I have this very simple function that checks the value of (N^N-1)^(N-2):
int main() {
// Declare Variables
double n;
double answer;
// Function
cout << "Please enter a double number >= 3: ";
cin >> n;
answer = pow(n,(n-1)*(n-2));
cout << "n to the n-1) to the n-2 for doubles is " << answer << endl;
}
Based on this formula, it is evident it will reach to infinity, but I am curious until what number/value of n would it hit infinity? Using a loop seems extremely inefficient, but that's all I can think of. Basically, creating a loop that says let n be a number between 1 - 100, iterate until n == inf
Is there a more efficient approach to this problem?
I think you are approaching this the wrong way.
Let : F(N) be the function (N^(N-1))(N-2)
Now you actually know whats the largest number that could be stored in a double type variable
is 0x 7ff0 0000 0000 0000 Double Precision
So now you have F(N) = max_double
just solve for X now.
Does this answer your question?
Two things: the first is that (N^(N-1))^(N-2)) can be written as N^((N-1)*(N-2)). So this would remove one pow call making your code faster.
pow(n, (n-1)*(n-2));
The second is that to know what practical limits you hit, testing all N will literally take a fraction of a second, so there really is no reason to find another practical way.
You could compute it by hand knowing variable size limits and all, but testing it is definitely faster. An example for code (C++11, since I use std::isinf):
#include <iostream>
#include <cmath>
#include <iomanip>
int main() {
double N = 1.0, diff = 10.0;
const unsigned digits = 10;
unsigned counter = digits;
while ( true ) {
double X = std::pow( N, (N-1.0) * (N-2.0) );
if ( std::isinf(X) ) {
--counter;
if ( !counter ) {
std::cout << std::setprecision(digits) << N << "\n";
break;
}
N -= diff;
diff /= 10;
}
N += diff;
}
return 0;
}
This example takes less than a millisecond on my computer, and prints 17.28894235
Related
I'm trying to compute math combinations. The formula I'm using is N! / K! (N-K)!.
I am able to get the right answer (10) with N=5, K=2, and 120 from N=10, K=3.
BUT when I tried to test with bigger number like N=50, K=5. The integer division by zero error popped out.
I tried to define finalAns with long int but it does not work as well. Any ideas?
int N;
int init;
int K;
int factN = 1;
int factK = 1;
double finalAns;
cout << "Input of N = ";
cin >> N;
cout << "Input of K = ";
cin >> K;
int subs = N - K;
int factsubs = 1;
for (init = 1; init <= N; init++)
{
factN = factN * init;
}
for (init = 1; init <= K; init++)
{
factK = factK * init;
}
cout << "K is " << factK << endl;
for (init = 1; init <= subs; init++)
{
factsubs = factsubs * init;
}
finalAns = factN / (factK * factsubs);
cout << N << "C" << K << " is " << finalAns << endl;
You need to change the multiply-at-one-go approach.
Don't calculate N! at one go.
Use the fact that division of any two positive integers reduces the end result, so favor division to have the lower intermediate values.
Expand the expression of N!/(N-K)! * K! to accommodate as much of division operation in intermediate steps as possible to lessen the chance of overflow.
Do not go for calculation of N! or (N-K)! or K! separately, you are more likely to face the overflow problem. Instead use the fact that eventually you need to divide the big numbers, why not do it before it becomes BIG!
More hints:
N!/(N-K)! = multiply i[N..N-K+1] one by one //not i[N..1]
and, check if any factor(f) of value j from [2..K] perfectly divides the intermediate-product-value(p), if yes, do the division : p = p/f and j = j/f.
10! is very big: 3.628.800 - if this one is big, just imagine 50!
Depending on what compiler you are using, you might handle preety good 15! using long long. However that is not big enough - so you need to do something else... You can make an algorithm for multiplication that returns a character array - there is no way to return a long int or something else like that.
