Related
Okay, I know that this code is crude, and all around a messy, but I am no programmer, so bear with me. I have this code that lists a bunch of numbers, but I want it to not list any circular copies of the numbers.
For example, if the number 111262 is on my list, I don't want 112621, 126211, 262111, 621112, or 211126 to be listed.
Sorry, that number cannot be on the list.
For a true example, if the number 111252 is on my list, I don't want 112521, 125211, 252111, 521112, or 211125 to be listed.
Any help is appreciated!
namespace Toric_Classes
{
class Program
{
static void Main(string[] args)
{
int number_of_perms=0;
bool badsubsum1;
bool badsubsum2;
int subsum1 = 0;
int subsum2 = 0;
int sum = 0;
int class_length=6;
int[] toric_class=new int[class_length];
// The nested for loops scroll through every possible number of length class_length, where each digit can have a value of 1,2,..., or class_length-1
// Each number is looked at as an array, and is not stored anywhere, only printed if it satisfies certain conditions
for(int i1=1; i1<class_length; i1++)
{
toric_class[0] = i1;
for (int i2 = 1; i2 < class_length; i2++)
{
toric_class[1] = i2;
for (int i3 = 1; i3 < class_length; i3++)
{
toric_class[2] = i3;
for (int i4 = 1; i4 < class_length; i4++)
{
toric_class[3] = i4;
for (int i5 = 1; i5 < class_length; i5++)
{
toric_class[4] = i5;
for (int i6 = 1; i6 < class_length; i6++)
{
badsubsum1 = false;
badsubsum2 = false;
toric_class[5] = i6;
// Find the value of the sum of the digits of our array.
// We only want numbers that have a total digit sum being a multiple of class_length
for (int k = 0; k < class_length; k++)
{
sum += toric_class[k];
}
// The follwong two nested loops find the value of every contiguous subsum of our number, but not the total subsum.
// We *do not* want any subsum to be a multiple of class_length.
// That is, if our number is, say, 121342, we want to find 1+2, 1+2+1, 1+2+1+3, 1+2+1+3+4, 2+1, 2+1+3, 2+1+3+4, 2+1+3+4+2, 1+3, 1+3+4, 1+3+4+2, 3+4, 3+4+2, and 4+2
// The following checks 1+2, 1+2+1, 1+2+1+3, 1+2+1+3+4, 2+1, 2+1+3, 2+1+3+4, 1+3, 1+3+4, and 3+4
for (int i = 0; i < class_length - 1; i++)
{
for (int j = i + 1; j < class_length - 1; j++)
{
for (int k = i; k < j; k++)
{
subsum1 += toric_class[k];
}
if (subsum1 % class_length == 0)
{
badsubsum1 = true;
break;
}
subsum1 = 0;
}
}
// The following checks 2+1, 2+1+3, 2+1+3+4, 2+1+3+4+2, 1+3, 1+3+4, 1+3+4+2, 3+4, 3+4+2, and 4+2
for (int i = 1; i < class_length; i++)
{
for (int j = i + 1; j < class_length; j++)
{
for (int k = i; k < j; k++)
{
subsum2 += toric_class[k];
}
if (subsum2 % class_length == 0)
{
badsubsum2 = true;
break;
}
subsum2 = 0;
}
}
// We only want numbers that satisfies the following conditions
if (sum % class_length == 0 && badsubsum1 == false && badsubsum2 == false)
{
foreach (var item in toric_class)
{
Console.Write(item.ToString());
}
Console.Write(Environment.NewLine);
number_of_perms++;
}
sum = 0;
subsum1 = 0;
subsum2 = 0;
}
}
}
}
}
}
Console.WriteLine("Number of Permuatations: "+number_of_perms);
Console.Read();
}
}
}
EDIT
To clarify, I am creating a list of all numbers with length n that satisfy certain conditions. Consider the number d1d2...dn, where each di is a digit of our number. Each di may have value 1,2,...,n. Our number is in the list if it satisfies the following
The sum of all the digits is a multiple of n, that is,
d1+d2+...+dn = 0 mod n
Every contiguous subsum of the digits is not a multiple of n, aside from the total sum, that is, if i !=1 and j != n, then
di+d(i+1)+...+dj != 0 mod n
I should mention again that a "number" does not strictly use the numbers 0-9 in its digits. It may take any value between 1 and n. In my code, I am using the case where n=6.
