1 files changed, 0 insertions, 600 deletions
diff --git a/Game/Code/lib/fft/UFFT.pas b/Game/Code/lib/fft/UFFT.pas
deleted file mode 100644
index 87c981e0..00000000
--- a/Game/Code/lib/fft/UFFT.pas
+++ /dev/null
@@ -1,600 +0,0 @@
-{**********************************************************************
-
-  FFT.cpp
-
-  Dominic Mazzoni
-
-  September 2000
-
-***********************************************************************
-
-Fast Fourier Transform routines.
-
-  This file contains a few FFT routines, including a real-FFT
-  routine that is almost twice as fast as a normal complex FFT,
-  and a power spectrum routine when you know you don't care
-  about phase information.
-
-  Some of this code was based on a free implementation of an FFT
-  by Don Cross, available on the web at:
-
-    http://www.intersrv.com/~dcross/fft.html
-
-  The basic algorithm for his code was based on Numerican Recipes
-  in Fortran.  I optimized his code further by reducing array
-  accesses, caching the bit reversal table, and eliminating
-  float-to-double conversions, and I added the routines to
-  calculate a real FFT and a real power spectrum.
-
-***********************************************************************
-
-  Salvo Ventura - November 2006
-  Added more window functions:
-    * 4: Blackman
-    * 5: Blackman-Harris
-    * 6: Welch
-    * 7: Gaussian(a=2.5)
-    * 8: Gaussian(a=3.5)
-    * 9: Gaussian(a=4.5)
-
-***********************************************************************
-
-  This file is part of Audacity 1.3.4 beta (http://audacity.sourceforge.net/)
-  Ported to Pascal by the UltraStar Deluxe Team
-}
-
-unit UFFT;
-
-{$IFDEF FPC}
-  {$MODE Delphi}
-  {$H+} // Use AnsiString
-{$ENDIF}
-
-interface
-type
-  TSingleArray = array[0..0] of Single;
-  PSingleArray = ^TSingleArray;
-
-  TFFTWindowFunc = (
-    fwfRectangular,
-    fwfBartlett,
-    fwfHamming,
-    fwfHanning,
-    fwfBlackman,
-    fwfBlackman_Harris,
-    fwfWelch,
-    fwfGaussian2_5,
-    fwfGaussian3_5,
-    fwfGaussian4_5
-  );
-  
-const
-  FFTWindowName: array[TFFTWindowFunc] of string = (
-     'Rectangular',
-     'Bartlett',
-     'Hamming',
-     'Hanning',
-     'Blackman',
-     'Blackman-Harris',
-     'Welch',
-     'Gaussian(a=2.5)',
-     'Gaussian(a=3.5)',
-     'Gaussian(a=4.5)'
-  );
-
-(*
- * This is the function you will use the most often.
- * Given an array of floats, this will compute the power
- * spectrum by doing a Real FFT and then computing the
- * sum of the squares of the real and imaginary parts.
- * Note that the output array is half the length of the
- * input array, and that NumSamples must be a power of two.
- *)
-procedure PowerSpectrum(NumSamples: Integer; In_, Out_: PSingleArray);
-
-(*
- * Computes an FFT when the input data is real but you still
- * want complex data as output.  The output arrays are half
- * the length of the input, and NumSamples must be a power of
- * two.
- *)
-procedure RealFFT(NumSamples: integer;
-                  RealIn, RealOut, ImagOut: PSingleArray);
-
-(*
- * Computes a FFT of complex input and returns complex output.
- * Currently this is the only function here that supports the
- * inverse transform as well.
