#include "TH1D.h"
#include "TVirtualFFT.h"
#include "TF1.h"
#include "TCanvas.h"
#include "TMath.h"
#include<iostream>
#include<fstream>
#define false 0
#define true 1
#define pi 3.14159

Int_t n=1000;
//Double_t *in = new Double_t[2*((n+1)/2+1)];
int OK;
Int_t nsize=1001;

double filter1(double, double, double);

void DoLPFilterNewest()
{
  //prepare the canvas for drawing
   TCanvas *myc = new TCanvas("myc", "Fast Fourier Transform", 800, 600);
   myc->SetFillColor(45);
   TPad *c1_1 = new TPad("c1_1", "c1_1",0.01,0.67,0.49,0.99);
   TPad *c1_2 = new TPad("c1_2", "c1_2",0.51,0.67,0.99,0.99);
   TPad *c1_3 = new TPad("c1_3", "c1_3",0.01,0.34,0.49,0.65);
   TPad *c1_4 = new TPad("c1_4", "c1_4",0.51,0.34,0.99,0.65);
   TPad *c1_5 = new TPad("c1_5", "c1_5",0.01,0.01,0.49,0.32);
   TPad *c1_6 = new TPad("c1_6", "c1_6",0.51,0.01,0.99,0.32);
   c1_1->Draw();
   c1_2->Draw();
   c1_3->Draw();
   c1_4->Draw();
   c1_5->Draw();
   c1_6->Draw();
   c1_1->SetFillColor(30);
   c1_1->SetFrameFillColor(42);
   c1_2->SetFillColor(30);
   c1_2->SetFrameFillColor(42);
   c1_3->SetFillColor(30);
   c1_3->SetFrameFillColor(42);
   c1_4->SetFillColor(30);
   c1_4->SetFrameFillColor(42);
   c1_5->SetFillColor(30);
   c1_5->SetFrameFillColor(42);
   c1_6->SetFillColor(30);
   c1_6->SetFrameFillColor(42);
   
   c1_1->cd();
   TH1::AddDirectory(kFALSE);

   ofstream smoothedhist;
   //A function to sample
   TF1 *fsin = new TF1("fsin", "sin(x)+sin(2*x)+sin(0.5*x)+1", 0, 4*TMath::Pi());

   //TH1D *hsin = new TH1D("hsin", "hsin", n+1, 0, 4*TMath::Pi());
   TH1D *hsin = new TH1D("hsin", "hsin", n+1, 0, 1000);
   Double_t x;

   //Fill the histogram with function values
   for (Int_t i=0; i<=n; i++){
      x = (Double_t(i)/n)*(1000);
      //hsin->SetBinContent(i+1,in[i]*(1+.1*sin(55*x))+1);
      hsin->SetBinContent(i+1,in[i]);
   }
   //cout << hsin->GetBinContent(43) << endl;
   //hsin->Smooth(2500);
   hsin->Draw();
   //fsin->GetXaxis()->SetLabelSize(0.05);
   //fsin->GetYaxis()->SetLabelSize(0.05);
   
   c1_2->cd();
   //Compute the transform and look at the magnitude of the output
   //TH1 *hm = 0;
   TVirtualFFT::SetTransform(0);
   hm = hsin->FFT(hm, "RE");
   hm->SetTitle("Real part of the 1st transform");
   hm->Draw();
   //NOTE: for "real" frequencies you have to divide the x-axes range with the range of your function 
   //(in this case 4*Pi); y-axes has to be rescaled by a factor of 1/SQRT(n) to be right: this is not done automatically!
   
   hm->SetStats(kFALSE);
   hm->GetXaxis()->SetLabelSize(0.05);
   hm->GetYaxis()->SetLabelSize(0.05);
   c1_3->cd();    
   //Look at the imaginary part
   TVirtualFFT *fft1 = TVirtualFFT::GetCurrentTransform();
   TH1 *hp =0;
   hp = hsin->FFT(hp, "IM");
   hp->SetTitle("Imaginary Part of the 1st transform");
   hp->Draw();
   hp->SetStats(kFALSE);
   hp->GetXaxis()->SetLabelSize(0.05);
   hp->GetYaxis()->SetLabelSize(0.05);

   int yy, ww, kk, jj, ll;
   double zz, xx;
   double beta=0.25;
   double omega=1.0;
   Double_t T=2*pi/omega;
   Double_t cc, dd, ee, ff;
   int stop=20;
   TComplex comp[n], out[n];
   zz = (1-beta)/(2*T);
   xx = (1+beta)/(2*T);
   ww = ceil(zz);
   yy = ceil(xx);
   //Look at the DC component and the Nyquist harmonic:
   Double_t re, im;
   //That's the way to get the current transform object:
   TVirtualFFT *fft = TVirtualFFT::GetCurrentTransform();
   c1_4->cd();

