File: FFT.cpp

package info (click to toggle)
audacity 0.98-3
  • links: PTS
  • area: main
  • in suites: woody
  • size: 2,896 kB
  • ctags: 4,089
  • sloc: cpp: 26,099; ansic: 4,961; sh: 2,465; makefile: 156; perl: 23
file content (391 lines) | stat: -rw-r--r-- 8,803 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
/**********************************************************************

  FFT.cpp

  Dominic Mazzoni

  September 2000

  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.

**********************************************************************/

#include <stdlib.h>
#include <stdio.h>
#include <math.h>

#include "FFT.h"

int **gFFTBitTable = NULL;
const int MaxFastBits = 16;

int IsPowerOfTwo(int x)
{
   if (x < 2)
      return false;

   if (x & (x - 1))             /* Thanks to 'byang' for this cute trick! */
      return false;

   return true;
}

int NumberOfBitsNeeded(int PowerOfTwo)
{
   int i;

   if (PowerOfTwo < 2) {
      fprintf(stderr, "Error: FFT called with size %d\n", PowerOfTwo);
      exit(1);
   }

   for (i = 0;; i++)
      if (PowerOfTwo & (1 << i))
         return i;
}

int ReverseBits(int index, int NumBits)
{
   int i, rev;

   for (i = rev = 0; i < NumBits; i++) {
      rev = (rev << 1) | (index & 1);
      index >>= 1;
   }

   return rev;
}

void InitFFT()
{
   gFFTBitTable = new int *[MaxFastBits];

   int len = 2;
   for (int b = 1; b <= MaxFastBits; b++) {

      gFFTBitTable[b - 1] = new int[len];

      for (int i = 0; i < len; i++)
         gFFTBitTable[b - 1][i] = ReverseBits(i, b);

      len <<= 1;
   }
}

inline int FastReverseBits(int i, int NumBits)
{
   if (NumBits <= MaxFastBits)
      return gFFTBitTable[NumBits - 1][i];
   else
      return ReverseBits(i, NumBits);
}

/*
 * Complex Fast Fourier Transform
 */

void FFT(int NumSamples,
         bool InverseTransform,
         float *RealIn, float *ImagIn, float *RealOut, float *ImagOut)
{
   int NumBits;                 /* Number of bits needed to store indices */
   int i, j, k, n;
   int BlockSize, BlockEnd;

   double angle_numerator = 2.0 * M_PI;
   float tr, ti;                /* temp real, temp imaginary */

   if (!IsPowerOfTwo(NumSamples)) {
      fprintf(stderr, "%d is not a power of two\n", NumSamples);
      exit(1);
   }

   if (!gFFTBitTable)
      InitFFT();

   if (InverseTransform)
      angle_numerator = -angle_numerator;

   NumBits = NumberOfBitsNeeded(NumSamples);

   /*
    **   Do simultaneous data copy and bit-reversal ordering into outputs...
    */

   for (i = 0; i < NumSamples; i++) {
      j = FastReverseBits(i, NumBits);
      RealOut[j] = RealIn[i];
      ImagOut[j] = (ImagIn == NULL) ? 0.0 : ImagIn[i];
   }

   /*
    **   Do the FFT itself...
    */

   BlockEnd = 1;
   for (BlockSize = 2; BlockSize <= NumSamples; BlockSize <<= 1) {

      double delta_angle = angle_numerator / (double) BlockSize;

      float sm2 = sin(-2 * delta_angle);
      float sm1 = sin(-delta_angle);
      float cm2 = cos(-2 * delta_angle);
      float cm1 = cos(-delta_angle);
      float w = 2 * cm1;
      float ar0, ar1, ar2, ai0, ai1, ai2;

      for (i = 0; i < NumSamples; i += BlockSize) {
         ar2 = cm2;
         ar1 = cm1;

         ai2 = sm2;
         ai1 = sm1;

         for (j = i, n = 0; n < BlockEnd; j++, n++) {
            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] += tr;
            ImagOut[j] += ti;
         }
      }