- *)
-procedure FFT(NumSamples: Integer;
-              InverseTransform: boolean;
-              RealIn, ImagIn, RealOut, ImagOut: PSingleArray);
-
-(*
- * Applies a windowing function to the data in place
- *
- * 0: Rectangular (no window)
- * 1: Bartlett    (triangular)
- * 2: Hamming
- * 3: Hanning
- * 4: Blackman
- * 5: Blackman-Harris
- * 6: Welch
- * 7: Gaussian(a=2.5)
- * 8: Gaussian(a=3.5)
- * 9: Gaussian(a=4.5)
- *)
-procedure WindowFunc(whichFunction: TFFTWindowFunc; NumSamples: Integer; in_: PSingleArray);
-
-(*
- * Returns the name of the windowing function (for UI display)
- *)
-function WindowFuncName(whichFunction: TFFTWindowFunc): string;
-
-(*
- * Returns the number of windowing functions supported
- *)
-function NumWindowFuncs(): integer;
-
-
-implementation
-
-uses
-  SysUtils;
-
-type TIntArray = array[0..0] of Integer;
-type TIntIntArray = array[0..0] of ^TIntArray;
-var gFFTBitTable: ^TIntIntArray;
-const MaxFastBits: Integer = 16;
-
-function IsPowerOfTwo(x: Integer): Boolean;
-begin
-   if (x < 2) then
-      result := false
-   else if ((x and (x - 1)) <> 0) then  { Thanks to 'byang' for this cute trick! }
-      result := false
-   else
-    result := true;
-end;
-
-function NumberOfBitsNeeded(PowerOfTwo: Integer): Integer;
-var i: Integer;
-begin
-  if (PowerOfTwo < 2) then begin
-    Writeln(ErrOutput, Format('Error: FFT called with size %d\n', [PowerOfTwo]));
-    Abort;
-  end;
-
-  i := 0;
-  while(true) do begin
-    if (PowerOfTwo and (1 shl i) <> 0) then begin
-      result := i;
-      Exit;
-    end;
-    Inc(i);
-  end;
-end;
-
-function ReverseBits(index, NumBits: Integer): Integer;
-var
-  i, rev: Integer;
-begin
-  rev := 0;
-  for i := 0 to NumBits-1 do begin
-    rev := (rev shl 1) or (index and 1);
-    index := index shr 1;
-  end;
-
-  result := rev;
-end;
-
-procedure InitFFT();
-var
-  len: Integer;
-  b, i: Integer;
-begin
-  GetMem(gFFTBitTable, MaxFastBits * sizeof(PSingle));
-
-  len := 2;
-  for b := 1 to MaxFastBits do begin
-    GetMem(gFFTBitTable^[b - 1], len * sizeof(Single));
-    for i := 0 to len-1 do
-      gFFTBitTable^[b - 1][i] := ReverseBits(i, b);
-      len := len shl 1;
-   end;
-end;
-
-function FastReverseBits(i, NumBits: Integer): Integer; {$IFDEF HasInline}inline;{$ENDIF}
-begin
-  if (NumBits <= MaxFastBits) then
-    result := gFFTBitTable[NumBits - 1][i]
-  else
-    result := ReverseBits(i, NumBits);
-end;
-
-{*
- * Complex Fast Fourier Transform
- *}
-procedure FFT(NumSamples: Integer;
-         InverseTransform: boolean;
-         RealIn, ImagIn, RealOut, ImagOut: PSingleArray);
-var
-  NumBits: Integer;                 { Number of bits needed to store indices }
-  i, j, k, n: Integer;
-  BlockSize, BlockEnd: Integer;
-  delta_angle: Double;
-  angle_numerator: Double;
-  tr, ti: Double;                   { temp real, temp imaginary }
-  sm2, sm1, cm2, cm1: Double;
-  w: Double;
-  ar0, ar1, ar2, ai0, ai1, ai2: Double;
-  denom: Single;
-begin
-
-   angle_numerator := 2.0 * Pi;
-
-   if (not IsPowerOfTwo(NumSamples)) then begin
-      Writeln(ErrOutput, Format('%d is not a power of two', [NumSamples]));
-      Abort;
-   end;
-
-   if (gFFTBitTable = nil) then
-      InitFFT();
-
-   if (InverseTransform) then
-      angle_numerator := -angle_numerator;
-
-   NumBits := NumberOfBitsNeeded(NumSamples);
-
-   {
-    **   Do simultaneous data copy and bit-reversal ordering into outputs...
