public static Image DrawTStatisticSpectrogramsOfSingleIndex(string key, LDSpectrogramRGB cs1, LDSpectrogramRGB cs2, double tStatThreshold)
{
var image1 = cs1.DrawGreyscaleSpectrogramOfIndex(key);
var image2 = cs2.DrawGreyscaleSpectrogramOfIndex(key);
if (image1 == null || image2 == null)
{
Console.WriteLine("WARNING: From method ColourSpectrogram.DrawTStatisticGreyscaleSpectrogramOfIndex()");
Console.WriteLine(" Null image returned with key: {0}", key);
return(null);
}
//frame image 1
int nyquist = cs1.SampleRate / 2;
int herzInterval = 1000;
string title = $"{key} SPECTROGRAM for: {cs1.FileName}. (scale:hours x kHz)";
var titleBar = LDSpectrogramRGB.DrawTitleBarOfGrayScaleSpectrogram(title, image1.Width);
image1 = LDSpectrogramRGB.FrameLDSpectrogram(image1, titleBar, cs1, nyquist, herzInterval);
//frame image 2
title = $"{key} SPECTROGRAM for: {cs2.FileName}. (scale:hours x kHz)";
titleBar = LDSpectrogramRGB.DrawTitleBarOfGrayScaleSpectrogram(title, image2.Width);
image2 = LDSpectrogramRGB.FrameLDSpectrogram(image2, titleBar, cs1, nyquist, herzInterval);
//get matrices required to calculate matrix of t-statistics
double[,] avg1 = cs1.GetSpectrogramMatrix(key);
if (key.Equals("ENT"))
{
avg1 = MatrixTools.SubtractValuesFromOne(avg1);
}
double[,] std1 = cs1.GetStandarDeviationMatrix(key);
double[,] avg2 = cs2.GetSpectrogramMatrix(key);
if (key.Equals("ENT"))
{
avg2 = MatrixTools.SubtractValuesFromOne(avg2);
}
double[,] std2 = cs2.GetStandarDeviationMatrix(key);
//draw a spectrogram of t-statistic values
//double[,] tStatMatrix = SpectrogramDifference.GetTStatisticMatrix(avg1, std1, cs1.SampleCount, avg2, std2, cs2.SampleCount);
//Image image3 = SpectrogramDifference.DrawTStatisticSpectrogram(tStatMatrix);
//titleBar = SpectrogramDifference.DrawTitleBarOfTStatisticSpectrogram(cs1.BaseName, cs2.BaseName, image1.Width, titleHt);
//image3 = ColourSpectrogram.FrameSpectrogram(image3, titleBar, minOffset, cs2.X_interval, cs2.Y_interval);
//draw a difference spectrogram derived from by thresholding a t-statistic matrix
var image4 = DrawDifferenceSpectrogramDerivedFromSingleTStatistic(key, cs1, cs2, tStatThreshold, ColourGain);
title = string.Format("{0} DIFFERENCE SPECTROGRAM (thresholded by t-statistic={3}) for: {1} - {2}. (scale:hours x kHz)", key, cs1.FileName, cs2.FileName, tStatThreshold);
titleBar = LDSpectrogramRGB.DrawTitleBarOfGrayScaleSpectrogram(title, image2.Width);
image4 = LDSpectrogramRGB.FrameLDSpectrogram(image4, titleBar, cs2, nyquist, herzInterval);
var combinedImage = ImageTools.CombineImagesVertically(image1, image2, image4);
return(combinedImage);
}
} // method DrawRidgeSpectrograms()
public static Image DrawRidgeSpectrograms(DirectoryInfo inputDirectory, FileInfo ipConfig, string fileStem, double scale, Dictionary <string, double[, ]> spectra = null)
{
string analysisType = AcousticIndices.TowseyAcoustic;
//double backgroundFilter = 0.0; // 0.0 means small values are removed.
double backgroundFilter = 0.75; // 0.75 means small values are accentuated.
