private async Task <string> ObtainLatestRadiometersParameters()
{
string retStr = "";
if (Directory.Exists(RadiometersDataPath))
{
List <FileInfo> lCSVdataFilesInfoList =
((new DirectoryInfo(RadiometersDataPath)).GetFiles("*.csv", SearchOption.AllDirectories)).ToList();
lCSVdataFilesInfoList.Sort((finfo1, finfo2) => finfo1.CreationTimeUtc.CompareTo(finfo2.CreationTimeUtc));
FileInfo lastCSVdataFileInfo = lCSVdataFilesInfoList.Last();
List <List <string> > Contents = ServiceTools.ReadDataFromCSV(lastCSVdataFileInfo.FullName, 2, true, ";");
List <string> lastRdDataStrings = Contents.Last();
retStr +=
"Radiometers:" + Environment.NewLine +
"Date,time: " + lastRdDataStrings[0] + Environment.NewLine +
"SW ave.(W/m2): " + lastRdDataStrings[7] + Environment.NewLine +
"LW downward ave.[W/m2]: " + lastRdDataStrings[15] + Environment.NewLine + Environment.NewLine;
}
else
{
retStr = "";
}
return(retStr);
}
private void ReadObservationsReportCSVfile()
{
if (File.Exists(strObservationsReportCSVfile))
{
List <List <string> > ObservationsReportCSVfileContents = ServiceTools.ReadDataFromCSV(strObservationsReportCSVfile, 1, true,
";", "\n");
lMissionObservedData =
ObservationsReportCSVfileContents.ConvertAll(strList => new MissionsObservedData(strList));
}
}
static async Task <ImageStatsDataCalculationResult> ConvertImageTask(object inputArgs)
{
ImageStatsDataCalculationResult Result = new ImageStatsDataCalculationResult();
Dictionary <string, object> ParametersPassed = inputArgs as Dictionary <string, object>;
string logFileName = "";
string currentFullFileName = ParametersPassed["currentFullFileName"] as string;
Stopwatch stopwatch = null;
List <Tuple <string, string> > lImagesRoundMasksMappingFiles = null;
if (ParametersPassed != null)
{
if (ParametersPassed.ContainsKey("ImagesRoundMasksXMLfilesMappingList"))
{
string ImagesRoundMasksXMLfilesMappingListPassed = (string)ParametersPassed["ImagesRoundMasksXMLfilesMappingList"];
if (File.Exists(ImagesRoundMasksXMLfilesMappingListPassed))
{
List <List <string> > llImagesRoundMasksMappingFiles =
ServiceTools.ReadDataFromCSV(ImagesRoundMasksXMLfilesMappingListPassed, 0, true, ";", Environment.NewLine);
lImagesRoundMasksMappingFiles =
llImagesRoundMasksMappingFiles.ConvertAll(
list => new Tuple <string, string>(list[0], list[1]));
}
}
if (ParametersPassed.ContainsKey("Stopwatch"))
{
stopwatch = ParametersPassed["Stopwatch"] as Stopwatch;
}
if (ParametersPassed.ContainsKey("logFileName"))
{
logFileName = ParametersPassed["logFileName"] as string;
}
}
TimeSpan procStart = Process.GetCurrentProcess().TotalProcessorTime;
try
{
RoundData predefinedRoundedMask = null;
if (lImagesRoundMasksMappingFiles != null)
{
if (lImagesRoundMasksMappingFiles.Any())
{
if (lImagesRoundMasksMappingFiles.Find(tpl => (new WildcardPattern(tpl.Item1)).IsMatch(currentFullFileName)) != null)
{
string strFoundPredefinedRoundedMaskParametersXMLfile =
lImagesRoundMasksMappingFiles.Find(
tpl => (new WildcardPattern(tpl.Item1)).IsMatch(currentFullFileName)).Item2;
strFoundPredefinedRoundedMaskParametersXMLfile =
strFoundPredefinedRoundedMaskParametersXMLfile.Substring(0, strFoundPredefinedRoundedMaskParametersXMLfile.IndexOf(".xml") + 4);
predefinedRoundedMask =
ServiceTools.ReadObjectFromXML(strFoundPredefinedRoundedMaskParametersXMLfile,
typeof(RoundData)) as RoundData;
}
}
}
Image <Bgr, byte> currImg = new Image <Bgr, byte>(currentFullFileName);
ImageProcessing imgP = new ImageProcessing(currImg, predefinedRoundedMask);
Image <Bgr, byte> maskImage =
new Image <Bgr, byte>(new Image <Gray, byte>[]
{
imgP.significantMaskImageCircled,
imgP.significantMaskImageCircled,
imgP.significantMaskImageCircled
});
Image <Bgr, byte> img = imgP.tmpImage.Mul(maskImage);
string ncFileName = ConventionalTransitions.NetCDFimageBareChannelsDataFilename(currentFullFileName,
ParametersPassed["outputNetCDFfilesDirectory"] as string, true, ParametersPassed["ImagesBasePath"] as string);
Dictionary <string, object> dataToNCwrite = new Dictionary <string, object>();
dataToNCwrite.Add("ColorChannels", img.Data);
NetCDFoperations.SaveVariousDataToFile(dataToNCwrite, ncFileName);
TimeSpan procEnd = Process.GetCurrentProcess().TotalProcessorTime;
Result = new ImageStatsDataCalculationResult()
{
calcResult = true,
imgFilename = currentFullFileName,
mp5Result = null,
grixyrgbStatsData = null,
stopwatch = stopwatch,
exception = null,
procTotalProcessorTimeEnd = procEnd,
procTotalProcessorTimeStart = procStart
};
return(Result);
}
catch (Exception ex)
{
TimeSpan procEnd = Process.GetCurrentProcess().TotalProcessorTime;
Result = new ImageStatsDataCalculationResult()
{
calcResult = false,
imgFilename = currentFullFileName,
stopwatch = stopwatch,
exception = ex,
procTotalProcessorTimeEnd = procEnd,
procTotalProcessorTimeStart = procStart
};
return(Result);
}
}
//private void ImageProcessing(ImagesProcessingData ipdt)
//{
//}
private void EnumerateFilesToProcess()
{
string directory = Path.GetDirectoryName(inputBasePath);
string filemask = "*.jpg";
List <string> filesList =
new List <string>(Directory.EnumerateFiles(directory, filemask,
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly));
#region filter by camID
//...devID1.jpg
string ptrnCamID = "devid" + CamIDtoProcess + ".jpg";
filesList = filesList.Where(fname => fname.ToLower().Contains(ptrnCamID)).ToList();
#endregion
Console.WriteLine("found " + filesList.Count + " images.");
#region list, read and map image stats files
Console.WriteLine("filtering by ready-to-use GrIxYRGB XML files...");
List <string> statsFilesList =
new List <string>(Directory.EnumerateFiles(imageYRGBstatsXMLdataFilesDirectory, ConventionalTransitions.ImageGrIxYRGBstatsFileNamesPattern(),
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly));
List <string> statsFilesListWOpath = statsFilesList.ConvertAll(Path.GetFileName);
Console.WriteLine("found " + statsFilesList.Count + " XML stats files in directory " + Environment.NewLine +
imageYRGBstatsXMLdataFilesDirectory + Environment.NewLine + "by mask " +
Environment.NewLine + ConventionalTransitions.ImageGrIxYRGBstatsFileNamesPattern());
int removed =
filesList.RemoveAll(
fname =>
!statsFilesListWOpath.Contains(ConventionalTransitions.ImageGrIxYRGBstatsDataFileName(fname, "",
false)));
Console.WriteLine("removed " + removed + " items (couldn`t find stats data files). Remains " + filesList.Count + " to process.");
if (!filesList.Any())
{
Console.WriteLine("There is no " + filemask + " files that sutisfy settings specified. Processing will not be started.");
return;
}
lStatsProcessing = filesList.ConvertAll(strImgFname =>
{
ImagesProcessingData retVal = new ImagesProcessingData()
{
filename = strImgFname
};
return(retVal);
});
#if DEBUG
//lStatsProcessing = lStatsProcessing.Where((ipd, ind) => ind < 10).ToList();
#endif
Console.WriteLine("started reading and mapping stats data");
int totalFilesCountToRead = lStatsProcessing.Count;
int filesRead = 0;
int currProgressPerc = 0;
foreach (ImagesProcessingData ipdt in lStatsProcessing)
{
ipdt.grixyrgbStatsXMLfile =
statsFilesList.First(
statsFname =>
statsFname.Contains(ConventionalTransitions.ImageGrIxYRGBstatsDataFileName(ipdt.filename, "",
false)));
ipdt.grixyrgbStats =
