#include <iostream>
using namespace std;
int main() {
float result = 50.0f;
float multiplier = 0.5f;
float fixed_multiplier = 1.0f - multiplier * 0.001f;
for (int i = 0; i < 1000; ++i) {
result *= fixed_multiplier;
}
cout << result << endl; // 30.322 -- want approximately 25
}
After the 1000 iterations, I want result to equal multiplier*result (result==25). How do I find what I need to modify multiplier (in fixed_multiplier) to get the desired result?
Your for loop is summarized by this mathematical equation:
result * fixed_multiplier ^ 1000 = result * multiplier
You can solve this equation to find your answer.
You can get the same result in C using the pow function:
fixed_multiplier = pow(multiplier, 0.001);
You have the following relationship:
result_out = result * fixed_multiplier^1000
where ^ denotes "to the power of". Simple algebra gives you this:
fixed_multiplier = (result_out / result) ^ (1/1000)
Related
Suppose we need to generate a very long harmonic signal, ideally infinitely long. At first glance, the solution seems trivial:
Sample1:
float t = 0;
while (runned)
{
float v = sinf(w * t);
t += dt;
}
Unfortunately, this is a non-working solution. For t >> dt due to limited float precision incorrect values will be obtained. Fortunately we can call to mind that sin(2*PI* n + x) = sin(x) where n - arbitrary integer value, therefore modifying the example is not difficult to get an "infinite" analog
Sample2:
float t = 0;
float tau = 2 * M_PI / w;
while (runned)
{
float v = sinf(w * t);
t += dt;
if (t > tau) t -= tau;
}
For one physical simulation, I needed to get an infinite signal, which is the sum of harmonic signals, like that:
Sample3:
float getSignal(float x)
{
float ret = 0;
for (int i = 0; i < modNum; i++)
ret += sin(w[i] * x);
return ret;
}
float t = 0;
while (runned)
{
float v = getSignal(t);
t += dt;
}
In this form, the code does not work correctly for large t, for similar reasons for the Sample1. The question is - how to get an "infinite" implementation of the Sample3 algorithm? I assume that the solution should looks like an Sample2. A very important note - generally speaking, w[i] is arbitrary and not harmonics, that is, all frequencies are not multiples of some base frequency, so i can't find common tau. Using types with greater precission (double, long double) is not allowed.
Thanks for your advice!
You can choose an arbitrary tau and store the phase reminders for each mod when subtracting it from t (as #Damien suggested in the comments).
Also, representing the time as t = dt * it where it is an integer can improve numerical stability (i think).
Maybe something like this:
int ndt = 1000; // accumulate phase every 1000 steps for example
float tau = dt * ndt;
std::vector<float> phases(modNum, 0.0f);
int it = 0;
float t = 0.0f;
while (runned)
{
t = dt * it;
float v = 0.0f;
for (int i = 0; i < modNum; i++)
{
v += sinf(w[i] * t + phases[i]);
}
if (++it >= ndt)
{
it = 0;
for (int i = 0; i < modNum; ++i)
{
phases[i] = fmod(w[i] * tau + phases[i], 2 * M_PI);
}
}
}
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";
}
}
Hello I am solving trigonometry functions like sin(x) and cos(x) with Taylor Series Expansions
Problem: My values are not wrong just not very precise
My question is whether I can improve the accuracy of these functions, I think I have tried everything but I need your suggestions.
double trig::funcsin(int value)
{
sum = 0;
//summation
factorial fac;
for(int i = 0; i < 7; i++)
{
sum += pow((-1), i)*(((double)pow(value, (double)2*i+1)/(double)fac.fact((double)2*i+ 1)));
}
return sum;
}
double trig::funccos(int value)
{
factorial fac;
sum = 0;
for(int i = 0;i < 7;i++)
{
sum += (pow((-1), i)*((double)pow(value, (double)2*i)/(double)fac.fact((double)2*i)));
}
return sum;
}
Example:
Real: -0.7568024953
Mine: -0.73207
Real: -0.27941549819
Mine: -0.501801
Aslo as x becomes larger the output values become less precise at an exponential rate.
I am on GCC compiler, please give me suggestions
The following code demonstrates the Taylor series (about x==0) for the sin() function.
As you know, the sine function repeats an identical cycle for every 2*pi interval.
But the Taylor series is just a polynomial -- it needs a lot of terms to approximate a wiggly function like sine. And trying to approximate the sine function at some point far away from the origin will require so many terms that accumulated errors will give an unsatisfactory result.
To avoid this problem, my function starts by remapping x into a single cycle's range centered around zero, between -pi and +pi.
It's best to avoid using pow and factorial functions if you can instead cheaply update components at each step in the summation. For example, I keep a running value for pow(x, 2*n+1): It starts off set to x (at n==0), then every time n is incremented, I multiply this by x*x. So it only costs a single multiplication to update this value at each step. A similar optimization is used for the factorial term.
