//public static Image DrawImageOfDistribution(double[,] matrix, int width, int height, string label)
//{
// double[] array = DataTools.Matrix2Array(matrix);
// SpectralStats stats = GetModeAndOneTailedStandardDeviation(array, width, UpperPercentileDefault);
// double value = stats.GetValueOfNthPercentile(UpperPercentileDefault);
// var image =
// GraphsAndCharts.DrawHistogram(
// label,
// stats.Distribution,
// stats.UpperPercentileBin,
// new Dictionary<string, double>()
// {
// { "min", stats.Minimum },
// { "max", stats.Maximum },
// { "mode", stats.Mode },
// { "sd", stats.StandardDeviation },
// { UpperPercentileLabel, value },
// { "count", stats.Count },
// },
// width,
// height);
// return image;
//}
public static Dictionary <string, SpectralStats> WriteSummaryIndexDistributionStatistics(Dictionary <string, double[]> summaryIndices, DirectoryInfo outputDirectory, string fileStem)
{
// to accumulate the images
int width = 100; // pixels
int height = 100; // pixels
var imageList = new List <Image>();
Dictionary <string, SpectralStats> indexDistributionStatistics = new Dictionary <string, SpectralStats>();
string[] indexKeys = summaryIndices.Keys.ToArray();
foreach (string key in indexKeys)
{
if (summaryIndices.ContainsKey(key))
{
double[] array = summaryIndices[key];
SpectralStats stats = GetModeAndOneTailedStandardDeviation(array, width, UpperPercentileDefault);
stats.GetValueOfNthPercentile(UpperPercentileDefault, out int binId, out double value);
stats.UpperPercentileBin = binId;
indexDistributionStatistics.Add(key, stats); // add index statistics
// CVR (cover) and EVN (events/sec) have discrete, sparse distributions when calculating for zoomed tiles,
// and most values are in the zero bin.
// Therefore they return value = 0.0; This is a bug!
// To avoid this problem, set value = maximum when percentileBin = 0
if (binId == 0)
{
value = stats.Maximum;
}
imageList.Add(
GraphsAndCharts.DrawHistogram(
key,
stats.Distribution,
stats.UpperPercentileBin,
new Dictionary <string, double>()
{
{ "min", stats.Minimum },
{ "max", stats.Maximum },
{ "mode", stats.Mode },
{ "sd", stats.StandardDeviation },
{ UpperPercentileLabel, value },
{ "count", stats.Count },
},
width,
height));
}
}
FileInfo statsFile = new FileInfo(GetSummaryStatsPath(outputDirectory, fileStem));
Json.Serialise(statsFile, indexDistributionStatistics);
Image image3 = ImageTools.CombineImagesVertically(imageList.ToArray());
string imagePath = GetSummaryImagePath(outputDirectory, fileStem);
image3.Save(imagePath);
return(indexDistributionStatistics);
}
public static Dictionary <string, SpectralStats> WriteSummaryIndexDistributionStatistics(Dictionary <string, double[]> summaryIndices, DirectoryInfo outputDirectory, string fileStem)
{
// to accumulate the images
int width = 100; // pixels
int height = 100; // pixels
var imageList = new List <Image>();
Dictionary <string, SpectralStats> indexDistributionStatistics = new Dictionary <string, SpectralStats>();
string[] indexKeys = summaryIndices.Keys.ToArray();
foreach (string key in indexKeys)
{
if (summaryIndices.ContainsKey(key))
{
double[] array = summaryIndices[key];
SpectralStats stats = GetModeAndOneTailedStandardDeviation(array, width, UpperPercentileDefault);
indexDistributionStatistics.Add(key, stats); // add index statistics
double value = stats.GetValueOfNthPercentile(UpperPercentileDefault);
imageList.Add(
GraphsAndCharts.DrawHistogram(
key,
stats.Distribution,
stats.UpperPercentileBin,
new Dictionary <string, double>()
{
{ "min", stats.Minimum },
{ "max", stats.Maximum },
{ "mode", stats.Mode },
{ "sd", stats.StandardDeviation },
{ UpperPercentileLabel, value },
{ "count", stats.Count },
},
width,
height));
}
}
FileInfo statsFile = new FileInfo(GetSummaryStatsPath(outputDirectory, fileStem));
Json.Serialise(statsFile, indexDistributionStatistics);
Image image3 = ImageTools.CombineImagesVertically(imageList.ToArray());
string imagePath = GetSummaryImagePath(outputDirectory, fileStem);
image3.Save(imagePath);
return(indexDistributionStatistics);
}
public static Image DrawImageOfDistribution(double[,] matrix, int width, int height, string label)
{
SpectralStats stats = GetModeAndOneTailedStandardDeviation(matrix, width, UpperPercentileDefault);
double value = stats.GetValueOfNthPercentile(UpperPercentileDefault);
var image =
GraphsAndCharts.DrawHistogram(
label,
stats.Distribution,
stats.UpperPercentileBin,
new Dictionary <string, double>()
{
{ "min", stats.Minimum },
{ "max", stats.Maximum },
{ "mode", stats.Mode },
{ "sd", stats.StandardDeviation },
{ UpperPercentileLabel, value },
{ "count", stats.Count },
},
width,
height);
return(image);
}
} // HiRes1()
/// <summary>
/// HERVE GLOTIN: This is used to analyse the BIRD50 data set.
