private static MLCell CreateCellArrayCustom(string name, string[] items)
{
var cell = new MLCell(name, new int[] { items.Length, 1 });
int i = 0;
foreach (var item in items)
{
double ans = 0;
if (double.TryParse(items[i], out ans))
{
cell[i] = new MLDouble(null, new double[] { ans }, 1);
i++;
continue;
}
if (items[i].TrimStart().StartsWith("[") && items[i].TrimEnd().EndsWith("]"))
{
cell[i] = CreateCellArrayCustom("",
items[i].Split(new[] { ' ', '[', ']' }, StringSplitOptions.RemoveEmptyEntries));
i++;
continue;
}
cell[i] = new MLChar(null, (string)items[i].Trim());
i++;
}
return(cell);
}
private static MLArray CreateCellArray(string name, string[] names)
{
MLCell cell = new MLCell(name, new int[] {names.Length, 1});
for (int i = 0; i < names.Length; i++)
cell[i] = new MLChar(null, names[i]);
return cell;
}
static void DoWrite(string fn, Dictionary <string, MatLab.DoubleList> data, Dictionary <string, List <MLCell> > dataCell, SortedDictionary <string, double> param,
List <MLArray> mlList, Hashtable seen)
{
log.Info("DoWrite start " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
foreach (var item in data)
{
double[][] temp = item.Value.ToArray();
MLArray dbarray = new MLDouble(item.Key, temp);
mlList.Add(dbarray);
log.Info("DoWrite Double " + item.Key + " " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
}
// datacell contains rows
foreach (var item in dataCell)
{
// create msg table
MLCell temp1 = new MLCell(item.Key + "1", new int[] { 1, item.Value.Count });
int a = 0;
// add rows to msg table
foreach (var mlCell in item.Value)
{
temp1[a] = item.Value[a];
a++;
}
// add table to masterlist
mlList.Add(temp1);
log.Info("DoWrite Cell " + item.Key + " " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
}
log.Info("DoWrite mllist " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
MLCell cell = new MLCell("PARM", new int[] { param.Keys.Count, 2 });
int m = 0;
foreach (var item in param.Keys)
{
cell[m, 0] = new MLChar(null, item.ToString());
cell[m, 1] = new MLDouble(null, new double[] { (double)param[item] }, 1);
m++;
}
mlList.Add(cell);
MLArray seenmsg = CreateCellArray("Seen", seen.Keys.Cast <string>().ToArray());
mlList.Add(seenmsg);
try
{
log.Info("write " + fn + ".mat");
log.Info("DoWrite before" + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
MatFileWriter mfw = new MatFileWriter(fn + ".mat", mlList, false);
log.Info("DoWrite done" + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
}
catch (Exception err)
{
throw new Exception("There was an error when creating the MAT-file: \n" + err.ToString(), err);
}
}
private static MLArray CreateCellArray()
{
string[] names = new string[] { "Hello", "World", "I am", "a", "MAT-file" };
MLCell cell = new MLCell("Names", new int[] { names.Length, 1 });
for (int i = 0; i < names.Length; i++)
cell[i] = new MLChar(null, names[i]);
return cell;
}
private static MLArray CreateCellArray(string name, string[] names)
{
MLCell cell = new MLCell(name, new int[] { names.Length, 1 });
for (int i = 0; i < names.Length; i++)
{
cell[i] = new MLChar(null, names[i]);
}
return(cell);
}
static MLArray CreateCellArray()
{
var names = new[] { "Hello", "World", "I am", "a", "MAT-file" };
var cell = new MLCell("Names", new[] { names.Length, 1 });
for (var i = 0; i < names.Length; i++)
{
cell[i] = new MLChar(null, names[i]);
}
return(cell);
}
private static MLArray CreateCellArray()
{
string[] names = new string[] { "Hello", "World", "I am", "a", "MAT-file" };
MLCell cell = new MLCell("Names", new int[] { names.Length, 1 });
for (int i = 0; i < names.Length; i++)
{
cell[i] = new MLChar(null, names[i]);
}
return(cell);
}
//public void CreateCSVFile(DataTable dt, string strFilePath)
//{
// #region Export Grid to CSV
// // Create the CSV file to which grid data will be exported.
// StreamWriter sw = new StreamWriter(strFilePath, false);
// // First we will write the headers.
// //DataTable dt = m_dsProducts.Tables[0];
// int iColCount = dt.Columns.Count;
// for (int i = 0; i < iColCount; i++)
// {
// sw.Write(dt.Columns[i]);
// if (i < iColCount - 1)
// {
// sw.Write(",");
// }
// }
// sw.Write(sw.NewLine);
// // Now write all the rows.
