Project euler number 10# - c#

The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17.
Find the sum of all the primes below two million.
And my answer is:
bool IsRishoni;
int soap = 0;
for (int i = 3; i < 2000000; i++)
{
IsRishoni = true;
for (int a = 2; (a <= Math.Sqrt(i)) && (IsRishoni); a++)
{
if (i % a == 0)
IsRishoni = false;
}
if (IsRishoni)
{
soap = i + soap;
}
}
Console.WriteLine(soap + 2);
Console.ReadLine();
Why is this not working? the answer I got is 1179908154 ... help please.

Replace
soap = i + soap;
with
soap = checked(i + soap);
..and the problem should be exposed.
This question has more details: No overflow exception for int in C#?

Your answer (stored in soap) is a value greater than int.Maxvalue (2,147,483,647).
Your answer is ~ 150,000,000,000
In other words you need to use an data type which is bigger than that.
long.MaxValue = 9,223,372,036,854,775,807
int.Maxvalue = 2,147,483,647

The result you’re after might be too large to represent through a 32-bit signed integer (int).
Let’s first determine the result’s upper bound by assuming that all numbers are prime. Through summation, we know that the sum of all numbers up to N (inclusive) is N * (N + 1) / 2; thus, the upper bound for the sum of all primes up to 2,000,000 is 2,000,001,000,000. This is larger than the maximum value allowed by int, 2,147,483,647, so you’re probably getting a numeric overflow which is silently ignored.
If you wanted a more accurate estimate of your answer, you could use the prime number theorem, which states that the probability of a random integer between 0 and N being prime is approximately 1 / ln(N). Combining this with our previous formula, the approximate sum of all primes up to N is N * (N + 1) / (2 * ln(N)). For 2,000,000, this evaluates to around 138,000,000,000, which is still larger than the maximum value for int.
To resolve your problem, you could simply switch the integral data type you’re using for the soap variable to a 64-bit integer representation, such as long. Its maximum value is 9,223,372,036,854,775,807, so it would definitely be able to represent your number.
long soap = 0;
On a separate note: Since you’re working with sequences of primes, you could achieve a huge performance gain (at least 100×) if you change your implementation to a Sieve of Eratosthenes.

Related

Can someone explain how Dmitry got the NMin math down?

The original problem is located at Project Euler Largest palindrome product and is below.
A palindromic number reads the same both ways. The largest palindrome made from the product of two 2-digit numbers is 9009 = 91 × 99. Find the largest palindrome made from the product of two 3-digit numbers.
The question in context is found at
Dmitry Answering Largest palindrome product - C#. I got the correct answer but did it from min to max instead of max to min so I looked for a more efficient answer to study. I understand what all the code does, but I can't figure out where Dmitry started to get the formula to get the minimum multiplicand from the maximum multiplicand constant. I'm blitzing through several coding challenge websites in preparation for some technical interviews.
This line:
const int NMin = NMax - (NMax + 1) / 10 + 1;
OF
// Store the maximum palindrome number here:
long maxNumber = 0;
// The maximum multiplicand (typically: 9...9):
const int NMax = 999;
// The minimum multiplicand.
// Obviously, it couldn't be less than 90...0:
const int NMin = NMax - (NMax + 1) / 10 + 1;
for (int i = NMax; i > NMin; i--)
{
// Starting from i since i * j = j * i for any i, j:
for (int j = i; j > NMin; j--)
{
long number = Math.BigMul(i, j);
// The fastest condition should be the first in the `if` statement:
if (number > maxNumber && isPalindome(number))
{
maxNumber = number;
Console.WriteLine("{0} = {1} * {2}", number, i, j);
break; // Leave the `j` loop, because it's guaranteed that there is
// no numbers greater than `number` for the current `i`
}
}
}
The websites I've been going through include:
Advent Of Code
HackerEarth and HackerRank
Leetcode I've been attempting to finish the Comprehensive Study Plans
Project Euler Only on Problem #4 right now
As stated in problem 4 the largest palindrome for the product of two-digit numbers is 91*99. I believe Dmitry recognized that of all max palindromes for a given digit range (3, 4, or 5 as he calculated but realistically to infinity) must be 9x -> 9y (where x represents 0's and y represents 9's). The amount of x and y needed is digit - 1 if you always want the highest palindrome. The lower 90% here is simply not worth checking for palindromes because they won't produce the highest multiplication.
Thus he can calculate the minimum every time given the equation he provided:
NMin = NMax - (NMax + 1) / 10 + 1 // NMin = 900 if NMax = 999
In the case of 4-digit palindrome, this produces 9,000 -> 9,999 or 90,000 -> 99,999 for 5.
The important thing to note here is he could have hard-coded NMin or picked a larger minimum number.