ServiceTools.ReadObjectFromXML(ipdt.grixyrgbStatsXMLfile, typeof(SkyImageIndexesStatsData)) as
SkyImageIndexesStatsData;
#region calculate and report progress
filesRead++;
double progress = 100.0d * (double)filesRead / (double)totalFilesCountToRead;
if (progress - (double)currProgressPerc > 1.0d)
{
currProgressPerc = Convert.ToInt32(progress);
Console.WriteLine("read " + currProgressPerc + "%");
}
#endregion calculate and report progress
}
#endregion
#region list, read and map concurrent data
List <string> concurrentDataFilesList =
Directory.EnumerateFiles(ConcurrentDataXMLfilesDirectory,
ConventionalTransitions.ImageConcurrentDataFilesNamesPattern(),
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly).ToList();
List <ConcurrentData> lConcurrentData = null;
#region reading
Console.WriteLine("started concurrent data reading");
totalFilesCountToRead = concurrentDataFilesList.Count;
filesRead = 0;
currProgressPerc = 0;
List <Dictionary <string, object> > lDictionariesConcurrentData =
new List <Dictionary <string, object> >();
foreach (string strConcDataXMLFile in concurrentDataFilesList)
{
Dictionary <string, object> currDict = ServiceTools.ReadDictionaryFromXML(strConcDataXMLFile);
currDict.Add("XMLfileName", Path.GetFileName(strConcDataXMLFile));
lDictionariesConcurrentData.Add(currDict);
#region calculate and report progress
filesRead++;
double progress = 100.0d * (double)filesRead / (double)totalFilesCountToRead;
if (progress - (double)currProgressPerc > 1.0d)
{
currProgressPerc = Convert.ToInt32(progress);
Console.WriteLine("read " + currProgressPerc + "%");
}
#endregion calculate and report progress
}
lDictionariesConcurrentData.RemoveAll(dict => dict == null);
lConcurrentData =
lDictionariesConcurrentData.ConvertAll <ConcurrentData>(dict =>
{
ConcurrentData retVal = null;
try
{
retVal = new ConcurrentData(dict);
}
catch (Exception ex)
{
string strError = "couldn`t parse XML file " + dict["XMLfileName"] + " : " +
Environment.NewLine + ex.Message;
Console.WriteLine(strError);
}
return(retVal);
});
lConcurrentData.RemoveAll(val => val == null);
#endregion reading
#region mapping
// map obtained concurrent data to images by its datetime
Console.WriteLine("concurrent data mapping started");
lStatsProcessing = lStatsProcessing.ConvertAll(ipdt =>
{
string currImgFilename = ipdt.filename;
currImgFilename = Path.GetFileNameWithoutExtension(currImgFilename);
string ptrn = @"(devID\d)";
Regex rgxp = new Regex(ptrn, RegexOptions.IgnoreCase);
string strCurrImgDT = rgxp.Replace(currImgFilename.Substring(4), "");
//2015-12-16T06-01-38
strCurrImgDT = strCurrImgDT.Substring(0, 11) + strCurrImgDT.Substring(11).Replace("-", ":");
DateTime currImgDT = DateTime.Parse(strCurrImgDT, null,
System.Globalization.DateTimeStyles.AdjustToUniversal);
ConcurrentData nearestConcurrentData = lConcurrentData.Aggregate((cDt1, cDt2) =>
{
TimeSpan tspan1 = new TimeSpan(Math.Abs((cDt1.datetimeUTC - currImgDT).Ticks));
TimeSpan tspan2 = new TimeSpan(Math.Abs((cDt2.datetimeUTC - currImgDT).Ticks));
return((tspan1 <= tspan2) ? (cDt1) : (cDt2));
});
if (new TimeSpan(Math.Abs((nearestConcurrentData.datetimeUTC - currImgDT).Ticks)) >=
TimeSpanForConcurrentDataMappingTolerance)
{
string strError = "couldn`t find close enough concurrent data file for image:" + Environment.NewLine +
currImgFilename + Environment.NewLine + "closest concurrent data file is:" +
Environment.NewLine + nearestConcurrentData.filename + Environment.NewLine +
"with date-time value " + nearestConcurrentData.datetimeUTC.ToString("o");
Console.WriteLine(strError);
nearestConcurrentData = null;
}
ipdt.concurrentData = nearestConcurrentData;
if (nearestConcurrentData != null)
{
ipdt.concurrentDataXMLfile = nearestConcurrentData.filename;
}
return(ipdt);
});
#endregion mapping
removed = lStatsProcessing.RemoveAll(ipdt => ipdt.concurrentData == null);
Console.WriteLine("removed " + removed + " items (couldn`t find concurrent data). " + lStatsProcessing.Count + " files remains to process.");
#endregion list, read and map concurrent data
if (!lStatsProcessing.Any())
{
Console.WriteLine("There is no files that sutisfy settings specified and have all required concurrent data (stats or GPS etc.). Processing will not be proceeded.");
return;
}
#region Predict SDC values using pre-trained NN parameters
string csvHeader = lStatsProcessing[0].grixyrgbStats.CSVHeader() +
",SunElevationDeg,SunAzimuthDeg,sunDiskCondition";
List <string> lCSVheader = csvHeader.Split(',').ToList();
List <int> columnsToDelete =
lCSVheader.Select((str, idx) => new Tuple <int, string>(idx, str))
.Where(tpl => tpl.Item2.ToLower().Contains("filename")).ToList().ConvertAll(tpl => tpl.Item1);
List <List <string> > lCalculatedData = lStatsProcessing.ConvertAll(dt =>
{
string currImageALLstatsDataCSVWithConcurrentData = dt.grixyrgbStats.ToCSV() + "," +
dt.concurrentData.gps.SunZenithAzimuth()
.ElevationAngle.ToString()
.Replace(",", ".") + "," +
dt.concurrentData.gps.SunZenithAzimuth()
.Azimuth.ToString()
.Replace(",", ".");
List <string> retVal = currImageALLstatsDataCSVWithConcurrentData.Split(',').ToList();
retVal = retVal.Where((str, idx) => !columnsToDelete.Contains(idx)).ToList();
return(retVal);
});
List <DenseVector> lDV_objects_features =
lCalculatedData.ConvertAll(
list =>
DenseVector.OfEnumerable(list.ConvertAll <double>(str => Convert.ToDouble(str.Replace(".", ",")))));
DenseVector dvMeans = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormMeansFile, 0, ",")).Row(0);
DenseVector dvRanges = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormRangeFile, 0, ",")).Row(0);
lDV_objects_features = lDV_objects_features.ConvertAll(dv =>
{
DenseVector dvShifted = dv - dvMeans;
DenseVector dvNormed = (DenseVector)dvShifted.PointwiseDivide(dvRanges);
return(dvNormed);
});
DenseMatrix dmObjectsFeatures = DenseMatrix.OfRowVectors(lDV_objects_features);
DenseVector dvThetaValues = (DenseVector)ServiceTools.ReadDataFromCSV(NNtrainedParametersFile, 0, ",");
List <int> NNlayersConfig =
new List <double>(((DenseMatrix)ServiceTools.ReadDataFromCSV(NNconfigFile, 0, ",")).Row(0)).ConvertAll
(dVal => Convert.ToInt32(dVal));
List <List <double> > lDecisionProbabilities = null;
List <SunDiskCondition> predictedSDClist =
NNclassificatorPredictor <SunDiskCondition> .NNpredict(dmObjectsFeatures, dvThetaValues, NNlayersConfig,
out lDecisionProbabilities, SunDiskConditionData.MatlabEnumeratedSDCorderedList()).ToList();
//List<SunDiskCondition> predictedSDClist = predictedSDC.ConvertAll(sdcInt =>
//{
// switch (sdcInt)
// {
// case 4:
// return SunDiskCondition.NoSun;
// break;
// case 1:
// return SunDiskCondition.Sun0;
// break;
// case 2:
// return SunDiskCondition.Sun1;
// break;
// case 3:
// return SunDiskCondition.Sun2;
// break;
// default:
// return SunDiskCondition.Defect;
// }
//});
string strToShow = "SDC values probabilities: " + Environment.NewLine +
"| No Sun | Sun_0 | Sun_1 | Sun_2 | Detected |" + Environment.NewLine;
foreach (List <double> lDecisionProbability in lDecisionProbabilities)
{
strToShow += "| " + lDecisionProbability[3].ToString("F4") +
" | " + lDecisionProbability[0].ToString("F4") +
" | " + lDecisionProbability[1].ToString("F4") +
" | " + lDecisionProbability[2].ToString("F4") + " |" +