// foreach (DataRow dr in dt.Rows)
// {
// for (int i = 0; i < iColCount; i++)
// {
// if (!Convert.IsDBNull(dr[i]))
// {
// sw.Write(dr[i].ToString());
// }
// if (i < iColCount - 1)
// {
// sw.Write(",");
// }
// }
// sw.Write(sw.NewLine);
// }
// sw.Close();
// #endregion
//}
private MLArray createStruct()
{
MLStructure outStruct = new MLStructure("kinectData", new int[] { 1, 1 });
//string[] headers = {"HipCenterX", "HipCenterY", "HipCenterZ", "SpineX", "SpineY", "SpineZ", "ShoulderCenterX",
// "ShoulderCenterY", "ShoulderCenterZ", "HeadX", "HeadY", "HeadZ", "ShoulderLeftX",
// "ShoulderLeftY", "ShoulderLeftZ", "ElbowLeftX", "ElbowLeftY", "ElbowLeftZ", "WristLeftX",
// "WristLeftY", "WristLeftZ", "HandLeftX", "HandLeftY", "HandLeftZ", "ShoulderRightX",
// "ShoulderRightY", "ShoulderRightZ", "ElbowRightX", "ElbowRightY", "ElbowRightZ",
// "WristRightX", "WristRightY", "WristRightZ", "HandRightX", "HandRightY", "HandRightZ",
// "HipLeftX", "HipLeftY", "HipLeftZ", "KneeLeftX", "KneeLeftY", "KneeLeftZ", "AnkleLeftX",
// "AnkleLeftY", "AnkleLeftZ", "FootLeftX", "FootLeftY", "FootLeftZ", "HipRightX", "HipRightY",
// "HipRightZ", "KneeRightX", "KneeRightY", "KneeRightZ", "AnkleRightX", "AnkleRightY",
// "AnkleRightZ", "FootRightX", "FootRightY", "FootRightZ"};
double criticalC1D = Convert.ToDouble(criticalC1);
double criticalC2D = Convert.ToDouble(criticalC2);
double criticalC3D = Convert.ToDouble(criticalC3);
double criticalC11D = Convert.ToDouble(criticalC11);
double criticalC21D = Convert.ToDouble(criticalC21);
double criticalC31D = Convert.ToDouble(criticalC31);
double criticalC12D = Convert.ToDouble(criticalC12);
double criticalC22D = Convert.ToDouble(criticalC22);
double criticalC32D = Convert.ToDouble(criticalC32);
double criticalC13D = Convert.ToDouble(criticalC13);
double criticalC23D = Convert.ToDouble(criticalC23);
double criticalC33D = Convert.ToDouble(criticalC33);
double criticalC14D = Convert.ToDouble(criticalC14);
double criticalC24D = Convert.ToDouble(criticalC24);
double criticalC34D = Convert.ToDouble(criticalC34);
double[] ccArray = { criticalC1D, criticalC2D, criticalC3D, criticalC11D, criticalC21D, criticalC31D, criticalC12D, criticalC22D, criticalC32D,
criticalC13D, criticalC23D, criticalC33D, criticalC14D, criticalC24D, criticalC34D };
Double[] skelDataA = (Double[])skelData.ToArray(typeof(double));
Double[] gpVectorA = (Double[])gpVector.ToArray(typeof(double));
Double[] kinectTiltA = (Double[])kinectTilt.ToArray(typeof(double));
outStruct["skelData", 0] = new MLDouble("", skelDataA, 60);
outStruct["dateHeader", 0] = new MLChar("", timeStamp);
outStruct["criticalComps", 0] = new MLDouble("", ccArray, 3);
outStruct["exercise", 0] = new MLChar("", exercise);
MLStructure groundStruct = new MLStructure("", new int[] { 1, 1 });
groundStruct["height", 0] = new MLDouble("", new double[] { 0.68 }, 1); // metres?
groundStruct["gpVector", 0] = new MLDouble("", gpVectorA, 4); //metres?
groundStruct["kinectTilt", 0] = new MLDouble("", kinectTiltA, 1); //degrees
outStruct["groundPlaneData", 0] = groundStruct;
return(outStruct);
}
static void DoWrite(string fn, Dictionary <string, DoubleList> data, SortedDictionary <string, double> param,
List <MLArray> mlList, Hashtable seen)
{
log.Info("DoWrite start " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
foreach (var item in data)
{
double[][] temp = item.Value.ToArray();
MLArray dbarray = new MLDouble(item.Key, temp);
mlList.Add(dbarray);
log.Info("DoWrite " + item.Key + " " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
}
log.Info("DoWrite mllist " + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
MLCell cell = new MLCell("PARM", new int[] { param.Keys.Count, 2 });
int m = 0;
foreach (var item in param.Keys)
{
cell[m, 0] = new MLChar(null, item.ToString());
cell[m, 1] = new MLDouble(null, new double[] { (double)param[item] }, 1);
m++;
}
mlList.Add(cell);
MLArray seenmsg = CreateCellArray("Seen", seen.Keys.Cast <string>().ToArray());
mlList.Add(seenmsg);
try
{
log.Info("write " + fn + ".mat");
log.Info("DoWrite before" + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
MatFileWriter mfw = new MatFileWriter(fn + ".mat", mlList, true);
log.Info("DoWrite done" + (GC.GetTotalMemory(false) / 1024.0 / 1024.0));
}
catch (Exception err)
{
CustomMessageBox.Show("There was an error when creating the MAT-file: \n" + err.ToString(),
"MAT-File Creation Error!", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return;
}
}
private static MLArray CreateTestStruct() {
MLStructure outStruct = new MLStructure("kinectData", new int[] { 1, 1 });
double[] myRealNums = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 };
// new MLInt64("IA", myRealNums, myImagNums, length);
// IA: matlab Name (blank for struct)
// realNumbers => Double array of the real parts
// imagNumbers => Double array of the img parts
// length => dimension of the matrix
outStruct["skelData", 0] = new MLDouble("", myRealNums, 2);
outStruct["dateHeader", 0] = new MLChar("", "January 29th... etc...");
MLStructure groundStruct = new MLStructure("", new int[] { 1, 1 });
groundStruct["height", 0] = new MLDouble("", new double[] { 0.68 }, 1); // metres?
groundStruct["gpVector", 0] = new MLDouble("", new double[] {1.4, 1, 1, 1}, 4); //metres?
