return dictionary;
}
private static SortedDictionary<int, List<int>> GetDictionary(int[] array, List<int> list, int poweroftwo)
{
SortedDictionary<int, List<int>> dictionary = new SortedDictionary<int, List<int>>();
foreach (var i in list)
{
array[i] = array[i] - poweroftwo;
if (array[i] < 2)
{
continue;
}
var log2 = Log2(array[i]);
if (dictionary.TryGetValue(log2, out var list2))
{
list2.Add(i);
}
else
{
list2 = new List<int> { i };
dictionary.Add(log2, list2);
}
}
return dictionary;
}
private static int GetMaxIndex(Lists lists, int[] array)
{
var maxIndex = 0;
var max = 0;
foreach (var list in lists)
{
foreach (var i in list)
{
if (array[i]>max)
{
maxIndex = i;
max = array[i];
}
}
}
return maxIndex;
}
private static HashSet<int> GetMinIndexes(Lists lists, int[] array, int k)
{
var mins = new HashSet<int>();
var minIndex = 0;
var min = int.MaxValue;
for (int j = 0; j < k; j++)
{
foreach (var list in lists)
{
foreach (var i in list)
{
if (array[i] < min && !mins.Contains(i))
{
minIndex = i;
min = array[i];
}
}
}
mins.Add(minIndex);
min = int.MaxValue;
}
return mins;
}
private static HashSet<int> GetMinIndexes(List<int> list, int[] array, int k)
{
var mins = new HashSet<int>();
var minIndex = 0;
var min = int.MaxValue;
for (int j = 0; j < k; j++)
{
foreach (var i in list)
{
if (array[i] < min && !mins.Contains(i))
{
minIndex = i;
min = array[i];
}
}
mins.Add(minIndex);
min = int.MaxValue;
}
return mins;
}
private static int Log2(int n)
{
return BitOperations.Log2((uint)n);
}
Lists Class:
public class Lists:List<List<int>>
{
public int Key { get; set; }
public int CountSum { get; set; }
public Lists(int countSum, int key):base()
{
CountSum = countSum;
Key = key;
}
}

Randomness in Sudoku solving algorithm

I am using this backtracking soduku solving algorithm which is really good and efficient
private void solve()
{
for (var y = 8; y >= 0; y--)
{
for (var x = 8; x >= 0; x--)
{
var a = grid[y, x];
if (a == 0)
{
for (var n = 1; n <= 9; n++)
{
if (possible(y, x, n))
{
grid[y, x] = n;
solve();
grid[y, x] = 0;
}
}
return;
}
}
}
print();
}
The thing is i want to add a little change which I haven't been able to do and it is that instead of trying numbers 1 to 9 in order i want it to choose a random number from 1 to 9, and then set it in the grid, without repetition of course.

public static class MyRandomGenerator
{
private static Random random = new Random();
public static int[] Generate(int inclusiveMinValue, int exclusiveMaxValue)
{
if (exclusiveMaxValue <= inclusiveMinValue)
throw new ArgumentException(nameof(exclusiveMaxValue));
var capacity = exclusiveMaxValue - inclusiveMinValue;
var result = new HashSet<int>(capacity);
while (result.Count < capacity)
{
result.Add(random.Next(inclusiveMinValue, exclusiveMaxValue));
}
return result.ToArray();
}
}

Hackerrank: Climbing the Leaderboard

i have a deal with a hackerrank algorithm problem.
It works at all cases, except 6-7-8-9. It gives timeout error. I had spent so much time at this level. Someone saw where is problem?
static long[] climbingLeaderboard(long[] scores, long[] alice)
{
//long[] ranks = new long[scores.Length];
long[] aliceRanks = new long[alice.Length]; // same length with alice length
long lastPoint = 0;
long lastRank;
for (long i = 0; i < alice.Length; i++)
{
lastPoint = scores[0];
lastRank = 1;
bool isIn = false; // if never drop in if statement
for (long j = 0; j < scores.Length; j++)
{
if (lastPoint != scores[j]) //if score is not same, raise the variable
{
lastPoint = scores[j];
lastRank++;
}
if (alice[i] >= scores[j])
{
aliceRanks[i] = lastRank;
isIn = true;
break;
}
aliceRanks[i] = !isIn & j + 1 == scores.Length ? ++lastRank : aliceRanks[i]; //drop in here
}
}
return aliceRanks;
}

