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Algorithm converting lotto ticket number to integer value and back again

I'm looking for the algorithm to convert a lotto ticket number to an integer value an back again.
Let's say the lotto number can be between 1 and 45 and a tickets contains 6 unique numbers. This means there are a maximum of 8145060 unique lotto tickets.
eg:
01-02-03-04-05-06 = 1
01-02-03-04-05-07 = 2
.
.
.
39-41-42-43-44-45 = 8145059
40-41-42-43-44-45 = 8145060
I'd like to have a function (C# preferable but any language will do) which converts between a lotto ticket and an integer and back again. At the moment I use the quick and dirty method of pre-calculating everything, which needs a lot of memory.

For enumerating integer combinations, you need to use the combinatorial number system. Here's a basic implementation in C#:
using System;
using System.Numerics;
using System.Collections.Generic;
public class CombinatorialNumberSystem
{
// Helper functions for calculating values of (n choose k).
// These are not optimally coded!
// ----------------------------------------------------------------------
protected static BigInteger factorial(int n) {
BigInteger f = 1;
while (n > 1) f *= n--;
return f;
}
protected static int binomial(int n, int k) {
if (k > n) return 0;
return (int)(factorial(n) / (factorial(k) * factorial(n-k)));
}
// In the combinatorial number system, a combination {c_1, c_2, ..., c_k}
// corresponds to the integer value obtained by adding (c_1 choose 1) +
// (c_2 choose 2) + ... + (c_k choose k)
// NOTE: combination values are assumed to start from zero, so
// a combination like {1, 2, 3, 4, 5} will give a non-zero result
// ----------------------------------------------------------------------
public static int combination_2_index(int[] combo) {
int ix = 0, i = 1;
Array.Sort(combo);
foreach (int c in combo) {
if (c > 0) ix += binomial(c, i);
i++;
}
return ix;
}
// The reverse of this process is a bit fiddly. See Wikipedia for an
// explanation: https://en.wikipedia.org/wiki/Combinatorial_number_system
// ----------------------------------------------------------------------
public static int[] index_2_combination(int ix, int k) {
List<int> combo_list = new List<int>();
while (k >= 1) {
int n = k - 1;
if (ix == 0) {
combo_list.Add(n);
k--;
continue;
}
int b = 0;
while (true) {
// (Using a linear search here, but a binary search with
// precomputed binomial values would be faster)
int b0 = b;
b = binomial(n, k);
if (b > ix || ix == 0) {
ix -= b0;
combo_list.Add(n-1);
break;
}
n++;
}
k--;
}
int[] combo = combo_list.ToArray();
Array.Sort(combo);
return combo;
}
}
The calculations are simpler if you work with combinations of integers that start from zero, so for example:
00-01-02-03-04-05 = 0
00-01-02-03-04-06 = 1
.
.
.
38-40-41-42-43-44 = 8145058
39-40-41-42-43-44 = 8145059
You can play around with this code at ideone if you like.

there seem to be actually 45^6 distinct numbers, a simple way is to treat the ticket number as a base-45 number and convert it to base 10:
static ulong toDec(string input){
ulong output = 0;
var lst = input.Split('-').ToList();
for (int ix =0; ix< lst.Count; ix++)
{
output = output + ( (ulong.Parse(lst[ix])-1) *(ulong) Math.Pow(45 , 5-ix));
}
return output;
}
examples:
01-01-01-01-01-01 => 0
01-01-01-01-01-02 => 1
01-01-01-01-02-01 => 45
45-45-45-45-45-45 => 8303765624

Pairs of amicable numbers

I have a task to find pairs of amicable numbers and I've already solved it. My solution is not efficient, so please help me to make my algorithm faster.
Amicable numbers are two different numbers so related that the sum of the proper divisors of each is equal to the other number. The smallest pair of amicable numbers is (220, 284). They are amicable because the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44, 55 and 110, of which the sum is 284; and the proper divisors of 284 are 1, 2, 4, 71 and 142, of which the sum is 220.
Task: two long numbers and find the first amicable numbers between them. Let s(n) be the sum of the proper divisors of n:
For example:
s(10) = 1 + 2 + 5 = 8
s(11) = 1
s(12) = 1 + 2 + 3 + 4 + 6 = 16
If s(firstlong) == s(secondLong) they are amicable numbers
My code:
public static IEnumerable<long> Ranger(long length) {
for (long i = 1; i <= length; i++) {
yield return i;
}
}
public static IEnumerable<long> GetDivisors(long num) {
return from a in Ranger(num/2)
where num % a == 0
select a;
}
public static string FindAmicable(long start, long limit) {
long numberN = 0;
long numberM = 0;
for (long n = start; n <= limit; n++) {
long sumN = GetDivisors(n).Sum();
long m = sumN;
long sumM = GetDivisors(m).Sum();
if (n == sumM ) {
numberN = n;
numberM = m;
break;
}
}
return $"First amicable numbers: {numberN} and {numberM}";
}