groundStruct["kinectTilt", 0] = new MLInt16("", new Int16[]{ -15 }, 1); //degrees
outStruct["groundPlaneData", 0] = groundStruct;
return outStruct;
}
private static MLCell CreateCellArrayCustom(string name, string[] items)
{
var cell = new MLCell(name, new int[] { items.Length, 1 });
int i = 0;
foreach (var item in items)
{
double ans = 0;
if (double.TryParse(items[i], out ans))
{
cell[i] = new MLDouble(null, new double[] { ans }, 1);
i++;
continue;
}
cell[i] = new MLChar(null, (string)items[i].Trim());
i++;
}
return(cell);
}
private static MLArray CreateTestStruct()
{
MLStructure outStruct = new MLStructure("kinectData", new int[] { 1, 1 });
double[] myRealNums = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 };
// new MLInt64("IA", myRealNums, myImagNums, length);
// IA: matlab Name (blank for struct)
// realNumbers => Double array of the real parts
// imagNumbers => Double array of the img parts
// length => dimension of the matrix
outStruct["skelData", 0] = new MLDouble("", myRealNums, 2);
outStruct["dateHeader", 0] = new MLChar("", "January 29th... etc...");
MLStructure groundStruct = new MLStructure("", new int[] { 1, 1 });
groundStruct["height", 0] = new MLDouble("", new double[] { 0.68 }, 1); // metres?
groundStruct["gpVector", 0] = new MLDouble("", new double[] { 1.4, 1, 1, 1 }, 4); //metres?
groundStruct["kinectTilt", 0] = new MLInt16("", new Int16[] { -15 }, 1); //degrees
outStruct["groundPlaneData", 0] = groundStruct;
return(outStruct);
}
public async static Task Export(String filename, Project project, ILogger logger = null, CancellationToken cancelletionToken = default(CancellationToken))
{
logger?.WriteLineInfo("");
logger?.WriteLineInfo("Saving project into MAT file!");
logger?.WriteLineInfo("MAT file location: " + filename);
List <MLArray> mlList = new List <MLArray>();
int pi = 0;
foreach (DataStream dataStream in project.DataStreams)
{
pi++;
cancelletionToken.ThrowIfCancellationRequested();
logger?.WriteLineInfo("Exporting " + dataStream.ShortName + " datastream...");
logger?.WriteProgress((double)pi / (double)project.DataStreams.Count() * 100.0);
MLStructure structDataStream = new MLStructure(dataStream.ShortName, new int[] { 1, 1 });
structDataStream["Name", 0] = new MLChar(null, dataStream.Name);
structDataStream["ShortName", 0] = new MLChar(null, dataStream.ShortName);
if (dataStream.DataLines.Count > 0)
{
// DataLines
MLCell arrayDataLines = new MLCell("DataLines", new int[] { dataStream.DataLines.Count, 1 });
int k = 0;
foreach (DataLine dataLine in dataStream.DataLines)
{
MLStructure structDataLine = new MLStructure(dataStream.ShortName, new int[] { 1, 1 });
structDataLine["Timestamp", 0] = new MLDouble("", new double[] { Utils.ConvertToUnixTimestamp(dataLine.TimeStamp) }, 1);
structDataLine["TimestampC", 0] = ConvertDateTimeToMLDouble(dataLine.TimeStamp);
if (dataLine is ImageDataLine)
{
structDataLine["ImageFileName", 0] = new MLChar(null, (dataLine as ImageDataLine).ImageFileName);
}
if (dataLine is VideoDataLine)
{
structDataLine["VideoFileName", 0] = new MLChar(null, (dataLine as VideoDataLine).VideoFileName);
}
arrayDataLines[k] = structDataLine;
k++;
}
structDataStream["DataLines", 0] = arrayDataLines;
}
if (dataStream is GPSDataStream)
{
GPSDataStream gpsDataStream = dataStream as GPSDataStream;
// Event Marker
if (gpsDataStream.MarkerEvents.Count > 0)
{
MLCell arrayMarkerEvents = new MLCell("MarkerEvents", new int[] { gpsDataStream.MarkerEvents.Count, 1 });
int k = 0;
foreach (EvenMarkerDataLine evnt in gpsDataStream.MarkerEvents)
{
MLStructure structEventMarkers = new MLStructure(dataStream.ShortName, new int[] { 1, 1 });
structEventMarkers["Timestamp", 0] = new MLDouble("", new double[] { (double)evnt.TimeStamp.Ticks }, 1);
structEventMarkers["TimestampC", 0] = ConvertDateTimeToMLDouble(evnt.TimeStamp);
structEventMarkers["Port", 0] = new MLChar(null, evnt.Port.ToString());
arrayMarkerEvents[k] = structEventMarkers;
k++;
}
structDataStream["MarkerEvents", 0] = arrayMarkerEvents;
}
// Positions
if (gpsDataStream.Positions.Count > 0)
{
double[][] points = new double[gpsDataStream.Positions.Count][];
int k = 0;
foreach (GPSPositionDataLine pt in gpsDataStream.Positions)
{
points[k] = new double[5];
points[k][0] = Utils.ConvertToUnixTimestamp(pt.TimeStamp);
points[k][1] = pt.Lat;
points[k][2] = pt.Lon;
points[k][3] = pt.Height;
points[k][4] = pt.Quality;
k++;
}
MLDouble arrayPoints = new MLDouble("Points", points);
structDataStream["Points", 0] = arrayPoints;
}
}
mlList.Add(structDataStream);
}
try
{
MatFileWriter mfw = new MatFileWriter(filename, mlList, false);
}
catch (Exception ex)
{
logger?.WriteLineError("Error occured: " + ex.ToString());
return;
}
logger?.WriteLineInfo("MAT file location: " + filename);
logger?.WriteLineInfo("Done.");
}
static void DoWrite(string fn, Dictionary<string, DoubleList> data, SortedDictionary<string, double> param,
List<MLArray> mlList, Hashtable seen)
{
log.Info("DoWrite start " + (GC.GetTotalMemory(false)/1024.0/1024.0));
foreach (var item in data)
{
double[][] temp = item.Value.ToArray();
MLArray dbarray = new MLDouble(item.Key, temp);
mlList.Add(dbarray);
log.Info("DoWrite " + item.Key + " " + (GC.GetTotalMemory(false)/1024.0/1024.0));
}
log.Info("DoWrite mllist " + (GC.GetTotalMemory(false)/1024.0/1024.0));
MLCell cell = new MLCell("PARM", new int[] {param.Keys.Count, 2});
int m = 0;
foreach (var item in param.Keys)
{
cell[m, 0] = new MLChar(null, item.ToString());
cell[m, 1] = new MLDouble(null, new double[] {(double) param[item]}, 1);
m++;
}
mlList.Add(cell);
MLArray seenmsg = CreateCellArray("Seen", seen.Keys.Cast<string>().ToArray());
mlList.Add(seenmsg);
try
{
log.Info("write " + fn + ".mat");
log.Info("DoWrite before" + (GC.GetTotalMemory(false)/1024.0/1024.0));
MatFileWriter mfw = new MatFileWriter(fn + ".mat", mlList, true);
log.Info("DoWrite done" + (GC.GetTotalMemory(false)/1024.0/1024.0));
}
catch (Exception err)
{
CustomMessageBox.Show("There was an error when creating the MAT-file: \n" + err.ToString(),
"MAT-File Creation Error!", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return;
}
}
//public void CreateCSVFile(DataTable dt, string strFilePath)
//{
// #region Export Grid to CSV
// // Create the CSV file to which grid data will be exported.
