Exemplo n.º 1
0
        public static AudioRecording Filter_IIR(AudioRecording audio, string filterName)
        {
            DSP_IIRFilter filter = new DSP_IIRFilter(filterName);

            filter.ApplyIIRFilter(audio.WavReader.Samples, out var output);
            int       channels      = audio.WavReader.Channels;
            int       bitsPerSample = audio.BitsPerSample;
            int       sampleRate    = audio.SampleRate;
            WavReader wr            = new WavReader(output, channels, bitsPerSample, sampleRate);
            var       ar            = new AudioRecording(wr);

            return(ar);
        }
        /// <summary>
        /// Do your analysis. This method is called once per segment (typically one-minute segments).
        /// </summary>
        /// <param name="audioRecording"></param>
        /// <param name="configuration"></param>
        /// <param name="segmentStartOffset"></param>
        /// <param name="getSpectralIndexes"></param>
        /// <param name="outputDirectory"></param>
        /// <param name="imageWidth"></param>
        /// <returns></returns>
        public override RecognizerResults Recognize(AudioRecording audioRecording, Config configuration, TimeSpan segmentStartOffset, Lazy <IndexCalculateResult[]> getSpectralIndexes, DirectoryInfo outputDirectory, int?imageWidth)
        {
            const double minAmplitudeThreshold = 0.1;
            const int    percentile            = 5;
            const double scoreThreshold        = 0.3;
            const bool   doFiltering           = true;
            const int    windowWidth           = 1024;
            const int    signalBuffer          = windowWidth * 2;

            //string path = @"C:\SensorNetworks\WavFiles\Freshwater\savedfortest.wav";
            //audioRecording.Save(path); // this does not work
            int sr      = audioRecording.SampleRate;
            int nyquist = audioRecording.Nyquist;

            // Get a value from the config file - with a backup default
            //int minHz = (int?)configuration[AnalysisKeys.MinHz] ?? 600;

            // Get a value from the config file - with no default, throw an exception if value is not present
            //int maxHz = ((int?)configuration[AnalysisKeys.MaxHz]).Value;

            // Get a value from the config file - without a string accessor, as a double
            //double someExampleSettingA = (double?)configuration.someExampleSettingA ?? 0.0;

            // common properties
            //string speciesName = (string)configuration[AnalysisKeys.SpeciesName] ?? "<no species>";
            //string abbreviatedSpeciesName = (string)configuration[AnalysisKeys.AbbreviatedSpeciesName] ?? "<no.sp>";

            // min score for an acceptable event
            double eventThreshold = (double)configuration.GetDoubleOrNull(AnalysisKeys.EventThreshold);

            // get samples
            var samples = audioRecording.WavReader.Samples;

            double[] bandPassFilteredSignal = null;

            if (doFiltering)
            {
                // high pass filter
                int      windowLength = 71;
                double[] highPassFilteredSignal;
                DSP_IIRFilter.ApplyMovingAvHighPassFilter(samples, windowLength, out highPassFilteredSignal);

                //DSP_IIRFilter filter2 = new DSP_IIRFilter("Chebyshev_Highpass_400");
                //int order2 = filter2.order;
                //filter2.ApplyIIRFilter(samples, out highPassFilteredSignal);

                // Amplify 40dB and clip to +/-1.0;
                double factor = 100; // equiv to 20dB
                highPassFilteredSignal = DspFilters.AmplifyAndClip(highPassFilteredSignal, factor);

                //low pass filter
                string        filterName = "Chebyshev_Lowpass_5000, scale*5";
                DSP_IIRFilter filter     = new DSP_IIRFilter(filterName);
                int           order      = filter.order;

                //System.LoggedConsole.WriteLine("\nTest " + filterName + ", order=" + order);
                filter.ApplyIIRFilter(highPassFilteredSignal, out bandPassFilteredSignal);
            }
            else // do not filter because already filtered - using Chris's filtered recording
            {
                bandPassFilteredSignal = samples;
            }