The code works by creating an array of length class_length (in the code above, I use class_length=6). We first have 6 nested for loops that simply assign values to the array toric_class. The first for assigns toric_class[0], the second for assigns toric_class[1], and so on. In the first go around, we are generating the array 111111, then 111112, up to 111115, then 111121, etc. So essentially, we are looking at all heximal numbers that do not include 0. Once we reach our sixth value in our array, we check the array toric_class and check its values to ensure that it satisfies the above conditions. If it does, we simply print the array in a line, and move on.
Here is my easy and inefficient way that should work with minimal changes to your code. It requires shared string list var strList = new List<string>(); to store the used numbers. Then this part:
foreach (var item in toric_class)
{
Console.Write(item.ToString());
}
Console.Write(Environment.NewLine);
number_of_perms++;
becomes something like this:
string strItem = " " + string.Join(" ", toric_class) + " "; // Example: int[] {1, 12, 123} becomes " 1 12 123 "
if (!strList.Any(str => str.Contains(strItem))) // Example: if " 1 12 123 1 12 123 " contains " 1 12 123 "
{
Console.WriteLine(strItem);
strItem += strItem.Substring(1); // double the string, but keep only one space between them
strList.Add(strItem);
}
number_of_perms++; // not sure if this should be in the if statement
The idea is that for example the string " 1 1 1 2 5 2 1 1 1 2 5 2 " contains all circular copies of the numbers {1, 1, 1, 2, 5, 2}. I used string as a lazy way to check if array contains sub-array, but you can use similar approach to store copy of the used numbers in a list of arrays new List<int[]>() and check if any of the arrays in the list is circular copy of the current array, or even better HashSet<int[]>() approach similar to #slavanap's answer.
The first version of my answer was the easiest, but it works only with array of single digit items.
List is almost the same as array (new List<string>() instead of new string[]), but makes it much easier and efficient to add items to it. For example {1,2}.Add(3) becomes {1,2,3}.
str => str.Contains(strItem) is shortcut for a function that accepts parameter str and returns the result of str.Contains(strItem). That "function" is then passed to the .Any LINQ extension, so
strList.Any(str => str.Contains(strItem))
is shortcut for something like this:
foreach(string str in strList)
{
if (str.Contains(strItem))
{
return true;
}
}
return false;
The following method:
private static List<int> GetCircularEquivalents(int value)
{
var circularList = new List<int>();
var valueString = value.ToString();
var length = valueString.Length - 1;
for (var i = 0; i < length; i++)
{
valueString = valueString.Substring(1, length) + valueString.Substring(0, 1);
circularList.Add(int.Parse(valueString));
}
return circularList;
}
will return a list of the circular numbers derived from the input value. Using your example, this method can be called like this:
var circularList = GetCircularEquivalents(111262);
var dirtyList = new List<int> { 1, 112621, 2, 126211, 3, 262111, 4, 621112, 5, 211126, 6 };
var cleanList = dirtyList.Except(circularList).ToList();
which would result in a cleanList made up of the numbers 1 through 6, i.e. the dirtyList with all the circular numbers derived from 111262 removed.
That's where OOP really benefits. Comments inlined.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace ConsoleApplication3 {
struct MyInt : IEquatable<MyInt> {
private int _value;
public MyInt(int value) {
_value = value;
}
// make it look like int
static public implicit operator MyInt(int value) {
return new MyInt(value);
}
public static explicit operator int(MyInt instance) {
return instance._value;
}
// main difference in these 3 methods
private int GetDigitsNum() {
int temp, res;
for (res = 0, temp = Math.Abs(_value); temp > 0; ++res, temp /= 10);
return res;
}
public bool Equals(MyInt other) {
int digits = other.GetDigitsNum();
if (digits != this.GetDigitsNum())
return false;
int temp = other._value;
// prepare mul used in shifts
int mul = 1;
for (int i = 0; i < digits - 1; ++i)
mul *= 10;
// compare
for (int i = 0; i < digits; ++i) {
if (temp == _value)
return true;
// ROR
int t = temp % 10;
temp = temp / 10 + t * mul;
}
return false;
}
public override int GetHashCode() {
// hash code must be equal for "equal" items,
// that's why use a sum of digits.
