Hi I am trying to calculate the results of the Taylor series expansion for sine to the specified number of terms.
I am running into some problems
Your task is to implement makeSineToOrder(k)
This is templated by the type of values used in the calculation.
It must yield a function that takes a value of the specified type and
returns the sine of that value (in the specified type again)
double factorial(double long order){
#include <iostream>
#include <iomanip>
#include <cmath>
double fact = 1;
for(int i = 1; i <= num; i++){
fact *= i;
}
return fact;
}
void makeSineToOrder(long double order,long double precision = 15){
double value = 0;
for(int n = 0; n < precision; n++){
value += pow(-1.0, n) * pow(num, 2*n+1) / factorial(2*n + 1);
}
return value;
int main()
{
using namespace std;
long double pi = 3.14159265358979323846264338327950288419716939937510L;
for(int order = 1;order < 20; order++) {
auto sine = makeSineToOrder<long double>(order);
cout << "order(" << order << ") -> sine(pi) = " << setprecision(15) << sine(pi) << endl;
}
return 0;
}
I tried debugging
here is a version that at least compiles and gives some output
#include <iostream>
#include <iomanip>
#include <cmath>
using namespace std;
double factorial(double long num) {
double fact = 1;
for (int i = 1; i <= num; i++) {
fact *= i;
}
return fact;
}
double makeSineToOrder(double num, double precision = 15) {
double value = 0;
for (int n = 0; n < precision; n++) {
value += pow(-1.0, n) * pow(num, 2 * n + 1) / factorial(2 * n + 1);
}
return value;
}
int main(){
long double pi = 3.14159265358979323846264338327950288419716939937510L;
for (int order = 1; order < 20; order++) {
auto sine = makeSineToOrder(order);
cout << "order(" << order << ") -> sine(pi) = " << setprecision(15) << sine << endl;
}
return 0;
}
not sure what that odd sine(pi) was supposed to be doing
Apart the obvious syntax errors (the includes should be before your factorial header) in your code:
I see no templates in your code which your assignment clearly states to use
so I would expect template like:
<class T> T mysin(T x,int n=15){ ... }
using pow for generic datatype is not safe
because inbuild pow will use float or double instead of your generic type so you might expect rounding/casting problems or even unresolved function in case of incompatible type.
To remedy that you can rewrite the code to not use pow as its just consequent multiplication in loop so why computing pow again and again?
using factorial function is waste
you can compute it similar to pow in the same loop no need to compute the already computed multiplications again and again. Also not using template for your factorial makes the same problems as using pow
so putting all together using this formula:
along with templates and exchanging pow,factorial functions with consequent iteration I got this:
template <class T> T mysin(T x,int n=15)
{
int i;
T y=0; // result
T x2=x*x; // x^2
T xi=x; // x^i
T ii=1; // i!
if (n>0) for(i=1;;)
{
y+=xi/ii; xi*=x2; i++; ii*=i; i++; ii*=i; n--; if (!n) break;
y-=xi/ii; xi*=x2; i++; ii*=i; i++; ii*=i; n--; if (!n) break;
}
return y;
}
so factorial ii is multiplied by i+1 and i+2 every iteration and power xi is multiplied by x^2 every iteration ... the sign change is hard coded so for loop does 2 iterations per one run (that is the reason for the break;)
As you can see this does not use anything funny so you do not need any includes for this not even math ...
You might want to add x=fmod(x,6.283185307179586476925286766559) at the start of mysin in order to use more than just first period however in that case you have to ensure fmod implementation uses T or compatible type to it ... Also the 2*pi constant should be in target precision or higher
beware too big n will overflow both int and generic type T (so you might want to limit n based on used type somehow or just use it wisely).
Also note on 32bit floats you can not get better than 5 decimal places no matter what n is with this kind of computation.
Btw. there are faster and more accurate methods of computing goniometrics like Chebyshev and CORDIC
Related
I am writing some code that prints out a sum series using a loop and a function.
I intend the equation to look like this
m(i) = (1/2) + (2/3) + ... (i / i + 1)
The problem is that my code always gives me incorrect answers and not printing what it's supposed to. For example, when I input 1 into 1 the answer should be 0.5
This is my code:
#include <iostream>
using namespace std;
void sumSeries(int x);
int main() {
sumSeries(1);
return 0;
}
void sumSeries(int x){
double sum = 0;
for(int i = 0; i < x; i++){
sum = (x/x + 1);
sum += sum;
}
cout<<sum;
}
Indeed, you overwrite your sum but also take care of your integer division.