   /*for (jj=1; jj <= stop; jj++) {
     fft->GetPointComplex(jj, re, im);
     //cout << comp[jj] << endl;
     }*/
   /*for (kk=(stop+1); kk <= n; kk++) {
     fft->GetPointComplex(kk, re, im);
     ee = re*filter1(kk, beta, T);
     ff = im*filter1(kk, beta, T);
     comp[kk] = (ee,ff);
     //cout << comp[kk] << endl;
     }*/
   /*for (ll=yy; ll<=n; ll++) {
     comp[ll] = 0;
     }*/
   //Use the following method to get just one point of the output
   fft->GetPointComplex(0, re, im);
   printf("1st transform: DC component: %f\n", re);
   fft->GetPointComplex(n/2+1, re, im);
   printf("1st transform: Nyquist harmonic: %f\n", re);

   //Use the following method to get the full output:
   Double_t *re_full = new Double_t[n];
   Double_t *im_full = new Double_t[n];
   fft->GetPointsComplex(re_full,im_full);
   
   //Now let's make a backward transform:
   TVirtualFFT *fft_back = TVirtualFFT::FFT(1, &n, "C2R M K");
   fft_back->SetPointsComplex(re_full,im_full);

   /*for (jj=1; jj <= zz; jj++) {
     fft_back->SetPointComplex(jj, comp[jj]);
     }*/
   cout << (1-beta)/(2*T) << " : " << (1+beta)/(2*T) << endl;
   for (kk=(stop+1); kk <= n; kk++) {
     fft_back->SetPointComplex(kk, 0);
   }
   /*for (ll=yy; ll <= n; ll++) {
     fft_back->SetPointComplex(ll, comp[ll]);
     }*/
   fft_back->Transform();
   TH1 *hb = 0;
   //Let's look at the output
   hb = TH1::TransformHisto(fft_back,hb,"Re");

   for (int jj=0; jj<nppw; jj++) {
     data[(g-1)*(nppw+1)+jj]= (hb->GetBinContent(jj))/n;
   }
   //Store smoothed results
   /*smoothedhist.open ("/usr/local/data/smoothedarr.txt");
   for (jj=0; jj <= n; jj++) {
     smoothedhist << (hb->GetBinContent(jj))/n << endl;
   }
   smoothedhist << 99999 << endl;
   smoothedhist.close();*/

   hb->SetTitle("The backward transform result");
   //hb->Smooth(2500);
   hb->Draw();
   //NOTE: here you get at the x-axes number of bins and not real values
   //(in this case 25 bins has to be rescaled to a range between 0 and 4*Pi; 
   //also here the y-axes has to be rescaled (factor 1/bins)
   hb->SetStats(kFALSE);
   hb->GetXaxis()->SetLabelSize(0.05);
   hb->GetYaxis()->SetLabelSize(0.05);
   delete fft_back;
   fft_back=0;

//********* Data array - same transform ********//

   //Allocate an array big enough to hold the transform output
   //Transform output in 1d contains, for a transform of size N, 
   //N/2+1 complex numbers, i.e. 2*(N/2+1) real numbers
   //our transform is of size n+1, because the histogram has n+1 bins

   ofstream outdata;
   int Z;
   Double_t re_2,im_2;
   //cout << in[122] << " : " << in[133] << " : " << n << endl;
   
   Int_t n_size = n+1;
   TVirtualFFT *fft_own = TVirtualFFT::FFT(1, &n_size, "R2C ES K");
   if (!fft_own) return;
   fft_own->SetPoints(in);
   fft_own->Transform();

   //Copy all the output points:
   fft_own->GetPoints(in);
   //Draw the real part of the output
   c1_5->cd();
   TH1 *hr = 0;
   hr = TH1::TransformHisto(fft_own, hr, "PH");
   hr->SetTitle("Phase of the 3rd (array) transform");
   hr->Draw();
   hr->SetStats(kFALSE);
   hr->GetXaxis()->SetLabelSize(0.05);
   hr->GetYaxis()->SetLabelSize(0.05);
   c1_6->cd();
   TH1 *him = 0;
   him = TH1::TransformHisto(fft_own, him, "MA");
   him->SetTitle("Magnitude of the 3rd (array) transform");
   him->Draw();
   him->SetStats(kFALSE);
   him->GetXaxis()->SetLabelSize(0.05);
   him->GetYaxis()->SetLabelSize(0.05);

   myc->cd();
   //Now let's make another transform of the same size
   //The same transform object can be used, as the size and the type of the transform
   //haven't changed
   /*TF1 *fcos = new TF1("fcos", "cos(x)+cos(0.5*x)+cos(2*x)+1", 0, 4*TMath::Pi());
   for (Int_t i=0; i<=n; i++){
      x = (Double_t(i)/n)*(4*TMath::Pi());
      in[i] =  fcos->Eval(x);
   }
   fft_own->SetPoints(in);
   fft_own->Transform();
   fft_own->GetPointComplex(0, re_2, im_2);
   printf("2nd transform: DC component: %f\n", re_2);
   fft_own->GetPointComplex(n/2+1, re_2, im_2);
   printf("2nd transform: Nyquist harmonic: %f\n", re_2);*/
   delete fft_own;
   //delete [] in;
   delete [] re_full;
   delete [] im_full;
   //delete hm;
   //delete hb;
   //delete hp;
   //delete hr;
   //delete him;
}

double filter1 (double f, double beta, double T)
{
	double Hf;
	Hf = T*(1+cos(pi*T*(fabs(f)-(1-beta)/(2*T))/beta))/2;
	return (Hf);
}