void AudioProcAnalyzePitch(int16_t * samples, uint8_t gain, int16_t ** raw_buckets, int16_t ** full_buckets, int16_t ** octave_buckets) { // Apply a window. VectorWindow(ANALOG_BUFFER_LEN, samples, samples, window); // Apply gain and convert to complex. for (unsigned i = 0; i < ANALOG_BUFFER_LEN; ++i) { complex_buf[i].real = samples[i] * gain; complex_buf[i].imag = 0; } // In-place FFT. FFTComplexIP(ANALOG_LOG2_BUFFER_LEN, complex_buf, twiddle, COEFFS_IN_DATA); BitReverseComplex(ANALOG_LOG2_BUFFER_LEN, complex_buf); // Compute magnitude (first half of the buffer). SquareMagnitudeCplx(ANALOG_BUFFER_LEN / 2, complex_buf, samples); // Harmonic suppression. for (int i = ANALOG_BUFFER_LEN / 2 - 1; i >= 0; --i) { samples[i] -= samples[i / 2] / 2; if (samples[i] < 0) samples[i] = 0; } // Apply bucketing. *raw_buckets = samples + ANALOG_BUFFER_LEN / 2; *full_buckets = *raw_buckets + PITCH_COUNT; *octave_buckets = *full_buckets + BUCKET_COUNT; Bucket(samples, *raw_buckets, *full_buckets, *octave_buckets); }
int main(void) { int i = 0; fractional *p_real = &sigCmpx[0].real ; fractcomplex *p_cmpx = &sigCmpx[0] ; #ifndef FFTTWIDCOEFFS_IN_PROGMEM /* Generate TwiddleFactor Coefficients */ TwidFactorInit (LOG2_BLOCK_LENGTH, &twiddleFactors[0], 0); /* We need to do this only once at start-up */ #endif for ( i = 0; i < FFT_BLOCK_LENGTH; i++ )/* The FFT function requires input data */ { /* to be in the fractional fixed-point range [-0.5, +0.5]*/ *p_real = *p_real >>1 ; /* So, we shift all data samples by 1 bit to the right. */ *p_real++; /* Should you desire to optimize this process, perform */ } /* data scaling when first obtaining the time samples */ /* Or within the BitReverseComplex function source code */ p_real = &sigCmpx[(FFT_BLOCK_LENGTH/2)-1].real ; /* Set up pointers to convert real array */ p_cmpx = &sigCmpx[FFT_BLOCK_LENGTH-1] ; /* to a complex array. The input array initially has all */ /* the real input samples followed by a series of zeros */ for ( i = FFT_BLOCK_LENGTH; i > 0; i-- ) /* Convert the Real input sample array */ { /* to a Complex input sample array */ (*p_cmpx).real = (*p_real--); /* We will simpy zero out the imaginary */ (*p_cmpx--).imag = 0x0000; /* part of each data sample */ } /* Perform FFT operation */ #ifndef FFTTWIDCOEFFS_IN_PROGMEM FFTComplexIP (LOG2_BLOCK_LENGTH, &sigCmpx[0], &twiddleFactors[0], COEFFS_IN_DATA); #else FFTComplexIP (LOG2_BLOCK_LENGTH, &sigCmpx[0], (fractcomplex *) __builtin_psvoffset(&twiddleFactors[0]), (int) __builtin_psvpage(&twiddleFactors[0])); #endif /* Store output samples in bit-reversed order of their addresses */ BitReverseComplex (LOG2_BLOCK_LENGTH, &sigCmpx[0]); /* Compute the square magnitude of the complex FFT output array so we have a Real output vetor */ SquareMagnitudeCplx(FFT_BLOCK_LENGTH, &sigCmpx[0], &sigCmpx[0].real); /* Find the frequency Bin ( = index into the SigCmpx[] array) that has the largest energy*/ /* i.e., the largest spectral component */ VectorMax(FFT_BLOCK_LENGTH/2, &sigCmpx[0].real, &peakFrequencyBin); /* Compute the frequency (in Hz) of the largest spectral component */ peakFrequency = peakFrequencyBin*(SAMPLING_RATE/FFT_BLOCK_LENGTH); while (1); /* Place a breakpoint here and observe the watch window variables */ }