how to overload minus operator to subtract two fractional numbers? - c++

I want to subtract two fractional numbers using operator overloading. I have write a piece of code in order to accomplish this task:
#include<iostream>
using namespace std;
void HCF(int& a, int& b)
{
int m, n;
m = a;
n = b;
while (m != n)
{
if (m > n)
m = m - n;
else
n = n - m;
}
a = a / m;
b = b / m;
}
class Rational {
int x1;
int y1;
public:
void simplify()
{
int m, n, r;
n = fabs(y1);
m = fabs(x1);
while (r = m % n)//Find the Maximum Common Number of m,n
{
m = n;
n = r;
}
y1 /= n; // Simplification
x1 /= n;
if (y1 < 0) // Convert denominator to positive number
{
y1 = -y1;
x1 = -x1;
}
}
Rational(int num = 0, int denom = 1)
{
if (denom) {
x1 = num;
y1 = denom;
}
else {
x1 = 0;
y1 = 1;
}
}
Rational(const Rational& copy)//Copy Constructor
{
x1 = copy.x1;
y1 = copy.y1;
}
Rational operator-(const Rational& x) const //Overloaded minus operator
{
Rational temp;
temp.x1 = x1 * x.y1 - x.x1 * y1;
temp.y1 = y1 * x.y1;
temp.simplify();
return temp;
}
operator string() const //Overloaded string operator
{
int numerator = x1, denominator = y1;
HCF(numerator, denominator);
string str;
if (denominator == 1)
str = to_string(numerator);
else
str = to_string(numerator) + "/" + to_string(denominator);
return str;
}
};
int main()
{
Rational a(5, 1);
Rational b(3, 4);
Rational c;
Rational d;
Rational x(5, 1);
c = a - x;
string expected1 = "0"; //Expected value
string actual1 = (string)c;//Actual value
cout << actual1.compare(expected1);//Comparing actual and expected value
d = c - b;
string expected2 = "-3/4";
string actual2 = (string)d;
cout << actual2.compare(expected2);
}
As we can see, in the main() function, both cout statements should print 0 because when we compare both strings, they must be equal. But the problem is, when I run this program, it prints nothing, and I don't know why.
My operator string() converts an integer fraction into a string. My operator- takes the LCM and finds the final value after subtracting two fractional numbers. In the main() function, I have declared five objects for class Rational, and then I simply perform subtraction and then I compare the expected and actual values, which should return 0 in the cout statement.
I have also used the simplify() member function to check whether the fraction is completely in simpler form or not. For example, it should simplify 2/4 into 1/2.
Where is the mistake? All other functions except operator- are running correctly. The real problem is with the operator-, ie when we perform c=a-x, the value of c would be 0 as a string. Similarly, if we perform d=c-b then the expected value should be -3/4 as a string.
I have also tried to run this code on Google Test, but it fails the test case.

Use this GCD (greatest common divisor) function to implement your HCF function. Yours currently exhibits an endless loop when given 0 as a first argument.
To reduce a fraction, divide numerator and denominator by their greatest common divisor.
This is called the Euclidean algorithm.
template <typename T>
T GCD(T a, T b) {
while (b != 0)
{
T t = a % b;
a = b;
b = t;
}
return std::max(a, -a);
}