// StreamWriter sw = new StreamWriter(strFilePath, false);
// // First we will write the headers.
// //DataTable dt = m_dsProducts.Tables[0];
// int iColCount = dt.Columns.Count;
// for (int i = 0; i < iColCount; i++)
// {
// sw.Write(dt.Columns[i]);
// if (i < iColCount - 1)
// {
// sw.Write(",");
// }
// }
// sw.Write(sw.NewLine);
// // Now write all the rows.
// foreach (DataRow dr in dt.Rows)
// {
// for (int i = 0; i < iColCount; i++)
// {
// if (!Convert.IsDBNull(dr[i]))
// {
// sw.Write(dr[i].ToString());
// }
// if (i < iColCount - 1)
// {
// sw.Write(",");
// }
// }
// sw.Write(sw.NewLine);
// }
// sw.Close();
// #endregion
//}
private MLArray createStruct()
{
MLStructure outStruct = new MLStructure("kinectData", new int[] { 1, 1 });
//string[] headers = {"HipCenterX", "HipCenterY", "HipCenterZ", "SpineX", "SpineY", "SpineZ", "ShoulderCenterX",
// "ShoulderCenterY", "ShoulderCenterZ", "HeadX", "HeadY", "HeadZ", "ShoulderLeftX",
// "ShoulderLeftY", "ShoulderLeftZ", "ElbowLeftX", "ElbowLeftY", "ElbowLeftZ", "WristLeftX",
// "WristLeftY", "WristLeftZ", "HandLeftX", "HandLeftY", "HandLeftZ", "ShoulderRightX",
// "ShoulderRightY", "ShoulderRightZ", "ElbowRightX", "ElbowRightY", "ElbowRightZ",
// "WristRightX", "WristRightY", "WristRightZ", "HandRightX", "HandRightY", "HandRightZ",
// "HipLeftX", "HipLeftY", "HipLeftZ", "KneeLeftX", "KneeLeftY", "KneeLeftZ", "AnkleLeftX",
// "AnkleLeftY", "AnkleLeftZ", "FootLeftX", "FootLeftY", "FootLeftZ", "HipRightX", "HipRightY",
// "HipRightZ", "KneeRightX", "KneeRightY", "KneeRightZ", "AnkleRightX", "AnkleRightY",
// "AnkleRightZ", "FootRightX", "FootRightY", "FootRightZ"};
double criticalC1D = Convert.ToDouble(criticalC1);
double criticalC2D = Convert.ToDouble(criticalC2);
double criticalC3D = Convert.ToDouble(criticalC3);
double criticalC11D = Convert.ToDouble(criticalC11);
double criticalC21D = Convert.ToDouble(criticalC21);
double criticalC31D = Convert.ToDouble(criticalC31);
double criticalC12D = Convert.ToDouble(criticalC12);
double criticalC22D = Convert.ToDouble(criticalC22);
double criticalC32D = Convert.ToDouble(criticalC32);
double criticalC13D = Convert.ToDouble(criticalC13);
double criticalC23D = Convert.ToDouble(criticalC23);
double criticalC33D = Convert.ToDouble(criticalC33);
double criticalC14D = Convert.ToDouble(criticalC14);
double criticalC24D = Convert.ToDouble(criticalC24);
double criticalC34D = Convert.ToDouble(criticalC34);
double[] ccArray = { criticalC1D, criticalC2D, criticalC3D, criticalC11D, criticalC21D, criticalC31D, criticalC12D, criticalC22D, criticalC32D,
criticalC13D, criticalC23D, criticalC33D, criticalC14D, criticalC24D, criticalC34D};
Double[] skelDataA = (Double[])skelData.ToArray(typeof(double));
Double[] gpVectorA = (Double[])gpVector.ToArray(typeof(double));
Double[] kinectTiltA = (Double[])kinectTilt.ToArray(typeof(double));
outStruct["skelData", 0] = new MLDouble("", skelDataA, 60);
outStruct["dateHeader", 0] = new MLChar("", timeStamp);
outStruct["criticalComps", 0] = new MLDouble("", ccArray, 3);
outStruct["exercise", 0] = new MLChar("", exercise);
MLStructure groundStruct = new MLStructure("", new int[] { 1, 1 });
groundStruct["height", 0] = new MLDouble("", new double[] { 0.68 }, 1); // metres?
