Here I have a little problem. Create something from this formula:
This is what I have, but it doesn't work. Franky, I really don't understand how it should work.. I tried to code it with some bad instructions. N is number of iteration and parts of fraction. I think it leads somehow to recursion but don't know how.
Thanks for any help.
double contFragLog(double z, int n)
{
double cf = 2 * z;
double a, b;
for(int i = n; i >= 1; i--)
{
a = sq(i - 2) * sq(z);
b = i + i - 2;
cf = a / (b - cf);
}
return (1 + cf) / (1 - cf);
}
The central loop is messed. Reworked. Recursion not needed either. Just compute the deepest term first and work your way out.
double contFragLog(double z, int n) {
double zz = z*z;
double cf = 1.0; // Important this is not 0
for (int i = n; i >= 1; i--) {
cf = (2*i -1) - i*i*zz/cf;
}
return 2*z/cf;
}
void testln(double z) {
double y = log((1+z)/(1-z));
double y2 = contFragLog(z, 8);
printf("%e %e %e\n", z, y, y2);
}
int main() {
testln(0.2);
testln(0.5);
testln(0.8);
return 0;
}
Output
2.000000e-01 4.054651e-01 4.054651e-01
5.000000e-01 1.098612e+00 1.098612e+00
8.000000e-01 2.197225e+00 2.196987e+00
[Edit]
As prompted by #MicroVirus, I found double cf = 1.88*n - 0.95; to work better than double cf = 1.0;. As more terms are used, the value used makes less difference, yet a good initial cf requires fewer terms for a good answer, especially for |z| near 0.5. More work could be done here as I studied 0 < z <= 0.5. #MicroVirus suggestion of 2*n+1 may be close to my suggestion due to an off-by-one of what n is.
This is based on reverse computing and noting the value of CF[n] as n increased. I was surprised the "seed" value did not appear to be some nice integer equation.
Here's a solution to the problem that does use recursion (if anyone is interested):
#include <math.h>
#include <stdio.h>
/* `i` is the iteration of the recursion and `n` is
just for testing when we should end. 'zz' is z^2 */
double recursion (double zz, int i, int n) {
if (!n)
return 1;
return 2 * i - 1 - i * i * zz / recursion (zz, i + 1, --n);
}
double contFragLog (double z, int n) {
return 2 * z / recursion (z * z, 1, n);
}
void testln(double z) {
double y = log((1+z)/(1-z));
double y2 = contFragLog(z, 8);
printf("%e %e %e\n", z, y, y2);
}
int main() {
testln(0.2);
testln(0.5);
testln(0.8);
return 0;
}
The output is identical to the solution above:
2.000000e-01 4.054651e-01 4.054651e-01
5.000000e-01 1.098612e+00 1.098612e+00
8.000000e-01 2.197225e+00 2.196987e+00
Related
The teacher asks to remove the pi subtraction cycle in the main function. I don’t know how to write the program so that the correct results will come out for any values.
#include <stdio.h>
#include <math.h>
double sinus(double x);
int main(void) {
double a, x;
scanf("%le", & x);
a = x;
while (fabs(x) > 2 * (M_PI)) {
x = fabs(x) - 2 * (M_PI);
}
if (a > 0)
a = sinus(x);
else a = (-1) * sinus(x);
printf("%le", (double) a);
return 0;
}
double sinus(double x) {
double sum = 0, h, eps = 1.e-16;
int i = 2;
h = x;
do {
sum += h;
h *= -((x * x) / (i * (i + 1)));
i += 2;
}
while (fabs(h) > eps);
return sum;
return 0;
}
#include <stdio.h>
#include <math.h>
double sinus(double x);
int main(void)
{
double a,x;
scanf("%le",&x);
a=x;
x=fmod(fabs(x),2*(M_PI));
if(a>0)
a=sinus(x);
else a=(-1)*sinus(x);
printf("%le",(double)a);
return 0;}
double sinus(double x)
{
double sum=0, h, eps=1.e-16; int i=2;
h=x;
do{
sum+=h;
h*=-((x*x)/(i*(i+1)));
i+=2;}
while( fabs(h)>eps );
return sum;
return 0;
}
… how to write the program so that the correct results will come out for any values.
OP's loop is slow with large x and an infinfite loop with very large x:
while (fabs(x) > 2 * (M_PI)) {
x = fabs(x) - 2 * (M_PI);
}
A simple, though not high quality solution, is to use fmod() in the function itself. #Damien:
#ifndef M_PI
#define M_PI 3.1415926535897932384626433832795
#endif
double sinus(double x) {
x = fmod(x, 2*M_PI); // Reduce to [-2*M_PI ... 2*M_PI]
...