Related

How do I implement the numerical differentiation (f'(x) = f(x+h)-f(x)/ h

2nd task:
For a function f : R^n → R the gradient at a point ~x ∈ R^n is to be calculated:
- Implement a function
CMyVector gradient(CMyVector x, double (*function)(CMyVector x)),
which is given in the first parameter the location ~x and in the second parameter the function f as function pointer in the second parameter, and which calculates the gradient ~g = grad f(~x) numerically
by
gi = f(x1, . . . , xi-1, xi + h, xi+1 . . . , xn) - f(x1, . . . , xn)/h
to fixed h = 10^-8.
My currently written program:
Header
#pragma once
#include <vector>
#include <math.h>
class CMyVektor
{
private:
/* data */
int Dimension = 0;
std::vector<double>Vector;
public:
CMyVektor();
~CMyVektor();
//Public Method
void set_Dimension(int Dimension /* Aktuelle Dim*/);
void set_specified_Value(int index, int Value);
double get_specified_Value(int key);
int get_Vector_Dimension();
int get_length_Vektor();
double& operator [](int index);
string umwandlung()
};
CMyVektor::CMyVektor(/* args */)
{
Vector.resize(0, 0);
}
CMyVektor::~CMyVektor()
{
for (size_t i = 0; i < Vector.size(); i++)
{
delete Vector[i];
}
}
void CMyVektor::set_Dimension(int Dimension /* Aktuelle Dim*/)
{
Vector.resize(Dimension);
};
void CMyVektor::set_specified_Value(int index, int Value)
{
if (Vector.empty())
{
Vector.push_back(Value);
}
else {
Vector[index] = Value;
}
};
double CMyVektor::get_specified_Value(int key)
{
// vom intervall anfang - ende des Vectors
for (unsigned i = 0; i < Vector.size(); i++)
{
if (Vector[i] == key) {
return Vector[i];
}
}
};
int CMyVektor::get_Vector_Dimension()
{
return Vector.size();
};
// Berechnet den Betrag "länge" eines Vectors.
int CMyVektor::get_length_Vektor()
{
int length = 0;
for (size_t i = 0; i < Vector.size(); i++)
{
length += Vector[i]^2
}
return sqrt(length);
}
// [] Operator überladen
double& CMyVektor::operator [](int index)
{
return Vector[index];
}
main.cpp
#include <iostream>
#include "ClassVektor.h"
using namespace std;
CMyVektor operator+(CMyVektor a, CMyVektor b);
CMyVektor operator*(double lambda, CMyVektor a);
CMyVektor gradient(CMyVektor x, double (*funktion)(CMyVektor x));
int main() {
CMyVektor V1;
CMyVektor V2;
CMyVektor C;
C.set_Dimension(V1.get_length_Vector());
C= V1 + V2;
std::cout << "Addition : "<< "(";;
for (int i = 0; i < C.get_length_Vector(); i++)
{
std::cout << C[i] << " ";
}
std::cout << ")" << endl;
C = lamda * C;
std::cout << "Skalarprodukt: "<< C[0]<< " ";
}
// Vector Addition
CMyVektor operator+(CMyVektor a, CMyVektor b)
{
int ai = 0, bi = 0;
int counter = 0;
CMyVektor c;
c.set_Dimension(a.get_length_Vector());
// Wenn Dimension Gleich dann addition
if (a.get_length_Vector() == b.get_length_Vector())
{
while (counter < a.get_length_Vector())
{
c[counter] = a[ai] + b[bi];
counter++;
}
return c;
}
}
//Berechnet das Skalarprodukt
CMyVektor operator*(double lambda, CMyVektor a)
{
CMyVektor c;
c.set_Dimension(1);
for (unsigned i = 0; i < a.get_length_Vector(); i++)
{
c[0] += lambda * a[i];
}
return c;
}
/*
* Differenzenquotient : (F(x0+h)+F'(x0)) / h
* Erster Parameter die Stelle X - Zweiter Parameter die Funktion
* Bestimmt numerisch den Gradienten.
*/
CMyVektor gradient(CMyVektor x, double (*funktion)(CMyVektor x))
{
}
My problem now is that I don't quite know how to deal with the
CMyVector gradient(CMyVector x, double (*function)(CMyVector x))
function and how to define a function that corresponds to it.
I hope that it is enough information. Many thanks.
The function parameter is the f in the difference formula. It takes a CMyVector parameter x and returns a double value. You need to supply a function parameter name. I'll assume func for now.