I generally don't write C#, so rather than stumble through some incoherent C# spaghetti, I'll describe an improvement in C#-madeup-psuedo-code.
The problem seems to be in your GetDivisors function. This is linear O(n) time with respect to each divisor n, when it could be O(sqrt(n)). The trick is to only divide up to the square root, and infer the rest of the factors from that.
GetDivisors(num) {
// same as before, but up to sqrt(num), plus a bit for floating point error
yield return a in Ranger((long)sqrt(num + 0.5)) where num % a == 0
if ((long)sqrt(num + 0.5) ** 2 == num) { // perfect square, exists
num -= 1 // don't count it twice
}
// repeat, but return the "other half"- num / a instead of a
yield return num/a in Ranger((long)sqrt(num + 0.5)) where num % a == 0
}
This will reduce your complexity of that portion from O(n) to O(sqrt(n)), which should provide a noticeable speedup.

There is a simple formula giving the sum of divisors of a number knowing its prime decomposition:
let x = p1^a1 * ... * pn^an, where pi is a prime for all i
sum of divisors = (1+p1+...+p1^a1) * ... (1+pn+...+pn^an)
= (1-p1^(a1+1))/(1-p1) * ... ((1-pn^(an+1))/(1-pn)
In order to do a prime decomposition you must compute all prime numbers up to the square root of the maximal value in your search range. This is easily done using the sieve of Erathostenes.

Get divisible numbers in a range without certain operators (+, -, /, *, %, += %=, etc)

find numbers in an input range that are evenly divisible by 3. Only =, ++, -- operators can be used.
I've tried to get the remainder using shift operators and other loops but I always require a -= or something similar.
Console.Clear();
int n,
d,
count = 1;
// get the ending number
n = getNumber();
// get the divisor
d = 3;// getDivisor();
Console.WriteLine();
Console.WriteLine(String.Format("Below are all the numbers that are evenly divisible by {0} from 1 up to {1}", d, n));
Console.WriteLine();
// loop through
while (count <= n)
{
// if no remainder then write number
if(count % d == 0)
Console.Write(string.Format("{0} ", count));
count++;
}
Console.WriteLine();
Console.WriteLine();
Console.Write("Press any key to try again. Press escape to cancel");
Expected results:
Enter the ending number: 15
Below are all the numbers that are evenly divisible by 3 from 1 up to 15
3, 6, 9, 12, 15

If the == operator is permitted for the assignment, you can have something like
int remainder = 0; // assumes we always count up from 1 to n, we will increment before test
Inside the loop replace the existing if with
remainder++;
if (remainder == 3) {
Console.Write(string.Format("{0} ", count));
remainder = 0;
}
[EDIT: Typo in code corrected]

Think about the underlying maths:
2 x 3 = 3 + 3
3 x 3 = 3 + 3 + 3
4 * 3 = 3 + 3 + 3 + 3
...and so on.
Also, to be evenly divisible by 3 means that the number multiplying 3 must be even.. So...
public bool EvenlyDivisibleBy3(int aNumber)
{
int even = 2;
int currentMultiple = 0;
while (currentMultiple < aNumber)
{
int xTimes = 0;
for (int x = 1; x <= even; x++)
{
((xTimes++)++)++; // add three to xTimes
}
currentMultiple = xTimes;
(even++)++: // next even number
}
return currentMultiple == aNumber;
}

C# writing a program that input of 2 numbers (a and b),gives an output of the sum of squares in between

I`m quite new to the whole programming world.
And i started studying C#
i got the following exersice to do:
Write a program that upon the input of 2 numbers (a and b), u receive
an output of the sum of squares in between.
I.e. - The program receives a and b where b > a and calculates a^2
+ (a+1)^2 + (a+2)^2 + ... + (b-1)^2 + b^2.
E.g. - If a = 3 and b = 6, the output would be 86, since 3^2 +
4^2 + 5^2 + 6^2 = 9 + 16 + 25 + 36 = 86
But i don't have any idea where do i even begin.
I`m guessing i need some sort of loop within a loop maybe?