int sum = 0;
for (int temp = _value; temp > 0; temp /= 10)
sum += temp % 10;
return sum;
}
// be consistent
public override bool Equals(object obj) {
return (obj is MyInt) ? Equals((MyInt)obj) : false;
}
public override string ToString() {
return _value.ToString();
}
}
class Program {
static void Main(string[] args) {
List<MyInt> list = new List<MyInt> { 112621, 126211, 262111, 621112, 211126 };
// make a set of unique items from list
HashSet<MyInt> set = new HashSet<MyInt>(list);
// print that set
foreach(int item in set)
Console.WriteLine(item);
}
}
}
Output:
112621
1/ DateTime before = DateTime.Now;
2/ shellSort(List1);
3/ DateTime after = DateTime.Now;
4/ Console.WriteLine(after - before);
5/
6/ before = DateTime.Now;
7/ insertionSort(List2);
8/ after = DateTime.Now;
9/ Console.WriteLine(after - before);
I am trying to compare the run time of two different sorting algorithms. List1 here is equal to List2. I was expecting shell sort to be faster than insertion sort but although first WriteLine differs, it usually prints something like this = 00:00:00.0035037. The second one however, either prints 00:00:00 or something smaller than the first print. I thought maybe the insertion sort was better suited for List's current state however even when i swap the line 7 and line 2 i still get the same result. What is causing this? Why is the second executed function runs faster? Or am i using the Dates completely wrong?
Edit : I used Stopwatch instead of DateTime Class as advised in another post. The result is pretty much the same. The second one usually runs faster but every now and then it's slower than the first one. I also used a pre-written shellsort code to see if my implementation was bad but that was also a dead end.
As requested, shellsort and insertionsort implementations
static void shellSort(List<int> numbers) // Implementation i found online
{
int i, j, increment, temp;
increment = 3;
while (increment > 0)
{
for (i = 0; i < numbers.Count ; i++)
{
j = i;
temp = numbers[i];
while ((j >= increment) && (numbers[j - increment] > temp))
{
numbers[j] = numbers[j - increment];
j = j - increment;
}
numbers[j] = temp;
}
if (increment / 2 != 0)
increment = increment / 2;
else if (increment == 1)
increment = 0;
else
increment = 1;
}
}
public static void insertionSort(List<int> numbers)
{
int i = 0;
while (i != numbers.Count)
{
int k = i;
while (k != 0 && numbers[k] < numbers[k - 1])
{
int temp = numbers[k - 1];
numbers[k - 1] = numbers[k];
numbers[k] = temp;
k--;
}
i++;
}
}
Also this was my implementation of shellsort
public static void shellSort(List<int> Liste)
{
int n = Liste.Count;
int gap = (Liste.Count - 1) / 2;
while (gap > 0)
{
int i = 0;
for(int k = gap; k < n; k++) {
int p = i;
int m = k;
while (p >= 0)
{
if (Liste[p] > Liste[m])
{
int temp = Liste[p];
Liste[p] = Liste[m];
Liste[m] = temp;
m = p;
}
else
break;
p = p - gap;
}
i++;
}
gap = gap / 2;
}
}
I need to "Find the minimal positive integer not occurring in a given sequence. "
A[0] = 1
A[1] = 3
A[2] = 6
A[3] = 4
A[4] = 1
A[5] = 2, the function should return 5.
Assume that:
N is an integer within the range [1..100,000];
each element of array A is an integer within the range [−2,147,483,648..2,147,483,647].
I wrote the code in codility, but for many cases it did not worked and the performance test gives 0 %. Please help me out, where I am wrong.
class Solution {
public int solution(int[] A) {
if(A.Length ==0) return -1;
int value = A[0];
int min = A.Min();
int max = A.Max();
for (int j = min+1; j < max; j++)
{
if (!A.Contains(j))
{
value = j;
if(value > 0)
{
break;
}
}
}
if(value > 0)
{
return value;
}
else return 1;
}
}
The codility gives error with all except the example, positive and negative only values.