predictedSDClist[lDecisionProbabilities.IndexOf(lDecisionProbability)] + "|" +
Environment.NewLine;
}
ServiceTools.logToTextFile(errorLogFilename, strToShow, true, false);
#endregion
//lStatsProcessing =
// lStatsProcessing.Where((ipd, idx) => predictedSDClist[idx] == SunDiskCondition.Sun2).ToList();
lStatsProcessing =
lStatsProcessing.Where((ipd, idx) => predictedSDClist[idx] == sdcFilter).ToList();
Console.WriteLine("Detected " + lStatsProcessing.Count + " images with SDC = " + sdcFilter.ToString());
if (!lStatsProcessing.Any())
{
Console.WriteLine("There is no files with SDC = Sun2. Processing will not be proceeded.");
return;
}
Console.WriteLine("finished enumerating and filtering files. Files to process: " + lStatsProcessing.Count);
}
public void Start(string[] args)
{
readDefaultProperties();
List <string> argsList = new List <string>(args);
if (argsList.Find(str => str == "--recursive") != null)
{
bEnumerateFilesRecursively = true;
}
if (argsList.Find(str => str == "-y") != null)
{
bStartWithoutConfirmation = true;
}
// --filter-by-observed-cloud-cover-records
// bFilterByObservedCloudCoverRecords
if (argsList.Find(str => str == "--filter-by-observed-cloud-cover-records") != null)
{
bFilterByObservedCloudCoverRecords = true;
}
// sdcFilter
if (argsList.Where(str => str.Contains("--sdc=")).Count() > 0)
{
string foundArg = argsList.Where(str => str.Contains("--sdc=")).ToList()[0];
string strValue = foundArg.Replace("--sdc=", "");
//sdcFilter
if (strValue == "none")
{
sdcFilter = SunDiskCondition.NoSun;
}
else if (strValue == "0")
{
sdcFilter = SunDiskCondition.Sun0;
}
else if (strValue == "1")
{
sdcFilter = SunDiskCondition.Sun1;
}
else if (strValue == "2")
{
sdcFilter = SunDiskCondition.Sun2;
}
else
{
sdcFilter = SunDiskCondition.Sun2;
}
}
else
{
Console.WriteLine("SDC filter is not specified. Filtering by SDC will not applied.");
sdcFilter = SunDiskCondition.Undefined; // Не применять фильтрацию
}
if (argsList.Where(str => str.Contains("--camera-id=")).Count() > 0)
{
string foundArg = argsList.Where(str => str.Contains("--camera-id=")).ToList()[0];
string strValue = foundArg.Replace("--camera-id=", "");
CamIDtoProcess = Convert.ToInt32(strValue);
if ((CamIDtoProcess != 1) && (CamIDtoProcess != 2))
{
Console.WriteLine("camera ID out of range detected. I will not filter by camera ID.");
CamIDtoProcess = 0;
}
}
else
{
Console.WriteLine("camera ID out of range detected. I will not filter by camera ID");
CamIDtoProcess = 0; // will not filter
}
if (!bStartWithoutConfirmation)
{
Console.Write("Start with the mentioned properties? [y/n] ");
string strReply = Console.ReadLine();
if (strReply.ToLower().First() != 'y')
{
Console.WriteLine("\nWill not proceed due to user interruprion.");
Console.WriteLine("===FINISHED===");
Console.ReadKey();
return;
}
}
outputDataFile = strOutputDirectory + Path.GetFileNameWithoutExtension(outputDataFile) + "-" + sdcFilter.ToString() + "-camID" +
CamIDtoProcess + ".xml";
string outputCSVfile = strOutputDirectory + Path.GetFileNameWithoutExtension(outputDataFile) + "-" + sdcFilter.ToString() + "-camID" +
CamIDtoProcess + ".csv";
Console.WriteLine("getting files list");
#region Enumerating files
string directory = Path.GetDirectoryName(inputBasePath);
string filemask = "*.jpg";
List <string> filesList =
new List <string>(Directory.EnumerateFiles(directory, filemask,
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly));
#region filter by camID
//...devID1.jpg
if (CamIDtoProcess > 0)
{
string ptrnCamID = "devid" + CamIDtoProcess + ".jpg";
filesList = filesList.Where(fname => fname.ToLower().Contains(ptrnCamID)).ToList();
}
#endregion
Console.WriteLine("found " + filesList.Count + " images.");
#region try to find concurrent and stats data already assembled into a small set of files
List <string> assembledDataFilesList =
Directory.EnumerateFiles(ConcurrentDataXMLfilesDirectory,
"*.xml", SearchOption.TopDirectoryOnly).ToList();
List <ImagesProcessingData> lReadAssembledData = new List <ImagesProcessingData>();
foreach (string strAssembledDataXMlfName in assembledDataFilesList)
{
try
{
List <ImagesProcessingData> currFileContent =
ServiceTools.ReadObjectFromXML(strAssembledDataXMlfName, typeof(List <ImagesProcessingData>)) as
List <ImagesProcessingData>;
lReadAssembledData.AddRange(currFileContent);
}
catch (Exception ex)
{
continue;
}
}
if (lReadAssembledData.Any())
{
Console.WriteLine("Found pre-assembled ImagesProcessingData XML files: ");
foreach (string s in assembledDataFilesList)
{
Console.WriteLine(s);
}
Console.WriteLine("Read records from this set: " + lReadAssembledData.Count);
Console.WriteLine("Images to process originally: " + filesList.Count);
Console.WriteLine("Should I use these pre-assembled data? (y/n): ");
string ans = Console.ReadKey().KeyChar.ToString();
if (ans == "y")
{
lStatsProcessing = lReadAssembledData;
}
}
#endregion try to find data already compiled into a small set of files
if (!lStatsProcessing.Any())
{
#region list, read and map image stats files
Console.WriteLine("filtering by ready-to-use GrIxYRGB XML files...");
List <string> statsFilesList =
new List <string>(Directory.EnumerateFiles(imageYRGBstatsXMLdataFilesDirectory, ConventionalTransitions.ImageGrIxYRGBstatsFileNamesPattern(),
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly));
List <string> statsFilesListWOpath = statsFilesList.ConvertAll(Path.GetFileName);
Console.WriteLine("found " + statsFilesList.Count + " XML stats files in directory " + Environment.NewLine +
imageYRGBstatsXMLdataFilesDirectory + Environment.NewLine + "by mask " +
Environment.NewLine + ConventionalTransitions.ImageGrIxYRGBstatsFileNamesPattern());
int removed =
filesList.RemoveAll(
fname =>
!statsFilesListWOpath.Contains(ConventionalTransitions.ImageGrIxYRGBstatsDataFileName(fname, "",
false)));
Console.WriteLine("removed " + removed + " items (couldn`t find stats data files). Remains " + filesList.Count + " to process.");
if (!filesList.Any())
{
Console.WriteLine("There is no " + filemask + " files that sutisfy settings specified. Processing will not be started.");
return;
}
lStatsProcessing = filesList.ConvertAll(strImgFname =>
{
ImagesProcessingData retVal = new ImagesProcessingData()
{
filename = strImgFname
};
return(retVal);
});
//#if DEBUG
// lStatsProcessing = lStatsProcessing.Where((ipd, ind) => ind < 10).ToList();
//#endif
Console.WriteLine("started reading and mapping stats data");
int totalFilesCountToRead = lStatsProcessing.Count;
int filesRead = 0;
int currProgressPerc = 0;
foreach (ImagesProcessingData ipdt in lStatsProcessing)
{
ipdt.grixyrgbStatsXMLfile =
statsFilesList.First(
statsFname =>
statsFname.Contains(ConventionalTransitions.ImageGrIxYRGBstatsDataFileName(ipdt.filename, "",
false)));
ipdt.grixyrgbStats =
ServiceTools.ReadObjectFromXML(ipdt.grixyrgbStatsXMLfile, typeof(SkyImageIndexesStatsData)) as
SkyImageIndexesStatsData;
#region calculate and report progress
filesRead++;
double progress = 100.0d * (double)filesRead / (double)totalFilesCountToRead;
if (progress - (double)currProgressPerc > 1.0d)
{
currProgressPerc = Convert.ToInt32(progress);
Console.WriteLine("read " + currProgressPerc + "%");
}
#endregion calculate and report progress
}
#endregion