var dataScale = TimeSpan.FromSeconds(scale);
Dictionary <string, IndexProperties> indexProperties = IndexProperties.GetIndexProperties(ipConfig);
string[] keys = SpectralPeakTracks.GetDefaultRidgeKeys();
// read the csv files of the indices in keys array
if (spectra == null)
{
//C:\SensorNetworks\Output\BIRD50\Training\ID0001\Towsey.Acoustic\ID0001__Towsey.Acoustic.ACI
spectra = IndexMatrices.ReadSpectralIndices(inputDirectory, fileStem, analysisType, keys);
}
var cs1 = new LDSpectrogramRGB(minuteOffset: TimeSpan.Zero, xScale: dataScale, sampleRate: 22050, frameWidth: 512, colorMap: null)
{
FileName = fileStem,
BackgroundFilter = backgroundFilter,
IndexCalculationDuration = dataScale,
};
// set the relevant dictionary of index properties
cs1.SetSpectralIndexProperties(indexProperties);
cs1.SpectrogramMatrices = spectra;
if (cs1.GetCountOfSpectrogramMatrices() == 0)
{
LoggedConsole.WriteLine("WARNING: " + fileStem + ": No spectrogram matrices in the dictionary. Spectrogram files do not exist?");
return(null);
}
else if (cs1.GetCountOfSpectrogramMatrices() < keys.Length)
{
LoggedConsole.WriteLine("WARNING: " + fileStem + ": Missing indices in the dictionary. Some files do not exist?");
return(null);
}
var stringFont = Drawing.Tahoma8;
// constants for labels
Color[] color = { Color.Blue, Color.Green, Color.Red, Color.Orange, Color.Purple };
int labelYvalue = 3;
int labelIndex = 0;
Image <Rgb24> ridges = null;
foreach (string key in keys)
{
Image <Rgb24> greyScaleImage = (Image <Rgb24>)cs1.DrawGreyscaleSpectrogramOfIndex(key);
var pixelWidth = greyScaleImage.Width;
int height = greyScaleImage.Height;
ridges.Mutate(g2 =>
{
if (ridges == null)
{
ridges = new Image <Rgb24>(pixelWidth, height);
g2.Clear(Color.White);
}
g2.DrawText(key, stringFont, color[labelIndex], new PointF(0, labelYvalue));
});
labelYvalue += 10;
//g1.DrawLine(new Pen(Color.Black, 1), 0, 0, width, 0);//draw upper boundary
//g1.DrawLine(new Pen(Color.Black, 1), 0, 1, width, 1);//draw upper boundary
// transfer greyscale image to colour image
for (int y = 0; y < height; y++)
{
for (int x = 0; x < pixelWidth; x++)
{
var col = greyScaleImage[x, y];
if (col.G < 150)
{
ridges[x, y] = color[labelIndex];
}
}
}
labelIndex += 1;
} //foreach key
return(ridges);
} // method DrawRidgeSpectrograms()
} // method DrawAggregatedSpectrograms()
public static Image <Rgb24> DrawGrayScaleSpectrograms(Arguments arguments, string fileStem, TimeSpan dataScale, Dictionary <string, double[, ]> spectra = null)
{
// default values
int sampleRate = 22050;
int frameWidth = 512;
//double backgroundFilter = 0.0; // 0.0 means small values are removed.
double backgroundFilter = 0.75; // 0.75 means small values are accentuated.