Edit: Added detail to answer your actual question more directly.
"Please help me out, where I am wrong."
In terms of correctness: Consider A = {7,2,5,6,3}. The correct output, given the contents of A, is 1, but our algorithm would fail to detect this since A.Min() would return 2 and we would start looping from 3 onward. In this case, we would return 4 instead; since it's the next missing value.
Same goes for something like A = {14,15,13}. The minimal missing positive integer here is again 1 and, since all the values from 13-15 are present, the value variable will retain its initial value of value=A[0] which would be 14.
In terms of performance: Consider what A.Min(), A.Max() and A.Contains() are doing behind the scenes; each one of these is looping through A in its entirety and in the case of Contains, we are calling it repeatedly for every value between the Min() and the lowest positive integer we can find. This will take us far beyond the specified O(N) performance that Codility is looking for.
By contrast, here's the simplest version I can think of that should score 100% on Codility. Notice that we only loop through A once and that we take advantage of a Dictionary which lets us use ContainsKey; a much faster method that does not require looping through the whole collection to find a value.
using System;
using System.Collections.Generic;
class Solution {
public int solution(int[] A) {
// the minimum possible answer is 1
int result = 1;
// let's keep track of what we find
Dictionary<int,bool> found = new Dictionary<int,bool>();
// loop through the given array
for(int i=0;i<A.Length;i++) {
// if we have a positive integer that we haven't found before
if(A[i] > 0 && !found.ContainsKey(A[i])) {
// record the fact that we found it
found.Add(A[i], true);
}
}
// crawl through what we found starting at 1
while(found.ContainsKey(result)) {
// look for the next number
result++;
}
// return the smallest positive number that we couldn't find.
return result;
}
}
The simplest solution that scored perfect score was:
public int solution(int[] A)
{
int flag = 1;
A = A.OrderBy(x => x).ToArray();
for (int i = 0; i < A.Length; i++)
{
if (A[i] <= 0)
continue;
else if (A[i] == flag)
{
flag++;
}
}
return flag;
}
Fastest C# solution so far for [-1,000,000...1,000,000].
public int solution(int[] array)
{
HashSet<int> found = new HashSet<int>();
for (int i = 0; i < array.Length; i++)
{
if (array[i] > 0)
{
found.Add(array[i]);
}
}
int result = 1;
while (found.Contains(result))
{
result++;
}
return result;
}
A tiny version of another 100% with C#
using System.Linq;
class Solution
{
public int solution(int[] A)
{
// write your code in C# 6.0 with .NET 4.5 (Mono)
var i = 0;
return A.Where(a => a > 0).Distinct().OrderBy(a => a).Any(a => a != (i = i + 1)) ? i : i + 1;
}
}
A simple solution that scored 100% with C#
int Solution(int[] A)
{
var A2 = Enumerable.Range(1, A.Length + 1);
return A2.Except(A).First();
}
public class Solution {
public int solution( int[] A ) {
return Arrays.stream( A )
.filter( n -> n > 0 )
.sorted()
.reduce( 0, ( a, b ) -> ( ( b - a ) > 1 ) ? a : b ) + 1;
}
}
It seemed easiest to just filter out the negative numbers. Then sort the stream. And then reduce it to come to an answer. It's a bit of a functional approach, but it got a 100/100 test score.
Got an 100% score with this solution:
https://app.codility.com/demo/results/trainingUFKJSB-T8P/
public int MissingInteger(int[] A)
{
A = A.Where(a => a > 0).Distinct().OrderBy(c => c).ToArray();
if (A.Length== 0)
{
return 1;
}
for (int i = 0; i < A.Length; i++)
{
//Console.WriteLine(i + "=>" + A[i]);
if (i + 1 != A[i])
{
return i + 1;
}
}
return A.Max() + 1;
}
JavaScript solution using Hash Table with O(n) time complexity.