#region list, read and map concurrent data
List <ConcurrentData> lConcurrentData = null;
List <string> concurrentDataFilesList =
Directory.EnumerateFiles(ConcurrentDataXMLfilesDirectory,
ConventionalTransitions.ImageConcurrentDataFilesNamesPattern(),
bEnumerateFilesRecursively ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly).ToList();
#region reading
Console.WriteLine("started concurrent data reading");
totalFilesCountToRead = concurrentDataFilesList.Count;
filesRead = 0;
currProgressPerc = 0;
List <Dictionary <string, object> > lDictionariesConcurrentData =
new List <Dictionary <string, object> >();
foreach (string strConcDataXMLFile in concurrentDataFilesList)
{
Dictionary <string, object> currDict = ServiceTools.ReadDictionaryFromXML(strConcDataXMLFile);
currDict.Add("XMLfileName", Path.GetFileName(strConcDataXMLFile));
lDictionariesConcurrentData.Add(currDict);
#region calculate and report progress
filesRead++;
double progress = 100.0d * (double)filesRead / (double)totalFilesCountToRead;
if (progress - (double)currProgressPerc > 1.0d)
{
currProgressPerc = Convert.ToInt32(progress);
Console.WriteLine("read " + currProgressPerc + "%");
}
#endregion calculate and report progress
}
lDictionariesConcurrentData.RemoveAll(dict => dict == null);
lConcurrentData =
lDictionariesConcurrentData.ConvertAll <ConcurrentData>(dict =>
{
ConcurrentData retVal = null;
try
{
retVal = new ConcurrentData(dict);
}
catch (Exception ex)
{
string strError = "couldn`t parse XML file " + dict["XMLfileName"] + " : " +
Environment.NewLine + ex.Message;
Console.WriteLine(strError);
}
return(retVal);
});
lConcurrentData.RemoveAll(val => val == null);
#endregion reading
#region mapping
// map obtained concurrent data to images by its datetime
Console.WriteLine("concurrent data mapping started");
lStatsProcessing = lStatsProcessing.ConvertAll(ipdt =>
{
string currImgFilename = ipdt.filename;
currImgFilename = Path.GetFileNameWithoutExtension(currImgFilename);
DateTime currImgDT = ConventionalTransitions.DateTimeOfSkyImageFilename(currImgFilename);
ConcurrentData nearestConcurrentData = lConcurrentData.Aggregate((cDt1, cDt2) =>
{
TimeSpan tspan1 = new TimeSpan(Math.Abs((cDt1.datetimeUTC - currImgDT).Ticks));
TimeSpan tspan2 = new TimeSpan(Math.Abs((cDt2.datetimeUTC - currImgDT).Ticks));
return((tspan1 <= tspan2) ? (cDt1) : (cDt2));
});
if (new TimeSpan(Math.Abs((nearestConcurrentData.datetimeUTC - currImgDT).Ticks)) >=
TimeSpanForConcurrentDataMappingTolerance)
{
string strError = "couldn`t find close enough concurrent data file for image:" + Environment.NewLine +
currImgFilename + Environment.NewLine + "closest concurrent data file is:" +
Environment.NewLine + nearestConcurrentData.filename + Environment.NewLine +
"with date-time value " + nearestConcurrentData.datetimeUTC.ToString("o");
Console.WriteLine(strError);
nearestConcurrentData = null;
}
ipdt.concurrentData = nearestConcurrentData;
if (nearestConcurrentData != null)
{
ipdt.concurrentDataXMLfile = nearestConcurrentData.filename;
}
return(ipdt);
});
#endregion mapping
removed = lStatsProcessing.RemoveAll(ipdt => ipdt.concurrentData == null);
Console.WriteLine("removed " + removed + " items (couldn`t find concurrent data). " + lStatsProcessing.Count + " files remains to process.");
#endregion list, read and map concurrent data
}
if (!lStatsProcessing.Any())
{
Console.WriteLine("There is no files that sutisfy settings specified and have all required concurrent data (stats or GPS etc.). Processing will not be proceeded.");
return;
}
#region Filter by SDC values predicting it using pre-trained NN parameters
#region //
//string csvHeader = lStatsProcessing[0].grixyrgbStats.CSVHeader() +
// ",SunElevationDeg,SunAzimuthDeg,sunDiskCondition";
//List<string> lCSVheader = csvHeader.Split(',').ToList();
//List<int> columnsToDelete =
// lCSVheader.Select((str, idx) => new Tuple<int, string>(idx, str))
// .Where(tpl => tpl.Item2.ToLower().Contains("filename")).ToList().ConvertAll(tpl => tpl.Item1);
//List<List<string>> lCalculatedData = lStatsProcessing.ConvertAll(dt =>
//{
// string currImageALLstatsDataCSVWithConcurrentData = dt.grixyrgbStats.ToCSV() + "," +
// dt.concurrentData.gps.SunZenithAzimuth()
// .ElevationAngle.ToString()
// .Replace(",", ".") + "," +
// dt.concurrentData.gps.SunZenithAzimuth()
// .Azimuth.ToString()
// .Replace(",", ".");
// List<string> retVal = currImageALLstatsDataCSVWithConcurrentData.Split(',').ToList();
// retVal = retVal.Where((str, idx) => !columnsToDelete.Contains(idx)).ToList();
// return retVal;
//});
//List<DenseVector> lDV_objects_features =
// lCalculatedData.ConvertAll(
// list =>
// DenseVector.OfEnumerable(list.ConvertAll<double>(str => Convert.ToDouble(str.Replace(".", ",")))));
#endregion
DenseVector dvMeans = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormMeansFile, 0, ",")).Row(0);
DenseVector dvRanges = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormRangeFile, 0, ",")).Row(0);
#region //
//lDV_objects_features = lDV_objects_features.ConvertAll(dv =>
//{
// DenseVector dvShifted = dv - dvMeans;
// DenseVector dvNormed = (DenseVector)dvShifted.PointwiseDivide(dvRanges);
// return dvNormed;
//});
//DenseMatrix dmObjectsFeatures = DenseMatrix.OfRowVectors(lDV_objects_features);
#endregion
DenseVector dvThetaValues = (DenseVector)ServiceTools.ReadDataFromCSV(NNtrainedParametersFile, 0, ",");
List <int> NNlayersConfig =
new List <double>(((DenseMatrix)ServiceTools.ReadDataFromCSV(NNconfigFile, 0, ",")).Row(0)).ConvertAll
(dVal => Convert.ToInt32(dVal));
#region //
// List<List<double>> lDecisionProbabilities = null;
#endregion
List <Tuple <ImagesProcessingData, List <SDCdecisionProbability>, SunDiskCondition> > lTplsPredictedSDClist =
new List <Tuple <ImagesProcessingData, List <SDCdecisionProbability>, SunDiskCondition> >();
List <List <double> > SDCdecisionProbabilitiesListDoubles = new List <List <double> >();
List <SunDiskCondition> imagesSDCpredicted = SDCpredictorNN.PredictSDC_NN(lStatsProcessing, NNlayersConfig,
dvThetaValues, dvMeans, dvRanges, out SDCdecisionProbabilitiesListDoubles);
List <List <SDCdecisionProbability> > SDCdecisionProbabilitiesLists =
SDCdecisionProbabilitiesListDoubles.ConvertAll(
currSDCdecisionProbabilities =>
currSDCdecisionProbabilities.Select((dProb, idx) => new SDCdecisionProbability()
{
sdc = SunDiskConditionData.MatlabSDCenum(idx + 1),
sdcDecisionProbability = dProb
}).ToList());
lTplsPredictedSDClist =
lStatsProcessing.Zip(
SDCdecisionProbabilitiesLists.Zip(imagesSDCpredicted,
(lDecProb, sdcPredicted) =>
new Tuple <List <SDCdecisionProbability>, SunDiskCondition>(lDecProb, sdcPredicted)).ToList(),
(ipd, tpl) =>
new Tuple <ImagesProcessingData, List <SDCdecisionProbability>, SunDiskCondition>(ipd, tpl.Item1,
tpl.Item2)).ToList();
#region //
//foreach (ImagesProcessingData dt in lStatsProcessing)
//{
// List<double> currSDCdecisionProbabilities = new List<double>();
// SunDiskCondition currSDC = SDCpredictorNN.PredictSDC_NN(dt.grixyrgbStats, dt.concurrentData,
// NNlayersConfig, dvThetaValues, dvMeans, dvRanges, out currSDCdecisionProbabilities);
// List<SDCdecisionProbability> currSDCdecisionProbabilitiesList = currSDCdecisionProbabilities.Select((dProb, idx) => new SDCdecisionProbability()
