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/* | |
Copyright 2015 Google Inc. All rights reserved. | |
Licensed under the Apache License, Version 2.0 (the "License"); | |
you may not use this file except in compliance with the License. | |
You may obtain a copy of the License at | |
http://www.apache.org/licenses/LICENSE-2.0 | |
Unless required by applicable law or agreed to in writing, software | |
distributed under the License is distributed on an "AS IS" BASIS, | |
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
See the License for the specific language governing permissions and | |
limitations under the License. | |
*/ | |
// Author: David Talkin ([email protected]) | |
/* Construct a FFT to perform a DFT of size 2^power. */ | |
FFT::FFT(int power) { | |
makefttable(power); | |
} | |
FFT::~FFT() { | |
delete [] fsine; | |
delete [] fcosine; | |
} | |
/*-----------------------------------------------------------------------*/ | |
/* z <- (10 * log10(x^2 + y^2)) for n elements */ | |
bool FFT::flog_mag(float *x, float *y, float *z, int n) { | |
float *xp, *yp, *zp, t1, t2, ssq; | |
if (x && y && z && n) { | |
for (xp = x + n, yp = y + n, zp = z + n; zp > z;) { | |
t1 = *--xp; | |
t2 = *--yp; | |
ssq = (t1 * t1) + (t2 * t2); | |
*--zp = (ssq > 0.0)? 10.0 * log10(ssq) : -200.0; | |
} | |
return true; | |
} else { | |
return false; | |
} | |
} | |
/*-----------------------------------------------------------------------*/ | |
float FFT::get_band_rms(float *x, float*y, int first_bin, int last_bin) { | |
double sum = 0.0; | |
for (int i = first_bin; i <= last_bin; ++i) { | |
sum += (x[i] * x[i]) + (y[i] * y[i]); | |
} | |
return sqrt(sum / (last_bin - first_bin + 1)); | |
} | |
/*-----------------------------------------------------------------------*/ | |
int FFT::makefttable(int pow2) { | |
int lmx, lm; | |
float *c, *s; | |
double scl, arg; | |
fftSize = 1 << pow2; | |
fft_ftablesize = lmx = fftSize/2; | |
fsine = new float[lmx]; | |
fcosine = new float[lmx]; | |
scl = (M_PI * 2.0) / fftSize; | |
for (s = fsine, c = fcosine, lm = 0; lm < lmx; ++lm) { | |
arg = scl * lm; | |
*s++ = sin(arg); | |
*c++ = cos(arg); | |
} | |
kbase = (fft_ftablesize * 2) / fftSize; | |
power2 = pow2; | |
return(fft_ftablesize); | |
} | |
/*-----------------------------------------------------------------------*/ | |
/* Compute the discrete Fourier transform of the 2**l complex sequence | |
* in x (real) and y (imaginary). The DFT is computed in place and the | |
* Fourier coefficients are returned in x and y. | |
*/ | |
void FFT::fft(float *x, float *y) { | |
float c, s, t1, t2; | |
int j1, j2, li, lix, i; | |
int lmx, lo, lixnp, lm, j, nv2, k = kbase, im, jm, l = power2; | |
for (lmx = fftSize, lo = 0; lo < l; lo++, k *= 2) { | |
lix = lmx; | |
lmx /= 2; | |
lixnp = fftSize - lix; | |
for (i = 0, lm = 0; lm < lmx; lm++, i += k) { | |
c = fcosine[i]; | |
s = fsine[i]; | |
for (li = lixnp + lm, j1 = lm, j2 = lm + lmx; j1 <= li; | |
j1 += lix, j2 += lix) { | |
t1 = x[j1] - x[j2]; | |
t2 = y[j1] - y[j2]; | |
x[j1] += x[j2]; | |
y[j1] += y[j2]; | |
x[j2] = (c * t1) + (s * t2); | |
y[j2] = (c * t2) - (s * t1); | |
} | |
} | |
} | |
/* Now perform the bit reversal. */ | |
j = 1; | |
nv2 = fftSize / 2; | |
for (i = 1; i < fftSize; i++) { | |
if (j < i) { | |
jm = j - 1; | |
im = i - 1; | |
t1 = x[jm]; | |
t2 = y[jm]; | |
x[jm] = x[im]; | |
y[jm] = y[im]; | |
x[im] = t1; | |
y[im] = t2; | |
} | |
k = nv2; | |
while (j > k) { | |
j -= k; | |
k /= 2; | |
} | |
j += k; | |
} | |
} | |
/*-----------------------------------------------------------------------*/ | |
/* Compute the discrete inverse Fourier transform of the 2**l complex | |
* sequence in x (real) and y (imaginary). The DFT is computed in | |
* place and the Fourier coefficients are returned in x and y. Note | |
* that this DOES NOT scale the result by the inverse FFT size. | |
*/ | |
void FFT::ifft(float *x, float *y) { | |
float c, s, t1, t2; | |
int j1, j2, li, lix, i; | |
int lmx, lo, lixnp, lm, j, nv2, k = kbase, im, jm, l = power2; | |
for (lmx = fftSize, lo = 0; lo < l; lo++, k *= 2) { | |
lix = lmx; | |
lmx /= 2; | |
lixnp = fftSize - lix; | |
for (i = 0, lm = 0; lm < lmx; lm++, i += k) { | |
c = fcosine[i]; | |
s = -fsine[i]; | |
for (li = lixnp + lm, j1 = lm, j2 = lm + lmx; j1 <= li; | |
j1 += lix, j2 += lix) { | |
t1 = x[j1] - x[j2]; | |
t2 = y[j1] - y[j2]; | |
x[j1] += x[j2]; | |
y[j1] += y[j2]; | |
x[j2] = (c * t1) + (s * t2); | |
y[j2] = (c * t2) - (s * t1); | |
} | |
} | |
} | |
/* Now perform the bit reversal. */ | |
j = 1; | |
nv2 = fftSize / 2; | |
for (i = 1; i < fftSize; i++) { | |
if (j < i) { | |
jm = j-1; | |
im = i-1; | |
t1 = x[jm]; | |
t2 = y[jm]; | |
x[jm] = x[im]; | |
y[jm] = y[im]; | |
x[im] = t1; | |
y[im] = t2; | |
} | |
k = nv2; | |
while (j > k) { | |
j -= k; | |
k /= 2; | |
} | |
j += k; | |
} | |
} | |