            // calculate an amplitude threshold that is above Nth percentile of amplitudes in the subsample
            int[]  histogramOfAmplitudes;
            double minAmplitude;
            double maxAmplitude;
            double binWidth;
            int    window = 66;

            Histogram.GetHistogramOfWaveAmplitudes(bandPassFilteredSignal, window, out histogramOfAmplitudes, out minAmplitude, out maxAmplitude, out binWidth);
            int percentileBin = Histogram.GetPercentileBin(histogramOfAmplitudes, percentile);

            double amplitudeThreshold = (percentileBin + 1) * binWidth;

            if (amplitudeThreshold < minAmplitudeThreshold)
            {
                amplitudeThreshold = minAmplitudeThreshold;
            }

            bool doAnalysisOfKnownExamples = true;

            if (doAnalysisOfKnownExamples)
            {
                // go to fixed location to check
                //1:02.07, 1:07.67, 1:12.27, 1:12.42, 1:12.59, 1:12.8, 1.34.3, 1:35.3, 1:40.16, 1:50.0, 2:05.9, 2:06.62, 2:17.57, 2:21.0
                //2:26.33, 2:43.07, 2:43.15, 3:16.55, 3:35.09, 4:22.44, 4:29.9, 4:42.6, 4:51.48, 5:01.8, 5:21.15, 5:22.72, 5:32.37, 5.36.1,
                //5:42.82, 6:03.5, 6:19.93, 6:21.55, 6:42.0, 6:42.15, 6:46.44, 7:12.17, 7:42.65, 7:45.86, 7:46.18, 7:52.38, 7:59.11, 8:10.63,
                //8:14.4, 8:14.63, 8_15_240, 8_46_590, 8_56_590, 9_25_77, 9_28_94, 9_30_5, 9_43_9, 10_03_19, 10_24_26, 10_24_36, 10_38_8,
                //10_41_08, 10_50_9, 11_05_13, 11_08_63, 11_44_66, 11_50_36, 11_51_2, 12_04_93, 12_10_05, 12_20_78, 12_27_0, 12_38_5,
                //13_02_25, 13_08_18, 13_12_8, 13_25_24, 13_36_0, 13_50_4, 13_51_2, 13_57_87, 14_15_00, 15_09_74, 15_12_14, 15_25_79

                //double[] times = { 2.2, 26.589, 29.62 };
                //double[] times = { 2.2, 3.68, 10.83, 24.95, 26.589, 27.2, 29.62 };
                //double[] times = { 2.2, 3.68, 10.83, 24.95, 26.589, 27.2, 29.62, 31.39, 62.1, 67.67, 72.27, 72.42, 72.59, 72.8, 94.3, 95.3,
                //                   100.16, 110.0, 125.9, 126.62, 137.57, 141.0, 146.33, 163.07, 163.17, 196.55, 215.09, 262.44, 269.9, 282.6,
                //                   291.48, 301.85, 321.18, 322.72, 332.37, 336.1, 342.82, 363.5, 379.93, 381.55, 402.0, 402.15, 406.44, 432.17,
                //                   462.65, 465.86, 466.18, 472.38, 479.14, 490.63, 494.4, 494.63, 495.240, 526.590, 536.590, 565.82, 568.94,
                //                   570.5, 583.9, 603.19, 624.26, 624.36, 638.8, 641.08, 650.9, 65.13, 68.63, 704.66,
                //                   710.36, 711.2, 724.93, 730.05, 740.78, 747.05, 758.5, 782.25, 788.18, 792.8,
                //                   805.24, 816.03, 830.4, 831.2, 837.87, 855.02, 909.74, 912.14, 925.81  };

                var filePath = new FileInfo(@"C:\SensorNetworks\WavFiles\Freshwater\GruntSummaryRevisedAndEditedByMichael.csv");
                List <CatFishCallData> data = Csv.ReadFromCsv <CatFishCallData>(filePath, true).ToList();

                //var catFishCallDatas = data as IList<CatFishCallData> ?? data.ToList();
                int count = data.Count();

                var subSamplesDirectory = outputDirectory.CreateSubdirectory("testSubsamples_5000LPFilter");