This problem can be solved in O(n) time, no binary search needed at all. First, we need to extract the most useful piece of data given in the problem statement, which is,
The existing leaderboard, scores, is in descending order.
Alice's scores, alice, are in ascending order.
An approach that makes this useful is to create two pointers, one at the start of alice array, let's call it "i", and the second is at the end of scores array, let's call it "j". We then loop until i reaches the end of alice array and at each iteration, we check for three main conditions. We increment i by one if alice[i] is less than scores[j] because the next element of alice may be also less than the current element of scores, or we decrement j if alice[i] is greater than scores[j] because we are sure that the next elements of alice are also greater than those elements discarded in scores. The last condition is that if alice[i] == scores[j], we only increment i.
I solved this question in C++, my goal here is to make you understand the algorithm, I think you can easily convert it to C# if you understand it. If there are any confusions, please tell me. Here is the code:
// Complete the climbingLeaderboard function below.
vector<int> climbingLeaderboard(vector<int> scores, vector<int> alice) {
int j = 1, i = 1;
// this is to remove duplicates from the scores vector
for(i =1; i < scores.size(); i++){
if(scores[i] != scores[i-1]){
scores[j++] = scores[i];
}
}
int size = scores.size();
for(i = 0; i < size-j; i++){
scores.pop_back();
}
vector<int> ranks;
i = 0;
j = scores.size()-1;
while(i < alice.size()){
if(j < 0){
ranks.push_back(1);
i++;
continue;
}
if(alice[i] < scores[j]){
ranks.push_back(j+2);
i++;
} else if(alice[i] > scores[j]){
j--;
} else {
ranks.push_back(j+1);
i++;
}
}
return ranks;
}
I think this may help you too:
vector is like an array list that resizes itself.
push_back() is inserting at the end of the vector.
pop_back() is removing from the end of the vector.

Here is my solution with c#
public static List<int> climbingLeaderboard(List<int> ranked, List<int> player)
{
List<int> result = new List<int>();
ranked = ranked.Distinct().ToList();
var pLength = player.Count;
var rLength = ranked.Count-1;
int j = rLength;
for (int i = 0; i < pLength; i++)
{
for (; j >= 0; j--)
{
if (player[i] == ranked[j])
{
result.Add(j + 1);
break;
}
else if(player[i] < ranked[j])
{
result.Add(j + 2);
break;
}
else if(player[i] > ranked[j]&&j==0)
{
result.Add(1);
break;
}enter code here
}
}
return result;
}

Here is a solution that utilizes BinarySearch. This method returns the index of the searched number in the array, or if the number is not found then it returns a negative number that is the bitwise complement of the index of the next element in the array. Binary search only works in sorted arrays.
public static int[] GetRanks(long[] scores, long[] person)
{
var defaultComparer = Comparer<long>.Default;
var reverseComparer = Comparer<long>.Create((x, y) => -defaultComparer.Compare(x, y));
var distinctOrderedScores = scores.Distinct().OrderBy(i => i, reverseComparer).ToArray();
return person
.Select(i => Array.BinarySearch(distinctOrderedScores, i, reverseComparer))
.Select(pos => (pos >= 0 ? pos : ~pos) + 1)
.ToArray();
}
Usage example:
var scores = new long[] { 100, 100, 50, 40, 40, 20, 10 };
var alice = new long[] { 5, 25, 50, 120 };
var ranks = GetRanks(scores, alice);
Console.WriteLine($"Ranks: {String.Join(", ", ranks)}");
Output:
Ranks: 6, 4, 2, 1

I was bored so i gave this a go with Linq and heavily commented it for you,
Given
public static IEnumerable<int> GetRanks(long[] scores, long[] person)
// Convert scores to a tuple
=> scores.Select(s => (scores: s, isPerson: false))
// convert persons score to a tuple and concat
.Concat(person.Select(s => (scores: s, isPerson: true)))
// Group by scores
.GroupBy(x => x.scores)
// order by score
.OrderBy(x => x.Key)
// select into an indexable tuple so we know everyones rank
.Select((groups, i) => (rank: i, groups))
// Filter the person
.Where(x => x.groups.Any(y => y.isPerson))
// select the rank
.Select(x => x.rank);
Usage
static void Main(string[] args)
{
var scores = new long[]{1, 34, 565, 43, 44, 56, 67};
var alice = new long[]{578, 40, 50, 67, 6};
var ranks = GetRanks(scores, alice);
foreach (var rank in ranks)
Console.WriteLine(rank);
}
Output
1
3
6
8
10

