Files
sdrtrunk/src/main/java/io/github/dsheirer/spectrum/ComplexDftProcessor.java
Denny Sheirer 9641d2ef59 #736 New JavaFX spectral display and waterfall for both tuner and channel spectrums. (#2637)
* Popout configuration panel (top-left of display)
* Themed color support
* Reworked signal averating/smoothing
* Optional decibel overlay with corrected decibel calculations
* Integrated noise floor slider in  channel view
* Traffic channel overlays
* Popup channel information when hovering over playlist channels.
* Removes legacy swing components.

Co-authored-by: denny <dennis.sheirer@gmail.com>
2026-11-13 07:30:31 -05:00

353 lines
11 KiB
Java

/*
* *****************************************************************************
* Copyright (C) 2014-2023 Dennis Sheirer
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>
* ****************************************************************************
*/
package io.github.dsheirer.spectrum;
import io.github.dsheirer.buffer.INativeBuffer;
import io.github.dsheirer.controller.NamingThreadFactory;
import io.github.dsheirer.dsp.window.WindowFactory;
import io.github.dsheirer.dsp.window.WindowType;
import io.github.dsheirer.properties.SystemProperties;
import io.github.dsheirer.sample.Listener;
import io.github.dsheirer.spectrum.converter.DFTResultsConverter;
import java.io.IOException;
import java.util.concurrent.CopyOnWriteArrayList;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.ScheduledFuture;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicBoolean;
import org.jtransforms.fft.FloatFFT_1D;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Processes both complex samples or float samples and dispatches a float array of DFT results, using configurable fft
* size and output dispatch timelines.
*/
public class ComplexDftProcessor<T extends INativeBuffer> implements Listener<T>, IDFTWidthChangeProcessor
{
private static final Logger mLog = LoggerFactory.getLogger(ComplexDftProcessor.class);
private static final String FRAME_RATE_PROPERTY = "spectral.display.frame.rate";
//The Cosine and Hann windows seem to offer the best spectral display with minimal bin leakage/smearing
private volatile WindowType mWindowType = WindowType.BLACKMAN_HARRIS_7;
private volatile boolean mWindowChanged = true;
private volatile boolean mUnityGainWindow = false;
private float[] mWindow;
private DFTSize mDFTSize = DFTSize.FFT04096;
private volatile DFTSize mNewDFTSize = DFTSize.FFT04096;
private FloatFFT_1D mFFT = new FloatFFT_1D(mDFTSize.getSize());
private int mFrameRate;
private AtomicBoolean mRunning = new AtomicBoolean();
private ScheduledFuture<?> mProcessorTaskHandle;
private ScheduledExecutorService mExecutorService = Executors.newSingleThreadScheduledExecutor(new NamingThreadFactory("sdrtrunk dft processor"));
private CopyOnWriteArrayList<DFTResultsConverter> mListeners = new CopyOnWriteArrayList<>();
private NativeBufferManager mDftBufferManager = new NativeBufferManager(mDFTSize.getSize() * 2);
private float[] mPreviousSamples = new float[mDFTSize.getSize() * 2];
public ComplexDftProcessor()
{
mFrameRate = SystemProperties.getInstance().get(FRAME_RATE_PROPERTY, 20);
mWindow = createWindow(mWindowType, mDFTSize.getSize(), mUnityGainWindow);
start();
}
public void dispose()
{
stop();
mExecutorService.shutdown();
mListeners.clear();
mWindow = null;
}
public WindowType getWindowType()
{
return mWindowType;
}
/**
* Queues a window type change. The processor applies the change before the next calculation.
*/
public void setWindowType(WindowType windowType)
{
if(windowType != null)
{
mWindowType = windowType;
mWindowChanged = true;
}
}
/**
* Scales the window to unity coherent gain, so that a full scale complex tone centered in a bin has a DFT
* magnitude equal to the DFT size, regardless of the window type. Use this with a full scale (dBFS) converter.
* Defaults to false, which leaves the window coefficients unscaled.
*/
public void setUnityGainWindow(boolean unityGain)
{
mUnityGainWindow = unityGain;
mWindowChanged = true;
}
/**
* Creates the window coefficients for interleaved complex samples, with the same coefficient applied to the I
* and Q values of each sample.
* @param type of window. Kaiser windows need extra parameters, so Kaiser uses a Blackman-Harris 7 window.
* @param size of the DFT in complex samples
* @param unityGain to scale the window so the coefficients sum to the DFT size (unity coherent gain)
* @return interleaved window coefficients, twice the DFT size
*/
public static float[] createWindow(WindowType type, int size, boolean unityGain)
{
if(type == null || type == WindowType.KAISER)
{
type = WindowType.BLACKMAN_HARRIS_7;
}
float[] window = WindowFactory.getWindow(type, size);