You may change it as sum += i/(double)(i + 1);
#include <iostream>
using namespace std;
void sumSeries(int x);
int main() {
sumSeries(5);
return 0;
}
void sumSeries(int x){
if (x<0)
{
return;
}
double sum = 0;
for(int i = 0; i < x; i++){
sum += i/(double)(i + 1);
}
cout<<sum;
}
I see two problems in your code.
First: (x/x+1) != (x/(x+1)), in this case C++ obeys the normal point before line calculation rules.
Second: You are overwriting your sum in each iteration, instead of that you should direct add to sum: sum+=x/(x+1)
And a third issue, as noted by Simon Kraemer, is that you are using integer division, to get the correct results you must cast at least one of the operands to a floating point number.
What you want is:
void sumSeries(int x){
double sum = 0;
for(int i = 1; i <= x; i++){ // include i in the list
sum += static_cast<double>(i)/(i + 1); // force the operation as double
}
cout<<sum;
}
your mathematical expression has something not normal. Do you mean M(i)= sum(1-i){i/i+1}? , or 1/2 and 1/3 are constants?
in your case as gerum answered it is a small Operator Precedence problem to learn how the C++ compiler prioritize the operators follow here.
your function also should have a guard against zero denominator (undefined values).
Also you should observe that you take int/int division which will ignore the remaining value. then you should consider that by converting the numerator or the denominator to double before the division here .
then your code should be:
#include <iostream>
using namespace std;
void sumSeries(int x);
int main() {
sumSeries(1);
return 0;
}
void sumSeries(int x){
double sum = 0;
for(int i = 0; i < x; i++){
if ((x+1)!=0){
sum += (double)x/(x + 1);
}
// the else will apply only if x==-1
else {
cout<<"the denominator is zero"<<endl;
throw;
}
}
cout<<sum;
}
So..
Here is the code:
#include <iostream>
#include <limits>
#include <math.h>
using namespace std;
int main()
{
unsigned long long i,y,n,x=45;
unsigned long long factorial = 1;
for(n = 0; n <= 5; n++)
{
y = (pow(-1,n)*pow(x,2*n)) / factorial;
cout << "COS IS " << y << endl;
}
for(int i = 1; i <=n; i++)
{
factorial *= 2*i;
}
}
I get an overflow but I really don't know why. I use unsigned long long just to make sure that I on't get but.. I still get it. Even limited to small numbers. I tried to implement this:
https://en.wikibooks.org/wiki/Trigonometry/Power_Series_for_Cosine_and_Sine
But I really can't do it because of the overflow. Do you have any ideea on what can I do ? I am newbie in programming so, take it easy on me :D
There are many issues.
you use integer types when you should use floating point types
you use unsigned types for signed calculations
you don't use radians but degrees (45° ≈ 0.78539 radians)
you don't calculate the factorial in the loop, it is always 1, you only calculate it at the end of the loop but then it's too late, and your calculation of the factorial is wrong anyway.
the algorithm is wrong, it just doesn't do what Maclaurin's therorem says, you need to sum up the terms, but you just print the terms.
You probably want this:
#include <iostream>
#include <cmath>
using namespace std;
long factorial(int n)
{
long result = 1;
for (int i = 1; i <= n; i++)
result *= i;
return result;
}
int main()
{
double x = 0.785398163397448309616; //PI/4 expectd result COS(PI/4) = 0.7071067
double mycosinus = 0;
for (int n = 0; n <= 5; n++)
{
mycosinus += (pow(-1, n) * pow(x, 2 * n)) / factorial(2*n);
cout << "COS IS " << mycosinus << endl;
}
}
This is your wrong algorithm for calculating the factorial of 5:
int main()
{
int n = 5;
int factorial = 1;
for (int i = 1; i <= n; i++)
{
factorial *= 2 * i;
}
cout << "factorial 5 = " << factorial << endl;
}
The calculated value is 3840 instead of 120. I let you find out what's wrong yourself.
For performing this sort of maths you need to use a floating point like float or double not integral types like long, int or long long, given that sin and cos can both return negative numbers you shouldn't be using unsigned either.