You need to use for loop for this. Please see below, if that helps-
int i, j, k;
int value=0;
Console.WriteLine("Enter the fist number ");
i = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Enter the second number ");
j = Convert.ToInt32(Console.ReadLine());
if (i > j)
{
Console.WriteLine("Second number should be greater then First");
Console.ReadLine();
Environment.Exit(0);
}
for (k = i; k <= j; k++)
{
value += k * k;
}
Console.WriteLine(value);
Console.ReadLine();

Perhaps a method that takes in two integers and returns a double is a good place to start (returning a double allows you to specify a wider range of numbers without getting inaccurate results):
public static double GetSumOfSquaresBetween(int first, int second)
{
}
Then you could implement the body by creating a loop that goes from the lowest number to the highest number, adding the square of the current number to a result, and then returning that result at the end.
Here's a Linq example that would most likely not be acceptable for this assignment but gives you the idea:
public static double GetSumOfSquaresBetween(int first, int second)
{
return Enumerable
.Range(Math.Min(first, second), Math.Abs(first - second) + 1)
.Select(number => Math.Pow(number, 2))
.Sum();
}

Try this
int a, b, sum = 0;
Console.WriteLine("Enter the fist number ");
a = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Enter the second number ");
b = Convert.ToInt32(Console.ReadLine());
if (a<b){
for (int x = a+1; x < b; x++)
{
sum += x * x;
}
Console.WriteLine(sum);
}
else{
Console.WriteLine("Wrong input!");
}
Console.ReadLine();
}
}

A for loop should do it.
double nTotal = 0;
for (int a = 3; a <= 6; a++)
{
nTotal += Math.Pow(a, 2);
}

Get n distinct random numbers between two values whose sum is equal to a given number

I would like to find distinct random numbers within a range that sums up to given number.
Note: I found similar questions in stackoverflow, however they do not address exactly this problem (ie they do not consider a negative lowerLimit for the range).
If I wanted that the sum of my random number was equal to 1 I just generate the required random numbers, compute the sum and divided each of them by the sum; however here I need something a bit different; I will need my random numbers to add up to something different than 1 and still my random numbers must be within a given range.
Example: I need 30 distinct random numbers (non integers) between -50 and 50 where the sum of the 30 generated numbers must be equal to 300; I wrote the code below, however it will not work when n is much larger than the range (upperLimit - lowerLimit), the function could return numbers outside the range [lowerLimit - upperLimit]. Any help to improve the current solution?
static void Main(string[] args)
{
var listWeights = GetRandomNumbersWithConstraints(30, 50, -50, 300);
}
private static List<double> GetRandomNumbersWithConstraints(int n, int upperLimit, int lowerLimit, int sum)
{
if (upperLimit <= lowerLimit || n < 1)
throw new ArgumentOutOfRangeException();
Random rand = new Random(Guid.NewGuid().GetHashCode());
List<double> weight = new List<double>();
for (int k = 0; k < n; k++)
{
//multiply by rand.NextDouble() to avoid duplicates
double temp = (double)rand.Next(lowerLimit, upperLimit) * rand.NextDouble();
if (weight.Contains(temp))
k--;
else
weight.Add(temp);
}
//divide each element by the sum
weight = weight.ConvertAll<double>(x => x / weight.Sum()); //here the sum of my weight will be 1
return weight.ConvertAll<double>(x => x * sum);
}
EDIT - to clarify
Running the current code will generate the following 30 numbers that add up to 300. However those numbers are not within -50 and 50
-4.425315699
67.70219958
82.08592061
46.54014109
71.20352208
-9.554070146
37.65032717
-75.77280868
24.68786878
30.89874589
142.0796933
-1.964407284
9.831226893
-15.21652248
6.479463312
49.61283063
118.1853036
-28.35462683
49.82661159
-65.82706541
-29.6865969
-54.5134262
-56.04708803
-84.63783048
-3.18402453
-13.97935982
-44.54265204
112.774348
-2.911427266
-58.94098071