I don't see a parameter for h. Are you going to pass a single small value into the gradient function or assume a constant?
The parameter x is a vector. Will you add a constant h to each element?
This function specification is a mess.
Function returns a double. How do you plan to turn that into a vector?
No wonder you're confused. I am.
Are you trying to do something like this?
You are given a function signature
CMyVector gradient(CMyVector x, double (*function)(CMyVector x))
Without knowing the exact definition I will assume, that at least the basic numerical vector operations are defined. That means, that the following statements compile:
CMyVector x {2.,5.,7.};
CMyVector y {1.,7.,4.};
CMyVector z {0.,0.,0.};
double a = 0.;
// vector addition and assigment
z = x + y;
// vector scalar multiplication and division
z = z * a;
z = x / 0.1;
Also we need to know the dimension of the CMyVector class. I assumed and will continue to do so that it is three dimensional.
The next step is to understand the function signature. You get two parameters. The first one denotes the point, at which you are supposed to calculate the gradient. The second is a pointer to the function f in your formula. You do not know it, but can call it on a vector from within your gradient function definition. That means, inside of the definition you can do something like
double f_at_x = function(x);
and the f_at_x will hold the value f(x) after that operation.
Armed with this, we can try to implement the formula, that you mentioned in the question title:
CMyVector gradient(CMyVector x, double (*function)(CMyVector x)) {
double h = 0.001;
// calculate first element of the gradient
CMyVector e1 {1.0, 0.0, 0.0};
double result1 = ( function(x + e1*h) - function(x) )/h;
// calculate second element of the gradient
CMyVector e2 {0.0, 1.0, 0.0};
double result2 = ( function(x + e2*h) - function(x) )/h;
// calculate third element of the gradient
CMyVector e3 {0.0, 0.0, 1.0};
double result3 = ( function(x + e3*h) - function(x) )/h;
// return the result
return CMyVector {result1, result2, result3};
}
There are several thing worth to mention in this code. First and most important I have chosen h = 0.001. This may like a very arbitrary choice, but the choice of the step size will very much impact the precision of your result. You can find a whole lot of discussion about that topic here. I took the same value that according to that wikipedia page a lot of handheld calculators use internally. That might not be the best choice for the floating point precision of your processor, but should be a fair one to start with.
Secondly the code looks very ugly for an advanced programmer. We are doing almost the same thing for each of the three dimensions. Ususally you would like to do that in a for loop. The exact way of how this is done depends on how the CMyVector type is defined.
Since the CMyVektor is just rewritting the valarray container, I will directly use the valarray:
#include <iostream>
#include <valarray>
using namespace std;
using CMyVektor = valarray<double>;
CMyVektor gradient(CMyVektor x, double (*funktion)(CMyVektor x));
const double h = 0.00000001;
int main()
{
// sum(x_i^2 + x_i)--> gradient: 2*x_i + 1
auto fun = [](CMyVektor x) {return (x*x + x).sum();};
CMyVektor d = gradient(CMyVektor{1,2,3,4,5}, fun);
for (auto i: d) cout << i<<' ';
return 0;
}
CMyVektor gradient(CMyVektor x, double (*funktion)(CMyVektor x)){
CMyVektor grads(x.size());
CMyVektor pos(x.size());
for (int i = 0; i<x.size(); i++){
pos[i] = 1;
grads[i] = (funktion(x + h * pos) - funktion(x))/ h;
pos[i] = 0;
}
return grads;
}
The prints out 3 5 7 9 11 which is what is expected from the given function and the given location