I'm working on this program that approximates a taylor series function. I have to approximate it so that the taylor series function stops approximating the sin function with a precision of .00001. In other words,the absolute value of the last approximation minus the current approximation equals less than or equal to 0.00001. It also approximates each angle from 0 to 360 degrees in 15 degree increments. My logic seems to be correct, but I cannot figure out why i am getting garbage values. Any help is appreciated!
#include <math.h>
#include <iomanip>
#include <iostream>
#include <string>
#include <stdlib.h>
#include <cmath>
double fact(int x){
int F = 1;
for(int i = 1; i <= x; i++){
F*=i;
}
return F;
}
double degreesToRadians(double angle_in_degrees){
double rad = (angle_in_degrees*M_PI)/180;
return rad;
}
using namespace std;
double mySine(double x){
int current =99999;
double comSin=x;
double prev=0;
int counter1 = 3;
int counter2 = 1;
while(current>0.00001){
prev = comSin;
if((counter2 % 2) == 0){
comSin += (pow(x,(counter1))/(fact(counter1)));
}else{
comSin -= (pow(x,(counter1))/(fact(counter1)));
}
current=abs(prev-comSin);
cout<<current<<endl;
counter1+=2;
counter2+=1;
}
return comSin;
}
using namespace std;
int main(){
cout<<"Angle\tSine"<<endl;
for (int i = 0; i<=360; i+=15){
cout<<i<<"\t"<<mySine(degreesToRadians(i));
}
}
Here is an example which illustrates how to go about doing this.
Using the pow function and calculating the factorial at each iteration is very inefficient -- these can often be maintained as running values which are updated alongside the sum during each iteration.
In this case, each iteration's addend is the product of two factors: a power of x and a (reciprocal) factorial. To get from one iteration's power factor to the next iteration's, just multiply by x*x. To get from one iteration's factorial factor to the next iteration's, just multiply by ((2*n+1) + 1) * ((2*n+1) + 2), before incrementing n (the iteration number).
And because these two factors are updated multiplicatively, they do not need to exist as separate running values, they can exists as a single running product. This also helps avoid precision problems -- both the power factor and the factorial can become large very quickly, but the ratio of their values goes to zero relatively gradually and is well-behaved as a running value.
So this example maintains these running values, updated at each iteration:
"sum" (of course)
"prod", the ratio: pow(x, 2n+1) / factorial 2n+1
"tnp1", the value of 2*n+1 (used in the factorial update)
The running update value, "prod" is negated every iteration in order to to factor in the (-1)^n.
I also included the function "XlatedSine". When x is too far away from zero, the sum requires more iterations for an accurate result, which takes longer to run and also can require more precision than our floating-point values can provide. When the magnitude of x goes beyond PI, "XlatedSine" finds another x, close to zero, with an equivalent value for sin(x), then uses this shifted x in a call to MaclaurinSine.
#include <iostream>
#include <iomanip>
// Importing cmath seemed wrong LOL, so define Abs and PI
static double Abs(double x) { return x < 0 ? -x : x; }
const double PI = 3.14159265358979323846;
// Taylor series about x==0 for sin(x):
//
// Sum(n=[0...oo]) { ((-1)^n) * (x^(2*n+1)) / (2*n + 1)! }
//
double MaclaurinSine(double x) {
const double xsq = x*x; // cached constant x squared
int tnp1 = 3; // 2*n+1 | n==1
double prod = xsq*x / 6; // pow(x, 2*n+1) / (2*n+1)! | n==1
double sum = x; // sum after n==0
for(;;) {
prod = -prod;
sum += prod;
static const double MinUpdate = 0.00001; // try zero -- the factorial will always dominate the power of x, eventually
if(Abs(prod) <= MinUpdate) {
return sum;
}
// Update the two factors in prod
prod *= xsq; // add 2 to the power factor's exponent
prod /= (tnp1 + 1) * (tnp1 + 2); // update the factorial factor by two iterations
tnp1 += 2;
}
}
// XlatedSine translates x to an angle close to zero which will produce the equivalent result.
double XlatedSine(double x) {
if(Abs(x) >= PI) {
// Use int casting to do an fmod PI (but symmetric about zero).