// {
// sdc = SunDiskConditionData.MatlabSDCenum(idx + 1),
// sdcDecisionProbability = dProb
// }).ToList();
// lTplsPredictedSDClist.Add(
// new Tuple<ImagesProcessingData, List<SDCdecisionProbability>, SunDiskCondition>(dt,
// currSDCdecisionProbabilitiesList, currSDC));
//}
#endregion
#region //
//List<int> predictedSDC =
// NNclassificatorPredictor.NNpredict(dmObjectsFeatures, dvThetaValues, NNlayersConfig,
// out lDecisionProbabilities).ToList();
//List<SunDiskCondition> predictedSDClist = predictedSDC.ConvertAll(sdcInt =>
//{
// switch (sdcInt)
// {
// case 4:
// return SunDiskCondition.NoSun;
// break;
// case 1:
// return SunDiskCondition.Sun0;
// break;
// case 2:
// return SunDiskCondition.Sun1;
// break;
// case 3:
// return SunDiskCondition.Sun2;
// break;
// default:
// return SunDiskCondition.Defect;
// }
//});
//List<Tuple<ImagesProcessingData, SunDiskCondition>> lTplsPredictedSDClist =
// predictedSDClist.Zip(lStatsProcessing,
// (sdc, ipd) => new Tuple<ImagesProcessingData, SunDiskCondition>(ipd, sdc)).ToList();
#endregion
#region output obtained SDC data to log file
string strToShow = "SDC values probabilities: " + Environment.NewLine +
"| NoSun | Sun0 | Sun1 | Sun2 |" + Environment.NewLine;
foreach (Tuple <ImagesProcessingData, List <SDCdecisionProbability>, SunDiskCondition> tpl in lTplsPredictedSDClist)
{
List <SDCdecisionProbability> currSDCdecisionProbabilitiesList = tpl.Item2;
strToShow += "|" +
String.Format("{0,9}",
(currSDCdecisionProbabilitiesList.First(
prob => prob.sdc == SunDiskCondition.NoSun).sdcDecisionProbability * 100.0d)
.ToString("F2") + "%") + "|" +
String.Format("{0,9}",
(currSDCdecisionProbabilitiesList.First(
prob => prob.sdc == SunDiskCondition.Sun0).sdcDecisionProbability * 100.0d)
.ToString("F2") + "%") + "|" +
String.Format("{0,9}",
(currSDCdecisionProbabilitiesList.First(
prob => prob.sdc == SunDiskCondition.Sun1).sdcDecisionProbability * 100.0d)
.ToString("F2") + "%") + "|" +
String.Format("{0,9}",
(currSDCdecisionProbabilitiesList.First(
prob => prob.sdc == SunDiskCondition.Sun2).sdcDecisionProbability * 100.0d)
.ToString("F2") + "%") + "|" + Environment.NewLine;
}
ServiceTools.logToTextFile(errorLogFilename, strToShow, true, false);
#endregion output obtained SDC data to log file
#region filter by SDC value if needed
if (sdcFilter != SunDiskCondition.Undefined)
{
lStatsProcessing = lStatsProcessing.Where((ipd, idx) => lTplsPredictedSDClist[idx].Item3 == sdcFilter).ToList();
Console.WriteLine("Detected " + lStatsProcessing.Count + " images with SDC = " + sdcFilter.ToString());
}
#endregion filter by SDC value if needed
#endregion Filter by SDC values predicting it using pre-trained NN parameters
#region ObservedCloudCoverDataCSVfile
if (bFilterByObservedCloudCoverRecords)
{
Console.WriteLine("Reading observed cloud cover data CSV file...");
if (!File.Exists(ObservedCloudCoverDataCSVfile))
{
Console.WriteLine("Unable to read observed data CSV file: " + ObservedCloudCoverDataCSVfile);
return;
}
List <List <string> > lCSVfileContents = ServiceTools.ReadDataFromCSV(ObservedCloudCoverDataCSVfile, 1,
true);
if (!lCSVfileContents.Any())
{
Console.WriteLine("The observed cloud cover CSV file seems to be empty: " +
ObservedCloudCoverDataCSVfile);
return;
}
List <ObservedClCoverData> lObservedData =
lCSVfileContents.ConvertAll(lStr => new ObservedClCoverData(lStr));
List <SkyImagesDataWith_Concurrent_Stats_CloudCover_SDC> lImagesFilteredByAvailableObservedData =
new List <SkyImagesDataWith_Concurrent_Stats_CloudCover_SDC>();
#region filter images by available observed data using DateTimeFilterTolerance
Console.WriteLine("Filtering by observed data available...");
foreach (ObservedClCoverData observedData in lObservedData)
{
DateTime currObservedDatumDateTime = observedData.dt;
List <SkyImagesDataWith_Concurrent_Stats_CloudCover_SDC> lImagesCloseToCurrObservedDatum = lStatsProcessing
.Where(ipd =>
{
TimeSpan tspan =
new TimeSpan(
Math.Abs(
(ConventionalTransitions.DateTimeOfSkyImageFilename(ipd.filename) -
currObservedDatumDateTime).Ticks));
return(tspan <= DateTimeFilterTolerance);
})
.ToList()
.ConvertAll(ifd => new SkyImagesDataWith_Concurrent_Stats_CloudCover_SDC()
{
// observedData
// ifd
skyImageFullFileName = ifd.filename,
skyImageFileName = Path.GetFileName(ifd.filename),
currImageDateTime = ConventionalTransitions.DateTimeOfSkyImageFilename(ifd.filename),
observedCloudCoverData = observedData,
concurrentDataXMLfile = ifd.concurrentDataXMLfile,
concurrentData = ifd.concurrentData,
grixyrgbStatsXMLfile = ifd.grixyrgbStatsXMLfile,
grixyrgbStats = ifd.grixyrgbStats,
SDCvalue = lTplsPredictedSDClist.First(tpl => tpl.Item1 == ifd).Item3,
SDCprobabilities = lTplsPredictedSDClist.First(tpl => tpl.Item1 == ifd).Item2
});
lImagesFilteredByAvailableObservedData.AddRange(lImagesCloseToCurrObservedDatum);
}
#endregion filter images by available observed data using DateTimeFilterTolerance
if (!lImagesFilteredByAvailableObservedData.Any())
{
Console.WriteLine(
"There is no images remain after filtering using all available data. Output will be empty.");
}
ServiceTools.WriteObjectToXML(lImagesFilteredByAvailableObservedData, outputDataFile);
#region Сформируем и запишем данные в CSV-файл
// Здесь есть данные по наблюдаемому CloudCover
string csvHeader = lImagesFilteredByAvailableObservedData[0].grixyrgbStats.CSVHeader() +
",SunElevationDeg,SunAzimuthDeg,ObservedTotalCloudCover,ObservedLowerCloudCover,SDC,SDCprobabilityNoSun,SDCprobabilitySun0,SDCprobabilitySun1,SDCprobabilitySun2";
List <string> lCSVoutputData = lImagesFilteredByAvailableObservedData.ConvertAll(ifd =>
{
// все стат. предикторы - как для SDC
// данные CloudCover
string retVal = "";
//ImagesProcessingData dt = tpl.Item2;
//ObservedClCoverData clCov = tpl.Item1;
retVal = ifd.grixyrgbStats.ToCSV() + "," +
ifd.concurrentData.gps.SunZenithAzimuth().ElevationAngle.ToString().Replace(",", ".") + "," +
ifd.concurrentData.gps.SunZenithAzimuth().Azimuth.ToString().Replace(",", ".") + "," +
ifd.observedCloudCoverData.CloudCoverTotal.ToString() + "," +
ifd.observedCloudCoverData.CloudCoverLower.ToString() + "," +
ifd.SDCvalue.ToString() + "," +
ifd.SDCprobabilities.First(prob => prob.sdc == SunDiskCondition.NoSun)
.sdcDecisionProbability.ToString().Replace(",", ".") + "," +
ifd.SDCprobabilities.First(prob => prob.sdc == SunDiskCondition.Sun0)
.sdcDecisionProbability.ToString().Replace(",", ".") + "," +
ifd.SDCprobabilities.First(prob => prob.sdc == SunDiskCondition.Sun1)
.sdcDecisionProbability.ToString().Replace(",", ".") + "," +
ifd.SDCprobabilities.First(prob => prob.sdc == SunDiskCondition.Sun2)
.sdcDecisionProbability.ToString().Replace(",", ".");
return(retVal);
});
string strToOutputToCSVfile = string.Join(Environment.NewLine, lCSVoutputData);
ServiceTools.logToTextFile(outputCSVfile, csvHeader + Environment.NewLine, true, false);
ServiceTools.logToTextFile(outputCSVfile, strToOutputToCSVfile, true, false);
#endregion Сформируем и запишем данные в CSV-файл
}
else
{
ServiceTools.WriteObjectToXML(lStatsProcessing, outputDataFile);
#region Сформируем и запишем данные в CSV-файл
// здесь нет данных по наблюдаемому Cloud Cover
// не надо нам такое. Оставим все это только в виде XML-файла.