Although function fmod() is not expected to inject any error, the problem is that M_PI (a rational number) is an approximation of π, (an irrational number). Using that value approximation injects error especially x near multiplies of π. This is likely OK for modest quality code.
Good range reduction is a problem as challenging as the trigonometric functions themselves.
See K.C. Ng's "ARGUMENT REDUCTION FOR HUGE ARGUMENTS: Good to the Last Bit" .
OP's sinus() should use additional range reduction and trigonometric properties to get x in range [-M_PI/4 ... M_PI/4] (example) before attempting the power series solution. Otherwise, convergence is slow and errors accumulate.
#include <stdio.h>
#include <math.h>
const int TERMS = 7;
const float PI = 3.14159265358979;
int fact(int n) {
return n<= 0 ? 1 : n * fact(n-1);
}
double sine(int x) {
double rad = x * (PI / 180);
double sin = 0;
int n;
for(n = 0; n < TERMS; n++) { // That's Taylor series!!
sin += pow(-1, n) * pow(rad, (2 * n) + 1)/ fact((2 * n) + 1);
}
return sin;
}
double cosine(int x) {
double rad = x * (PI / 180);
double cos = 0;
int n;
for(n = 0; n < TERMS; n++) { // That's also Taylor series!
cos += pow(-1, n) * pow(rad, 2 * n) / fact(2 * n);
}
return cos;
}
int main(void){
int y;
scanf("%d",&y);
printf("sine(%d)= %lf\n",y, sine(y));
printf("cosine(%d)= %lf\n",y, cosine(y));
return 0;
}
The code above was implemented to compute sine and cosine using Taylor series.
I tried testing the code and it works fine for sine(120).
I am getting wrong answers for sine(240) and sine(300).
Can anyone help me find out why those errors occur?
You should calculate the functions in the first quadrant only [0, pi/2). Exploit the properties of the functions to get the values for other angles. For instance, for values of x between [pi/2, pi), sin(x) can be calculated by sin(pi - x).
The sine of 120 degrees, which is 40 past 90 degrees, is the same as 50 degrees: 40 degrees before 90. Sine starts at 0, then rises toward 1 at 90 degrees, and then falls again in a mirror image to zero at 180.
The negative sine values from pi to 2pi are just -sin(x - pi). I'd handle everything by this recursive definition:
sin(x):
cases x of:
[0, pi/2) -> calculate (Taylor or whatever)
[pi/2, pi) -> sin(pi - x)
[pi/2, 2pi) -> -sin(x - pi)
< 0 -> sin(-x)
>= 2pi -> sin(fmod(x, 2pi)) // floating-point remainder
A similar approach for cos, using identity cases appropriate for it.
The key point is:
TERMS is too small to have proper precision. And if you increase TERMS, you have to change fact implementation as it will likely overflow when working with int.
I would use a sign to toggle the -1 power instead of pow(-1,n) overkill.
Then use double for the value of PI to avoid losing too many decimals
Then for high values, you should increase the number of terms (this is the main issue). using long long for your factorial method or you get overflow. I set 10 and get proper results:
#include <stdio.h>
#include <math.h>
const int TERMS = 10;
const double PI = 3.14159265358979;
long long fact(int n) {
return n<= 0 ? 1 : n * fact(n-1);
}
double powd(double x,int n) {
return n<= 0 ? 1 : x * powd(x,n-1);
}
double sine(int x) {
double rad = x * (PI / 180);
double sin = 0;
int n;
int sign = 1;
for(n = 0; n < TERMS; n++) { // That's Taylor series!!
sin += sign * powd(rad, (2 * n) + 1)/ fact((2 * n) + 1);
sign = -sign;
}
return sin;
}
double cosine(int x) {
double rad = x * (PI / 180);
double cos = 0;
int n;
int sign = 1;
for(n = 0; n < TERMS; n++) { // That's also Taylor series!
cos += sign * powd(rad, 2 * n) / fact(2 * n);
sign = -sign;
}
return cos;
}
int main(void){
int y;
scanf("%d",&y);
printf("sine(%d)= %lf\n",y, sine(y));
printf("cosine(%d)= %lf\n",y, cosine(y));
return 0;
}
result:
240
sine(240)= -0.866026
cosine(240)= -0.500001
Notes:
my recusive implementation of pow using successive multiplications is probably not needed, since we're dealing with floating point. It introduces accumulation error if n is big.
