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286 lines
11 KiB
286 lines
11 KiB
/* analyze_fft1024_F32.h Converted from Teensy I16 Audio Library
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*
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* Audio Library for Teensy 3.X
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* Copyright (c) 2014, Paul Stoffregen, paul@pjrc.com
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*
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* Development of this audio library was funded by PJRC.COM, LLC by sales of
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* Teensy and Audio Adaptor boards. Please support PJRC's efforts to develop
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* open source software by purchasing Teensy or other PJRC products.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice, development funding notice, and this permission
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* notice shall be included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*/
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/* Translated from I16 to F32. Bob Larkin 16 Feb 2021
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* Does real input FFT of 1024 points. Output is not audio, and is magnitude
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* only. Multiple output formats of RMS (same as I16 version, and default),
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* Power or dBFS (full scale). Output can be bin by bin or a pointer to
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* the output array is available. Several window functions are provided by
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* in-class design, or a custom window can be provided from the INO.
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*
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* Functions (See comments below and #defines above:
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* bool available()
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* float read(unsigned int binNumber)
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* float read(unsigned int binFirst, unsigned int binLast)
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* int windowFunction(int wNum)
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* int windowFunction(int wNum, float _kdb) // Kaiser only
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* float* getData(void)
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* float* getWindow(void)
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* void putWindow(float *pwin)
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* void setOutputType(int _type)
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* void setNAverage(int nAverage)
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*
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* Timing, max is longest update() time. Comparison is using full complex FFT
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* and no load sharing on "states".
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* T3.6 Windowed, Power Out, 682 uSec (was 975 w/ 1024 FFT)
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* T3.6 Windowed, dBFS out, 834 uSec (was 1591 w/1024 FFT)
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* No Window saves 60 uSec on T3.6 for any output.
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* T4.0 Windowed, Power Out, 54 uSec (was 156 w/1024 FFT)
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* T4.0 Windowed, dBFS Out, 203 uSec (was 302 w/1024 FFT)
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* Scaling:
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* Full scale for floating point DSP is a nebulous concept. Normally the
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* full scale is -1.0 to +1.0. This is an unscaled FFT and for a sine
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* wave centered in frequency on a bin and of FS amplitude, the power
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* at that center bin will grow by 1024^2/4 = 262144 without windowing.
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* Windowing loss cuts this down. The RMS level can grow to sqrt(262144)
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* or 512. The dBFS has been scaled to make this max value 0 dBFS by
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* removing 54.2 dB. With floating point, the dynamic range is maintained
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* no matter how it is scaled, but this factor needs to be considered
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* when building the INO.
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*/
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// Fixed float/int problem in read(first, last). RSL 3 Mar 21
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// Converted to using half-size FFT for real input, with no zero inputs.
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// See E. Oran Brigham and many other FFT references. 16 March 2021 RSL
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// Moved post-FFT calculations to state 4 to load share. RSL 18 Mar 2021
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#ifndef analyze_fft1024_F32_h_
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#define analyze_fft1024_F32_h_
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#include "Arduino.h"
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#include "AudioStream_F32.h"
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#include "arm_math.h"
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#include "mathDSP_F32.h"
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#if defined(__IMXRT1062__)
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#include "arm_const_structs.h"
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#endif
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// Doing an FFT with NFFT real inputs
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#define NFFT 1024
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#define NFFT_M1 NFFT-1
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#define NFFT_D2 NFFT/2
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#define NFFT_D2M1 (NFFT/2)-1
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#define NFFT_X2 NFFT*2
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#define FFT_PI 3.14159265359f
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#define FFT_2PI 6.28318530718f
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#define FFT_RMS 0
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#define FFT_POWER 1
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#define FFT_DBFS 2
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#define NO_WINDOW 0
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#define AudioWindowNone 0
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#define AudioWindowHanning1024 1
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#define AudioWindowKaiser1024 2
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#define AudioWindowBlackmanHarris1024 3
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class AudioAnalyzeFFT1024_F32 : public AudioStream_F32 {
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//GUI: inputs:1, outputs:0 //this line used for automatic generation of GUI node
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//GUI: shortName:FFT1024
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public:
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AudioAnalyzeFFT1024_F32() : AudioStream_F32(1, inputQueueArray) {
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// __MK20DX128__ T_LC; __MKL26Z64__ T3.0; __MK20DX256__T3.1 and T3.2
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// __MK64FX512__) T3.5; __MK66FX1M0__ T3.6; __IMXRT1062__ T4.0 and T4.1
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#if defined(__IMXRT1062__)
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// Teensy4 core library has the right files for new FFT
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// arm CMSIS library has predefined structures of type arm_cfft_instance_f32
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Sfft = arm_cfft_sR_f32_len512; // Like this. Changes with size <<<
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#else
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arm_cfft_radix2_init_f32(&fft_inst, NFFT_D2, 0, 1); // for T3.x (check radix2/radix4)<<<
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#endif
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// This class is always 128 block size. Any sample rate. No use of "settings"
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useHanningWindow();
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// Factors for using half size complex FFT
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for(int n=0; n<NFFT_D2; n++) {
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sinN[n] = sinf(FFT_PI*((float)n)/((float)NFFT_D2));
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cosN[n] = cosf(FFT_PI*((float)n)/((float)NFFT_D2));
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}
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}
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// Inform that the output is available for read()
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bool available() {
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if (outputflag == true) {
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outputflag = false;
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return true;
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}
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return false;
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}
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// Output data from a single bin is transferred
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float read(unsigned int binNumber) {
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if (binNumber>NFFT_D2M1 || binNumber<0) return 0.0;
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return output[binNumber];
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}
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// Return sum of several bins. Normally use with power output.