#endregion Сформируем и запишем данные в CSV-файл
}
#endregion ObservedCloudCoverDataCSVfile
#endregion Enumerating files and output to XML and CSV file
Console.WriteLine("saved output data to file: " + Environment.NewLine + outputDataFile + Environment.NewLine +
Environment.NewLine);
Console.WriteLine("===FINISHED===");
Console.ReadKey();
}
private async Task <string> ObtainLatestMeteoParameters()
{
string retStr = "";
// WSLufftUMBappPath
// Date time ; Temperature [°C] ; Abs. air pressure [hPa] ; Relative humidity [%] ; Abs. humidity [g/m³]
if (Directory.Exists(WSLufftUMBappPath))
{
List <FileInfo> lTXTdataFilesInfoList =
((new DirectoryInfo(WSLufftUMBappPath)).GetFiles("????-??-??Values.Txt",
SearchOption.AllDirectories)).ToList();
lTXTdataFilesInfoList.Sort((finfo1, finfo2) => finfo1.CreationTimeUtc.CompareTo(finfo2.CreationTimeUtc));
FileInfo lastTXTdataFileInfo = lTXTdataFilesInfoList.Last();
List <List <string> > Contents = ServiceTools.ReadDataFromCSV(lastTXTdataFileInfo.FullName, 2, true, ";");
List <string> lastWSdataStrings = Contents.Last();
retStr +=
"WS:" + Environment.NewLine +
"Date time: " + lastWSdataStrings[0] + Environment.NewLine +
"Temperature [°C]: " + lastWSdataStrings[1] + Environment.NewLine +
"Abs. air pressure [hPa]: " + lastWSdataStrings[2] + Environment.NewLine +
"Relative humidity [%]: " + lastWSdataStrings[3] + Environment.NewLine +
"Abs. humidity [g/m³]" + lastWSdataStrings[4] + Environment.NewLine + Environment.NewLine;
// retStr += string.Join(" ; ", Contents.Last()) + Environment.NewLine;
}
// R2SLufftUMBappPath
if (Directory.Exists(R2SLufftUMBappPath))
{
List <FileInfo> lTXTdataFilesInfoList =
((new DirectoryInfo(R2SLufftUMBappPath)).GetFiles("????-??-??Values.Txt",
SearchOption.AllDirectories)).ToList();
lTXTdataFilesInfoList.Sort((finfo1, finfo2) => finfo1.CreationTimeUtc.CompareTo(finfo2.CreationTimeUtc));
FileInfo lastTXTdataFileInfo = lTXTdataFilesInfoList.Last();
List <List <string> > Contents = ServiceTools.ReadDataFromCSV(lastTXTdataFileInfo.FullName, 2, true, ";");
List <string> lastR2SdataStrings = Contents.Last();
retStr +=
"R2S:" + Environment.NewLine +
"Date,time:" + lastR2SdataStrings[0] + Environment.NewLine +
"Precipitation absol. [mm]: " + lastR2SdataStrings[1] + Environment.NewLine +
"Precipitation type: " + lastR2SdataStrings[2] + Environment.NewLine +
"Ambient temperature [°C]" + lastR2SdataStrings[3] + Environment.NewLine +
"Precipitat.intensity [mil/h]: " + lastR2SdataStrings[4] + Environment.NewLine + Environment.NewLine;
//retStr += string.Join(" ; ", Contents.Last()) + Environment.NewLine;
}
// VentusLufftUMBappPath
// Date time ; Virtual temperature [°C] ; Wind speed [m/s] ; Wind speed [m/s] Vect. ; Wind direction [°] ; Wind direction [°] Vect. ; Abs. air pressure [hPa] ; Wind value quality [%]
if (Directory.Exists(VentusLufftUMBappPath))
{
List <FileInfo> lTXTdataFilesInfoList =
((new DirectoryInfo(VentusLufftUMBappPath)).GetFiles("????-??-??Values.Txt",
SearchOption.AllDirectories)).ToList();
lTXTdataFilesInfoList.Sort((finfo1, finfo2) => finfo1.CreationTimeUtc.CompareTo(finfo2.CreationTimeUtc));
FileInfo lastTXTdataFileInfo = lTXTdataFilesInfoList.Last();
List <List <string> > Contents = ServiceTools.ReadDataFromCSV(lastTXTdataFileInfo.FullName, 2, true, ";");
List <string> lastVentusdataStrings = Contents.Last();
retStr +=
"Ventus:" + Environment.NewLine +
"Date,time: " + lastVentusdataStrings[0] + Environment.NewLine +
"Virtual temperature [°C]: " + lastVentusdataStrings[1] + Environment.NewLine +
"Wind speed [m/s]: " + lastVentusdataStrings[2] + Environment.NewLine +
"Wind speed [m/s] Vect.:" + lastVentusdataStrings[3] + Environment.NewLine +
"Wind direction [°]: " + lastVentusdataStrings[4] + Environment.NewLine +
"Wind direction [°] Vect.: " + lastVentusdataStrings[5] + Environment.NewLine +
"Abs. air pressure [hPa]: " + lastVentusdataStrings[6] + Environment.NewLine +
"Wind value quality [%]: " + lastVentusdataStrings[7] + Environment.NewLine + Environment.NewLine;
//retStr += string.Join(" ; ", Contents.Last()) + Environment.NewLine;
}
return(retStr);
}
private void CurrFileProcessing(ImagesConvertingData dat)
{
string currentFullFileName = dat.filename;
try
{
List <List <string> > csvFileContents = ServiceTools.ReadDataFromCSV(currentFullFileName, 3, true, ";", Environment.NewLine);
List <double> lCenterXValues = csvFileContents.ConvertAll <double>(lStr => Convert.ToDouble(lStr[1]));
List <double> lCenterYValues = csvFileContents.ConvertAll <double>(lStr => Convert.ToDouble(lStr[2]));
List <double> lRadiiValues = csvFileContents.ConvertAll <double>(lStr => Convert.ToDouble(lStr[3]));
// filter default values
// filteringMarks = "те, которые оставляем"
List <bool> filteringMarks = csvFileContents.ConvertAll <bool>(lStr => true);
if (filterDefaultDoubleValueCenterX > 0.0d)
{
List <bool> filteringMarksAdd = lCenterXValues.ConvertAll <bool>(dVal => dVal != filterDefaultDoubleValueCenterX);
filteringMarks =
(filteringMarks.Zip <bool, bool, bool>(filteringMarksAdd, (bVal1, bVal2) => bVal1 && bVal2))
.ToList();
}
if (filterDefaultDoubleValueCenterY > 0.0d)
{
List <bool> filteringMarksAdd = lCenterYValues.ConvertAll <bool>(dVal => dVal != filterDefaultDoubleValueCenterY);
filteringMarks =
(filteringMarks.Zip <bool, bool, bool>(filteringMarksAdd, (bVal1, bVal2) => bVal1 && bVal2))
.ToList();
}
if (filterDefaultDoubleValueRadius > 0.0d)
{
List <bool> filteringMarksAdd = lRadiiValues.ConvertAll <bool>(dVal => dVal != filterDefaultDoubleValueRadius);
filteringMarks =
(filteringMarks.Zip <bool, bool, bool>(filteringMarksAdd, (bVal1, bVal2) => bVal1 && bVal2))
.ToList();
}
List <int> indexes =
filteringMarks
.Select((val, idx) => new { val, idx })
.Where(x => x.val)
.Select(x => x.idx)
.ToList();
lCenterXValues = lCenterXValues
.Select((dVal, idx) => new { dVal, idx })
.Where(x => indexes.Contains(x.idx))
.Select(x => x.dVal).ToList();
lCenterYValues = lCenterYValues
.Select((dVal, idx) => new { dVal, idx })
.Where(x => indexes.Contains(x.idx))
.Select(x => x.dVal).ToList();
lRadiiValues = lRadiiValues
.Select((dVal, idx) => new { dVal, idx })
.Where(x => indexes.Contains(x.idx))
.Select(x => x.dVal).ToList();