This series alternates between positive and negative terms, so to avoid the hassle of keeping track of whether we need to add or subtract a term, the loop handles two terms on each iteration -- it adds the first and subtracts the second.
Each time a new sum is calculated, it is compared with the previous sum. If the two are equal (indicating the updates have surpassed the sum variable's precision), the function returns. This isn't a great way to test for a terminating condition, but it makes the function simpler.
#include <iostream>
#include <iomanip>
double mod_pi(double x) {
static const double two_pi = 3.14159265358979 * 2;
const int q = static_cast<int>(x / two_pi + 0.5);
return x - two_pi * q;
}
double func_sin(double x) {
x = mod_pi(x);
double sum = 0;
double a = 1; // 2*n+1 [1, 3, 5, 7, ...]
double b = x; // x^a
double c = 1; // (2*n+1)!
const double x_sq = x * x;
for(;;) {
const double tp = b / c;
// update for negative term
c *= (a+1) * (a+2);
a += 2;
b *= x_sq;
const double tn = b / c;
const double ns = tp - tn + sum;
if(ns == sum) return ns;
sum = ns;
// update for positive term (at top of loop)
c *= (a+1) * (a+2);
a += 2;
b *= x_sq;
}
}
int main() {
const double y = func_sin(-0.858407346398077);
std::cout << std::setprecision(13) << y << std::endl;
}
I am trying to write a block of codes in C++ that calculates sinX value with Taylor's series.
#include <iostream>
using namespace std;
// exp example
#include <cstdio> // printf
#include <cmath> // exp
double toRadians(double angdeg) //convert to radians to degree
{ //x is in radians
const double PI = 3.14159265358979323846;
return angdeg / 180.0 * PI;
}
double fact(double x) //factorial function
{ //Simply calculates factorial for denominator
if(x==0 || x==1)
return 1;
else
x * fact(x - 1);
}
double mySin(double x) //mySin function
{
double sum = 0.0;
for(int i = 0; i < 9; i++)
{
double top = pow(-1, i) * pow(x, 2 * i + 1); //calculation for nominator
double bottom = fact(2 * i + 1); //calculation for denominator
sum = sum + top / bottom; //1 - x^2/2! + x^4/4! - x^6/6!
}
return sum;
}
int main()
{
double param = 45, result;
result = mySin(toRadians(param)); //This is my sin value
cout << "Here is my homemade sin : " << result << endl;
result = sin(param); //This is library value
cout << "Here is the API sin : " << result << endl;
return 0;
}
So my program works without any error. My output is exactly:
Here is my homemade sin : nan
Here is the API sin:0.850904
I know I am making a big logic mistake but I couldn't find it out. It is my second week with C++. I am more familiar with Java. I coded the same thing and It worked absolutely perfect. The answers matched each other.
Thanks for your time and attention!
in fact, you miss the return: x*fact(x-1); should be return x*fact(x-1);. You can see the compiler complaining if you turn the warnings on. For example, with GCC, calling g++ -Wall program.cpp gives Warning: control reaches end of non-void function for the factorial function.
The API sin also needs the angle in radians, so change result=sin(param); into result=sin(toRadians(param));. Generally, if in doubt about the API, consult the docs, like here.
Your codes seems to have some logical mistakes. Here is my corrected one:
#include <iostream>
using namespace std;
double radians(double degrees) // converts degrees to radians
{
double radians;
double const pi = 3.14159265358979323846;
radians = (pi/180)*degrees;
return radians;
}
double factorial(int x) //calculates the factorial
{
double fact = 1;
for(; x >= 1 ; x--)
{
fact = x * fact;
}
return fact;
}
double power(double x,double n) //calculates the power of x
{
double output = 1;
while(n>0)
{
output =( x*output);
n--;
}
return output;
}
float sin(double radians) //value of sine by Taylors series
{
double a,b,c;
float result = 0;
for(int y=0 ; y!=9 ; y++)
{
a= power(-1,y);
b= power(radians,(2*y)+1);
c= factorial((2*y)+1);
result = result+ (a*b)/c;
}
return result;
}
double n,output;
int main()
{
cout<<"enter the value\t";
cin>>n;
n = radians(n);
cout<< "\nthe value in radians is\t"<< n << "\n";
output = sin(n);
cout<< "\nsine of the given value is\t"<< output;
return 0;
}
The intention of this program was to use custom functions instead of libraries to make learning for others easy.
There are four user defined functions in this program.The first three user defined functions 'radians()', 'factorial()','power()', are apparently simple functions that perform operations as their name suggests.
The fourth function 'sin()' takes input in radians given by the function 'radians()'. The sin function uses Taylors series iterated term wise in the function's 'for(int y= 0;y!=9;y++)' loop till nine iterations to calculate the output.The 'for()' loop iterates the general mathematical expression: Term(n)=((-1)^n).(x^(2n+1))/(2n+1)!
sin(x)= x- x^3/3! + x^5/5! -x^7/7! + x^9/9!
