//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);
}