Request for explanation of for-loop logic as it is applied in this C# armstrong number checker

Homework alert! I am trying to build a console app to determine whether a given integer is an Armstrong number. I found a working solution online, but after spending far too much time analyzing it, I still don't understand the logic well enough to reproduce it on my own... The two pain points I've identified are 1) I do not understand exactly how the Parse method is acting upon the integer that the user inputs, and 2) the logic sequence of the for loop is not self-evident (see code and my logic description below):
int number, remainder, sum = 0;
Console.WriteLine("Enter a number: ");
number = int.Parse(Console.ReadLine());
for (int i = number; i > 0; i = i / 10)
{
remainder = i % 10;
sum = sum + remainder * remainder * remainder;
}
if (sum == number)
{
Console.Write("Entered Number is an Armstrong Number");
}
else
Console.Write("Entered Number is not an Armstrong Number");
Console.ReadLine();
This is how my understanding of the for loop logic breaks down:
The integer is passed into the for loop and assigned to int i
//e.g. i = 153//
If the value of i is greater than 0, then re-assign the value of i to i/10 //e.g. 153/10 == 15r3 //
Assign the remainder value of i/10 to int remainder //e.g. remainder = 3//
Compute the sum as sum + remainder * remainder * remainder //e.g. sum = 0 + 3 * 3 * 3//
if the sum is equal to the number, then print "Entered number is Armstrong number" //e.g. however, 27 !== 153//
What am I missing here?
Since this is self-admitted homework, I'm not going to give you a complete answer, but pointers instead.
Make number a string variable. You can then use your for loop to go through each character in the string and perform the math on them.
Use math.pow to create your sum, not sum = sum + remainder * remainder * remainder, since this makes the assumption that you are always using a 3-digit number. (hint: int N = number.Length()
Helper links:
math.pow
Armstrong Numbers