-   }
-
-   for i := 0 to NumSamples-1 do begin
-      j := FastReverseBits(i, NumBits);
-      RealOut[j] := RealIn[i];
-      if(ImagIn = nil) then
-        ImagOut[j] := 0.0
-      else
-        ImagOut[j] := ImagIn[i];
-   end;
-
-   {
-    **   Do the FFT itself...
-   }
-
-   BlockEnd := 1;
-   BlockSize := 2;
-   while(BlockSize <= NumSamples) do
-   begin
-
-      delta_angle := angle_numerator / BlockSize;
-
-      sm2 := sin(-2 * delta_angle);
-      sm1 := sin(-delta_angle);
-      cm2 := cos(-2 * delta_angle);
-      cm1 := cos(-delta_angle);
-      w := 2 * cm1;
-
-      i := 0;
-      while(i < NumSamples) do
-      begin
-         ar2 := cm2;
-         ar1 := cm1;
-
-         ai2 := sm2;
-         ai1 := sm1;
-
-         j := i;
-         for n := 0 to BlockEnd-1 do
-         begin
-            ar0 := w * ar1 - ar2;
-            ar2 := ar1;
-            ar1 := ar0;
-
-            ai0 := w * ai1 - ai2;
-            ai2 := ai1;
-            ai1 := ai0;
-
-            k := j + BlockEnd;
-            tr := ar0 * RealOut[k] - ai0 * ImagOut[k];
-            ti := ar0 * ImagOut[k] + ai0 * RealOut[k];
-
-            RealOut[k] := RealOut[j] - tr;
-            ImagOut[k] := ImagOut[j] - ti;
-
-            RealOut[j] := RealOut[j] + tr;
-            ImagOut[j] := ImagOut[j] + ti;
-
-            Inc(j);
-         end;
-
-         Inc(i, BlockSize);
-      end;
-
-      BlockEnd := BlockSize;
-      BlockSize := BlockSize shl 1;
-   end;
-
-   {
-      **   Need to normalize if inverse transform...
-   }
-
-   if (InverseTransform) then begin
-      denom := NumSamples;
-
-      for i := 0 to NumSamples-1 do begin
-         RealOut[i] := RealOut[i] / denom;
-         ImagOut[i] := ImagOut[i] / denom;
-      end;
-   end;
-end;
-
-(*
- * Real Fast Fourier Transform
- *
- * This function was based on the code in Numerical Recipes in C.
- * In Num. Rec., the inner loop is based on a single 1-based array
- * of interleaved real and imaginary numbers.  Because we have two
- * separate zero-based arrays, our indices are quite different.
- * Here is the correspondence between Num. Rec. indices and our indices:
- *
- * i1  <->  real[i]
- * i2  <->  imag[i]
- * i3  <->  real[n/2-i]
- * i4  <->  imag[n/2-i]
- *)
-procedure RealFFT(NumSamples: integer; RealIn, RealOut, ImagOut: PSingleArray);
-var
-  Half: Integer;
-  i: Integer;
-  theta: Single;
-  tmpReal, tmpImag: PSingleArray;
-  wtemp: Single;
-  wpr, wpi, wr, wi: Single;
-  i3: Integer;
-  h1r, h1i, h2r, h2i: Single;
-begin
-   Half := NumSamples div 2;
-
-   theta := Pi / Half;
-
-   GetMem(tmpReal, Half * sizeof(Single));
-   GetMem(tmpImag, Half * sizeof(Single));
-
-   for i := 0 to Half-1 do
-   begin
-      tmpReal[i] := RealIn[2 * i];
-      tmpImag[i] := RealIn[2 * i + 1];
-   end;
-
-   FFT(Half, false, tmpReal, tmpImag, RealOut, ImagOut);
-
-   wtemp := sin(0.5 * theta);
-
