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fix : updated the documentation

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Ameya Chawla 2021-10-17 23:12:52 +05:30 committed by GitHub
parent 89b2ce7b10
commit 748ba48e9d
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1 changed files with 13 additions and 8 deletions
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21
numerical_methods/fast_fourier_transform.cpp
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@ -1,7 +1,9 @@
/**
* @fast_fourier_transform.cpp
* @brief A fast Fourier transform (FFT) is an algorithm that computes the
* discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT).
* discrete Fourier transform (DFT) of a sequence , or its inverse (IDFT) , this algorithm
* has application in use case scenario where a user wants to find points of a function
* in short period time by just using the coefficents of the polynomial function.
* @details
* https://medium.com/@aiswaryamathur/understanding-fast-fourier-transform-from-scratch-to
-solve-polynomial-multiplication-8018d511162f
@ -65,6 +67,8 @@ complex<double>* FastFourierTransform(complex<double>*p,int n)
/**
* @brief Self-test implementations
*declaring two test cases and checking for the error
*in predicted and true value is less than 0.000000000001.
* @returns void
*/
static void test() {
@ -72,17 +76,17 @@ static void test() {
complex<double> t1[2]={1,2};///Test case 1
complex<double> t2[4]={1,2,3,4};///Test case 2
complex<double> t2[4]={1,2,3,4};///Test case 2
int n1=sizeof(t1)/sizeof(complex<double>);
int n2=sizeof(t2)/sizeof(complex<double>);
int n1=sizeof(t1)/sizeof(complex<double>);
int n2=sizeof(t2)/sizeof(complex<double>);
complex<double> r1[2]={{3,0},{-1,0} };///True Answer for test case 1
complex<double> r2[4]={{10,0},{-2,-2},{-2,0},{-2,2} };///True Answer for test case 2
complex<double> r2[4]={{10,0},{-2,-2},{-2,0},{-2,2} };///True Answer for test case 2
complex<double> *o1=FastFourierTransform(t1,n1);
@ -91,13 +95,13 @@ static void test() {
for(int i=0;i<n1;i++)
{
assert(r1[i].real()-o1->real()<0.000000000001 and r1[i].imag()-o1->imag()<0.000000000001 );
assert(r1[i].real()-o1->real()<0.000000000001 and r1[i].imag()-o1->imag()<0.000000000001 );/// Comparing for both real and imaginary values for test case 1
o1++;
}
for(int i=0;i<n2;i++)
{
assert(r2[i].real()-o2->real()<0.000000000001 and r2[i].imag()-o2->imag()<0.000000000001 );
assert(r2[i].real()-o2->real()<0.000000000001 and r2[i].imag()-o2->imag()<0.000000000001 );/// Comparing for both real and imaginary values for test case 2
o2++;
}
@ -108,6 +112,7 @@ static void test() {
* @brief Main function
* @param argc commandline argument count (ignored)
* @param argv commandline array of arguments (ignored)
* calls automated test function to test the working of fast fourier transform.
* @returns 0 on exit
*/
@ -118,5 +123,5 @@ int main(int argc, char const *argv[])
test();
return 0;
return 0;
}