Based on the given constraint brute-force solution will not be efficient for the problem.
you have to optimize your code and the key part here is to look up for exact place which can be effectively done by using binary search.
Here is the solution using binary search:-
static int[] climbingLeaderboard(int[] scores, int[] alice) {
int n = scores.length;
int m = alice.length;
int res[] = new int[m];
int[] rank = new int[n];
rank[0] = 1;
for (int i = 1; i < n; i++) {
if (scores[i] == scores[i - 1]) {
rank[i] = rank[i - 1];
} else {
rank[i] = rank[i - 1] + 1;
}
}
for (int i = 0; i < m; i++) {
int aliceScore = alice[i];
if (aliceScore > scores[0]) {
res[i] = 1;
} else if (aliceScore < scores[n - 1]) {
res[i] = rank[n - 1] + 1;
} else {
int index = binarySearch(scores, aliceScore);
res[i] = rank[index];
}
}
return res;
}
private static int binarySearch(int[] a, int key) {
int lo = 0;
int hi = a.length - 1;
while (lo <= hi) {
int mid = lo + (hi - lo) / 2;
if (a[mid] == key) {
return mid;
} else if (a[mid] < key && key < a[mid - 1]) {
return mid;
} else if (a[mid] > key && key >= a[mid + 1]) {
return mid + 1;
} else if (a[mid] < key) {
hi = mid - 1;
} else if (a[mid] > key) {
lo = mid + 1;
}
}
return -1;
}
You can refer to this link for a more detailed video explanation.

static int[] climbingLeaderboard(int[] scores, int[] alice) {
int[] uniqueScores = IntStream.of(scores).distinct().toArray();
int [] rank = new int [alice.length];
int startIndex=0;
for(int j=alice.length-1; j>=0;j--) {
for(int i=startIndex; i<=uniqueScores.length-1;i++) {
if (alice[j]<uniqueScores[uniqueScores.length-1]){
rank[j]=uniqueScores.length+1;
break;
}
else if(alice[j]>=uniqueScores[i]) {
rank[j]=i+1;
startIndex=i;
break;
}
else{continue;}
}
}
return rank;
}

My solution in javascript for climbing the Leaderboard Hackerrank problem. The time complexity of the problem can be O(i+j), i is the length of scores and j is the length of alice. The space complexity is O(1).
// Complete the climbingLeaderboard function below.
function climbingLeaderboard(scores, alice) {
const ans = [];
let count = 0;
// the alice array is arranged in ascending order
let j = alice.length - 1;
for (let i = 0 ; i < scores.length ; i++) {
const score = scores[i];
for (; j >= 0 ; j--) {
if (alice[j] >= score) {
// if higher than score
ans.unshift(count+1);
} else if (i === scores.length - 1) {
// if smallest
ans.unshift(count+2);
} else {
break;
}
}
// actual rank of the score in leaderboard
if (score !== scores[i-1]) {
count++;
}
}
return ans;
}

Here is my solution
List<int> distinct = null;
List<int> rank = new List<int>();
foreach (int item in player)
{
ranked.Add(item);
ranked.Sort();
ranked.Reverse();
distinct = ranked.Distinct().ToList();
for (int i = 0; i < distinct.Count; i++)
{
if (item == distinct[i])
{
rank.Add(i + 1);
break;
}
}
}
return rank;
This can be modified by removing the inner for loop also
List<int> distinct = null;
List<int> rank = new List<int>();
foreach (int item in player)
{
ranked.Add(item);
ranked.Sort();
ranked.Reverse();
distinct = ranked.Distinct().ToList();
var index = ranked.FindIndex(x => x == item);
rank.Add(index + 1);
}
return rank;

This is my solution in c# for Hackerrank Climbing the Leaderboard based on C++ answer here.
public static List<int> climbingLeaderboard(List<int> ranked, List<int> player)
{
List<int> _ranked = new List<int>();
_ranked.Add(ranked[0]);
for(int a=1; a < ranked.Count(); a++)
if(_ranked[_ranked.Count()-1] != ranked[a])
_ranked.Add(ranked[a]);
int j = _ranked.Count()-1;
int i = 0;
while(i < player.Count())
{
if(j < 0)
{
player[i] = 1;
i++;
continue;
}
if(player[i] < _ranked[j])
{
player[i] = j+2;
i++;
}
else
if(player[i] == _ranked[j])
{
player[i] = j+1;
i++;
}
else
{
j--;
}
}
return player;
}

My solution in Java for climbing the Leaderboard Hackerrank problem.
// Complete the climbingLeaderboard function below.
static int[] climbingLeaderboard(int[] scores, int[] alice) {
Arrays.sort(scores);
HashSet<Integer> set = new HashSet<Integer>();
int[] ar = new int[alice.length];
int sc = 0;
for(int i=0; i<alice.length; i++){
sc = 1;
set.clear();
for(int j=0; j<scores.length; j++){
if(alice[i] < scores[j] && !set.contains(scores[j])){
sc++;
set.add(scores[j]);
}
}
ar[i] = sc;
}return ar;
}