double sum = 0.0;
for(float coefficient: window)
{
sum += coefficient;
}
float scale = (unityGain && sum > 0) ? (float)(size / sum) : 1.0f;
float[] interleaved = new float[size * 2];
for(int x = 0; x < size; x++)
{
interleaved[2 * x] = window[x] * scale;
interleaved[2 * x + 1] = window[x] * scale;
}
return interleaved;
}
/**
* Equivalent noise bandwidth of the window type, in DFT bins. This is how much wider the window's noise
* bandwidth is than one bin: 1.0 for no window and about 2 to 4 for the low leakage windows.
*/
public static double getNoiseBandwidth(WindowType type)
{
if(type == null || type == WindowType.KAISER)
{
type = WindowType.BLACKMAN_HARRIS_7;
}
int size = 4096;
float[] window = WindowFactory.getWindow(type, size);
double sum = 0.0;
double sumSquares = 0.0;
for(float coefficient: window)
{
sum += coefficient;
sumSquares += coefficient * coefficient;
}
return sum > 0 ? size * sumSquares / (sum * sum) : 1.0;
}
/**
* Queues an FFT size change request. The scheduled executor will apply
* the change when it runs.
*/
public void setDFTSize(DFTSize size)
{
mNewDFTSize = size;
}
public DFTSize getDFTSize()
{
return mDFTSize;
}
public int getFrameRate()
{
return mFrameRate;
}
public void setFrameRate(int framesPerSecond)
{
setFrameRateNoSave(framesPerSecond);
SystemProperties.getInstance().set(FRAME_RATE_PROPERTY, mFrameRate);
}
/**
* Sets the frame rate without saving it as the default frame rate setting.
*/
public void setFrameRateNoSave(int framesPerSecond)
{
if(framesPerSecond < 1 || framesPerSecond > 1000)
{
throw new IllegalArgumentException("DFTProcessor cannot run more than 1000 times per second -- requested " +
"setting:" + framesPerSecond);
}
mFrameRate = framesPerSecond;
restart();
}
public void start()
{
if(mProcessorTaskHandle == null)
{
//Schedule the DFT to run calculations at a fixed rate
int initialDelay = 0;
int period = (int) (1000 / mFrameRate);
mProcessorTaskHandle = mExecutorService.scheduleAtFixedRate(new DFTCalculationTask(), initialDelay, period,
TimeUnit.MILLISECONDS);
}
}
public void stop()
{
//Cancel running DFT calculation task
if(mProcessorTaskHandle != null)
{
mProcessorTaskHandle.cancel(false);
mProcessorTaskHandle = null;
}
}
public boolean isRunning()
{
return mProcessorTaskHandle != null;
}
public void restart()
{
stop();
start();
}
/**
* Places the sample into a transfer queue for future processing.
*/
@Override
public void receive(T buffer)
{
mDftBufferManager.add(buffer);
}
private void calculate()
{
//We always send the previous calculated samples - this should improve the screen rendering since the frame
//rate will always occur on an even rhythm. Any delays caused by processing will be absorbed and not impact
//the screen rendering.
dispatch(mPreviousSamples);
try
{
//If this throws an IO exception, the buffer queue is (temporarily) empty and we return from the method
float[] samples = mDftBufferManager.get(mDFTSize.getSize());
if(mWindow == null || mWindow.length != samples.length)
{
mWindow = createWindow(mWindowType, mDFTSize.getSize(), mUnityGainWindow);
}
WindowFactory.apply(mWindow, samples);
mFFT.complexForward(samples);
mPreviousSamples = samples;
}
catch(IOException ioe)
{
//Not enough samples available, dispatch the previous samples again
}
catch(Exception e)
{
if(e instanceof InterruptedException)
{
mLog.info("FFT Library interrupted exception - this is normal during application shutdown");
}
else
{
mLog.error("Error while calculating FFT results", e);
}
}
}
/**
* Takes a calculated DFT results set, reformats the data, and sends it
* out to all registered listeners.
*/
private void dispatch(float[] results)
{
for (DFTResultsConverter mListener : mListeners)
{
mListener.receive(results);
}
}
public void addConverter(DFTResultsConverter listener)
{
mListeners.add(listener);
}
private class DFTCalculationTask implements Runnable
{
@Override
public void run()
{
try
{
/* Only run if we're not currently running */
if(mRunning.compareAndSet(false, true))
{
checkFFTSize();
calculate();
mRunning.set(false);
}
}
catch(Exception e)
{
mLog.error("error during dft processor calculation task", e);
}
}
}
/**
* Checks for a queued FFT width or window change request and applies it. This
* method will only be accessed by the scheduled executor that gains
* access to run a calculate method, thus providing thread safety.
*/
private void checkFFTSize()
{
if(mNewDFTSize.getSize() != mDFTSize.getSize())
{
mDFTSize = mNewDFTSize;
mWindowChanged = true;
mFFT = new FloatFFT_1D(mDFTSize.getSize());
}
if(mWindowChanged)
{
mWindowChanged = false;
mWindow = createWindow(mWindowType, mDFTSize.getSize(), mUnityGainWindow);
}
}
public void clearBuffer()
{
mDftBufferManager.clear();
}
}