function solution(A) {
let hashTable = {}
for (let item of A) {
hashTable[item] = true
}
let answer = 1
while(true) {
if(!hashTable[answer]) {
return answer
}
answer++
}
}
The Simplest solution for C# would be:
int value = 1;
int min = A.Min();
int max = A.Max();
if (A.Length == 0) return value = 1;
if (min < 0 && max < 0) return value = 1;
List<int> range = Enumerable.Range(1, max).ToList();
List<int> current = A.ToList();
List<int> valid = range.Except(current).ToList();
if (valid.Count() == 0)
{
max++;
return value = max;
}
else
{
return value = valid.Min();
}
Considering that the array should start from 1 or if it needs to start from the minimum value than the Enumerable.range should start from Min
MissingInteger solution in C
int solution(int A[], int N) {
int i=0,r[N];
memset(r,0,(sizeof(r)));
for(i=0;i<N;i++)
{
if(( A[i] > 0) && (A[i] <= N)) r[A[i]-1]=A[i];
}
for(i=0;i<N;i++)
{
if( r[i] != (i+1)) return (i+1);
}
return (N+1);
}
My solution for it:
public static int solution()
{
var A = new[] { -1000000, 1000000 }; // You can try with different integers
A = A.OrderBy(i => i).ToArray(); // We sort the array first
if (A.Length == 1) // if there is only one item in the array
{
if (A[0]<0 || A[0] > 1)
return 1;
if (A[0] == 1)
return 2;
}
else // if there are more than one item in the array
{
for (var i = 0; i < A.Length - 1; i++)
{
if (A[i] >= 1000000) continue; // if it's bigger than 1M
if (A[i] < 0 || (A[i] + 1) >= (A[i + 1])) continue; //if it's smaller than 0, if the next integer is bigger or equal to next integer in the sequence continue searching.
if (1 < A[0]) return 1;
return A[i] + 1;
}
}
if (1 < A[0] || A[A.Length - 1] + 1 == 0 || A[A.Length - 1] + 1 > 1000000)
return 1;
return A[A.Length-1] +1;
}
class Solution {
public int solution(int[] A) {
int size=A.length;
int small,big,temp;
for (int i=0;i<size;i++){
for(int j=0;j<size;j++){
if(A[i]<A[j]){
temp=A[j];
A[j]=A[i];
A[i]=temp;
}
}
}
int z=1;
for(int i=0;i<size;i++){
if(z==A[i]){
z++;
}
//System.out.println(a[i]);
}
return z;
}
enter code here
}
In C# you can solve the problem by making use of built in library functions. How ever the performance is low for very large integers
public int solution(int[] A)
{
var numbers = Enumerable.Range(1, Math.Abs(A.Max())+1).ToArray();
return numbers.Except(A).ToArray()[0];
}
Let me know if you find a better solution performance wise
C# - MissingInteger
Find the smallest missing integer between 1 - 1000.000.
Assumptions of the OP take place
TaskScore/Correctness/Performance: 100%
using System;
using System.Linq;
namespace TestConsole
{
class Program
{
static void Main(string[] args)
{
var A = new int[] { -122, -5, 1, 2, 3, 4, 5, 6, 7 }; // 8
var B = new int[] { 1, 3, 6, 4, 1, 2 }; // 5
var C = new int[] { -1, -3 }; // 1
var D = new int[] { -3 }; // 1
var E = new int[] { 1 }; // 2
var F = new int[] { 1000000 }; // 1
var x = new int[][] { A, B, C, D, E, F };
x.ToList().ForEach((arr) =>
{
var s = new Solution();
Console.WriteLine(s.solution(arr));
});
Console.ReadLine();
}
}
// ANSWER/SOLUTION
class Solution
{
public int solution(int[] A)
{
// clean up array for negatives and duplicates, do sort
A = A.Where(entry => entry > 0).Distinct().OrderBy(it => it).ToArray();
int lowest = 1, aLength = A.Length, highestIndex = aLength - 1;
for (int i = 0; i < aLength; i++)
{
var currInt = A[i];
if (currInt > lowest) return lowest;
if (i == highestIndex) return ++lowest;
lowest++;
}
return 1;
}
}
}
Got 100% - C# Efficient Solution
public int solution (int [] A){
int len = A.Length;
HashSet<int> realSet = new HashSet<int>();
HashSet<int> perfectSet = new HashSet<int>();
int i = 0;
while ( i < len)
{
realSet.Add(A[i]); //convert array to set to get rid of duplicates, order int's
perfectSet.Add(i + 1); //create perfect set so can find missing int
i++;
}
perfectSet.Add(i + 1);
if (realSet.All(item => item < 0))
return 1;
int notContains =
perfectSet.Except(realSet).Where(item=>item!=0).FirstOrDefault();
return notContains;
}
class Solution {
public int solution(int[] a) {
int smallestPositive = 1;
while(a.Contains(smallestPositive)) {
smallestPositive++;
}
return smallestPositive;
}
}
Well, this is a new winner now. At least on C# and my laptop. It's 1.5-2 times faster than the previous champion and 3-10 times faster, than most of the other solutions. The feature (or a bug?) of this solution is that it uses only basic data types. Also 100/100 on Codility.