My task is to ask the user to how many decimal places of accuracy they want the summation to iterate compared to the actual value of pi. So 2 decimal places would stop when the loop reaches 3.14. I have a complete program, but I am unsure if it actually works as intended. I have checked for 0 and 1 decimal places with a calculator and they seem to work, but I don't want to assume it works for all of them. Also my code may be a little clumsy since were are still learning the basics. We only just learned loops and nested loops. If there are any obvious mistakes or parts that could be cleaned up, I would appreciate any input.
Edit: I only needed to have this work for up to five decimal places. That is why my value of pi was not precise. Sorry for the misunderstanding.
#include <iostream>
#include <cmath>
using namespace std;
int main() {
const double PI = 3.141592;
int n, sign = 1;
double sum = 0,test,m;
cout << "This program determines how many iterations of the infinite series for\n"
"pi is needed to get with 'n' decimal places of the true value of pi.\n"
"How many decimal places of accuracy should there be?" << endl;
cin >> n;
double p = PI * pow(10.0, n);
p = static_cast<double>(static_cast<int>(p) / pow(10, n));
int counter = 0;
bool stop = false;
for (double i = 1;!stop;i = i+2) {
sum = sum + (1.0/ i) * sign;
sign = -sign;
counter++;
test = (4 * sum) * pow(10.0,n);
test = static_cast<double>(static_cast<int>(test) / pow(10, n));
if (test == p)
stop = true;
}
cout << "The series was iterated " << counter<< " times and reached the value of pi\nwithin "<< n << " decimal places." << endl;
return 0;
}
One of the problems of the Leibniz summation is that it has an extremely low convergence rate, as it exhibits sublinear convergence. In your program you also compare a calculated extimation of π with a given value (a 6 digits approximation), while the point of the summation should be to find out the right figures.
You can slightly modify your code to make it terminate the calculation if the wanted digit doesn't change between iterations (I also added a max number of iterations check). Remember that you are using doubles not unlimited precision numbers and sooner or later rounding errors will affect the calculation. As a matter of fact, the real limitation of this code is the number of iterations it takes (2,428,700,925 to obtain 3.141592653).
#include <iostream>
#include <cmath>
#include <iomanip>
using std::cout;
// this will take a long long time...
const unsigned long long int MAX_ITER = 100000000000;
int main() {
int n;
cout << "This program determines how many iterations of the infinite series for\n"
"pi is needed to get with 'n' decimal places of the true value of pi.\n"
"How many decimal places of accuracy should there be?\n";
std::cin >> n;
// precalculate some values
double factor = pow(10.0,n);
double inv_factor = 1.0 / factor;
double quad_factor = 4.0 * factor;
long long int test = 0, old_test = 0, sign = 1;
unsigned long long int count = 0;
double sum = 0;
for ( long long int i = 1; count < MAX_ITER; i += 2 ) {
sum += 1.0 / (i * sign);
sign = -sign;
old_test = test;
test = static_cast<long long int>(sum * quad_factor);
++count;
// perform the test on integer values
if ( test == old_test ) {
cout << "Reached the value of Pi within "<< n << " decimal places.\n";
break;
}
}
double pi_leibniz = static_cast<double>(inv_factor * test);
cout << "Pi = " << std::setprecision(n+1) << pi_leibniz << '\n';
cout << "The series was iterated " << count << " times\n";
return 0;
}
I have summarized the results of several runs in this table:
digits Pi iterations
---------------------------------------
0 3 8
1 3.1 26
2 3.14 628
3 3.141 2,455
4 3.1415 136,121
5 3.14159 376,848
6 3.141592 2,886,751
7 3.1415926 21,547,007
8 3.14159265 278,609,764
9 3.141592653 2,428,700,925
10 3.1415926535 87,312,058,383
Your program will never terminate, because test==p will never be true. This is a comparison between two double-precision numbers that are calculated differently. Due to round-off errors, they will not be identical, even if you run an infinite number of iterations, and your math is correct (and right now it isn't, because the value of PI in your program is not accurate).