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// This produces the equivalent of bigger bins.
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float read(unsigned int binFirst, unsigned int binLast) {
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if (binFirst > binLast) {
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unsigned int tmp = binLast;
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binLast = binFirst;
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binFirst = tmp;
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}
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if (binFirst > NFFT_D2M1) return 0.0;
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if (binLast > NFFT_D2M1) binLast = NFFT_D2M1;
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float sum = 0.0f;
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do {
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sum += output[binFirst++];
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} while (binFirst <= binLast);
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return sum;
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}
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int windowFunction(int wNum) {
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if(wNum == AudioWindowKaiser1024) // Changes with size <<<
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return -1; // Kaiser needs the kdb
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windowFunction(wNum, 0.0f);
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return 0;
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}
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int windowFunction(int wNum, float _kdb) {
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float kd;
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pWin = window;
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if(wNum == NO_WINDOW)
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pWin = NULL;
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else if (wNum == AudioWindowKaiser1024) { // Changes with size <<<
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if(_kdb<20.0f)
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kd = 20.0f;
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else
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kd = _kdb;
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useKaiserWindow(kd);
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}
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else if (wNum == AudioWindowBlackmanHarris1024) // Changes with size <<<
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useBHWindow();
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else
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useHanningWindow(); // Default
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return 0;
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}
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// Fast pointer transfer. Be aware that the data will go away
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// after the next 512 data points occur.
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float* getData(void) {
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return output;
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}
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// You can use this to design windows
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float* getWindow(void) {
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return window;
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}
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// Bring custom window from the INO
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void putWindow(float *pwin) {
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float *p = window;
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for(int i=0; i<NFFT; i++)
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*p++ = *pwin++;
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}
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// Output RMS (default) Power or dBFS
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void setOutputType(int _type) {
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outputType = _type;
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}
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// Output power (non-coherent) averaging
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void setNAverage(int _nAverage) {
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nAverage = _nAverage;
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}
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virtual void update(void);
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private:
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float output[NFFT_D2];
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float sumsq[NFFT_D2]; // Accumulates averages of outputs
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float window[NFFT];
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float *pWin = window;
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float fft_buffer[NFFT];
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// The cosN and sinN would seem to be twidddle factors. Someday
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// look at this and see if they can be stolen from arm math/DSP.
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float cosN[NFFT_D2];
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float sinN[NFFT_D2];
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audio_block_f32_t *blocklist[8];
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uint8_t state = 0;
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bool outputflag = false;
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audio_block_f32_t *inputQueueArray[1];
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#if defined(__IMXRT1062__)
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// For T4.x, 512 length for real 1024 input, etc.
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// const static arm_cfft_instance_f32 arm_cfft_sR_f32_len512;
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arm_cfft_instance_f32 Sfft;
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#else
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arm_cfft_radix2_instance_f32 fft_inst; // Check radix2/radix4 <<<
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#endif
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int outputType = FFT_RMS; //Same type as I16 version init
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int nAverage = 1;
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int count = 0; // used to average for nAverage of powers
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// The Hann window is a good all-around window
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void useHanningWindow(void) {
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for (int i=0; i < NFFT; i++) {
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float kx = FFT_2PI/((float)NFFT_M1); // 0.006141921 for 1024
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window[i] = 0.5f*(1.0f - cosf(kx*(float)i));
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}
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}
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// Blackman-Harris produces a first sidelobe more than 90 dB down.
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// The price is a bandwidth of about 2 bins. Very useful at times.
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void useBHWindow(void) {
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for (int i=0; i < NFFT; i++) {
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float kx = FFT_2PI/((float)NFFT_M1); // 0.006141921 for 1024
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int ix = (float) i;
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window[i] = 0.35875f -
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0.48829f*cosf( kx*ix) +
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0.14128f*cosf(2.0f*kx*ix) -
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0.01168f*cosf(3.0f*kx*ix);
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}
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}
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/* The windowing function here is that of James Kaiser. This has a number
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* of desirable features. The sidelobes drop off as the frequency away from a transition.
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* Also, the tradeoff of sidelobe level versus cutoff rate is variable.
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* Here we specify it in terms of kdb, the highest sidelobe, in dB, next to a sharp cutoff. For
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* calculating the windowing vector, we need a parameter beta, found as follows:
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*/
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void useKaiserWindow(float kdb) {
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float32_t beta, kbes, xn2;
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mathDSP_F32 mathEqualizer; // For Bessel function
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if (kdb < 20.0f)
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beta = 0.0;
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else
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beta = -2.17+0.17153*kdb-0.0002841*kdb*kdb; // Within a dB or so
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// Note: i0f is the fp zero'th order modified Bessel function (see mathDSP_F32.h)
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kbes = 1.0f / mathEqualizer.i0f(beta); // An additional derived parameter used in loop
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for (int n=0; n<NFFT_D2; n++) {
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xn2 = 0.5f+(float32_t)n;
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float kx = 4.0f/(((float)NFFT_M1) * ((float)NFFT_M1)); // 0.00000382215877f for 1024
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xn2 = kx*xn2*xn2;
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window[NFFT_D2M1 - n]=kbes*(mathEqualizer.i0f(beta*sqrtf(1.0-xn2)));
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window[NFFT_D2 + n] = window[NFFT_D2M1 - n];
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}
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}
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};
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#endif
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