kopia lustrzana https://github.com/kosme/arduinoFFT
126 wiersze
3.8 KiB
C++
126 wiersze
3.8 KiB
C++
/*
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Example of use of the FFT library to compute FFT for several signals over a range of frequencies.
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The exponent is calculated once before the execution since it is a constant.
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This saves resources during the execution of the sketch and reduces the compiled size.
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The sketch shows the time that the computing is taking.
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Copyright (C) 2014 Enrique Condes
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "arduinoFFT.h"
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arduinoFFT FFT = arduinoFFT(); /* Create FFT object */
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/*
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These values can be changed in order to evaluate the functions
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*/
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const uint16_t samples = 64;
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const double sampling = 40;
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const uint8_t amplitude = 4;
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uint8_t exponent;
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const double startFrequency = 2;
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const double stopFrequency = 16.4;
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const double step_size = 0.1;
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/*
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These are the input and output vectors
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Input vectors receive computed results from FFT
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*/
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double vReal[samples];
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double vImag[samples];
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unsigned long time;
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#define SCL_INDEX 0x00
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#define SCL_TIME 0x01
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#define SCL_FREQUENCY 0x02
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#define SCL_PLOT 0x03
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void setup()
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{
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Serial.begin(115200);
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while(!Serial);
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Serial.println("Ready");
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exponent = FFT.Exponent(samples);
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}
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void loop()
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{
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Serial.println("Frequency\tDetected\ttakes (ms)");
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Serial.println("=======================================\n");
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for(double frequency = startFrequency; frequency<=stopFrequency; frequency+=step_size)
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{
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/* Build raw data */
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double cycles = (((samples-1) * frequency) / sampling);
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for (uint16_t i = 0; i < samples; i++)
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{
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vReal[i] = int8_t((amplitude * (sin((i * (twoPi * cycles)) / samples))) / 2.0);
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vImag[i] = 0; //Reset the imaginary values vector for each new frequency
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}
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/*Serial.println("Data:");
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PrintVector(vReal, samples, SCL_TIME);*/
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time=millis();
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FFT.Windowing(vReal, samples, FFT_WIN_TYP_HAMMING, FFT_FORWARD); /* Weigh data */
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/*Serial.println("Weighed data:");
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PrintVector(vReal, samples, SCL_TIME);*/
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FFT.Compute(vReal, vImag, samples, exponent, FFT_FORWARD); /* Compute FFT */
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/*Serial.println("Computed Real values:");
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PrintVector(vReal, samples, SCL_INDEX);
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Serial.println("Computed Imaginary values:");
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PrintVector(vImag, samples, SCL_INDEX);*/
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FFT.ComplexToMagnitude(vReal, vImag, samples); /* Compute magnitudes */
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/*Serial.println("Computed magnitudes:");
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PrintVector(vReal, (samples >> 1), SCL_FREQUENCY);*/
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double x = FFT.MajorPeak(vReal, samples, sampling);
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Serial.print(frequency);
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Serial.print(": \t\t");
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Serial.print(x, 4);
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Serial.print("\t\t");
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Serial.print(millis()-time);
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Serial.println(" ms");
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// delay(2000); /* Repeat after delay */
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}
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while(1); /* Run Once */
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}
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void PrintVector(double *vData, uint16_t bufferSize, uint8_t scaleType)
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{
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for (uint16_t i = 0; i < bufferSize; i++)
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{
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double abscissa;
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/* Print abscissa value */
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switch (scaleType)
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{
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case SCL_INDEX:
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abscissa = (i * 1.0);
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break;
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case SCL_TIME:
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abscissa = ((i * 1.0) / sampling);
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break;
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case SCL_FREQUENCY:
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abscissa = ((i * 1.0 * sampling) / samples);
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break;
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}
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Serial.print(abscissa, 6);
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if(scaleType==SCL_FREQUENCY)
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Serial.print("Hz");
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Serial.print(" ");
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Serial.println(vData[i], 4);
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}
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Serial.println();
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}
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