Trying to calculate GCD in C++

I think I am not calling the function or passing it correctly. Here are a couple of snippets that I am having issues with.
Using test data, 1/2 and 8/16 returns 1/2 instead of 1/1.
This is my code to calculate the GCD:
void Fractions::gcd(int n, int d)
{
int a,b,c;
a = n;
b = d;
while (a%b != 0)
{
c = a % b;
a = b;
b = c;
}
num = n/b;
denom = d/b;
}
This is the code that calculates will add numbers from input and calculate the GCD based from those numbers:
Fractions Fractions::operator+(Fractions& fraction2)
{
Fractions totalAddition;
totalAddition.num = (num * fraction2.denom + denom * fraction2.num);
totalAddition.denom = (denom * fraction2.denom);
totalAddition.gcd(num, denom); // i think issue is here
return totalAddition;
}
The only problem here is the name of the function.
A function called gcd should return the Greatest Common Divisor:
int gcd(int n, int d) {
int a, b, c;
a = n;
b = d;
while (a % b != 0) {
c = a % b;
a = b;
b = c;
}
return b;
}
It doesn't need to be a member function of Fraction to do this - it can be a standalone function, which is better, as it makes Fraction more encapsulated. But you can give it an overload which digests Fraction:
int gcd(const Fraction& frac){
return gcd(frac.numerator(), frac.denominator());
}
The name gcd is on the terse side but clear enough in context.
What your function is doing is it's simplifying a fraction, as a member function of a Fraction object, and overwriting that Fraction's member variables. So, it should be called simplify, and it doesn't need to take any input:
void Fractions::simplify() {
int a, b, c;
a = num;
b = denom;
while (a % b != 0) {
c = a % b;
a = b;
b = c;
}
num = n / b;
denom = d / b;
}
You might find you don't need a gcd function in which case simplify will be enough. But if you do need both functions, you can avoid some duplication of code here:
void Fractions::simplify() {
int g = gcd(*this);
num /= g;
denom /= g;
}
//Euclidean algorithm
//if b<a the gcd(a,b)=gcd(a-b,b)
int gcd(int a,int b)
{
while(a!=b)
{
if(a>b)
a=a-b;
else
b=b-a;
}
return a;
}
Output
15 12
3
//Optimal implementation of Euclidean Algorithm
int gcd(int a,int b)
{
if(b==0)
return a;
else
return gcd(b,a%b);
}
Output
15 12
3

Overloading operator + for fractions (using lcm)

I want to compute the sum of two fraction using lcm of numerator and denominator. That means as a result I want to get a fraction in the reduced form. I have the following cpp file.
#include <iostream> //need it for cin and cout
#include "fraction.h"
Fraction::Fraction()
{
num = 1;
den = 1;
}
Fraction::Fraction(int n, int d)
{
int tmp_gcd = gcd(n, d);
num = n / tmp_gcd;
den = d / tmp_gcd;
}
int Fraction::gcd(int a, int b)
{
int tmp_gcd = 1;
// Implement GCD of two numbers;
return tmp_gcd;
}
int Fraction::lcm(int a, int b)
{
return a * b / gcd(a, b);
}
Fraction operator+(const Fraction&a,const Fraction &b)
{
int c=(lcm(b.den,a.den)/b.den)*a.num+b.num*(lcm(b.den,a.den)/a.den);
int d=lcm(b.den,a.den);
Fraction result(c,d);
return result;
}
However this code does not work because lcm is not defined in this scope.
What is the key that allows lcm work in this scope? If you please could explain more, I would be very thankful.
lcm is a member of Fraction. You can refer to it just as lcm within members of Fraction; but operator+ isn't a member, so you'll have to use the qualified name Fraction::lcm.
It will also need to be static. (Hopefully it already is, but I can't see the declaration to be sure).

Finding square root without using sqrt function?