-   wpr := -2.0 * wtemp * wtemp;
-   wpi := sin(theta);
-   wr := 1.0 + wpr;
-   wi := wpi;
-
-   for i := 1 to (Half div 2)-1 do
-   begin
-      i3 := Half - i;
-
-      h1r := 0.5 * (RealOut[i] + RealOut[i3]);
-      h1i := 0.5 * (ImagOut[i] - ImagOut[i3]);
-      h2r := 0.5 * (ImagOut[i] + ImagOut[i3]);
-      h2i := -0.5 * (RealOut[i] - RealOut[i3]);
-
-      RealOut[i] := h1r + wr * h2r - wi * h2i;
-      ImagOut[i] := h1i + wr * h2i + wi * h2r;
-      RealOut[i3] := h1r - wr * h2r + wi * h2i;
-      ImagOut[i3] := -h1i + wr * h2i + wi * h2r;
-
-      wtemp := wr;
-      wr := wtemp * wpr - wi * wpi + wr;
-      wi := wi * wpr + wtemp * wpi + wi;
-   end;
-
-   h1r := RealOut[0];
-   RealOut[0] := h1r + ImagOut[0];
-   ImagOut[0] := h1r - ImagOut[0];
-
-   FreeMem(tmpReal);
-   FreeMem(tmpImag);
-end;
-
-{*
- * PowerSpectrum
- *
- * This function computes the same as RealFFT, above, but
- * adds the squares of the real and imaginary part of each
- * coefficient, extracting the power and throwing away the
- * phase.
- *
- * For speed, it does not call RealFFT, but duplicates some
- * of its code.
- *}
-procedure PowerSpectrum(NumSamples: Integer; In_, Out_: PSingleArray);
-var
-  Half: Integer;
-  i: Integer;
-  theta: Single;
-  tmpReal, tmpImag, RealOut, ImagOut: PSingleArray;
-  wtemp: Single;
-  wpr, wpi, wr, wi: Single;
-  i3: Integer;
-  h1r, h1i, h2r, h2i, rt, it: Single;
-begin
-   Half := NumSamples div 2;
-
-   theta := Pi / Half;
-
-   GetMem(tmpReal, Half * sizeof(Single));
-   GetMem(tmpImag, Half * sizeof(Single));
-   GetMem(RealOut, Half * sizeof(Single));
-   GetMem(ImagOut, Half * sizeof(Single));
-
-   for i := 0 to Half-1 do begin
-      tmpReal[i] := In_[2 * i];
-      tmpImag[i] := In_[2 * i + 1];
-   end;
-
-   FFT(Half, false, tmpReal, tmpImag, RealOut, ImagOut);
-
-   wtemp := sin(0.5 * theta);
-
-   wpr := -2.0 * wtemp * wtemp;
-   wpi := sin(theta);
-   wr := 1.0 + wpr;
-   wi := wpi;
-
-   for i := 1 to (Half div 2)-1 do
-   begin
-      i3 := Half - i;
-
-      h1r := 0.5 * (RealOut[i] + RealOut[i3]);
-      h1i := 0.5 * (ImagOut[i] - ImagOut[i3]);
-      h2r := 0.5 * (ImagOut[i] + ImagOut[i3]);
-      h2i := -0.5 * (RealOut[i] - RealOut[i3]);
-
-      rt := h1r + wr * h2r - wi * h2i;
-      it := h1i + wr * h2i + wi * h2r;
-
-      Out_[i] := rt * rt + it * it;
-
-      rt := h1r - wr * h2r + wi * h2i;
-      it := -h1i + wr * h2i + wi * h2r;
-
-      Out_[i3] := rt * rt + it * it;
-
-      wtemp := wr;
-      wr := wtemp * wpr - wi * wpi + wr;
-      wi := wi * wpr + wtemp * wpi + wi;
-   end;
-
-   h1r := RealOut[0];
-   rt := h1r + ImagOut[0];
-   it := h1r - ImagOut[0];
-   Out_[0] := rt * rt + it * it;
-
-   rt := RealOut[Half div 2];
-   it := ImagOut[Half div 2];
-   Out_[Half div 2] := rt * rt + it * it;
-
-   FreeMem(tmpReal);
-   FreeMem(tmpImag);
-   FreeMem(RealOut);
-   FreeMem(ImagOut);
-end;
-
-(*