                //for (int t = 0; t < times.Length; t++)
                foreach (var fishCall in data)
                {
                    //Image bmp1 = IctalurusFurcatus.AnalyseLocation(bandPassFilteredSignal, sr, times[t], windowWidth);

                    // use following line where using time in seconds
                    //int location = (int)Math.Round(times[t] * sr); //assume location points to start of grunt
                    //double[] subsample = DataTools.Subarray(bandPassFilteredSignal, location - signalBuffer, 2 * signalBuffer);

                    // use following line where using sample
                    int location1 = fishCall.Sample / 2;                        //assume Chris's sample location points to centre of grunt. Divide by 2 because original recording was 44100.
                    int location  = (int)Math.Round(fishCall.TimeSeconds * sr); //assume location points to centre of grunt

                    double[] subsample = DataTools.Subarray(bandPassFilteredSignal, location - signalBuffer, 2 * signalBuffer);

                    // calculate an amplitude threshold that is above 95th percentile of amplitudes in the subsample
                    //int[] histogramOfAmplitudes;
                    //double minAmplitude;
                    //double maxAmplitude;
                    //double binWidth;
                    //int window = 70;
                    //int percentile = 90;
                    //Histogram.GetHistogramOfWaveAmplitudes(subsample, window, out histogramOfAmplitudes, out minAmplitude, out maxAmplitude, out binWidth);
                    //int percentileBin = Histogram.GetPercentileBin(histogramOfAmplitudes, percentile);

                    //double amplitudeThreshold = (percentileBin + 1) * binWidth;
                    //if (amplitudeThreshold < minAmplitudeThreshold) amplitudeThreshold = minAmplitudeThreshold;

                    double[] scores1 = AnalyseWaveformAtLocation(subsample, amplitudeThreshold, scoreThreshold);
                    string   title1  = $"scores={fishCall.Timehms}";
                    Image    bmp1    = GraphsAndCharts.DrawGraph(title1, scores1, subsample.Length, 300, 1);

                    //bmp1.Save(path1.FullName);

                    string title2 = $"tStart={fishCall.Timehms}";
                    Image  bmp2   = GraphsAndCharts.DrawWaveform(title2, subsample, 1);
                    var    path1  = subSamplesDirectory.CombineFile($"scoresForTestSubsample_{fishCall.TimeSeconds}secs.png");

                    //var path2 = subSamplesDirectory.CombineFile($@"testSubsample_{times[t]}secs.wav.png");
                    Image[] imageList = { bmp2, bmp1 };
                    Image   bmp3      = ImageTools.CombineImagesVertically(imageList);
                    bmp3.Save(path1.FullName);

                    //write wave form to txt file for later work in XLS
                    //var path3 = subSamplesDirectory.CombineFile($@"testSubsample_{times[t]}secs.wav.csv");
                    //signalBuffer = 800;
                    //double[] subsample2 = DataTools.Subarray(bandPassFilteredSignal, location - signalBuffer, 3 * signalBuffer);
                    //FileTools.WriteArray2File(subsample2, path3.FullName);
                }
            }

            int signalLength = bandPassFilteredSignal.Length;

            // count number of 1000 sample segments
            int blockLength = 1000;
            int blockCount  = signalLength / blockLength;

            int[]    indexOfMax = new int[blockCount];
            double[] maxInBlock = new double[blockCount];

            for (int i = 0; i < blockCount; i++)
            {
                double max        = -2.0;
                int    blockStart = blockLength * i;
                for (int s = 0; s < blockLength; s++)
                {
                    double absValue = Math.Abs(bandPassFilteredSignal[blockStart + s]);
                    if (absValue > max)
                    {
                        max           = absValue;
                        maxInBlock[i] = max;
                        indexOfMax[i] = blockStart + s;
                    }
                }
            }

            // transfer max values to a list
            var indexList = new List <int>();

            for (int i = 1; i < blockCount - 1; i++)
            {
                // only find the blocks that contain a max value that is > neighbouring blocks
                if (maxInBlock[i] > maxInBlock[i - 1] && maxInBlock[i] > maxInBlock[i + 1])
                {
                    indexList.Add(indexOfMax[i]);
                }