I was finding out the algorithm for finding out the square root without using sqrt function and then tried to put into programming. I end up with this working code in C++
#include <iostream>
using namespace std;
double SqrtNumber(double num)
{
double lower_bound=0;
double upper_bound=num;
double temp=0; /* ek edited this line */
int nCount = 50;
while(nCount != 0)
{
temp=(lower_bound+upper_bound)/2;
if(temp*temp==num)
{
return temp;
}
else if(temp*temp > num)
{
upper_bound = temp;
}
else
{
lower_bound = temp;
}
nCount--;
}
return temp;
}
int main()
{
double num;
cout<<"Enter the number\n";
cin>>num;
if(num < 0)
{
cout<<"Error: Negative number!";
return 0;
}
cout<<"Square roots are: +"<<sqrtnum(num) and <<" and -"<<sqrtnum(num);
return 0;
}
Now the problem is initializing the number of iterations nCount in the declaratione ( here it is 50). For example to find out square root of 36 it takes 22 iterations, so no problem whereas finding the square root of 15625 takes more than 50 iterations, So it would return the value of temp after 50 iterations. Please give a solution for this.
There is a better algorithm, which needs at most 6 iterations to converge to maximum precision for double numbers:
#include <math.h>
double sqrt(double x) {
if (x <= 0)
return 0; // if negative number throw an exception?
int exp = 0;
x = frexp(x, &exp); // extract binary exponent from x
if (exp & 1) { // we want exponent to be even
exp--;
x *= 2;
}
double y = (1+x)/2; // first approximation
double z = 0;
while (y != z) { // yes, we CAN compare doubles here!
z = y;
y = (y + x/y) / 2;
}
return ldexp(y, exp/2); // multiply answer by 2^(exp/2)
}
Algorithm starts with 1 as first approximation for square root value.
Then, on each step, it improves next approximation by taking average between current value y and x/y. If y = sqrt(x), it will be the same. If y > sqrt(x), then x/y < sqrt(x) by about the same amount. In other words, it will converge very fast.
UPDATE: To speed up convergence on very large or very small numbers, changed sqrt() function to extract binary exponent and compute square root from number in [1, 4) range. It now needs frexp() from <math.h> to get binary exponent, but it is possible to get this exponent by extracting bits from IEEE-754 number format without using frexp().
Why not try to use the Babylonian method for finding a square root.
Here is my code for it:
double sqrt(double number)
{
double error = 0.00001; //define the precision of your result
double s = number;
while ((s - number / s) > error) //loop until precision satisfied
{
s = (s + number / s) / 2;
}
return s;
}
Good luck!
Remove your nCount altogether (as there are some roots that this algorithm will take many iterations for).
double SqrtNumber(double num)
{
double lower_bound=0;
double upper_bound=num;
double temp=0;
while(fabs(num - (temp * temp)) > SOME_SMALL_VALUE)
{
temp = (lower_bound+upper_bound)/2;
if (temp*temp >= num)
{
upper_bound = temp;
}
else
{
lower_bound = temp;
}
}
return temp;
}
As I found this question is old and have many answers but I have an answer which is simple and working great..
#define EPSILON 0.0000001 // least minimum value for comparison
double SquareRoot(double _val) {
double low = 0;
double high = _val;
double mid = 0;
while (high - low > EPSILON) {
mid = low + (high - low) / 2; // finding mid value
if (mid*mid > _val) {
high = mid;
} else {
low = mid;
}
}
return mid;
}
I hope it will be helpful for future users.
if you need to find square root without using sqrt(),use root=pow(x,0.5).
Where x is value whose square root you need to find.
//long division method.
#include<iostream>
using namespace std;
int main() {
int n, i = 1, divisor, dividend, j = 1, digit;
cin >> n;
while (i * i < n) {
i = i + 1;
}
i = i - 1;
cout << i << '.';
divisor = 2 * i;
dividend = n - (i * i );
while( j <= 5) {
dividend = dividend * 100;
digit = 0;
while ((divisor * 10 + digit) * digit < dividend) {
digit = digit + 1;
}
digit = digit - 1;
cout << digit;
dividend = dividend - ((divisor * 10 + digit) * digit);
divisor = divisor * 10 + 2*digit;
j = j + 1;
}
cout << endl;
return 0;
}
Here is a very simple but unsafe approach to find the square-root of a number.
Unsafe because it only works by natural numbers, where you know that the base respectively the exponent are natural numbers. I had to use it for a task where i was neither allowed to use the #include<cmath> -library, nor i was allowed to use pointers.