Average function without overflow exception

.NET Framework 3.5.
I'm trying to calculate the average of some pretty large numbers.
For instance:
using System;
using System.Linq;
class Program
{
static void Main(string[] args)
{
var items = new long[]
{
long.MaxValue - 100,
long.MaxValue - 200,
long.MaxValue - 300
};
try
{
var avg = items.Average();
Console.WriteLine(avg);
}
catch (OverflowException ex)
{
Console.WriteLine("can't calculate that!");
}
Console.ReadLine();
}
}
Obviously, the mathematical result is 9223372036854775607 (long.MaxValue - 200), but I get an exception there. This is because the implementation (on my machine) to the Average extension method, as inspected by .NET Reflector is:
public static double Average(this IEnumerable<long> source)
{
if (source == null)
{
throw Error.ArgumentNull("source");
}
long num = 0L;
long num2 = 0L;
foreach (long num3 in source)
{
num += num3;
num2 += 1L;
}
if (num2 <= 0L)
{
throw Error.NoElements();
}
return (((double) num) / ((double) num2));
}
I know I can use a BigInt library (yes, I know that it is included in .NET Framework 4.0, but I'm tied to 3.5).
But I still wonder if there's a pretty straight forward implementation of calculating the average of integers without an external library. Do you happen to know about such implementation?
Thanks!!
UPDATE:
The previous example, of three large integers, was just an example to illustrate the overflow issue. The question is about calculating an average of any set of numbers which might sum to a large number that exceeds the type's max value. Sorry about this confusion. I also changed the question's title to avoid additional confusion.
Thanks all!!
This answer used to suggest storing the quotient and remainder (mod count) separately. That solution is less space-efficient and more code-complex.
In order to accurately compute the average, you must keep track of the total. There is no way around this, unless you're willing to sacrifice accuracy. You can try to store the total in fancy ways, but ultimately you must be tracking it if the algorithm is correct.
For single-pass algorithms, this is easy to prove. Suppose you can't reconstruct the total of all preceding items, given the algorithm's entire state after processing those items. But wait, we can simulate the algorithm then receiving a series of 0 items until we finish off the sequence. Then we can multiply the result by the count and get the total. Contradiction. Therefore a single-pass algorithm must be tracking the total in some sense.
Therefore the simplest correct algorithm will just sum up the items and divide by the count. All you have to do is pick an integer type with enough space to store the total. Using a BigInteger guarantees no issues, so I suggest using that.
var total = BigInteger.Zero
var count = 0
for i in values
count += 1
total += i
return total / (double)count //warning: possible loss of accuracy, maybe return a Rational instead?
If you're just looking for an arithmetic mean, you can perform the calculation like this:
public static double Mean(this IEnumerable<long> source)
{
if (source == null)
{
throw Error.ArgumentNull("source");
}
double count = (double)source.Count();
double mean = 0D;
foreach(long x in source)
{
mean += (double)x/count;
}
return mean;
}
Edit:
In response to comments, there definitely is a loss of precision this way, due to performing numerous divisions and additions. For the values indicated by the question, this should not be a problem, but it should be a consideration.
You may try the following approach:
let number of elements is N, and numbers are arr[0], .., arr[N-1].
You need to define 2 variables:
mean and remainder.
initially mean = 0, remainder = 0.
at step i you need to change mean and remainder in the following way:
mean += arr[i] / N;
remainder += arr[i] % N;
mean += remainder / N;
remainder %= N;
after N steps you will get correct answer in mean variable and remainder / N will be fractional part of the answer (I am not sure you need it, but anyway)
If you know approximately what the average will be (or, at least, that all pairs of numbers will have a max difference < long.MaxValue), you can calculate the average difference from that value instead. I take an example with low numbers, but it works equally well with large ones.
// Let's say numbers cannot exceed 40.
List<int> numbers = new List<int>() { 31 28 24 32 36 29 }; // Average: 30
List<int> diffs = new List<int>();
// This can probably be done more effectively in linq, but to show the idea:
foreach(int number in numbers.Skip(1))
{
diffs.Add(numbers.First()-number);
}
// diffs now contains { -3 -6 1 5 -2 }
var avgDiff = diffs.Sum() / diffs.Count(); // the average is -1
// To get the average value, just add the average diff to the first value:
var totalAverage = numbers.First()+avgDiff;
You can of course implement this in some way that makes it easier to reuse, for example as an extension method to IEnumerable<long>.
Here is how I would do if given this problem. First let's define very simple RationalNumber class, which contains two properties - Dividend and Divisor and an operator for adding two complex numbers. Here is how it looks:
public sealed class RationalNumber
{
public RationalNumber()
{
this.Divisor = 1;
}
public static RationalNumberoperator +( RationalNumberc1, RationalNumber c2 )
{
RationalNumber result = new RationalNumber();
Int64 nDividend = ( c1.Dividend * c2.Divisor ) + ( c2.Dividend * c1.Divisor );
Int64 nDivisor = c1.Divisor * c2.Divisor;
Int64 nReminder = nDividend % nDivisor;
if ( nReminder == 0 )
{
// The number is whole
result.Dividend = nDividend / nDivisor;
}
else
{
Int64 nGreatestCommonDivisor = FindGreatestCommonDivisor( nDividend, nDivisor );
if ( nGreatestCommonDivisor != 0 )
{
nDividend = nDividend / nGreatestCommonDivisor;
nDivisor = nDivisor / nGreatestCommonDivisor;
}
result.Dividend = nDividend;
result.Divisor = nDivisor;
}
return result;
}
private static Int64 FindGreatestCommonDivisor( Int64 a, Int64 b)
{
Int64 nRemainder;
while ( b != 0 )
{
nRemainder = a% b;
a = b;
b = nRemainder;
}
return a;
}
// a / b = a is devidend, b is devisor
public Int64 Dividend { get; set; }
public Int64 Divisor { get; set; }
}
Second part is really easy. Let's say we have an array of numbers. Their average is estimated by Sum(Numbers)/Length(Numbers), which is the same as Number[ 0 ] / Length + Number[ 1 ] / Length + ... + Number[ n ] / Length. For to be able to calculate this we will represent each Number[ i ] / Length as a whole number and a rational part ( reminder ). Here is how it looks:
Int64[] aValues = new Int64[] { long.MaxValue - 100, long.MaxValue - 200, long.MaxValue - 300 };
List<RationalNumber> list = new List<RationalNumber>();