To help you figure out what's going on, print the value of test in each iteration, as well as the distance between test and pi, as follows:
#include<iostream>
using namespace std;
void main() {
double pi = atan(1.0) * 4; // Make sure you have a precise value of PI
double sign = 1.0, sum = 0.0;
for (int i = 1; i < 1000; i += 2) {
sum = sum + (1.0 / i) * sign;
sign = -sign;
double test = 4 * sum;
cout << test << " " << fabs(test - pi) << "\n";
}
}
After you make sure the program works well, change the stopping condition eventually to be based on the distance between test and pi.
for (int i=1; fabs(test-pi)>epsilon; i+=2)
I am trying to generate a number of series of double random numbers with high precision. For example, 0.856365621 (has 9 digits after decimal).
I've found some methods from internet, however, they do generate double random number, but the precision is not as good as I request (only 6 digits after the decimal).
Thus, may I know how to achieve my goal?
In C++11 you can using the <random> header and in this specific example using std::uniform_real_distribution I am able to generate random numbers with more than 6 digits. In order to see set the number of digits that will be printed via std::cout we need to use std::setprecision:
#include <iostream>
#include <random>
#include <iomanip>
int main()
{
std::random_device rd;
std::mt19937 e2(rd());
std::uniform_real_distribution<> dist(1, 10);
for( int i = 0 ; i < 10; ++i )
{
std::cout << std::fixed << std::setprecision(10) << dist(e2) << std::endl ;
}
return 0 ;
}
you can use std::numeric_limits::digits10 to determine the precision available.
std::cout << std::numeric_limits<double>::digits10 << std::endl;
In a typical system, RAND_MAX is 231-1 or something similar to that. So your "precision" from using a method like:L
double r = rand()/RAND_MAX;
would be 1/(2<sup>31</sup)-1 - this should give you 8-9 digits "precision" in the random number. Make sure you print with high enough precision:
cout << r << endl;
will not do. This will work better:
cout << fixed << sprecision(15) << r << endl;
Of course, there are some systems out there with much smaller RAND_MAX, in which case the results may be less "precise" - however, you should still get digits down in the 9-12 range, just that they are more likely to be "samey".
Why not create your value out of multiple calls of the random function instead?
For instance:
const int numDecimals = 9;
double result = 0.0;
double div = 1.0;
double mul = 1.0;
for (int n = 0; n < numDecimals; ++n)
{
int t = rand() % 10;
result += t * mul;
mul *= 10.0;
div /= 10.0;
}
result = result * div;
I would personally try a new implementation of the rand function though or at least multiply with the current time or something..
In my case, I'm using MQL5, a very close derivative of C++ for a specific market, whose only random generator produces a random integer from 0 to 32767 (= (2^15)-1). Far too low precision.
So I've adapted his idea -- randomly generate a string of digits any length I want -- to solve my problem, more reliably (and arguably more randomly also), than anything else I can find or think of. My version builds a string and converts it to a double at the end -- avoids any potential math/rounding errors along the way (because we all know 0.1 + 0.2 != 0.3 😉 )
Posting it here in case it helps anyone.
(Disclaimer: The following is valid MQL5. MQL5 and C++ are very close, but some differences. eg. No RAND_MAX constant (so I've hard-coded the 32767). I'm not entirely sure of all the differences, so there may be C++ syntax errors here. Please adapt accordingly).
const int RAND_MAX_INCL = 32767;
const int RAND_MAX_EXCL = RAND_MAX_INCL + 1;
int iRandomDigit() {
const double dRand = rand()/RAND_MAX_EXCL; // double 0.0 <= dRand < 1.0
return (int)(dRand * 10); // int 0 <= result < 10
};
double dRandom0IncTo1Exc(const int iPrecisionDigits) {
int iPrecisionDigits2 = iPrecisionDigits;
if ( iPrecisionDigits > DBL_DIG ) { // DBL_DIG == "Number of significant decimal digits for double type"
Print("WARNING: Can't generate random number with precision > ", DBL_DIG, ". Adjusted precision to ", DBL_DIG, " accordingly.");
iPrecisionDigits2 = DBL_DIG;
};
string sDigits = "";
for (int i = 0; i < iPrecisionDigits2; i++) {
sDigits += (string)iRandomDigit();
};
const string sResult = "0." + sDigits;
const double dResult = StringToDouble(sResult);
return dResult;
}
Noted in a comment on #MasterPlanMan's answer -- the other answers use more "official" methods designed for the question, from standard library, etc. However, I think conceptually it's a good solution when faced with limitations that the other answers can't address.
