WSJT-X/ffft.f

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subroutine ffft(d,npts,isign,ireal)
C Fourier transform of length npts=2**k, performed in place.
C Input data in array d, treated as complex if ireal=0, and as real if ireal=1.
C In either case the transform values are returned in array d, treated as
C complex. The DC term is d(1), and d(npts/2+1) is the term at the Nyquist
C frequency. The basic algorithm is the same as Norm Brenner's FOUR1, and
C uses radix-2 transforms.
C J. H. Taylor, Princeton University.
complex d(npts),t,w,wstep,tt,uu
data pi/3.14159265359/
C Shuffle the data to bit-reversed order.
imax=npts/(ireal+1)
irev=1
do 5 i=1,imax
if(i.ge.irev) go to 2
t=d(i)
d(i)=d(irev)
d(irev)=t
2 mmax=imax/2
3 if(irev.le.mmax) go to 5
irev=irev-mmax
mmax=mmax/2
if(mmax.ge.1) go to 3
5 irev=irev+mmax
C The radix-2 transform begins here.
api=isign*pi/2.
mmax=1
6 istep=2*mmax
wstep=cmplx(-2.*sin(api/mmax)**2,sin(2.*api/mmax))
w=1.
do 9 m=1,mmax
C This in the inner-most loop -- optimization here is important!
do 8 i=m,imax,istep
t=w*d(i+mmax)
d(i+mmax)=d(i)-t
8 d(i)=d(i)+t
9 w=w*(1.+wstep)
mmax=istep
if(mmax.lt.imax) go to 6
if(ireal.eq.0) return
C Now complete the last stage of a doubled-up real transform.
jmax=imax/2 + 1
wstep=cmplx(-2.*sin(isign*pi/npts)**2,sin(isign*pi/imax))
w=1.0
d(imax+1)=d(1)
do 10 j=1,jmax
uu=cmplx(real(d(j))+real(d(2+imax-j)),aimag(d(j)) -
+ aimag(d(2+imax-j)))
tt=w*cmplx(aimag(d(j))+aimag(d(2+imax-j)),-real(d(j)) +
+ real(d(2+imax-j)))
d(j)=uu+tt
d(2+imax-j)=conjg(uu-tt)
10 w=w*(1.+wstep)
return
end