Int64 nAverage = 0;
for ( Int32 i = 0; i < aValues.Length; ++i )
{
Int64 nReminder = aValues[ i ] % aValues.Length;
Int64 nWhole = aValues[ i ] / aValues.Length;
nAverage += nWhole;
if ( nReminder != 0 )
{
list.Add( new RationalNumber() { Dividend = nReminder, Divisor = aValues.Length } );
}
}
RationalNumber rationalTotal = new RationalNumber();
foreach ( var rational in list )
{
rationalTotal += rational;
}
nAverage = nAverage + ( rationalTotal.Dividend / rationalTotal.Divisor );
At the end we have a list of rational numbers, and a whole number which we sum together and get the average of the sequence without an overflow. Same approach can be taken for any type without an overflow for it, and there is no lost of precision.
EDIT:
Why this works:
Define: A set of numbers.
if Average( A ) = SUM( A ) / LEN( A ) =>
Average( A ) = A[ 0 ] / LEN( A ) + A[ 1 ] / LEN( A ) + A[ 2 ] / LEN( A ) + ..... + A[ N ] / LEN( 2 ) =>
if we define An to be a number that satisfies this: An = X + ( Y / LEN( A ) ), which is essentially so because if you divide A by B we get X with a reminder a rational number ( Y / B ).
=> so
Average( A ) = A1 + A2 + A3 + ... + AN = X1 + X2 + X3 + X4 + ... + Reminder1 + Reminder2 + ...;
Sum the whole parts, and sum the reminders by keeping them in rational number form. In the end we get one whole number and one rational, which summed together gives Average( A ). Depending on what precision you'd like, you apply this only to the rational number at the end.
Simple answer with LINQ...
var data = new[] { int.MaxValue, int.MaxValue, int.MaxValue };
var mean = (int)data.Select(d => (double)d / data.Count()).Sum();
Depending on the size of the set fo data you may want to force data .ToList() or .ToArray() before your process this method so it can't requery count on each pass. (Or you can call it before the .Select(..).Sum().)
If you know in advance that all your numbers are going to be 'big' (in the sense of 'much nearer long.MaxValue than zero), you can calculate the average of their distance from long.MaxValue, then the average of the numbers is long.MaxValue less that.
However, this approach will fail if (m)any of the numbers are far from long.MaxValue, so it's horses for courses...
I guess there has to be a compromise somewhere or the other. If the numbers are really getting so large then few digits of lower orders (say lower 5 digits) might not affect the result as much.
Another issue is where you don't really know the size of the dataset coming in, especially in stream/real time cases. Here I don't see any solution other then the
(previousAverage*oldCount + newValue) / (oldCount <- oldCount+1)
Here's a suggestion:
*LargestDataTypePossible* currentAverage;
*SomeSuitableDatatypeSupportingRationalValues* newValue;
*int* count;
addToCurrentAverage(value){
newValue = value/100000;
count = count + 1;
currentAverage = (currentAverage * (count-1) + newValue) / count;
}
getCurrentAverage(){
return currentAverage * 100000;
}
Averaging numbers of a specific numeric type in a safe way while also only using that numeric type is actually possible, although I would advise using the help of BigInteger in a practical implementation. I created a project for Safe Numeric Calculations that has a small structure (Int32WithBoundedRollover) which can sum up to 2^32 int32s without any overflow (the structure internally uses two int32 fields to do this, so no larger data types are used).
Once you have this sum you then need to calculate sum/total to get the average, which you can do (although I wouldn't recommend it) by creating and then incrementing by total another instance of Int32WithBoundedRollover. After each increment you can compare it to the sum until you find out the integer part of the average. From there you can peel off the remainder and calculate the fractional part. There are likely some clever tricks to make this more efficient, but this basic strategy would certainly work without needing to resort to a bigger data type.
That being said, the current implementation isn't build for this (for instance there is no comparison operator on Int32WithBoundedRollover, although it wouldn't be too hard to add). The reason is that it is just much simpler to use BigInteger at the end to do the calculation. Performance wise this doesn't matter too much for large averages since it will only be done once, and it is just too clean and easy to understand to worry about coming up with something clever (at least so far...).
As far as your original question which was concerned with the long data type, the Int32WithBoundedRollover could be converted to a LongWithBoundedRollover by just swapping int32 references for long references and it should work just the same. For Int32s I did notice a pretty big difference in performance (in case that is of interest). Compared to the BigInteger only method the method that I produced is around 80% faster for the large (as in total number of data points) samples that I was testing (the code for this is included in the unit tests for the Int32WithBoundedRollover class). This is likely mostly due to the difference between the int32 operations being done in hardware instead of software as the BigInteger operations are.
How about BigInteger in Visual J#.
If you're willing to sacrifice precision, you could do something like:
long num2 = 0L;
foreach (long num3 in source)
{
num2 += 1L;
}
if (num2 <= 0L)
{
throw Error.NoElements();
}
double average = 0;
foreach (long num3 in source)
{
average += (double)num3 / (double)num2;
}
return average;
Perhaps you can reduce every item by calculating average of adjusted values and then multiply it by the number of elements in collection. However, you'll find a bit different number of of operations on floating point.
var items = new long[] { long.MaxValue - 100, long.MaxValue - 200, long.MaxValue - 300 };
var avg = items.Average(i => i / items.Count()) * items.Count();
You could keep a rolling average which you update once for each large number.
Use the IntX library on CodePlex.
NextAverage = CurrentAverage + (NewValue - CurrentAverage) / (CurrentObservations + 1)
Here is my version of an extension method that can help with this.
public static long Average(this IEnumerable<long> longs)
{
long mean = 0;
long count = longs.Count();
foreach (var val in longs)
{
mean += val / count;
}
return mean;
}
Let Avg(n) be the average in first n number, and data[n] is the nth number.
Avg(n)=(double)(n-1)/(double)n*Avg(n-1)+(double)data[n]/(double)n
Can avoid value overflow however loss precision when n is very large.
For two positive numbers (or two negative numbers) , I found a very elegant solution from here.
where an average computation of (a+b)/2 can be replaced with a+((b-a)/2.