public int Solution(int[] A)
{
bool[] B = new bool[(A.Length + 1)];
for (int i = 0; i < A.Length; i++)
{
if ((A[i] > 0) && (A[i] <= A.Length))
B[A[i]] = true;
}
for (int i = 1; i < B.Length; i++)
{
if (!B[i])
return i;
}
return A.Length + 1;
}
Simple C++ solution. No additional memory need, time execution order O(N*log(N)):
int solution(vector<int> &A) {
sort (A.begin(), A.end());
int prev = 0; // the biggest integer greater than 0 found until now
for( auto it = std::begin(A); it != std::end(A); it++ ) {
if( *it > prev+1 ) break;// gap found
if( *it > 0 ) prev = *it; // ignore integers smaller than 1
}
return prev+1;
}
int[] A = {1, 3, 6, 4, 1, 2};
Set<Integer> integers = new TreeSet<>();
for (int i = 0; i < A.length; i++) {
if (A[i] > 0) {
integers.add(A[i]);
}
}
Integer[] arr = integers.toArray(new Integer[0]);
final int[] result = {Integer.MAX_VALUE};
final int[] prev = {0};
final int[] curr2 = {1};
integers.stream().forEach(integer -> {
if (prev[0] + curr2[0] == integer) {
prev[0] = integer;
} else {
result[0] = prev[0] + curr2[0];
}
});
if (Integer.MAX_VALUE == result[0]) result[0] = arr[arr.length-1] + 1;
System.out.println(result[0]);
I was surprised but this was a good lesson. LINQ IS SLOW. my answer below got me 11%
public int solution (int [] A){
if (Array.FindAll(A, x => x >= 0).Length == 0) {
return 1;
} else {
var lowestValue = A.Where(x => Array.IndexOf(A, (x+1)) == -1).Min();
return lowestValue + 1;
}
}
I think I kinda look at this a bit differently but gets a 100% evaluation. Also, I used no library:
public static int Solution(int[] A)
{
var arrPos = new int[1_000_001];
for (int i = 0; i < A.Length; i++)
{
if (A[i] >= 0)
arrPos[A[i]] = 1;
}
for (int i = 1; i < arrPos.Length; i++)
{
if (arrPos[i] == 0)
return i;
}
return 1;
}
public int solution(int[] A) {
// write your code in Java SE 8
Set<Integer> elements = new TreeSet<Integer>();
long lookFor = 1;
for (int i = 0; i < A.length; i++) {
elements.add(A[i]);
}
for (Integer integer : elements) {
if (integer == lookFor)
lookFor += 1;
}
return (int) lookFor;
}
I tried to use recursion in C# instead of sorting, because I thought it would show more coding skill to do it that way, but on the scaling tests it didn't preform well on large performance tests. Suppose it's best to just do the easy way.