=x-x^3/2*3 (1- x^2/4*5 + x^4/4*5*6*7 + x^6/4*5*6*7*8*9)
=x - x^3/2*3 {1- x^2/4*5(1- x^2/6*7 + x^4/6*7*8*9)}
=x - x^3/2*3 [{1- x^2/4*5 ( 1- x^2/6*7 (1- x^2/8*9))}]
=x(1 - x^2/2*3 [{1- x^2/4*5 ( 1- x^2/6*7 (1- x^2/8*9))}])
double sin_series_recursion(double x, int n){
static double r=1;
if(n>1){
r=1-((x*x*r)/(n*(n-1)));
return sin_series_recursion(x,n-2);
}else return r*x;
}
I wrote the following code to sum the series (-1)^i*(i/(i+1)). But when I run it I get -1 for any value of n.
Can some one please point out what I am doing wrong? Thank you in advance!
#include <iostream>
using namespace std;
int main()
{
int sum = 0;
int i = 1.0;
int n = 5.0;
for(i=1;i<=n;i++)
sum = (-1)^i*(i/(i+1));
cout << "Sum" <<" = "<< sum << endl;
return 0;
}
Problem #1: The C++ ^ operator isn't the math power operator. It's a bitwise XOR.
You should use pow() instead.
Problem #2:
You are storing floating-point types into an integer type. So the following will result in integer division (truncated division):
i/(i+1)
Problem #3:
You are not actually summing anything up:
sum = ...
should be:
sum += ...
A corrected version of the code is as follows:
double sum = 0;
int i = 1;
int n = 5;
for(i = 1; i <= n; i++)
sum += pow(-1.,(double)i) * ((double)i / (i + 1));
Although you really don't need to use pow in this case. A simple test for odd/even will do.
double sum = 0;
int i = 1;
int n = 5;
for(i = 1; i <= n; i++){
double val = (double)i / (i + 1);
if (i % 2 != 0){
val *= -1.;
}
sum += val;
}
You need too put sum += pow(-1,i)*(i/(i+1));
Otherwise you lose previous result each time.
Use pow function for pow operation.
edit : as said in other post, use double or float instead of int to avoid truncated division.
How about this
((i % 2) == 0 ? 1 : -1)
instead of
std::pow(-1, i)
?
Full answer:
double sum = 0;
int i = 1.0;
int n = 5.0;
for (i = 1; i <= n; ++i) {
signed char sign = ((i % 2) == 0 ? 1 : -1);
sum += sign * (i / (i+1));
}
Few problems:
^ is teh bitwise exclusive or in c++ not "raised to power". Use pow() method.
Remove the dangling opening bracket from the last line
Use ints not floats when assigning to ints.
You seem to have a few things wrong with your code:
using namespace std;
This is not directly related to your problem at hand, but don't ever say using namespace std; It introduces subtle bugs.
int i = 1.0;
int n = 5.0;
You are initializaing integral variables with floating-point constants. Try
int i = 1;
int n = 5;
sum = (-1)^i*(i/(i+1));
You have two problems with this expression. First, the quantity (i/(i+1)) is always zero. Remember dividing two ints rounds the result. Second, ^ doesn't do what you think it does. It is the exclusive-or operator, not the exponentiation operator. Third, ^ binds less tightly than *, so your expression is:
-1 xor (i * (i/(i+1)))
-1 xor (i * 0)
-1 xor 0
-1
^ does not do what you think it does. Also there are some other mistakes in your code.
What it should be:
#include <iostream>
#include <cmath>
int main( )
{
long sum = 0;
int i = 1;
int n = 5;
for( i = 1; i <= n; i++ )
sum += std::pow( -1.f, i ) * ( i / ( i + 1 ) );
std::cout << "Sum = " << sum << std::endl;
return 0;
}
To take a power of a value, use std::pow (see here). Also you can not assign int to a decimal value. For that you need to use float or double.
The aforementioned ^ is a bitwise-XOR, not a mark for an exponent.
Also be careful of Integer Arithmetic as you may get unexpected results. You most likely want to change your variables to either float or double.
There are a few issues with the code:
int sum = 0;
The intermediate results are not integers, this should be a double
int i = 1.0;
Since you will use this in a division, it should be a double, 1/2 is 0 if calculated in integers.
int n = 5.0;
This is an int, not a floating point value, no .0 is needed.
for(i=1;i<=n;i++)
You've already initialized i to 1, why do it again?
sum = (-1)^i*(i/(i+1));
Every iteration you lose the previous value, you should use sum+= 'new values'
Also, you don't need pow to calculate (-1)^i, all this does is switch between +1 and -1 depending on the odd/even status of i. You can do this easier with an if statement or with 2 for's, one for odd i one for even ones... Many choices really.