potency = base ^ exponent
// FUNCTION: square-root
int sqrt(int x)
{
int quotient = 0;
int i = 0;
bool resultfound = false;
while (resultfound == false) {
if (i*i == x) {
quotient = i;
resultfound = true;
}
i++;
}
return quotient;
}
This a very simple recursive approach.
double mySqrt(double v, double test) {
if (abs(test * test - v) < 0.0001) {
return test;
}
double highOrLow = v / test;
return mySqrt(v, (test + highOrLow) / 2.0);
}
double mySqrt(double v) {
return mySqrt(v, v/2.0);
}
Here is a very awesome code to find sqrt and even faster than original sqrt function.
float InvSqrt (float x)
{
float xhalf = 0.5f*x;
int i = *(int*)&x;
i = 0x5f375a86 - (i>>1);
x = *(float*)&i;
x = x*(1.5f - xhalf*x*x);
x = x*(1.5f - xhalf*x*x);
x = x*(1.5f - xhalf*x*x);
x=1/x;
return x;
}
After looking at the previous responses, I hope this will help resolve any ambiguities. In case the similarities in the previous solutions and my solution are illusive, or this method of solving for roots is unclear, I've also made a graph which can be found here.
This is a working root function capable of solving for any nth-root
(default is square root for the sake of this question)
#include <cmath>
// for "pow" function
double sqrt(double A, double root = 2) {
const double e = 2.71828182846;
return pow(e,(pow(10.0,9.0)/root)*(1.0-(pow(A,-pow(10.0,-9.0)))));
}
Explanation:
click here for graph
This works via Taylor series, logarithmic properties, and a bit of algebra.
Take, for example:
log A = N
x
*Note: for square-root, N = 2; for any other root you only need to change the one variable, N.
1) Change the base, convert the base 'x' log function to natural log,
log A => ln(A)/ln(x) = N
x
2) Rearrange to isolate ln(x), and eventually just 'x',
ln(A)/N = ln(x)
3) Set both sides as exponents of 'e',
e^(ln(A)/N) = e^(ln(x)) >~{ e^ln(x) == x }~> e^(ln(A)/N) = x
4) Taylor series represents "ln" as an infinite series,
ln(x) = (k=1)Sigma: (1/k)(-1^(k+1))(k-1)^n
<~~~ expanded ~~~>
[(x-1)] - [(1/2)(x-1)^2] + [(1/3)(x-1)^3] - [(1/4)(x-1)^4] + . . .
*Note: Continue the series for increased accuracy. For brevity, 10^9 is used in my function which expresses the series convergence for the natural log with about 7 digits, or the 10-millionths place, for precision,
ln(x) = 10^9(1-x^(-10^(-9)))
5) Now, just plug in this equation for natural log into the simplified equation obtained in step 3.
e^[((10^9)/N)(1-A^(-10^-9)] = nth-root of (A)
6) This implementation might seem like overkill; however, its purpose is to demonstrate how you can solve for roots without having to guess and check. Also, it would enable you to replace the pow function from the cmath library with your own pow function:
double power(double base, double exponent) {
if (exponent == 0) return 1;
int wholeInt = (int)exponent;
double decimal = exponent - (double)wholeInt;
if (decimal) {
int powerInv = 1/decimal;
if (!wholeInt) return root(base,powerInv);
else return power(root(base,powerInv),wholeInt,true);
}
return power(base, exponent, true);
}
double power(double base, int exponent, bool flag) {
if (exponent < 0) return 1/power(base,-exponent,true);
if (exponent > 0) return base * power(base,exponent-1,true);
else return 1;
}
int root(int A, int root) {
return power(E,(1000000000000/root)*(1-(power(A,-0.000000000001))));
}

How can i format a decimal to a fraction with limits to the denominator

Hi All I am trying to format a decimal A into a fraction B + C/D, where certain limit is imposed on D, say D could be one among [2...9] or [2...19] etc. BCD are integers
The goal is to get the formatted fraction as close to the decimal as possible.
Is there an existing algorithm/theory on this?
Or is there any API I can call on Mac SDK?
// Not tested or even compiled :-). Assumes you are handling sign
// in: a - the decimal to convert
// limit - the largest denominator you will allow
// out: outN - Numerator
// outD Denominator
#include <math.h>
void d2f(double a, int limit, int& outN, int& outD) {
double z;
int dPrev, d, n;
a = fabs(a);
z = a;
d = 1;
n = a;
dPrev = 0;
while (a - (double)(n/d) != 0 && z != floor(z)) {
z = 1 / (z - floor(z));
int tmp = d;
d = d * (int)floor(z) + dPrev;
if (d > limit) {
d = tmp;
break;
}
dPrev = tmp;
n = floor(a * d + 0.5);
}
outN = n;
outD = d;
}
Hope that helps/works :-)
Look into continued fractions.