// Keep in mind that a really big x could overflow the int,
// however such a large double value will have lost so much precision
// at a sub-PI-sized scale that doing this in a legit fashion
// would also disappoint.
const int p = static_cast<int>(x / PI);
x -= PI * p;
if(p % 2) {
x = -x;
}
}
return MaclaurinSine(x);
}
double DegreesToRadians(double angle_deg) {
return PI / 180 * angle_deg;
}
int main() {
std::cout<<"Angle\tSine\n" << std::setprecision(12);
for(int i = 0; i<=360; i+=15) {
std::cout << i << "\t" << MaclaurinSine(DegreesToRadians(i)) << "\n";
//std::cout << i << "\t" << XlatedSine(DegreesToRadians(i)) << "\n";
}
}
I've written a few programs to find pi, this one being the most advanced. I used Machin's formula, pi/4 = 4(arc-tan(1/5)) - (arc-tan(1/239)).
The problem is that however many iterations I do, I get the same result, and I can't seem to understand why.
#include "stdafx.h"
#include <iostream>
#include <iomanip>
#include <math.h>
using namespace std;
double arctan_series(int x, double y) // x is the # of iterations while y is the number
{
double pi = y;
double temp_Pi;
for (int i = 1, j = 3; i < x; i++, j += 2)
{
temp_Pi = pow(y, j) / j; //the actual value of the iteration
if (i % 2 != 0) // for every odd iteration that subtracts
{
pi -= temp_Pi;
}
else // for every even iteration that adds
{
pi += temp_Pi;
}
}
pi = pi * 4;
return pi;
}
double calculations(int x) // x is the # of iterations
{
double value_1, value_2, answer;
value_1 = arctan_series(x, 0.2);
value_2 = arctan_series(x, 1.0 / 239.0);
answer = (4 * value_1) - (value_2);
return answer;
}
int main()
{
double pi;
int iteration_num;
cout << "Enter the number of iterations: ";
cin >> iteration_num;
pi = calculations(iteration_num);
cout << "Pi has the value of: " << setprecision(100) << fixed << pi << endl;
return 0;
}
I have not been able to reproduce your issue, but here is a bit cleaned up code with a few C++11 idioms and better variable names.
#include <iostream>
#include <iomanip>
#include <math.h>
using namespace std;
// double arctan_series(int x, double y) // x is the # of iterations while y is the number
// then why not name the parameters accoringly? In math we usually use x for the parameter.
// prefer C++11 and the auto notation wherever possible
auto arctan_series(int iterations, double x) -> double
{
// note, that we don't need any temporaries here.
// note, that this loop will never run, when iterations = 1
// is that really what was intended?
for (int i = 1, j = 3; i < iterations; i++, j += 2)
{
// declare variables as late as possible and always initialize them
auto t = pow(x, j) / j;
// in such simple cases I prefer ?: over if-else. Your milage may vary
x += (i % 2 != 0) ? -t : t;
}
return x * 4;
}
// double calculations(int x) // x is the # of iterations
// then why not name the parameter accordingly
// BTW rename the function to what it is supposed to do
auto approximate_pi(int iterations) -> double
{
// we don't need all of these temporaries. Just write one expression.
return 4 * arctan_series(iterations, 0.2) - arctan_series(iterations, 1.0 / 239.0);
}
auto main(int, char**) -> int
{
cout << "Enter the number of iterations: ";
// in C++ you should declare variables as late as possible
// and always initialize them.
int iteration_num = 0;
cin >> iteration_num;
cout << "Pi has the value of: "
<< setprecision(100) << fixed
<< approximate_pi(iteration_num) << endl;
return 0;
}
When you remove my explanatory comments, you'll see, that the resulting code is a lot more concise, easier to read, and therefore easier to maintain.
I tried a bit:
Enter the number of iterations: 3
Pi has the value of: 3.1416210293250346197169164952356368303298950195312500000000000000000000000000000000000000000000000000
Enter the number of iterations: 2
Pi has the value of: 3.1405970293260603298790556436870247125625610351562500000000000000000000000000000000000000000000000000
Enter the number of iterations: 7
Pi has the value of: 3.1415926536235549981768144789384678006172180175781250000000000000000000000000000000000000000000000000
Enter the number of iterations: 42
Pi has the value of: 3.1415926535897940041763831686694175004959106445312500000000000000000000000000000000000000000000000000
As you see, I obviously get different results for different numbers of iterations.
