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