How to convert number to next higher multiple of five?

I am coding a program where a form opens for a certain period of time before closing. I am giving the users to specify the time in seconds. But i'd like this to be in mutliples of five. Or the number gets rounded off to the nearest multiple.
if they enter 1 - 4, then the value is automatically set to 5.
If they enter 6 - 10 then the value is automatically set to 10.
max value is 60, min is 0.
what i have, but i am not happy with this logic since it resets it to 10 seconds.
if (Convert.ToInt32(maskedTextBox1.Text) >= 60 || Convert.ToInt32(maskedTextBox1.Text) <= 0)
mySettings.ToastFormTimer = 10000;
else
mySettings.ToastFormTimer = Convert.ToInt32 (maskedTextBox1.Text) * 1000;
use the Modulus Operator
if(num % 5 == 0)
{
// the number is a multiple of 5.
}
what about this:
int x = int.Parse(maskedTextBox1.Text)/5;
int y = Math.Min(Math.Max(x,1),12)*5; // between [5,60]
// use y as the answer you need
5 * ((num - 1) / 5 + 1)
Should work if c# does integer division.
For the higher goal of rounding to the upper multiple of 5, you don't need to test whether a number is a multiple. Generally speaking, you can round-up or round-to-nearest by adding a constant, then rounding down. To round up, the constant is one less than n. Rounding an integer down to a multiple of n is simple: divide by n and multiply the result by n. Here's a case where rounding error works in your favor.
int ceil_n(int x, int n) {
return ((x+n-1) / n) * n;
}
In dynamic languages that cast the result of integer division to prevent rounding error (which doesn't include C#), you'd need to cast the quotient back to an integer.
Dividing by n can be viewed as a right-shift by 1 place in base n; similarly, multiplying by n is equivalent to a left-shift by 1. This is why the above approach works: it sets the least-significant digit of the number in base n to 0.
2410=445, 2510=505, 2610=515
((445+4 = 535) >>5 1) <<5 1 = 505 = 2510
((505+4 = 545) >>5 1) <<5 1 = 505 = 2510
((515+4 = 605) >>5 1) <<5 1 = 605 = 3010
Another way of zeroing the LSD is to subtract the remainder to set the least significant base n digit to 0, as Jeras does in his comment.
int ceil_n(int x, int n) {
x += n-1;
return x - x%n;
}

