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3a5edb5af5
New optional argument to jt9: -w patience
Default is patience = 1
Example timing measurements for 130610_2343.wav:
patience plan execute
(s) (s)
-----------------------------------------------
0 0.01 1.25 FFTW_ESTIMATE
1 0.69 1.25 FFTW_ESTIMATE_PATIENT
2 16.97 1.15 FFTW_MEASURE
3 390.88 1.15 FFTW_PATIENT
Conclusions, consistent with expectation based on past experience
with similar FFTs:
- First decode (in each mode) with patience = 2 is slow.
- Speed advantage of patience = 2 is small but measurable.
- No measurable advantage in using patience > 2.
Present mainwindow.cpp has "-w 1" hard-wired.
git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@4610 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
134 lines
3.8 KiB
Fortran
134 lines
3.8 KiB
Fortran
subroutine filbig(dd,npts,f0,newdat,c4a,n4,sq0)
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! Filter and downsample the real data in array dd(npts), sampled at 12000 Hz.
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! Output is complex, sampled at 1378.125 Hz.
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parameter (NSZ=3413)
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parameter (NFFT1=672000,NFFT2=77175)
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parameter (NZ2=1000)
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real*4 dd(npts) !Input data
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real*4 rca(NFFT1)
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complex ca(NFFT1/2+1) !FFT of input
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complex c4a(NFFT2) !Output data
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real*4 s(NZ2)
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real*8 df
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real halfpulse(8) !Impulse response of filter (one sided)
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complex cfilt(NFFT2) !Filter (complex; imag = 0)
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real rfilt(NFFT2) !Filter (real)
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integer*8 plan1,plan2,plan3
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logical first
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include 'fftw3.f90'
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equivalence (rfilt,cfilt),(rca,ca)
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data first/.true./
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data halfpulse/114.97547150,36.57879257,-20.93789101, &
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5.89886379,1.59355187,-2.49138308,0.60910773,-0.04248129/
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common/refspec/dfref,ref(NSZ)
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common/patience/npatience
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save
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if(npts.lt.0) go to 900 !Clean up at end of program
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if(first) then
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nflags=FFTW_ESTIMATE
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if(npatience.eq.1) nflags=FFTW_ESTIMATE_PATIENT
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if(npatience.eq.2) nflags=FFTW_MEASURE
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if(npatience.eq.3) nflags=FFTW_PATIENT
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if(npatience.eq.4) nflags=FFTW_EXHAUSTIVE
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! Plan the FFTs just once
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call timer('FFTplans ',0)
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call sfftw_plan_dft_r2c_1d(plan1,nfft1,rca,rca,nflags)
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call sfftw_plan_dft_1d(plan2,nfft2,c4a,c4a,FFTW_FORWARD,nflags)
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call sfftw_plan_dft_1d(plan3,nfft2,cfilt,cfilt,FFTW_BACKWARD,nflags)
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call timer('FFTplans ',1)
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! Convert impulse response to filter function
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do i=1,nfft2
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cfilt(i)=0.
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enddo
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fac=0.00625/nfft1
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cfilt(1)=fac*halfpulse(1)
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do i=2,8
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cfilt(i)=fac*halfpulse(i)
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cfilt(nfft2+2-i)=fac*halfpulse(i)
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enddo
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call timer('FFTfilt ',0)
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call sfftw_execute(plan3)
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call timer('FFTfilt ',1)
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base=cfilt(nfft2/2+1)
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do i=1,nfft2
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rfilt(i)=real(cfilt(i))-base
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enddo
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df=12000.d0/nfft1
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first=.false.
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endif
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! When new data comes along, we need to compute a new "big FFT"
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! If we just have a new f0, continue with the existing data in ca.
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if(newdat.ne.0) then
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nz=min(npts,nfft1)
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rca(1:nz)=dd(1:nz)
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rca(nz+1:)=0.
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call timer('FFTbig ',0)
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call sfftw_execute(plan1)
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call timer('FFTbig ',1)
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do i=1,NFFT1/2 !Flatten the spectrum
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j=nint(i*df/dfref)
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if(j.lt.1) j=1
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if(j.gt.NSZ) j=NSZ
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fac=sqrt(min(30.0,1.0/ref(j)))
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ca(i)=conjg(fac * ca(i))
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enddo
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endif
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! NB: f0 is the frequency at which we want our filter centered.
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! i0 is the bin number in ca closest to f0.
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i0=nint(f0/df) + 1
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nh=nfft2/2
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do i=1,nh !Copy data into c4a and apply
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j=i0+i-1 !the filter function
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if(j.ge.1 .and. j.le.nfft1/2+1) then
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c4a(i)=rfilt(i)*ca(j)
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else
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c4a(i)=0.
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endif
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enddo
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do i=nh+1,nfft2
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j=i0+i-1-nfft2
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! if(j.lt.1) j=j+nfft1 !nfft1 was nfft2
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if(j.ge.1) then
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c4a(i)=rfilt(i)*ca(j)
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else
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c4a(i)=rfilt(i)*conjg(ca(2-j))
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endif
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enddo
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nadd=nfft2/NZ2
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i=0
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do j=1,NZ2
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s(j)=0.
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do n=1,nadd
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i=i+1
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s(j)=s(j) + real(c4a(i))**2 + aimag(c4a(i))**2
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enddo
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enddo
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call pctile(s,NZ2,30,sq0)
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! Do the short reverse transform, to go back to time domain.
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call timer('FFTsmall',0)
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call sfftw_execute(plan2)
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call timer('FFTsmall',1)
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n4=min(npts/8,nfft2)
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return
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900 call sfftw_destroy_plan(plan1)
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call sfftw_destroy_plan(plan2)
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call sfftw_destroy_plan(plan3)
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return
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end subroutine filbig
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