fact could be using floating point to allow bigger numbers and better precision. Actually I suggested long long but it would be better not to assume that the size will be enough. Better use standard type like int64_t for that.
fact and pow results could be pre-computed/hardcoded as well. This would save computation time.
const double TERMS = 14;
const double PI = 3.14159265358979;
double fact(double n) {return n <= 0.0 ? 1 : n * fact(n - 1);}
double sine(double x)
{
double rad = x * (PI / 180);
rad = fmod(rad, 2 * PI);
double sin = 0;
for (double n = 0; n < TERMS; n++)
sin += pow(-1, n) * pow(rad, (2 * n) + 1) / fact((2 * n) + 1);
return sin;
}
double cosine(double x)
{
double rad = x * (PI / 180);
rad = fmod(rad,2*PI);
double cos = 0;
for (double n = 0; n < TERMS; n++)
cos += pow(-1, n) * pow(rad, 2 * n) / fact(2 * n);
return cos;
}
int main()
{
printf("sine(240)= %lf\n", sine(240));
printf("cosine(300)= %lf\n",cosine(300));
}
One of my C assignments was it to write an approximation of arctan(x) in the language C. The equation which I should base it on is
arctan(x)=\sum {k=0}^{\infty }(-1)^{k} \tfrac{x^{2k+1}}{2k+1}
In addition x is only defined as -1<=x<=1.
Here is my code.
#include <stdio.h>
#include <math.h>
double main(void) {
double x=1;
double k;
double sum;
double sum_old;
int count;
double pw(double y, double n) {
double i;
double number = 1;
for (i = 0; i < n; i++) {
number *= y;
}
return(number);
}
double fc (double y) {
double i;
double number = 1;
for (i = 1; i <= y; i++){
number *= i;
}
return(number);
}
if(x >= (-1) && x <= 1) {
for(k=0; sum!=sum_old; k++) {
sum_old = sum;
sum += pw((-1), k) * pw(x, (2*k) + 1)/((2*k) + 1);
count++;
printf("%d || %.17lf\n", count, sum);
}
printf("My result is: %.17lf\n",sum);
printf("atan(%f) is: %.17f\n", x, atan(x));
printf("My result minus atan(x) = %.17lf\n", sum - atan(x));
} else {
printf("x is not defined. Please choose an x in the intervall [-1, 1]\n");
}
return 0;
}
It seemingly works fine with every value, except value 1 and -1. If x=1, then the output ends with:
...
7207 || 0.78543285189457468
7208 || 0.78536
Whereas the output should look more like this. In this case x=0.5.
25 || 0.46364760900080587
26 || 0.46364760900080587
My result is: 0.46364760900080587
atan(0.500000) is: 0.46364760900080609
My result minus atan(x) atan(x) = -0.00000000000000022
How can I improve my code so that it can run with x=1 and x=-1.
Thanks in advance.
PS: I use my own created pw() function instead of pow(), because I wanted to bybass the restriction of not using pow() as we didn't had that in our lectures yet.
PPS: I'd appreciate any advice as to how to improve my code.
In each iteration, you add (-1)k • x2k+1 / (2k+1), and you stop when there is no change to the sum.
If this were calculated with ideal arithmetic (exact, infinitely precise arithmetic), it would never stop for non-zero x, since you are always changing the sum. When calculating with fixed-precision arithmetic, it stops when the term is so small it does not change the sum because of the limited precision.
When |x| is less than one by any significant amount, this comes quickly because x2k+1 gets smaller. When |x| is one, the term becomes just 1 / (2k+1), which gets smaller very slowly. Not until k is around 253 would the sum stop changing.
You might consider changing your stopping condition to be when sum has not changed from sum_old very much rather than when it has not changed at all.
if(x >= (-1) && x <= 1) {
for(k=0; sum!=sum_old; k++) {
sum_old = sum;
sum += pw((-1), k) * pw(x, (2*k) + 1)/((2*k) + 1);
count++;
printf("%d || %.17lf\n", count, sum);
}
Comparing doubles can be tricky. The conventional way to compare doubles is to test within epsilon. There should be an epsilon value defined somewhere, but for your purposes how many digits are enough to approximate? If you only need like 3 or 4 digits you can instead have
#define EPSILON 0.0001 //make this however precise you need to approximate.
if(x >= (-1) && x <= 1) {
for(k=0; fabs(sum - sum_old) > EPSILON; k++) {
sum_old = sum;
sum += pw((-1), k) * pw(x, (2*k) + 1)/((2*k) + 1);
count++;
printf("%d || %.17lf\n", count, sum);
}
If the issue is that -1,1 iterate too many times either reduce the precision or increase the step per iteration. I am not sure that is what you're asking though, please clarify.