/// Draws HIres spectrogram images AFTER indices have been calculated.
/// This method does NOT produce acoustic indices.
/// That is, only call this method if hires1() has already been used to produce the indices.
/// </summary>
public static void HiRes2()
{
string histoDir = @"C:\SensorNetworks\Output\BIRD50";
string histoPath = Path.Combine(histoDir, "TrainingRecordingDurations.png");
//string histoPath = Path.Combine(histoDir, "TestingRecordingDurations.png");
// set up histogram of recording durations
int histogramWidth = 600; // equivalent to ten minutes at 0.1 second resolution
int[] recordingDurations = new int[histogramWidth];
// set up IP and OP directories
string inputDir = @"C:\SensorNetworks\Output\BIRD50\Training";
string imageOutputDir = @"C:\SensorNetworks\Output\BIRD50\TrainingImages";
//string imageOutputDir = @"C:\SensorNetworks\Output\BIRD50\TestingRidgeImages";
string indexPropertiesConfig = @"C:\Work\GitHub\audio-analysis\AudioAnalysis\AnalysisConfigFiles\IndexPropertiesConfigHiRes.yml";
// comment next two lines when debugging a single recording file
var inputDirInfo = new DirectoryInfo(inputDir);
//string match = @"*.wav";
//DirectoryInfo[] directories = inputDirInfo.GetDirectories(match, SearchOption.AllDirectories);
DirectoryInfo[] directories = inputDirInfo.GetDirectories();
int count = directories.Length;
//count = 3;
//string fileStem = "ID0003"; //\ID0001\Towsey.Acoustic\
string fileStemFormatString = "ID{0:d4}"; // for training files
//string fileStemFormatString = "ID1{0:d3}"; // for testing files
for (int i = 0; i < count; i++)
{
string fileStem = string.Format(fileStemFormatString, i + 1);
string dataDir = directories[i].FullName + @"\Towsey.Acoustic\";
var ldfcSpectrogramArguments = new DrawLongDurationSpectrograms.Arguments
{
// use the default set of index properties in the AnalysisConfig directory.
InputDataDirectory = dataDir,
OutputDirectory = imageOutputDir,
IndexPropertiesConfig = indexPropertiesConfig,
};
// there are two possible tasks
// 1: draw the aggregated grey scale spectrograms
int secDuration = DrawLongDurationSpectrograms.DrawAggregatedSpectrograms(ldfcSpectrogramArguments, fileStem);
// 2: draw the coloured ridge spectrograms
DrawLongDurationSpectrograms.DrawRidgeSpectrograms(ldfcSpectrogramArguments, fileStem);
if (secDuration >= recordingDurations.Length)
{
secDuration = recordingDurations.Length - 1;
}
recordingDurations[secDuration]++;
}
string title = "Recording Duration: Width = " + histogramWidth + "secs";
Image histoImage = GraphsAndCharts.DrawHistogram(title, recordingDurations, 95, null, histogramWidth, 50);
histoImage.Save(histoPath);
} // HiRes2() produces spectrogram images