class Solution {
public int lowest=1;
public int solution(int[] A) {
// write your code in C# 6.0 with .NET 4.5 (Mono)
if (A.Length < 1)
return 1;
for (int i=0; i < A.Length; i++){
if (A[i]==lowest){
lowest++;
solution(A);
}
}
return lowest;
}
}
Here is my solution in javascript
function solution(A) {
// write your code in JavaScript (Node.js 8.9.4)
let result = 1;
let haveFound = {}
let len = A.length
for (let i=0;i<len;i++) {
haveFound[`${A[i]}`] = true
}
while(haveFound[`${result}`]) {
result++
}
return result
}
class Solution {
public int solution(int[] A) {
var sortedList = A.Where(x => x > 0).Distinct().OrderBy(x => x).ToArray();
var output = 1;
for (int i = 0; i < sortedList.Length; i++)
{
if (sortedList[i] != output)
{
return output;
}
output++;
}
return output;
}
}
You should just use a HashSet as its look up time is also constant instead of a dictionary. The code is less and cleaner.
public int solution (int [] A){
int answer = 1;
var set = new HashSet<int>(A);
while (set.Contains(answer)){
answer++;
}
return answer;
}
This snippet should work correctly.
using System;
using System.Collections.Generic;
public class Program
{
public static void Main()
{
int result = 1;
List<int> lst = new List<int>();
lst.Add(1);
lst.Add(2);
lst.Add(3);
lst.Add(18);
lst.Add(4);
lst.Add(1000);
lst.Add(-1);
lst.Add(-1000);
lst.Sort();
foreach(int curVal in lst)
{
if(curVal <=0)
result=1;
else if(!lst.Contains(curVal+1))
{
result = curVal + 1 ;
}
Console.WriteLine(result);
}
}
}
I've been working on an Access file editor in C#, and i've been trying to get a search feature added to my program. So far, I have the database file populate a 2D array, which i then use to populate a ListView box in another window. From this new window, I would like to be able to search each entry by Model Number. So far, i've managed to incorporate the Levenstein Algorithm, which seems to have much use. I can get the algorithm to assign the distance value between each entry and the search keyboard, and assign that value to another integer array. I can also sort the results in increasing order.
However, my current problem is that i'd would like to have the Model numbers sorted with the same respect to the distance values from the Levenstein Algorithm, so that the most relevant result becomes the first choice in the ListView box. Any ideas anyone??!?!
Here's what i've got so far:
private void OnSearch(object sender, System.EventArgs e)
{
string a;
string b;
int[] result = new int[1000];
int[] sorted = new int[1000];
for (int i = 0; i < rowC; i++)
{
a = PartNum[i]; // Array to search
b = SearchBox1.Text; // keyword to search with
if (GetDistance(a, b) == 0)
{
return;
}
result[i] = GetDistance(a, b); //add each distance result into array
}
int index;
int x;
for (int j = 1; j < rowC; j++) //quick insertion sort
{
index = result[j];
x = j;
while ((x > 0) && (result[x - 1] > index))
{
result[x] = result[x - 1];
x = x - 1;
}
result[x] = index;
}
}
public static int GetDistance(string s, string t)
{
if (String.IsNullOrEmpty(s) || String.IsNullOrEmpty(t))
{
MessageBox.Show("Please enter something to search!!");
return 0;
}
int n = s.Length;
int m = t.Length;
if (n == 0)
{
return m;
}
else if (m == 0)
{
return n;
}
int[] p = new int[n + 1];
int[] d = new int[n + 1];
int[] _d;
char t_j;
int cost;
for (int i = 0; i <= n; i++)
{
p[i] = i;
}
for (int j = 1; j <= m; j++)
{
t_j = t[j - 1];
d[0] = j;
for (int i = 1; i <= n; i++)
{
cost = (s[i - 1] == t_j) ? 0 : 1;
d[i] = Math.Min(Math.Min(d[i - 1] + 1, p[i] + 1), p[i - 1] + cost);
}
_d = p;
p = d;
d = _d;
}
return p[n];
}
Do you have LINQ available to you? If so:
var ordered = PartNum.OrderBy(x => GetDistance(x, SearchBox1.Text))
.ToList();
// Do whatever with the ordered list
Note that this has the disadvantage of not aborting early if you find an exact match, as well as not making the actual distances available - but it's not entirely clear how you're using the results anyway...
Another option would be:
var ordered = (from word in PartNum
let distance = GetDistance(word, SearchBox1.Text))
orderby distance
select new { word, distance }).ToList();
Then you've got the distance as well.