I am having the hardest time figuring out what is wrong here:
#include <iostream>
#include <cmath>
#include <iomanip>
using namespace std;
double fact(double);
double sinTaylor(double);
double cosTaylor(double);
int main()
{
double number, sineOfnumber, cosineOfnumber;
cout << "Enter a number, then I will calculate the sine and cosine of this number" << endl;
cin >> number;
sineOfnumber = sinTaylor(number);
cosineOfnumber = cosTaylor(number);
cout << fixed << endl;
cout << cosineOfnumber << endl;
cout << sineOfnumber << endl;
return 0;
}
double fact(double n)
{
double product = 1;
while(n > 1)
product *= n--;
return product;
}
double sinTaylor(double x)
{
double currentIteration, sumSine;
for(double n = 0; n < 5; n++)
{
currentIteration = pow(-1, n)*pow(x, 2*n+1) / fact(2*n+1);
sumSine += currentIteration;
}
return sumSine;
}
double cosTaylor(double y)
{
double currentIteration, sumCosine;
for(double n = 0; n < 5; n++)
{
double currentIteration = pow(-1, n)*pow(y, 2*n) / fact(2*n);
sumCosine += currentIteration;
}
return sumCosine;
}
Ok, so here's my code. I'm pretty content with it. Except for one thing:
sineOfnumber and cosOfnumber, after the calling of sinTaylor and cosTaylor, will add each other in the following cout line that will print each other.
In other words, if number is equal to lets say, .7853, 1.14 will be printed in the line that is intended to print cosineOfnumber, and sineOfnumber will print the result normally.
Can anyone help me identify why this is? Thank you so much!
Are you ever initializing the variables sumSine and sumCosine in your functions? They're not guaranteed to start at zero, so when you call += inside your loop you could be adding computed values to garbage.
Try initializing those two variables to zero and see what happens, as other than that the code seems okay.
The series for the sine is (sorry for the LaTeX):
sin(x) = \sum_{n \ge 0} \frac{x^{2 n + 1}}{(2 n + 1)!}
If you look, given term t_{2 n + 1} you can compute term t_{2 n + 3} as
t_{2 n + 3} = t_{2 n + 1} * \frac{x^2}{(2 n + 2)(2 n + 3)}
So, given a term you can compute the next one easily. If you look at the series for the cosine, it is similar. The resulting program is more efficient (no recomputing factorials) and might be more precise. When adding up floating point numbers, it is more precise to add them from smallest to largest, but I doubt that will make a difference here.
I'm doing another C++ exercise. I have to calculate the value of pi from the infinite series:
pi=4 - 4/3 + 4/5 – 4/7 + 4/9 -4/11+ . . .
The program has to print the approximate value of pi after each of the first 1,000 terms of this series.
Here is my code:
#include <iostream>
using namespace std;
int main()
{
double pi=0.0;
int counter=1;
for (int i=1;;i+=2)//infinite loop, should "break" when pi=3.14159
{
double a=4.0;
double b=0.0;
b=a/static_cast<double>(i);
if(counter%2==0)
pi-=b;
else
pi+=b;
if(i%1000==0)//should print pi value after 1000 terms,but it doesn't
cout<<pi<<endl;
if(pi==3.14159)//this if statement doesn't work as well
break;
counter++;
}
return 0;
}
It compiles without errors and warnings, but only the empty console window appears after execution. If I remove line” if(i%1000==0)” , I can see it does run and print every pi value, but it doesn’t stop, which means the second if statement doesn’t work either. I’m not sure what else to do. I’m assuming it is probably a simple logical error.
Well, i % 1000 will never = 0, as your counter runs from i = 1, then in increments of 2. Hence, i is always odd, and will never be a multiple of 1000.
The reason it never terminates is that the algorithm doesn't converge to exactly 3.14157 - it'll be a higher precision either under or over approximation. You want to say "When within a given delta of 3.14157", so write
if (fabs(pi - 3.14157) < 0.001)
break
or something similar, for however "close" you want to get before you stop.