Evenly divide a dollar amount (decimal) by an integer

I need to write an accounting routine for a program I am building that will give me an even division of a decimal by an integer. So that for example:
$143.13 / 5 =
28.62
28.62
28.63
28.63
28.63
I have seen the article here: Evenly divide in c#, but it seems like it only works for integer divisions. Any idea of an elegant solution to this problem?
Calculate the amounts one at a time, and subtract each amount from the total to make sure that you always have the correct total left:
decimal total = 143.13m;
int divider = 5;
while (divider > 0) {
decimal amount = Math.Round(total / divider, 2);
Console.WriteLine(amount);
total -= amount;
divider--;
}
result:
28,63
28,62
28,63
28,62
28,63
You can solve this (in cents) without constructing an array:
int a = 100 * amount;
int low_value = a / n;
int high_value = low_value + 1;
int num_highs = a % n;
int num_lows = n - num_highs;
It's easier to deal with cents. I would suggest that instead of 143.13, you divide 14313 into 5 equal parts. Which gives you 2862 and a remainder of 3. You can assign this remainder to the first three parts or any way you like. Finally, convert the cents back to dollars.
Also notice that you will always get a remainder less than the number of parts you want.
First of all, make sure you don't use a floating point number to represent dollars and cents (see other posts for why, but the simple reason is that not all decimal numbers can be represented as floats, e.g., $1.79).
Here's one way of doing it:
decimal total = 143.13m;
int numberOfEntries = 5;
decimal unadjustedEntryAmount = total / numberOfEntries;
decimal leftoverAmount = total - (unadjustedEntryAmount * numberOfEntries);
int numberOfPenniesToDistribute = leftoverAmount * 100;
int numberOfUnadjustedEntries = numberOfEntries - numberOfPenniesToDistribute;
So now you have the unadjusted amounts of 28.62, and then you have to decide how to distribute the remainder. You can either distribute an extra penny to each one starting at the top or at the bottom (looks like you want from the bottom).
for (int i = 0; i < numberOfUnadjustedEntries; i++) {
Console.WriteLine(unadjustedEntryAmount);
}
for (int i = 0; i < numberOfPenniesToDistribute; i++) {
Console.WriteLine(unadjustedEntryAmount + 0.01m);
}
You could also add the entire remainder to the first or last entries. Finally, depending on the accounting needs, you could also create a separate transaction for the remainder.
If you have a float that is guaranteed exactly two digits of precision, what about this (pseudocode):
amount = amount * 100 (convert to cents)
int[] amounts = new int[divisor]
for (i = 0; i < divisor; i++) amounts[i] = amount / divisor
extra = amount % divisor
for (i = 0; i < extra; i++) amounts[i]++
and then do whatever you want with amounts, which are in cents - you could convert back to floats if you absolutely had to, or format as dollars and cents.
If not clear, the point of all this is not just to divide a float value evenly but to divide a monetary amount as evenly as possible, given that cents are an indivisible unit of USD. To the OP: let me know if this isn't what you wanted.
You can use the algorithm in the question you're referencing by multipling by 100, using the integer evenly divide function, and then dividing each of the results by 100 (assuming you only want to handle 2 dp, if you want 3dp multiple by 1000 etc)
It is also possible to use C# iterator generation to make Guffa's answer more convenient:
public static IEnumerable<decimal> Divide(decimal amount, int numBuckets)
{
while(numBuckets > 0)
{
// determine the next amount to return...
var partialAmount = Math.Round(amount / numBuckets, 2);
yield return partialAmount;
// reduce th remaining amount and #buckets
// to account for previously yielded values
amount -= partialAmount;
numBuckets--;
}
}

Categories

Resources