DescriptiveStatistics stats = new DescriptiveStatistics(lCenterXValues, true);
double dCenterXvalue = stats.Mean;
stats = new DescriptiveStatistics(lCenterYValues, true);
double dCenterYvalue = stats.Mean;
stats = new DescriptiveStatistics(lRadiiValues, true);
double dRadiusvalue = stats.Mean;
RoundData rd = new RoundData(dCenterXvalue, dCenterYvalue, dRadiusvalue);
string xmlFilename = Path.GetDirectoryName(currentFullFileName);
xmlFilename += (xmlFilename.Last() == Path.DirectorySeparatorChar)
? ("")
: (Path.DirectorySeparatorChar.ToString());
xmlFilename += Path.GetFileNameWithoutExtension(currentFullFileName) + "-RoundImagemask.xml";
ServiceTools.WriteObjectToXML(rd, xmlFilename);
Console.WriteLine("finished processing file " + Environment.NewLine + currentFullFileName);
}
catch (Exception ex)
{
#region report
#if DEBUG
Console.WriteLine("exception has been thrown: " + ex.Message + Environment.NewLine +
ServiceTools.CurrentCodeLineDescription());
#else
ServiceTools.logToTextFile(errorLogFilename,
"exception has been thrown: " + ex.Message + Environment.NewLine +
ServiceTools.CurrentCodeLineDescription(), true, true);
#endif
#endregion report
}
}
public void Start(string[] args)
{
readDefaultProperties();
List <string> argsList = new List <string>(args);
string filename = argsList.Last();
if (!File.Exists(filename))
{
Console.WriteLine("Couldn`t find input file \"" + filename + "\"");
return;
}
CommonTools.PrintDictionaryToConsole(defaultProperties,
"Default settings specified in file \"" + defaultPropertiesXMLfileName + "\"");
if (!File.Exists(NNconfigFile) || !File.Exists(NNtrainedParametersFile) || !File.Exists(NormMeansFile) || !File.Exists(NormRangeFile))
{
Console.WriteLine(
"couldn`t find at least one of pre-calculated NN parameters file specified in settings: ");
return;
}
List <List <string> > csvFileContentStrings = ServiceTools.ReadDataFromCSV(filename, 0, true, ",");
List <string> csvFileHeader = csvFileContentStrings[0];
csvFileContentStrings = csvFileContentStrings.Where((list, idx) => idx > 0).ToList();
List <int> columnsToDelete =
csvFileHeader.Select((str, idx) => new Tuple <int, string>(idx, str))
.Where(tpl => tpl.Item2.ToLower().Contains("filename")).ToList().ConvertAll(tpl => tpl.Item1);
List <List <string> > csvFileContentStringsFiltered = new List <List <string> >();
foreach (List <string> listDataStrings in csvFileContentStrings)
{
csvFileContentStringsFiltered.Add(
listDataStrings.Where((str, idx) => !columnsToDelete.Contains(idx)).ToList());
}
List <SunDiskCondition> trueAnswers =
csvFileContentStringsFiltered.ConvertAll(
lstr => (SunDiskCondition)Enum.Parse(typeof(SunDiskCondition), lstr.Last()));
//List<int> trueAnswersInt = trueAnswers.ConvertAll(sdc => SunDiskConditionData.MatlabNumeralSDC(sdc));
List <List <string> > csvFileContentStringsFiltered_wo_sdc =
csvFileContentStringsFiltered.ConvertAll(list => list.Where((val, idx) => idx < list.Count - 1).ToList());
List <DenseVector> lDV_objects_features =
csvFileContentStringsFiltered_wo_sdc.ConvertAll(
list =>
DenseVector.OfEnumerable(list.ConvertAll <double>(str => Convert.ToDouble(str.Replace(".", ",")))));
DenseVector dvMeans = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormMeansFile, 0, ",")).Row(0);
DenseVector dvRanges = (DenseVector)((DenseMatrix)ServiceTools.ReadDataFromCSV(NormRangeFile, 0, ",")).Row(0);
lDV_objects_features = lDV_objects_features.ConvertAll(dv =>
{
DenseVector dvShifted = dv - dvMeans;
DenseVector dvNormed = (DenseVector)dvShifted.PointwiseDivide(dvRanges);
return(dvNormed);
});
DenseMatrix dmObjectsFeatures = DenseMatrix.OfRowVectors(lDV_objects_features);
DenseVector dvThetaValues = (DenseVector)ServiceTools.ReadDataFromCSV(NNtrainedParametersFile, 0, ",");
List <int> NNlayersConfig =
new List <double>(((DenseMatrix)ServiceTools.ReadDataFromCSV(NNconfigFile, 0, ",")).Row(0)).ConvertAll
(dVal => Convert.ToInt32(dVal));
List <SunDiskCondition> predictedSDC =
NNclassificatorPredictor <SunDiskCondition> .NNpredict(dmObjectsFeatures, dvThetaValues, NNlayersConfig,
SunDiskConditionData.MatlabEnumeratedSDCorderedList()).ToList();
List <Tuple <SunDiskCondition, SunDiskCondition> > PredictedVStrue = predictedSDC.Zip(trueAnswers,
(predVal, trueVal) => new Tuple <SunDiskCondition, SunDiskCondition>(predVal, trueVal)).ToList();
Console.WriteLine("=== Prediction result vs true ===");
foreach (Tuple <SunDiskCondition, SunDiskCondition> tpl in PredictedVStrue)
{
Console.WriteLine("pred: " + tpl.Item1.ToString() + ":" + tpl.Item2.ToString() + " :true");
}
double accuracy = 100.0d * ((double)PredictedVStrue.Count(tpl => tpl.Item1 == tpl.Item2)) /
(double)PredictedVStrue.Count();
Console.WriteLine("accuracy: " + accuracy);
Console.WriteLine("Finished. Press any key...");
Console.ReadKey();
}
private void btnCreateList_Click(object sender, EventArgs e)
{
theLogWindow = ServiceTools.LogAText(theLogWindow, "Started processing...");
BackgroundWorker bgwCreateList = new BackgroundWorker();
bgwCreateList.DoWork += (bgwSender, bgwArgs) =>
{
List <ImageFileDescription> lImagesFilesList = new List <ImageFileDescription>();
List <ImagesProcessingData> lImagesAllConcurrentData = new List <ImagesProcessingData>();
List <ObservedClCoverData> lObservedData = new List <ObservedClCoverData>();
#region check available data
//ImagesBaseSourcePath = "";
//ConcurrentAndStatsXMLfilesDir = "";
//ObservedDataCSVfile = "";
//DestinationPath = "";
//DateTimeFilterTolerance = new TimeSpan(0, 5, 0);
#region ImagesBaseSourcePath
theLogWindow = ServiceTools.LogAText(theLogWindow, "Started enumerating images...");
if (!Directory.Exists(ImagesBaseSourcePath))
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to find sky-images base source path. Please check if it does exist and contain at least one sky-image *.jpg file.");
FINISHED();
return;
}
lImagesFilesList =
Directory.GetFiles(ImagesBaseSourcePath, "*.jpg", SearchOption.AllDirectories)
.ToList()
.ConvertAll(str => new ImageFileDescription(str));
if (!lImagesFilesList.Any())
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to find any sky-images. Please check if at least one sky-image exists in base source path.");
FINISHED();
return;
}