I think the cause of this is for a mathematical reason rather than a programming one.
Away from the little mistakes and adjustments that you should do to your code, putting x = 1 in the infinite series of arctan, is a boundary condition:
In this series, we add a negative value to a positive value then a negative value. This means the sum will be increasing, decreasing, increasing, ... and this will make some difference each iteration. This difference will be smaller until the preciseness of double won't catch it, so the program will stop and give us the value.
But in the sum equation. When we set z = 1 and n goes from 0 to ∞, this will make this term (-1^n) equal to 1 in one time and -1 in the next iteration. Also,
the value of the z-term will be one and the denominator value when n approaches infinity will = ∞ .
So the sum several iterations will be like +1/∞ -1/∞ +1/∞ -1/∞ ... (where ∞ here represents a big number). That way the series will not reach a specific number. This is because z = 1 is a boundary in this equation. And that is causing infinite iterations in your solution without reaching a number.
If you need to calculate arctan(1) I think you should use this formula:
All formulas are from this Wikipedia article.
Here is some modifications that make your code more compact and has less errors:
#include <stdio.h>
#include <math.h>
#define x 0.5 //here x is much easier to change
double pw(double, double); //declaration of the function should be done
int main() { //the default return type of main is int.
double k;
double sum = 0 ; //you should initiate your variables.
double sum_old = 1 ; //=1 only to pass the for condition first time.
//you don't need to define counter here
if(x < -1 || x > 1){
printf("x is not defined. Please choose an x in the interval [-1, 1]\n");
return 0;
}
for(k=0; sum!=sum_old; k++) {
sum_old = sum;
sum += pw((-1), k) * pw(x, (2*k) + 1)/((2*k) + 1);
printf("%.0f || %.17lf\n", k, sum);
}
printf("My result is: %.17lf\n",sum);
printf("atan(%f) is: %.17f\n", x, atan(x));
printf("My result minus atan(x) = %.17lf\n", sum - atan(x));
return 0;
}
double pw(double y, double n) { //functions should be declared out of the main function
double i;
double number = 1;
for (i = 0; i < n; i++) {
number *= y;
}
return(number);
}
double fc (double y) {
double i;
double number = 1;
for (i = 1; i <= y; i++){
number *= i;
}
return(number);
}
Second part of Q: Then solve the integral between 0 and y of (x^2)(e^(-x^2))dx=0.1 for y using bracketing and bisection.
Here's what I have done so far:
#include <stdio.h>
#include <math.h>
double f(double x, double y);
int main(void) {
int i, steps;
double a, b, y, h, m, lower, upper, x, simp, val;
/*
* Integrate (x^2)(e^(-x^2)) from 0 to y
*/
steps = 20000;
a = 0;
b = y;
h= (b-a)/steps;
/*
* now apply Simpson's rule. Note that the steps should be even.
*/
simp = -f(a, y);
x = a;
for (i =0; i < steps; i += 2) {
simp += 2.0*f(x,y)+4.0*f(x+h, y);
x += 2*h;
}
simp += f(b, y);
simp *= h/3.0;
/*
* print out the answer
*/
printf("The integral from 0 to y with respect to x by Simpson's Rule is %f\n", simp);
/*
* Now we need to bracket and bisect to find y
*/
lower = 0;
/*
* Lower bound is from turning point
*/
upper = 100;
/*
*Upper value given.
*/
while (upper - lower > 10E-10){
m = (lower + upper)/2;
val = f(m, y);
if (val >=0)
upper = m;
if (val <=0)
lower = m;
}
m = (lower + upper)/2;
printf("The value for y is: %lf\n", m);
return 0;
}
double f(double x, double y) {
return pow(x,2)*exp(pow(-x,2))-0.1;
}
Output: The integral from 0 to y with respect to x by Simpson's Rule is -0.000000
The value for y is: 0.302120
It runs but doesn't do exactly what I need it to do. I need to be able to continue working with the integral once I've used 0 and y as the limits. I can't do this. Then continue on and solve for y. It gives me a value for y but is not the same one I get if i solve using online calculators. Also, the output gave zero for the integral even when I changed the equation to be integrated to x^2. Can anyone help explain in as simple terms as possible?
I need to write my own asin() function without math.h library with the use of Taylor series. It works fine for numbers between <-0.98;0.98> but when I am close to limits it stops with 1604 iterations and therefore is inaccurate.
I don't know how to make it more accurete. Any suggestions are very appreciated!