Ok, here how it could be done
We will use Dirichlet Distribution, which is distribution for random numbers xi in the range [0...1] such that
Sumi xi = 1
So, after linear rescaling condition for sum would be satisfied automatically. Dirichlet distribution is parametrized by αi, but we assume all RN to be from the same marginal distribution, so there is only one parameter α for each and every index.
For reasonable large value of α, mean value of sampled random numbers would be =1/n, and variance ~1/(n * α), so larger α lead to random value more close to the mean.
Ok, now back to rescaling,
vi = A + B*xi
And we have to get A and B. As #HansKesting rightfully noted, with only two free parameters we could satisfy only two constraints, but you have three. So we would strictly satisfy low bound constraint, sum value constraint, but occasionally violate upper bound constraint. In such case we just throw whole sample away and do another one.
Again, we have a knob to turn, α getting larger means we are close to mean values and less likely to hit upper bound. With α = 1 I'm rarely getting any good sample, but with α = 10 I'm getting close to 40% of good samples. With α = 16 I'm getting close to 80% of good samples.
Dirichlet sampling is done via Gamma distribution, using code from MathDotNet.
Code, tested with .NET Core 2.1
using System;
using MathNet.Numerics.Distributions;
using MathNet.Numerics.Random;
class Program
{
static void SampleDirichlet(double alpha, double[] rn)
{
if (rn == null)
throw new ArgumentException("SampleDirichlet:: Results placeholder is null");
if (alpha <= 0.0)
throw new ArgumentException($"SampleDirichlet:: alpha {alpha} is non-positive");
int n = rn.Length;
if (n == 0)
throw new ArgumentException("SampleDirichlet:: Results placeholder is of zero size");
var gamma = new Gamma(alpha, 1.0);
double sum = 0.0;
for(int k = 0; k != n; ++k) {
double v = gamma.Sample();
sum += v;
rn[k] = v;
}
if (sum <= 0.0)
throw new ApplicationException($"SampleDirichlet:: sum {sum} is non-positive");
// normalize
sum = 1.0 / sum;
for(int k = 0; k != n; ++k) {
rn[k] *= sum;
}
}
static bool SampleBoundedDirichlet(double alpha, double sum, double lo, double hi, double[] rn)
{
if (rn == null)
throw new ArgumentException("SampleDirichlet:: Results placeholder is null");
if (alpha <= 0.0)
throw new ArgumentException($"SampleDirichlet:: alpha {alpha} is non-positive");
if (lo >= hi)
throw new ArgumentException($"SampleDirichlet:: low {lo} is larger than high {hi}");
int n = rn.Length;
if (n == 0)
throw new ArgumentException("SampleDirichlet:: Results placeholder is of zero size");
double mean = sum / (double)n;
if (mean < lo || mean > hi)
throw new ArgumentException($"SampleDirichlet:: mean value {mean} is not within [{lo}...{hi}] range");
SampleDirichlet(alpha, rn);
bool rc = true;
for(int k = 0; k != n; ++k) {
double v = lo + (mean - lo)*(double)n * rn[k];
if (v > hi)
rc = false;
rn[k] = v;
}
return rc;
}
static void Main(string[] args)
{
double[] rn = new double [30];
double lo = -50.0;
double hi = 50.0;
double alpha = 10.0;
double sum = 300.0;
for(int k = 0; k != 1_000; ++k) {
var q = SampleBoundedDirichlet(alpha, sum, lo, hi, rn);
Console.WriteLine($"Rng(BD), v = {q}");
double s = 0.0;
foreach(var r in rn) {
Console.WriteLine($"Rng(BD), r = {r}");
s += r;
}
Console.WriteLine($"Rng(BD), summa = {s}");
}
}
}
UPDATE
Usually, when people ask such question, there is an implicit assumption/requirement - all random numbers shall be distribution in the same way. It means that if I draw marginal probability density function (PDF) for item indexed 0 from the sampled array, I shall get the same distribution as I draw marginal probability density function for the last item in the array. People usually sample random arrays to pass it down to other routines to do some interesting stuff. If marginal PDF for item 0 is different from marginal PDF for last indexed item, then just reverting array will produce wildly different result with the code which uses such random values.
Here I plotted distributions of random numbers for item 0 and last item (#29) for original conditions([-50...50] sum=300), using my sampling routine. Look similar, isn't it?
Ok, here is a picture from your sampling routine, same original conditions([-50...50] sum=300), same number of samples
UPDATE II
User supposed to check return value of the sampling routine and accept and use sampled array if (and only if) return value is true. This is acceptance/rejection method. As an illustration, below is code used to histogram samples:
int[] hh = new int[100]; // histogram allocated
var s = 1.0; // step size
int k = 0; // good samples counter
for( ;; ) {
var q = SampleBoundedDirichlet(alpha, sum, lo, hi, rn);
if (q) // good sample, accept it
{
var v = rn[0]; // any index, 0 or 29 or ....
var i = (int)((v - lo) / s);
i = System.Math.Max(i, 0);
i = System.Math.Min(i, hh.Length-1);
hh[i] += 1;
++k;
if (k == 100000) // required number of good samples reached
break;
}
}
for(k = 0; k != hh.Length; ++k)
{
var x = lo + (double)k * s + 0.5*s;
var v = hh[k];
Console.WriteLine($"{x} {v}");
}