groundStruct["gpVector", 0] = new MLDouble("", gpVectorA, 4); //metres?
groundStruct["kinectTilt", 0] = new MLDouble("", kinectTiltA, 1); //degrees
outStruct["groundPlaneData", 0] = groundStruct;
return outStruct;
}
public static void log(string fn)
{
// read the file
string[] filelines = File.ReadAllLines(fn);
// store all the arrays
List<MLArray> mlList = new List<MLArray>();
// store data to putinto the arrays
Dictionary<string, List<double[]>> data = new Dictionary<string, List<double[]>>();
// store line item lengths
Hashtable len = new Hashtable();
// store whats we have seen in the log
Hashtable seen = new Hashtable();
// store the params seen
SortedDictionary<string, double> param = new SortedDictionary<string, double>();
// keep track of line no
int a = 0;
foreach (var line in filelines)
{
a++;
Console.Write(a + "\r");
string strLine = line.Replace(", ", ",");
strLine = strLine.Replace(": ", ":");
string[] items = strLine.Split(',', ':');
// process the fmt messages
if (line.StartsWith("FMT"))
{
// +1 for line no
string[] names = new string[items.Length - 5 + 1];
names[0] = "LineNo";
Array.ConstrainedCopy(items, 5, names, 1, names.Length - 1);
MLArray format = CreateCellArray(items[3] + "_label", names);
if (items[3] == "PARM")
{
}
else
{
mlList.Add(format);
}
len[items[3]] = names.Length;
} // process param messages
else if (line.StartsWith("PARM"))
{
param[items[1]] = double.Parse(items[2]);
}// everyting else is generic
else
{
// make sure the line is long enough
if (items.Length < 2)
continue;
// check we have a valid fmt message for this message type
if (!len.ContainsKey(items[0]))
continue;
// check the fmt length matchs what the log has
if (items.Length != (int)len[items[0]])
continue;
// make it as being seen
seen[items[0]] = 1;
double[] dbarray = new double[items.Length];
// set line no
dbarray[0] = a;
for (int n = 1; n < items.Length; n++)
{
try
{
dbarray[n] = double.Parse(items[n]);
}
catch { }
}
if (!data.ContainsKey(items[0]))
data[items[0]] = new List<double[]>();
data[items[0]].Add(dbarray);
}
}
foreach (var item in data)
{
double[][] temp = item.Value.ToArray();
MLArray dbarray = new MLDouble(item.Key, temp);
mlList.Add(dbarray);
}
MLCell cell = new MLCell("PARM", new int[] { param.Keys.Count, 2 });
int m = 0;
foreach (var item in param.Keys)
{
cell[m, 0] = new MLChar(null, item.ToString());
cell[m, 1] = new MLDouble(null, new double[] { (double)param[item] }, 1);
m++;
}
mlList.Add(cell);
MLArray seenmsg = CreateCellArray("Seen", seen.Keys.Cast<string>().ToArray());
mlList.Add(seenmsg);
try
{
MatFileWriter mfw = new MatFileWriter(fn + ".mat", mlList, true);
}
catch (Exception err)
{
MessageBox.Show("There was an error when creating the MAT-file: \n" + err.ToString(),
"MAT-File Creation Error!", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return;
}
}
public static void log(string fn)
{
string[] filelines;
if (fn.ToLower().EndsWith(".bin"))
{
filelines = BinaryLog.ReadLog(fn).ToArray();
}
else
{
// read the file
filelines = File.ReadAllLines(fn);
}
// store all the arrays
List <MLArray> mlList = new List <MLArray>();
// store data to putinto the arrays
Dictionary <string, List <double[]> > data = new Dictionary <string, List <double[]> >();
// store line item lengths
Hashtable len = new Hashtable();
// store whats we have seen in the log
Hashtable seen = new Hashtable();
// store the params seen
SortedDictionary <string, double> param = new SortedDictionary <string, double>();
// keep track of line no
int a = 0;
foreach (var line in filelines)
{
a++;
Console.Write(a + "\r");
string strLine = line.Replace(", ", ",");
strLine = strLine.Replace(": ", ":");
string[] items = strLine.Split(',', ':');
// process the fmt messages
if (line.StartsWith("FMT"))
{
// +1 for line no
string[] names = new string[items.Length - 5 + 1];
names[0] = "LineNo";
Array.ConstrainedCopy(items, 5, names, 1, names.Length - 1);
MLArray format = CreateCellArray(items[3] + "_label", names);
if (items[3] == "PARM")
{
}
else
{
mlList.Add(format);
}
len[items[3]] = names.Length;
} // process param messages
else if (line.StartsWith("PARM"))
{
try
{
param[items[1]] = double.Parse(items[2], CultureInfo.InvariantCulture);
}
catch { }
}// everyting else is generic
else
{
// make sure the line is long enough
if (items.Length < 2)
{
continue;
}
// check we have a valid fmt message for this message type