      BlockEnd = BlockSize;
   }

   /*
      **   Need to normalize if inverse transform...
    */

   if (InverseTransform) {
      float denom = (float) NumSamples;

      for (i = 0; i < NumSamples; i++) {
         RealOut[i] /= denom;
         ImagOut[i] /= denom;
      }
   }
}

/*
 * 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]
 */

void RealFFT(int NumSamples, float *RealIn, float *RealOut, float *ImagOut)
{
   int Half = NumSamples / 2;
   int i;

   float theta = M_PI / Half;

   float *tmpReal = new float[Half];
   float *tmpImag = new float[Half];

   for (i = 0; i < Half; i++) {
      tmpReal[i] = RealIn[2 * i];
      tmpImag[i] = RealIn[2 * i + 1];
   }

   FFT(Half, 0, tmpReal, tmpImag, RealOut, ImagOut);

   float wtemp = float (sin(0.5 * theta));

   float wpr = -2.0 * wtemp * wtemp;
   float wpi = float (sin(theta));
   float wr = 1.0 + wpr;
   float wi = wpi;

   int i3;

   float h1r, h1i, h2r, h2i;

   for (i = 1; i < Half / 2; i++) {

      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;

      wr = (wtemp = wr) * wpr - wi * wpi + wr;
      wi = wi * wpr + wtemp * wpi + wi;
   }

   RealOut[0] = (h1r = RealOut[0]) + ImagOut[0];
   ImagOut[0] = h1r - ImagOut[0];

   delete[]tmpReal;
   delete[]tmpImag;
}

/*
 * 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.
 */

void PowerSpectrum(int NumSamples, float *In, float *Out)
{
   int Half = NumSamples / 2;
   int i;

   float theta = M_PI / Half;

   float *tmpReal = new float[Half];
   float *tmpImag = new float[Half];
   float *RealOut = new float[Half];
   float *ImagOut = new float[Half];

   for (i = 0; i < Half; i++) {
      tmpReal[i] = In[2 * i];
      tmpImag[i] = In[2 * i + 1];
   }

   FFT(Half, 0, tmpReal, tmpImag, RealOut, ImagOut);

   float wtemp = float (sin(0.5 * theta));

   float wpr = -2.0 * wtemp * wtemp;
   float wpi = float (sin(theta));
   float wr = 1.0 + wpr;
   float wi = wpi;

   int i3;

   float h1r, h1i, h2r, h2i, rt, it;

   for (i = 1; i < Half / 2; i++) {

      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;

      wr = (wtemp = wr) * wpr - wi * wpi + wr;
      wi = wi * wpr + wtemp * wpi + wi;
   }

   rt = (h1r = RealOut[0]) + ImagOut[0];
   it = h1r - ImagOut[0];
   Out[0] = rt * rt + it * it;

   rt = RealOut[Half / 2];
   it = ImagOut[Half / 2];
   Out[Half / 2] = rt * rt + it * it;

   delete[]tmpReal;
   delete[]tmpImag;
   delete[]RealOut;
   delete[]ImagOut;
}

/*
 * Windowing Functions
 */

int NumWindowFuncs()
{
   return 4;
}

char *WindowFuncName(int whichFunction)
{
   switch (whichFunction) {
   default:
   case 0:
      return "Rectangular";
   case 1:
      return "Bartlett";
   case 2:
      return "Hamming";
   case 3:
      return "Hanning";
   }
}

void WindowFunc(int whichFunction, int NumSamples, float *in)
{
   int i;

   if (whichFunction == 1) {
      // Bartlett (triangular) window
      for (i = 0; i < NumSamples / 2; i++) {
         in[i] *= (i / (float) (NumSamples / 2));
         in[i + (NumSamples / 2)] *=
             (1.0 - (i / (float) (NumSamples / 2)));
      }
   }

   if (whichFunction == 2) {
      // Hamming
      for (i = 0; i < NumSamples; i++)
         in[i] *= 0.54 - 0.46 * cos(2 * M_PI * i / (NumSamples - 1));
   }

   if (whichFunction == 3) {
      // Hanning
      for (i = 0; i < NumSamples; i++)
         in[i] *= 0.50 - 0.50 * cos(2 * M_PI * i / (NumSamples - 1));
   }
}