That method converges very quickly. You'll get more accuracy if you start with the smallest numbers first. Since 5^23 > 2^53 (the number of bits in the mantissa of a double), probably the maximum number of iterations is 12 (13 won't make any difference). You'll get more accuracy starting with the smaller numbers. The changed lines have comments:
double arctan_series(int x, double y)
{
double pi = y;
double temp_Pi;
for (int i = 1, j = x*2-1; i < x; i++, j -= 2) // changed this line
{
temp_Pi = pow(y, j) / j;
if ((j & 2) != 0) // changed this line
{
pi -= temp_Pi;
}
else
{
pi += temp_Pi;
}
}
pi = pi * 4;
return pi;
}
For doubles, there is no point in setting precision > 18.
If you want an alternative formula that takes more iterations to converge, use pi/4 = arc-tan(1/2) + arc-tan(1/3), which will take about 24 iterations.
This is another way if some of you are interested. The loop calculates the integral of the function : sqrt(1-x²)
Which represents a semicircle of radius 1. Then we multiply by two the area. Finally we got the surface of the circle which is PI.
#include <iomanip>
#include <cmath>
#define f(x) sqrt(1-pow(x,2))
double integral(int a, int b, int p)
{
double d=pow(10, -p), s=0;
for (double x=a ; x+d<=b ; x+=d)
{
s+=f(x)+f(x+d);
}
s*=d/2.0;
return s;
}
int main()
{
cout << "PI=" << setprecision (9) << 2.0*integral(-1,1,6) << endl;
}
What is more accurate way to calculate average of set of numbers, ARR[0]/N+ARR[1]/N...+ARR[N-1]/N or (ARR[0]+ARR[1]...+ARR[N-1])/N? (ARR is the set of numbers and N is the count of the numbers in that set)
Consider I have set of numbers that each ranges from 0.0 to 1.0 (they are double\floating-point numbers) and there are thousands of them or even millions.
I am open to new methods like recursive average (average twin-cells into array and then again average it until it outputs one-cell array).
If the values near zero are very close to zero, you'll have an issue with rounding (could be rounding error up or down) in a summation, or any range of numbers if summing a large set of numbers. One way around this issue is to use a summation function that only adds numbers with the same exponent (until you call getsum() to get the total sum, where it keeps exponents as close as possible). Example C++ class to do this (note code was compiled using Visual Studio, written before uint64_t was available).
// SUM contains an array of 2048 IEEE 754 doubles, indexed by exponent,
// used to minimize rounding / truncation issues when doing
// a large number of summations
class SUM{
double asum[2048];
public:
SUM(){for(int i = 0; i < 2048; i++)asum[i] = 0.;}
void clear(){for(int i = 0; i < 2048; i++)asum[i] = 0.;}
// getsum returns the current sum of the array
double getsum(){double d = 0.; for(int i = 0; i < 2048; i++)d += asum[i];
return(d);}
void addnum(double);
};
void SUM::addnum(double d) // add a number into the array
{
size_t i;
while(1){
// i = exponent of d
i = ((size_t)((*(unsigned long long *)&d)>>52))&0x7ff;
if(i == 0x7ff){ // max exponent, could be overflow
asum[i] += d;
return;
}
if(asum[i] == 0.){ // if empty slot store d
asum[i] = d;
return;
}
d += asum[i]; // else add slot to d, clear slot
asum[i] = 0.; // and continue until empty slot
}
}
Example program that uses the sum class:
#include <iostream>
#include <iomanip>
using namespace std;
static SUM sum;
int main()
{
double dsum = 0.;
double d = 1./5.;
unsigned long i;
for(i = 0; i < 0xffffffffUL; i++){
sum.addnum(d);
dsum += d;
}
cout << "dsum = " << setprecision(16) << dsum << endl;
cout << "sum.getsum() = " << setprecision(16) << sum.getsum() << endl;
cout << "0xffffffff * 1/5 = " << setprecision(16) << d * (double)0xffffffffUL << endl;
return(0);
}
(ARR[0]+ARR[1]...+ARR[N-1])/N is faster and more accurate because you omit useless divisions with N that both slow down the process and add error in the calculations.
If you have a bunch of floating-point numbers, the most accurate way to get the mean is like this:
template<class T> T mean(T* arr, size_t N) {
std::sort(+arr, arr+N, [](T a, T b){return std::abs(a) < std::abs(b);});
T r = 0;
for(size_t n = 0; n < N; n++)
r += arr[n];
return r / N;
}
Important points:
The numbers of least magnitude are added first to preserve significant digits.
Only one division, to reduce rounding error there.
Still, the intermediate sum might become too big.