string analysisType = AcousticIndices.TowseyAcoustic;
string[] keys = LDSpectrogramRGB.GetArrayOfAvailableKeys();
var inputDirectory = arguments.InputDataDirectory;
Dictionary <string, IndexProperties> indexProperties = IndexProperties.GetIndexProperties(arguments.IndexPropertiesConfig.ToFileInfo());
if (spectra == null)
{
spectra = IndexMatrices.ReadSpectralIndices(inputDirectory.ToDirectoryInfo(), fileStem, analysisType, keys);
}
// note: the spectra are oriented as per visual orientation, i.e. xAxis = time frames
//int frameCount = spectra[keys[0]].GetLength(1);
var cs1 = new LDSpectrogramRGB(minuteOffset: TimeSpan.Zero, xScale: dataScale, sampleRate: sampleRate, frameWidth: frameWidth, colorMap: null)
{
FileName = fileStem,
BackgroundFilter = backgroundFilter,
IndexCalculationDuration = dataScale,
};
cs1.SetSpectralIndexProperties(indexProperties); // set the relevant dictionary of index properties
cs1.SpectrogramMatrices = spectra;
if (cs1.GetCountOfSpectrogramMatrices() == 0)
{
LoggedConsole.WriteLine("WARNING: " + fileStem + ": No spectrogram matrices in the dictionary. Spectrogram files do not exist?");
return(null);
}
var list = new List <Image <Rgb24> >();
var stringFont = Drawing.Arial14;
foreach (string key in keys)
{
var image = cs1.DrawGreyscaleSpectrogramOfIndex(key);
int width = 70;
int height = image.Height;
var label = new Image <Rgb24>(width, height);
label.Mutate(g1 =>
{
g1.Clear(Color.Gray);
g1.DrawText(key, stringFont, Color.Black, new PointF(4, 30));
g1.DrawLine(new Pen(Color.Black, 1), 0, 0, width, 0); //draw upper boundary
g1.DrawLine(new Pen(Color.Black, 1), 0, 1, width, 1); //draw upper boundary
});
var imagearray = new[] { label, image };
var labelledImage = ImageTools.CombineImagesInLine(imagearray);
list.Add(labelledImage);
} //foreach key
var combinedImage = ImageTools.CombineImagesVertically(list);
return(combinedImage);
} // method DrawGrayScaleSpectrograms()
} // method DrawAggregatedSpectrograms()
public static Image DrawGrayScaleSpectrograms(Arguments arguments, string fileStem, TimeSpan dataScale, Dictionary <string, double[, ]> spectra = null)
{
int sampleRate = 22050;
int frameWidth = 512;
//double backgroundFilter = 0.0; // 0.0 means small values are removed.
double backgroundFilter = 0.75; // 0.75 means small values are accentuated.
string analysisType = AcousticIndices.TowseyAcoustic;
string[] keys = LDSpectrogramRGB.GetArrayOfAvailableKeys();
//LoggedConsole.WriteLine("# Spectrogram Config file: " + arguments.SpectrogramConfigPath);
//LoggedConsole.WriteLine("# Index Properties Config file: " + arguments.IndexPropertiesConfig);
var inputDirectory = arguments.InputDataDirectory;
Dictionary <string, IndexProperties> indexProperties = IndexProperties.GetIndexProperties(arguments.IndexPropertiesConfig.ToFileInfo());
if (spectra == null)
{
//C:\SensorNetworks\Output\BIRD50\Training\ID0001\Towsey.Acoustic\ID0001__Towsey.Acoustic.ACI
spectra = IndexMatrices.ReadSpectralIndices(inputDirectory.ToDirectoryInfo(), fileStem, analysisType, keys);
}
// note: the spectra are oriented as per visual orientation, i.e. xAxis = time frames
//int frameCount = spectra[keys[0]].GetLength(1);
var cs1 = new LDSpectrogramRGB(minuteOffset: TimeSpan.Zero, xScale: dataScale, sampleRate: sampleRate, frameWidth: frameWidth, colourMap: null)
{
FileName = fileStem,
BackgroundFilter = backgroundFilter,
IndexCalculationDuration = dataScale,
};
cs1.SetSpectralIndexProperties(indexProperties); // set the relevant dictionary of index properties
cs1.SpectrogramMatrices = spectra;
if (cs1.GetCountOfSpectrogramMatrices() == 0)
{
LoggedConsole.WriteLine("WARNING: " + fileStem + ": No spectrogram matrices in the dictionary. Spectrogram files do not exist?");
return(null);
}
List <Image> list = new List <Image>();
Font stringFont = new Font("Arial", 14);
foreach (string key in keys)
{
var image = cs1.DrawGreyscaleSpectrogramOfIndex(key);
int width = 70;
int height = image.Height;
var label = new Bitmap(width, height);
var g1 = Graphics.FromImage(label);
g1.Clear(Color.Gray);
g1.DrawString(key, stringFont, Brushes.Black, new PointF(4, 30));
g1.DrawLine(new Pen(Color.Black), 0, 0, width, 0); //draw upper boundary
g1.DrawLine(new Pen(Color.Black), 0, 1, width, 1); //draw upper boundary
Image[] imagearray = { label, image };
var labelledImage = ImageTools.CombineImagesInLine(imagearray);
list.Add(labelledImage);
} //foreach key
var combinedImage = ImageTools.CombineImagesVertically(list.ToArray());
return(combinedImage);
} // method DrawGrayScaleSpectrograms()