#endregion ImagesBaseSourcePath
#region ConcurrentAndStatsXMLfilesDir
theLogWindow = ServiceTools.LogAText(theLogWindow, "Started reading concurrent data and stats data using existing XML files...");
if (!Directory.Exists(ConcurrentAndStatsXMLfilesDir))
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to find sky-images pre-calculated concurrent data XML files directory: " +
Environment.NewLine + ConcurrentAndStatsXMLfilesDir + Environment.NewLine +
". Please check if it does exist.");
FINISHED();
return;
}
#region read all concurrent data using all-included XML files
List <string> lXMLfiles =
Directory.GetFiles(ConcurrentAndStatsXMLfilesDir, "ImagesCameraPositioning-stats-*-camID?.xml", SearchOption.AllDirectories).ToList();
if (!lXMLfiles.Any())
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to find any XML file satisfied the following mask: \"ImagesCameraPositioning-stats-*-camID?.xml\". Please check if at least one XML of that kind does exist in directory " +
ConcurrentAndStatsXMLfilesDir);
FINISHED();
return;
}
foreach (string xmlFile in lXMLfiles)
{
theLogWindow = ServiceTools.LogAText(theLogWindow, "trying to read and parse file " + xmlFile);
try
{
List <ImagesProcessingData> currFileContents =
ServiceTools.ReadObjectFromXML(xmlFile, typeof(List <ImagesProcessingData>)) as
List <ImagesProcessingData>;
if (currFileContents != null)
{
lImagesAllConcurrentData.AddRange(currFileContents);
}
}
catch (Exception ex)
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"ERROR! Unable to read data from file: " + xmlFile + Environment.NewLine + ex.Message);
continue;
}
}
if (!lImagesAllConcurrentData.Any())
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to read any concurrent data. Please check the directory for files containing valid concurrent data XML files: " + Environment.NewLine +
"directory: " + ConcurrentAndStatsXMLfilesDir + Environment.NewLine +
"XML files mask: \"ImagesCameraPositioning-stats-*-camID?.xml\"");
FINISHED();
return;
}
#endregion read all concurrent data using all-included XML files
#endregion ConcurrentAndStatsXMLfilesDir
#region ObservedDataCSVfile
theLogWindow = ServiceTools.LogAText(theLogWindow, "Started reading observed data CSV file...");
if (!File.Exists(ObservedDataCSVfile))
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to read observed data CSV file: " + ObservedDataCSVfile);
FINISHED();
return;
}
List <List <string> > lCSVfileContents = ServiceTools.ReadDataFromCSV(ObservedDataCSVfile, 1, true);
if (!lCSVfileContents.Any())
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to read observed data CSV file: " + ObservedDataCSVfile);
FINISHED();
return;
}
lObservedData = lCSVfileContents.ConvertAll(lStr => new ObservedClCoverData(lStr));
#endregion ObservedDataCSVfile
#region DestinationPath
if (!Directory.Exists(DestinationPath))
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"Unable to find the output directory: " + DestinationPath);
FINISHED();
return;
}
#endregion DestinationPath
#endregion check available data
List <Tuple <ObservedClCoverData, ImageFileDescription> > lImagesFilteredByAvailableObservedData =
new List <Tuple <ObservedClCoverData, ImageFileDescription> >();
#region filter images by available observed data using DateTimeFilterTolerance
theLogWindow = ServiceTools.LogAText(theLogWindow, "Filtering by observed data available...");
foreach (ObservedClCoverData observedData in lObservedData)
{
DateTime currObservedDatumDateTime = observedData.dt;
List <Tuple <ObservedClCoverData, ImageFileDescription> > lImagesCloseToCurrObservedDatum = lImagesFilesList
.Where(ifd =>
{
TimeSpan tspan =
new TimeSpan(Math.Abs((ifd.currImageDateTime - currObservedDatumDateTime).Ticks));
return(tspan <= DateTimeFilterTolerance);
})
.ToList()
.ConvertAll(ifd => new Tuple <ObservedClCoverData, ImageFileDescription>(observedData, ifd));
lImagesFilteredByAvailableObservedData.AddRange(lImagesCloseToCurrObservedDatum);
}
#endregion filter images by available observed data using DateTimeFilterTolerance
List <SkyImagesDataWith_Concurrent_Stats_CloudCover> lImagesFilteredByAnyAvailableData =
new List <SkyImagesDataWith_Concurrent_Stats_CloudCover>();
#region map available stats data using image filename
theLogWindow = ServiceTools.LogAText(theLogWindow, "Mapping concurrent and stats data...");
lImagesFilteredByAnyAvailableData = lImagesFilteredByAvailableObservedData.ConvertAll(tpl =>
{
SkyImagesDataWith_Concurrent_Stats_CloudCover retVal = null;
try
{
ImagesProcessingData foundConcurrentData =
lImagesAllConcurrentData.Where(ipd => Path.GetFileName(ipd.filename) == tpl.Item2.fileName)
.ElementAt(0);
retVal = new SkyImagesDataWith_Concurrent_Stats_CloudCover()
{
skyImageFullFileName = tpl.Item2.fullFileName,
skyImageFileName = tpl.Item2.fileName,
currImageDateTime = tpl.Item2.currImageDateTime,
observedCloudCoverData = tpl.Item1,
concurrentDataXMLfile = foundConcurrentData.concurrentDataXMLfile,
concurrentData = foundConcurrentData.concurrentData,
grixyrgbStatsXMLfile = foundConcurrentData.grixyrgbStatsXMLfile,
grixyrgbStats = foundConcurrentData.grixyrgbStats
};
//(tpl.Item1, tpl.Item2, foundConcurrentData);
}
catch (Exception ex)
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"ERROR! Couldn`t find concurrent data for file " + Path.GetFileName(tpl.Item2.fileName) +
Environment.NewLine + ex.Message);
}
return(retVal);
});
lImagesFilteredByAnyAvailableData.RemoveAll(tpl => tpl == null);
if (!lImagesFilteredByAnyAvailableData.Any())
{
theLogWindow = ServiceTools.LogAText(theLogWindow,
"There is no images remain after filtering using all available data. Output will be empty.");
}
#endregion map available stats data using image filename
theLogWindow = ServiceTools.LogAText(theLogWindow, "Writing output list to file...");
string strOutputXMLfileName = DestinationPath +
((DestinationPath.Last() == Path.DirectorySeparatorChar)
? ("")
: (Path.DirectorySeparatorChar.ToString())) + "FilesListToDetectCloudCover.xml";
ServiceTools.WriteObjectToXML(lImagesFilteredByAnyAvailableData, strOutputXMLfileName);
theLogWindow = ServiceTools.LogAText(theLogWindow, "images list wrote to file: " + strOutputXMLfileName);
};
bgwCreateList.RunWorkerAsync();
}