if (!len.ContainsKey(items[0]))
{
continue;
}
// check the fmt length matchs what the log has
if (items.Length != (int)len[items[0]])
{
continue;
}
// make it as being seen
seen[items[0]] = 1;
double[] dbarray = new double[items.Length];
// set line no
dbarray[0] = a;
for (int n = 1; n < items.Length; n++)
{
try
{
dbarray[n] = double.Parse(items[n], CultureInfo.InvariantCulture);
}
catch { }
}
if (!data.ContainsKey(items[0]))
{
data[items[0]] = new List <double[]>();
}
data[items[0]].Add(dbarray);
}
}
foreach (var item in data)
{
double[][] temp = item.Value.ToArray();
MLArray dbarray = new MLDouble(item.Key, temp);
mlList.Add(dbarray);
}
MLCell cell = new MLCell("PARM", new int[] { param.Keys.Count, 2 });
int m = 0;
foreach (var item in param.Keys)
{
cell[m, 0] = new MLChar(null, item.ToString());
cell[m, 1] = new MLDouble(null, new double[] { (double)param[item] }, 1);
m++;
}
mlList.Add(cell);
MLArray seenmsg = CreateCellArray("Seen", seen.Keys.Cast <string>().ToArray());
mlList.Add(seenmsg);
try
{
MatFileWriter mfw = new MatFileWriter(fn + ".mat", mlList, true);
}
catch (Exception err)
{
MessageBox.Show("There was an error when creating the MAT-file: \n" + err.ToString(),
"MAT-File Creation Error!", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return;
}
}
public static void ExportHotFrame(String rootFolder, String annotationName, HotFrame frame,
MatlabExporterOptions options = MatlabExporterOptions.Overwrite, ILogger logger = null, CancellationToken cancelletionToken = default(CancellationToken))
{
// delete features
/*List<Feature> newFeatureSet = new List<Feature>();
* foreach (Feature feature in frame.Features)
* {
* if (feature.DataStream != null) newFeatureSet.Add(feature);
* }
* frame.Features = newFeatureSet;*/
String folderName = rootFolder + "\\frame_" + annotationName;
String matFilePath = folderName + "\\frame_" + annotationName + ".mat";
Directory.CreateDirectory(folderName);
logger?.WriteLineInfo("");
logger?.WriteLineInfo("Convert frame to Matlab MAT format and export images!");
logger?.WriteLineInfo("Export folder: " + folderName);
logger?.WriteLineInfo("MAT file location: " + matFilePath);
List <MLArray> mlList = new List <MLArray>();
Dictionary <DataStream, List <VeloFeature> > velodyneData = new Dictionary <DataStream, List <VeloFeature> >();
if ((options == MatlabExporterOptions.Append) && (File.Exists(matFilePath)))
{
MatFileReader matReader = new MatFileReader(matFilePath);
mlList = matReader.Data;
}
int i = 0;
foreach (Feature feature in frame.Features)
{
logger?.WriteLineInfo("Exporting: " + feature.DataStream.ShortName);
MLStructure structFeatures = new MLStructure(feature.DataStream.ShortName, new int[] { 1, 1 });
structFeatures["Name", 0] = new MLChar(null, feature.DataStream.Name);
structFeatures["ShortName", 0] = new MLChar(null, feature.DataStream.ShortName);
if (cancelletionToken.IsCancellationRequested == true)
{
logger?.WriteLineWarning("Export cancelled!");
return;
}
if (feature is GPSFeature)
{
var gpsFeature = feature as GPSFeature;
structFeatures["Lat", 0] = new MLDouble("", new double[] { gpsFeature.Position.Lat }, 1);
structFeatures["Lon", 0] = new MLDouble("", new double[] { gpsFeature.Position.Lon }, 1);
structFeatures["Height", 0] = new MLDouble("", new double[] { gpsFeature.Position.Height }, 1);
structFeatures["Quality", 0] = new MLDouble("", new double[] { gpsFeature.Position.Quality }, 1);
mlList.Add(structFeatures);
}
else if (feature is ImageFeature)
{
ImageFeature imageFeature = feature as ImageFeature;
structFeatures["Timestamp", 0] = new MLDouble("", new double[] { Utils.ConvertToUnixTimestamp(imageFeature.TimeStamp) }, 1);
structFeatures["TimestampC", 0] = ConvertDateTimeToMLDouble(imageFeature.TimeStamp);
double[][] points = new double[imageFeature.Points.Count][];
int k = 0;
foreach (ImagePoint pt in ((ImageFeature)feature).Points)
{
points[k] = new double[3];
points[k][0] = pt.ID;
points[k][1] = pt.X;
points[k][2] = pt.Y;
k++;
}
if (k != 0)
{
MLDouble arrayPoints = new MLDouble("Points", points);
structFeatures["Points", 0] = arrayPoints;
}
// save images
if (imageFeature.Image != null)
{
using (Bitmap img = new Bitmap(imageFeature.Image))
{
img.Save(folderName + "\\frame_" + annotationName + "_" + feature.DataStream.ShortName + ".bmp");
}
// you can export the images here, but it's very slow and the code also needs to be tested!