In order to sort your array by Levenstein distance you need to include the model numbers as part of your array so that, when you sort the array by Levenstein number, the model numbers will go along for the ride.
To do this, create a class representing each part:
public class Part
{
public string PartNumber;
public int LevensteinDistance;
}
and then create an array of Part:
Part[] parts;
You can then reference each element like so:
parts[n].LevensteinDistance
parts[n].PartNumber
I am practising a C# console application, and I am trying to get the function to verify if the number appears in a fibonacci series or not but I'm getting errors.
What I did was:
class Program
{
static void Main(string[] args)
{
System.Console.WriteLine(isFibonacci(20));
}
static int isFibonacci(int n)
{
int[] fib = new int[100];
fib[0] = 1;
fib[1] = 1;
for (int i = 2; i <= 100; i++)
{
fib[i] = fib[i - 1] + fib[i - 2];
if (n == fib[i])
{
return 1;
}
}
return 0;
}
}
Can anybody tell me what am I doing wrong here?
Here's a fun solution using an infinite iterator block:
IEnumerable<int> Fibonacci()
{
int n1 = 0;
int n2 = 1;
yield return 1;
while (true)
{
int n = n1 + n2;
n1 = n2;
n2 = n;
yield return n;
}
}
bool isFibonacci(int n)
{
foreach (int f in Fibonacci())
{
if (f > n) return false;
if (f == n) return true;
}
}
I actually really like this kind of Fibonacci implementation vs the tradition recursive solution, because it keeps the work used to complete a term available to complete the next. The traditional recursive solution duplicates some work, because it needs two recursive calls each term.
The problem lies in <= the following statement:
for (int i = 2; i <= 100; i++)
more to the point the =. There is no fib[100] (C# zero counts) so when you check on i=100 you get an exception.
the proper statement should be
for (int i = 2; i < 100; i++)
or even better
for (int i = 2; i < fib.Length; i++)
And here is a solution that beats all of yours!
Because, why iteration when you have smart mathematicians doing closed-form solutions for you? :)
static bool IsFibonacci(int number)
{
//Uses a closed form solution for the fibonacci number calculation.
//http://en.wikipedia.org/wiki/Fibonacci_number#Closed-form_expression
double fi = (1 + Math.Sqrt(5)) / 2.0; //Golden ratio
int n = (int) Math.Floor(Math.Log(number * Math.Sqrt(5) + 0.5, fi)); //Find's the index (n) of the given number in the fibonacci sequence
int actualFibonacciNumber = (int)Math.Floor(Math.Pow(fi, n) / Math.Sqrt(5) + 0.5); //Finds the actual number corresponding to given index (n)
return actualFibonacciNumber == number;
}
Well, for starters your array is only 10 long and you're filling it with ~100 items (out-of-range-exception) - but there are better ways to do this...
for example, using this post:
long val = ...
bool isFib = Fibonacci().TakeWhile(x => x <= val).Last() == val;
int[] fib = new int[10];
for (int i = 2; i <= *100*; i++)
You're going out of the bounds of your array because your loop conditional is too large. A more traditional approach would be to bound the loop by the size of the array:
for (int i = 2; i < fib.Length; i++)
And make your array bigger, but as Marc said, there are better ways to do this, and I would advise you spend some time reading the wikipedia article on Fibonacci numbers.
One thing you can do is check for an early exit. Since you're trying to determine if a given number is in the Fibonacci sequence, you can do bounds checking to exit early.
Example:
static bool isFibonacci(int n)
{
int[] fib = new int[100];
fib[0] = 1;
fib[1] = 1;
for (int i = 2; i <= fib.Length; i++)
{
fib[i] = fib[i - 1] + fib[i - 2];
if (n == fib[i])
{
return true;
}
else if (n < fib[i])
{
return false; //your number has been surpassed in the fib seq
}
}
return false;
}
public static int FibNo(int n) {
int result = 0; int No = 0; int N1 = 1;
if (n< 0)
{ throw new ArguementException("number must be a positive value"); }
if (n <= 1)
{ result = n; return result; }
for(int x=1; x < n; x++)
{ result = No + N1; No = N1; N1=result; }
return result;
}