Here you go. It'll probably run for centuries before actually returning the list, but it'll comply :)
public List<double> TheThing(int qty, double lowest, double highest, double sumto)
{
if (highest * qty < sumto)
{
throw new Exception("Impossibru!");
// heresy
highest = sumto / 1 + (qty * 2);
lowest = -highest;
}
double rangesize = (highest - lowest);
Random r = new Random();
List<double> ret = new List<double>();
while (ret.Sum() != sumto)
{
if (ret.Count > 0)
ret.RemoveAt(0);
while (ret.Count < qty)
ret.Add((r.NextDouble() * rangesize) + lowest);
}
return ret;
}

I come up with this solution which is fast. I am sure it couldbe improved, but for the moment it does the job.
n = the number of random numbers that I will need to find
Constraints
the n random numbers must add up to finalSum the n random numbers
the n random numbers must be within lowerLimit and upperLimit
The idea is to remove from the initial list (that sums up to finalSum) of random numbers the numbers outside the range [lowerLimit, upperLimit].
Then count the number left of the list (called nValid) and their sum (called sumOfValid).
Now, iteratively search for (n-nValid) random numbers within the range [lowerLimit, upperLimit] whose sum is (finalSum-sumOfValid)
I tested it with several combinations for the inputs variables (including negative sum) and the results looks good.
static void Main(string[] args)
{
int n = 100;
int max = 5000;
int min = -500000;
double finalSum = -1000;
for (int i = 0; i < 5000; i++)
{
var listWeights = GetRandomNumbersWithConstraints(n, max, min, finalSum);
Console.WriteLine("=============");
Console.WriteLine("sum = " + listWeights.Sum());
Console.WriteLine("max = " + listWeights.Max());
Console.WriteLine("min = " + listWeights.Min());
Console.WriteLine("count = " + listWeights.Count());
}
}
private static List<double> GetRandomNumbersWithConstraints(int n, int upperLimit, int lowerLimit, double finalSum, int precision = 6)
{
if (upperLimit <= lowerLimit || n < 1) //todo improve here
throw new ArgumentOutOfRangeException();
Random rand = new Random(Guid.NewGuid().GetHashCode());
List<double> randomNumbers = new List<double>();
int adj = (int)Math.Pow(10, precision);
bool flag = true;
List<double> weights = new List<double>();
while (flag)
{
foreach (var d in randomNumbers.Where(x => x <= upperLimit && x >= lowerLimit).ToList())
{
if (!weights.Contains(d)) //only distinct
weights.Add(d);
}
if (weights.Count() == n && weights.Max() <= upperLimit && weights.Min() >= lowerLimit && Math.Round(weights.Sum(), precision) == finalSum)
return weights;
/* worst case - if the largest sum of the missing elements (ie we still need to find 3 elements,
* then the largest sum is 3*upperlimit) is smaller than (finalSum - sumOfValid)
*/
if (((n - weights.Count()) * upperLimit < (finalSum - weights.Sum())) ||
((n - weights.Count()) * lowerLimit > (finalSum - weights.Sum())))
{
weights = weights.Where(x => x != weights.Max()).ToList();
weights = weights.Where(x => x != weights.Min()).ToList();
}
int nValid = weights.Count();
double sumOfValid = weights.Sum();
int numberToSearch = n - nValid;
double sum = finalSum - sumOfValid;
double j = finalSum - weights.Sum();
if (numberToSearch == 1 && (j <= upperLimit || j >= lowerLimit))
{
weights.Add(finalSum - weights.Sum());
}
else
{
randomNumbers.Clear();
int min = lowerLimit;
int max = upperLimit;
for (int k = 0; k < numberToSearch; k++)
{
randomNumbers.Add((double)rand.Next(min * adj, max * adj) / adj);
}
if (sum != 0 && randomNumbers.Sum() != 0)
randomNumbers = randomNumbers.ConvertAll<double>(x => x * sum / randomNumbers.Sum());
}
}
return randomNumbers;
}