                //ALTERNATIVELY
                // look at max in each block
                //indexList.Add(indexOfMax[i]);
            }

            // now process neighbourhood of each max
            int binCount = windowWidth / 2;

            FFT.WindowFunc wf               = FFT.Hamming;
            var            fft              = new FFT(windowWidth, wf);
            int            maxHz            = 1000;
            double         hzPerBin         = nyquist / (double)binCount;
            int            requiredBinCount = (int)Math.Round(maxHz / hzPerBin);

            // init list of events
            List <AcousticEvent> events = new List <AcousticEvent>();

            double[] scores = new double[signalLength]; // init of score array

            int id = 0;

            foreach (int location in indexList)
            {
                //System.LoggedConsole.WriteLine("Location " + location + ", id=" + id);

                int start = location - binCount;
                if (start < 0)
                {
                    continue;
                }

                int end = location + binCount;
                if (end >= signalLength)
                {
                    continue;
                }

                double[] subsampleWav = DataTools.Subarray(bandPassFilteredSignal, start, windowWidth);

                var spectrum = fft.Invoke(subsampleWav);

                // convert to power
                spectrum = DataTools.SquareValues(spectrum);
                spectrum = DataTools.filterMovingAverageOdd(spectrum, 3);
                spectrum = DataTools.normalise(spectrum);
                var subBandSpectrum = DataTools.Subarray(spectrum, 1, requiredBinCount); // ignore DC in bin zero.

                // now do some tests on spectrum to determine if it is a candidate grunt
                bool eventFound = false;

                double[] scoreArray = CalculateScores(subBandSpectrum, windowWidth);
                double   score      = scoreArray[0];

                if (score > scoreThreshold)
                {
                    eventFound = true;
                }

                if (eventFound)
                {
                    for (int i = location - binCount; i < location + binCount; i++)
                    {
                        scores[location] = score;
                    }

                    var    startTime  = TimeSpan.FromSeconds((location - binCount) / (double)sr);
                    string startLabel = startTime.Minutes + "." + startTime.Seconds + "." + startTime.Milliseconds;
                    Image  image4     = GraphsAndCharts.DrawWaveAndFft(subsampleWav, sr, startTime, spectrum, maxHz * 2, scoreArray);

                    var path4 = outputDirectory.CreateSubdirectory("subsamples").CombineFile($@"subsample_{location}_{startLabel}.png");
                    image4.Save(path4.FullName);

                    // have an event, store the data in the AcousticEvent class
                    double duration = 0.2;
                    int    minFreq  = 50;
                    int    maxFreq  = 1000;
                    var    anEvent  = new AcousticEvent(segmentStartOffset, startTime.TotalSeconds, duration, minFreq, maxFreq);
                    anEvent.Name = "grunt";

                    //anEvent.Name = DataTools.WriteArrayAsCsvLine(subBandSpectrum, "f4");
                    anEvent.Score = score;
                    events.Add(anEvent);
                }

                id++;
            }

            // make a spectrogram
            var config = new SonogramConfig
            {
                NoiseReductionType      = NoiseReductionType.Standard,
                NoiseReductionParameter = configuration.GetDoubleOrNull(AnalysisKeys.NoiseBgThreshold) ?? 0.0,
            };
            var sonogram = (BaseSonogram) new SpectrogramStandard(config, audioRecording.WavReader);

            //// when the value is accessed, the indices are calculated
            //var indices = getSpectralIndexes.Value;

            //// check if the indices have been calculated - you shouldn't actually need this
            //if (getSpectralIndexes.IsValueCreated)
            //{
            //    // then indices have been calculated before
            //}

            var plot = new Plot(this.DisplayName, scores, eventThreshold);

            return(new RecognizerResults()
            {
                Events = events,
                Hits = null,

                //ScoreTrack = null,
                Plots = plot.AsList(),
                Sonogram = sonogram,
            });
        }