- * Windowing Functions
- *)
-function NumWindowFuncs(): integer;
-begin
-  Result := Length(FFTWindowName);
-end;
-
-function WindowFuncName(whichFunction: TFFTWindowFunc): string;
-begin
-  Result := FFTWindowName[whichFunction];
-end;
-
-procedure WindowFunc(whichFunction: TFFTWindowFunc; NumSamples: Integer; in_: PSingleArray);
-var
-  i: Integer;
-  A: Single;
-begin
-  case whichFunction of
-    fwfBartlett:
-    begin
-      // Bartlett (triangular) window
-      for i := 0 to (NumSamples div 2)-1 do
-      begin
-        in_[i] := in_[i] * (i / (NumSamples / 2));
-        in_[i + (NumSamples div 2)] :=
-            in_[i + (NumSamples div 2)] *
-            (1.0 - (i / (NumSamples / 2)));
-      end;
-    end;
-    fwfHamming:
-    begin
-      // Hamming
-      for i := 0 to NumSamples-1 do
-      begin
-        in_[i] := in_[i] * (0.54 - 0.46 * cos(2 * Pi * i / (NumSamples - 1)));
-      end;
-    end;
-    fwfHanning:
-    begin
-      // Hanning
-      for i := 0 to NumSamples-1 do
-      begin
-        in_[i] := in_[i] * (0.50 - 0.50 * cos(2 * Pi * i / (NumSamples - 1)));
-      end;
-    end;
-    fwfBlackman:
-    begin
-      // Blackman
-      for i := 0 to NumSamples-1 do
-      begin
-        in_[i] := in_[i] * (0.42 - 0.5 * cos (2 * Pi * i / (NumSamples - 1)) + 0.08 * cos (4 * Pi * i / (NumSamples - 1)));
-      end;
-    end;
-    fwfBlackman_Harris:
-    begin
-      // Blackman-Harris
-      for i := 0 to NumSamples-1 do
-      begin
-        in_[i] := in_[i] * (0.35875 - 0.48829 * cos(2 * Pi * i /(NumSamples-1)) + 0.14128 * cos(4 * Pi * i/(NumSamples-1)) - 0.01168 * cos(6 * Pi * i/(NumSamples-1)));
-      end;
-    end;
-    fwfWelch:
-    begin
-      // Welch
-      for i := 0 to NumSamples-1 do
-      begin
-        in_[i] := in_[i] * 4*i/NumSamples*(1-(i/NumSamples));
-      end;
-    end;
-    fwfGaussian2_5:
-    begin
-      // Gaussian (a=2.5)
-      // Precalculate some values, and simplify the fmla to try and reduce overhead
-      A := -2*2.5*2.5;
-
-      for i := 0 to NumSamples-1 do
-      begin
-        // full
-        // in_[i] := in_[i] * exp(-0.5*(A*((i-NumSamples/2)/NumSamples/2))*(A*((i-NumSamples/2)/NumSamples/2)));
-        // reduced
-        //in_[i] := in_[i] * exp(A*(0.25 + ((i/NumSamples)*(i/NumSamples)) - (i/NumSamples)));
-      end;
-    end;
-    fwfGaussian3_5:
-    begin
-      // Gaussian (a=3.5)
-      A := -2*3.5*3.5;
-
-      for i := 0 to NumSamples-1 do
-      begin
-        // reduced
-        in_[i] := in_[i] * exp(A*(0.25 + ((i/NumSamples)*(i/NumSamples)) - (i/NumSamples)));
-      end;
-    end;
-    fwfGaussian4_5:
-    begin
-      // Gaussian (a=4.5)
-      A := -2*4.5*4.5;
-
-      for i := 0 to NumSamples-1 do
-      begin
-        // reduced
-        in_[i] := in_[i] * exp(A*(0.25 + ((i/NumSamples)*(i/NumSamples)) - (i/NumSamples)));
-      end;
-    end;
-  end;
-end;
-
-end.