Since you start i at 1 and increment by 2, i is always an odd number, so i % 1000 will never be 0.
you have more than one problem:
A. i%1000==0 will never be true because you're iterating only odd numbers.
B. pi==3.14159 : you cannot compare double values just like that because the way floating point numbers are represented (you can read about it here in another question). in order for it to work you should compare the values in another way - one way is to subtract them from each other and check that the absolute result is lower than 0.0000001.
You have floating point precision issues. Try if(abs(pi - 3.14159) < 0.000005).
i%1000 will never be 0 because i is always odd.
Shouldn't it be:
if (counter%1000==0)
i starts at 1 and then increments by 2. Therefore i is always odd and will never be a multiple of 1000, which is why if (i % 1000 == 0) never passes.
Directly comparing floats doesn't work, due to floating precision issues. You will need to compare that the difference between the values is close enough.
pi=4 - 4/3 + 4/5 – 4/7 + 4/9 -4/11 + ...
Generalising
pi = Σi=0∞ (-1)i 4 / (2i+1)
Which gives us a cleaner approach to each term; the i'th term is given by:
double term = pow(-1,i%2) * 4 / (2*i+1);
where i=0,1,2,...,N
So, our loop can be fairly simple, given some number of iterations N
int N=2000;
double pi=0;
for(int i=0; i<N; i++)
{
double term = pow(-1,i%2) * 4 / (2*(double)i+1);
pi += term;
cout << i << "\t" << pi <<endl;
}
Your original question stated "The program has to print the approximate value of pi after each of the first 1,000 terms of this series". This does not imply any need to check whether 3.14159 has been reached, so I have not included this here. The pow(-1,i%2) call is just to avoid if statements (which are slow) and prevent any complications with large i.
Be aware that after a number of iterations, the difference between the magnitude of pi and the magnitude of the correcting term (say -4/25) will be so small that it will go beyond the precision of a double, so you would need higher precision types to deal with it.
By default abs uses the abs macro which is for int. For doubles, use the cmath library.
#include <iostream>
#include <cmath>
int main()
{
double pi=0.0;
double a=4.0;
int i = 1;
for (i=1;;i+=2)
{
pi += (1 - 2 * ((i/2)%2)) * a/static_cast<double>(i);
if( std::abs(pi - 3.14159) < 0.000001 )
break;
if (i > 2000) //1k iterations
break;
}
std::cout<<pi<<std::endl;
return 0;
}
Here is the corrected code. I thought it may be helpful in the future if somebody has similar problem.
#include <iostream>
#include <cmath>
using namespace std;
int main()
{
double pi=0.0;
int counter=1;
for (int i=1;;i+=2)
{
double a=4.0;
double b=0.0;
b=a/static_cast<double>(i);
if(counter%2==0)
pi-=b;
else
pi+=b;
if(counter%1000==0)
cout<<pi<<" "<<counter<<endl;
if (fabs(pi - 3.14159) < 0.000001)
break;
counter++;
}
cout<<pi;
return 0;
}
Here is a better one:
class pi_1000
{
public:
double doLeibniz( int i ) // Leibniz famous formula for pi, source: Calculus II :)
{
return ( ( pow( -1, i ) ) * 4 ) / ( ( 2 * i ) + 1 );
}
void piCalc()
{
double pi = 4;
int i;
cout << "\npi calculated each iteration from 1 to 1000\n"; //wording was a bit confusing.
//I wasn't sure which one is the right one: 0-1000 or each 1000th.
for( i = 1; i < 1000; i++ )
{
pi = pi + doLeibniz( i );
cout << fixed << setprecision( 5 ) << pi << "\t" << i + 1 << "\n";
}
pi = 4;
cout << "\npi calculated each 1000th iteration from 1 to 20000\n";
for( i = 1; i < 21000; i++ )
{
pi = pi + doLeibniz( i );
if( ( ( i - 1 ) % 1000 ) == 0 )
cout << fixed << setprecision( 5 ) << pi << "\t" << i - 1 << "\n";
}
}