The code is following:
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define EPS 0.000000000001
double my_arcsin(double x)
{
long double a, an, b, bn;
a = an = 1.0;
b = bn = 2.0;
long double n = 3.0;
double xn;
double xs = x;
double xp = x;
int iterace = 0;
xn = xs + (a/b) * (my_pow(xp,n) / n);
while (my_abs(xn - xs) >= EPS)
{
n += 2.0;
an += 2.0;
bn += 2.0;
a = a * an;
b = b * bn;
xs = xn;
xn = xs + (a/b) * (my_pow(xp,n) / n);
iterace++;
}
//printf("%d\n", iterace);
return xn;
}
int main(int argc, char* argv[])
{
double x = 0.0;
if (argc > 2)
x = strtod(argv[2], NULL);
if (strcmp(argv[1], "--asin") == 0)
{
if (x < -1 || x > 1)
printf("nan\n");
else
{
printf("%.10e\n", my_arcsin(x));
//printf("%.10e\n", asin(x));
}
return 0;
}
}
And also a short list of my values and expected ones:
My values Expected values my_asin(x)
5.2359877560e-01 5.2359877560e-01 0.5
1.5567132089e+00 1.5707963268e+00 1 //problem
1.4292568534e+00 1.4292568535e+00 0.99 //problem
1.1197695150e+00 1.1197695150e+00 0.9
1.2532358975e+00 1.2532358975e+00 0.95
Even though the convergence radius of the series expansion you are using is 1, therefore the series will eventually converge for -1 < x < 1, convergence is indeed painfully slow close to the limits of this interval. The solution is to somehow avoid these parts of the interval.
I suggest that you
use your original algorithm for |x| <= 1/sqrt(2),
use the identity arcsin(x) = pi/2 - arcsin(sqrt(1-x^2)) for 1/sqrt(2) < x <= 1.0,
use the identity arcsin(x) = -pi/2 + arcsin(sqrt(1-x^2)) for -1.0 <= x < -1/sqrt(2).
This way you can transform your input x into [-1/sqrt(2),1/sqrt(2)], where convergence is relatively fast.
PLEASE NOTICE: In this case I strongly recommend #Bence's method, since you can't expect a slowly convergent method with low data accuracy to obtain arbitrary precision.
However I'm willing to show you how to improve the result using your current algorithm.
The main problem is that a and b grows too fast and soon become inf (after merely about 150 iterations). Another similar problem is my_pow(xp,n) grows fast when n grows, however this doesn't matter much in this very case since we could assume the input data goes inside the range of [-1, 1].
So I've just changed the method you deal with a/b by introducing ab_ratio, see my edited code:
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define EPS 0.000000000001
#include <math.h>
#define my_pow powl
#define my_abs fabsl
double my_arcsin(double x)
{
#if 0
long double a, an, b, bn;
a = an = 1.0;
b = bn = 2.0;
#endif
unsigned long _n = 0;
long double ab_ratio = 0.5;
long double n = 3.0;
long double xn;
long double xs = x;
long double xp = x;
int iterace = 0;
xn = xs + ab_ratio * (my_pow(xp,n) / n);
long double step = EPS;
#if 0
while (my_abs(step) >= EPS)
#else
while (1) /* manually stop it */
#endif
{
n += 2.0;
#if 0
an += 2.0;
bn += 2.0;
a = a * an;
b = b * bn;
#endif
_n += 1;
ab_ratio *= (1.0 + 2.0 * _n) / (2.0 + 2.0 * _n);
xs = xn;
step = ab_ratio * (my_pow(xp,n) / n);
xn = xs + step;
iterace++;
if (_n % 10000000 == 0)
printf("%lu %.10g %g %g %g %g\n", _n, (double)xn, (double)ab_ratio, (double)step, (double)xn, (double)my_pow(xp, n));
}
//printf("%d\n", iterace);
return xn;
}
int main(int argc, char* argv[])
{
double x = 0.0;
if (argc > 2)
x = strtod(argv[2], NULL);
if (strcmp(argv[1], "--asin") == 0)
{
if (x < -1 || x > 1)
printf("nan\n");
else
{
printf("%.10e\n", my_arcsin(x));
//printf("%.10e\n", asin(x));
}
return 0;
}
}
For 0.99 (and even 0.9999999) it soon gives correct results with more than 10 significant digits. However it gets slow when getting near to 1.
Actually the process has been running for nearly 12 minutes on my laptop calculating --asin 1, and the current result is 1.570786871 after 3560000000 iterations.
UPDATED: It's been 1h51min now and the result 1.570792915 and iteration count is 27340000000.