/*using (Bitmap img = new Bitmap(imageFeature.Image))
* {
*
* int[] dims = new int[] { img.Width, img.Height, 3 };
* MLDouble arrImg = new MLDouble("Image", dims);
* for (int i = 0; i < img.Width; i++)
* {
* for (int j = 0; j < img.Height; j++)
* {
* Color col = img.GetPixel(i, j);
* arrImg.Set(col.R, i, j + img.Height * 0);
* arrImg.Set(col.G, i, j + img.Height * 1);
* arrImg.Set(col.B, i, j + img.Height * 2);
* }
* }
*
* structFeatures["Image", 0] = arrImg;
* }*/
}
mlList.Add(structFeatures);
}
else if (feature is VeloFeature)
{
VeloFeature veloFeature = feature as VeloFeature;
// if key does not exist create one
if (!velodyneData.ContainsKey(veloFeature.DataStream))
{
velodyneData.Add(veloFeature.DataStream, new List <VeloFeature>());
}
velodyneData[veloFeature.DataStream].Add(veloFeature);
}
i++;
logger?.WriteProgress((double)i / (double)frame.Features.Count() * 100.0);
}
// ok, now finalize velodyne data
foreach (KeyValuePair <DataStream, List <VeloFeature> > entry in velodyneData)
{
if (cancelletionToken.IsCancellationRequested == true)
{
logger?.WriteLineWarning("Export cancelled!");
return;
}
MLStructure structFeatures = new MLStructure(entry.Key.ShortName, new int[] { 1, 1 });
structFeatures["Name", 0] = new MLChar(null, entry.Key.Name);
structFeatures["ShortName", 0] = new MLChar(null, entry.Key.ShortName);
structFeatures["TimeStamp", 0] = new MLDouble("", new double[] { Utils.ConvertToUnixTimestamp(frame.Timestamp) }, 1);
// get number of points
long n_points = 0;
foreach (VeloFeature feature in entry.Value)
{
n_points += feature.Points.Count();
}
if (n_points == 0)
{
logger?.WriteLineWarning(entry.Key.ShortName + ": No features!");
continue;
}
// populate points
double[][] points = new double[n_points][];
int k = 0;
foreach (VeloFeature feature in entry.Value)
{
foreach (VelodynePoint pt in feature.Points)
{
points[k] = new double[9];
points[k][0] = feature.ID;
points[k][1] = pt.X;
points[k][2] = pt.Y;
points[k][3] = pt.Z;
points[k][4] = Convert.ToDouble(pt.Intensity);
points[k][5] = pt.Distance;
points[k][6] = pt.Hz;
points[k][7] = pt.Vz;
points[k][8] = pt.InternalTime;
k++;
}
}
MLDouble arrayPoints = new MLDouble("Points", points);
structFeatures["Points", 0] = arrayPoints;
mlList.Add(structFeatures);
}
try
{
logger?.WriteLineInfo("Saving mat file...");
MatFileWriter mfw = new MatFileWriter(matFilePath, mlList, true);
}
catch (Exception ex)
{
logger?.WriteLineError("Error occured: " + ex.ToString());
return;
}
logger?.WriteProgress(100.0);
logger?.WriteLineInfo("Done.");
}
/// <summary>
/// Reads <c>miMATRIX</c> from the input stream.
/// </summary>
/// <remarks>
/// If reading was not finished (which is normal for filtered results)
/// returns <c>null</c>.
/// </remarks>
/// <param name="buf">The <c>BinaryReader</c> input stream.</param>
/// <param name="isRoot">When <c>true</c> informs that if this is a top level
/// matrix.</param>
/// <returns><c>MLArray</c> or <c>null</c> if matrix does not match <c>filter</c></returns>
private MLArray ReadMatrix( Stream buf, bool isRoot )
{
// result
MLArray mlArray = null;
ISMatTag tag;
// read flags
int[] flags = ReadFlags( buf );
int attributes = (flags.Length != 0 ) ? flags[0] : 0;
int nzmax = ( flags.Length != 0 ) ? flags[1] : 0;
int type = attributes & 0xff;
// read Array dimension
int[] dims = ReadDimension( buf );
// read Array name
string name = ReadName( buf );
// If this array is filtered out return immediately
if( isRoot && !_filter.Matches(name) )
{
return null;
}
// read data
switch (type)
{
case MLArray.mxSTRUCT_CLASS:
MLStructure mlStruct = new MLStructure(name, dims, type, attributes);
BinaryReader br = new BinaryReader(buf);
// field name length - this subelement always uses the compressed data element format
tag = new ISMatTag(br.BaseStream);
int maxlen = br.ReadInt32();
// Read fields data as Int8
tag = new ISMatTag(br.BaseStream);
// calculate number of fields
int numOfFields = tag.Size / maxlen;
// padding after field names
int padding = (tag.Size % 8) != 0 ? 8 - tag.Size % 8 : 0;
string[] fieldNames = new string[numOfFields];
for (int i = 0; i < numOfFields; i++)
{
byte[] names = new byte[maxlen];
br.Read(names, 0, names.Length);
fieldNames[i] = ZeroEndByteArrayToString(names);
}
br.ReadBytes(padding);
// read fields
for (int index = 0; index < mlStruct.M * mlStruct.N; index++)
{
for (int i = 0; i < numOfFields; i++)
{
// read matrix recursively
tag = new ISMatTag(br.BaseStream);
if (tag.Size > 0)
{
MLArray fieldValue = ReadMatrix(br.BaseStream, false);
mlStruct[fieldNames[i], index] = fieldValue;
}
else
{
mlStruct[fieldNames[i], index] = new MLEmptyArray();
}
}
}
mlArray = mlStruct;
//br.Close();
break;
case MLArray.mxCELL_CLASS:
MLCell cell = new MLCell(name, dims, type, attributes);
for (int i = 0; i < cell.M * cell.N; i++)
{
tag = new ISMatTag(buf);
if (tag.Size > 0)
{
MLArray cellmatrix = ReadMatrix(buf, false);
cell[i] = cellmatrix;
}
else
{
cell[i] = new MLEmptyArray();
}
}
mlArray = cell;
break;
case MLArray.mxDOUBLE_CLASS:
mlArray = new MLDouble(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<double>)mlArray).RealByteBuffer,
(ByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<double>)mlArray).ImaginaryByteBuffer,
(ByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT8_CLASS:
mlArray = new MLUInt8(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).RealByteBuffer,
(ByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).ImaginaryByteBuffer,
(ByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT8_CLASS:
mlArray = new MLInt8(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).RealByteBuffer,
(ByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).ImaginaryByteBuffer,
(ByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT64_CLASS:
mlArray = new MLUInt64(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).RealByteBuffer,
(ByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).ImaginaryByteBuffer,
(ByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT64_CLASS:
mlArray = new MLInt64(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).RealByteBuffer,
(ByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray<byte>)mlArray).ImaginaryByteBuffer,
(ByteStorageSupport)mlArray);
}
break;
case MLArray.mxCHAR_CLASS:
MLChar mlchar = new MLChar(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
char[] ac = tag.ReadToCharArray();
for (int i = 0; i < ac.Length; i++)
{
mlchar.SetChar(ac[i], i);
}
mlArray = mlchar;
break;
case MLArray.mxSPARSE_CLASS:
MLSparse sparse = new MLSparse(name, dims, attributes, nzmax);
// read ir (row indices)
tag = new ISMatTag(buf);
int[] ir = tag.ReadToIntArray();
// read jc (column indices)
tag = new ISMatTag(buf);
int[] jc = tag.ReadToIntArray();
// read pr (real part)
tag = new ISMatTag(buf);
double[] ad1 = tag.ReadToDoubleArray();
int n = 0;
for (int i = 0; i < ir.Length; i++)
{
if (i < sparse.N)
{
n = jc[i];
}
sparse.SetReal(ad1[i], ir[i], n);
}
//read pi (imaginary part)
if (sparse.IsComplex)
{
tag = new ISMatTag(buf);
double[] ad2 = tag.ReadToDoubleArray();
int n1 = 0;
for (int i = 0; i < ir.Length; i++)
{
if (i < sparse.N)
{
n1 = jc[i];
}
sparse.SetImaginary(ad2[i], ir[i], n1);
}
}
mlArray = sparse;
break;
default:
throw new MatlabIOException("Incorrect Matlab array class: " + MLArray.TypeToString(type));
}
return mlArray;
}
public static void SaveMatFile()
{
// create a MATLAB char and double variable and add it to the structure
//MLChar scoreName = ;
//MLDouble scoreValue = new MLDouble("", new double[] { 12345 }, 1);
int maxIter = 0;
foreach(ActionData ad in ActionData.actionList)
{
if(ad.iterationNum > maxIter)
{
maxIter = ad.iterationNum;
}
}
string dateLbl = "";
dateLbl += System.DateTime.Now.Year.ToString();
dateLbl += System.DateTime.Now.Month.ToString();
dateLbl += System.DateTime.Now.Day.ToString();
dateLbl += System.DateTime.Now.ToFileTimeUtc().ToString();
int chunkSize = 50;
int effChunkSize = 50;
int chunk = 0;
int actionIndex = 0;
List<string> fieldList = new List<string> ();
fieldList.Add ("obstacle");
fieldList.Add ("goal");
fieldList.Add ("item");
fieldList.Add ("robot");
fieldList.Add ("selectedItem");
while((chunk)*chunkSize < ActionData.actionList.Count)
{
int i = 0;
int ii = 0;
actionIndex = chunk*chunkSize;
if(chunkSize + actionIndex >= ActionData.actionList.Count)
effChunkSize = ActionData.actionList.Count-actionIndex;
else
effChunkSize = chunkSize;
MLStructure structure = new MLStructure("simDat", new int[] { effChunkSize, 1 });
List<MLArray> mlList = new List<MLArray>();
MLDouble arr;
while(actionIndex < ActionData.actionList.Count)
{
ActionData ad = actionList[actionIndex] as ActionData;
structure["speed", i] = new MLDouble("", new double[] {maxIter}, 1);
structure["beforePos", i] = new MLDouble("", new double[] {ad.beforePos.x,ad.beforePos.y,ad.beforePos.z }, 1);
structure["beforeOrient", i] = new MLDouble("", new double[] {ad.beforeOrient.eulerAngles.x,ad.beforeOrient.eulerAngles.y,ad.beforeOrient.eulerAngles.z}, 1);
//Debug.Log(dateLbl+"_"+chunk+"["+i+"]" +"("+ad.beforeOrient.x+","+ad.beforeOrient.y+","+ad.beforeOrient.z+")");
structure["afterPos", i] = new MLDouble("", new double[] {ad.afterPos.x,ad.afterPos.y,ad.afterPos.z}, 1);
structure["afterOrient", i] = new MLDouble("", new double[] {ad.afterOrient.eulerAngles.x,ad.afterOrient.eulerAngles.y,ad.afterOrient.eulerAngles.z}, 1);
structure["robotType", i] = new MLChar("", ad.robotType);
structure["itemType", i] = new MLChar("", ad.itemType);
ii=0;
foreach(string fieldName in fieldList)
{
int id = ad.positionNames.IndexOf(fieldName);
Vector3 vecValue;
if(id >= 0)
vecValue = ad.positionVecs[id];
else
vecValue = new Vector3(100,100,100); // We pass an invalid value
structure[fieldName, i] = new MLDouble("", new double[] {vecValue.x,vecValue.y,vecValue.z}, 1);
ii++;
}
i++;
actionIndex++;
}
mlList.Add(structure);
MatFileWriter mfw = new MatFileWriter("playDat"+dateLbl+"_"+chunk+".mat", mlList, false);
mfw.GetType();
Debug.Log ("Saved (" + chunk + ")playDat" + dateLbl + ".mat");
chunk ++;
ActionData.actionList = new List<ActionData>();
}
}
public static void writeDOTnirs(core.Data data, string filename, int startIdx = 0, int endIdx = Int32.MaxValue)
{
// Store the data into the *.nirs matlab format
try
{
int numsamples = data.numsamples;
int numch = data.probe.numChannels;
int naux = data.auxillaries.Length;
numsamples = Math.Min(endIdx - startIdx, numsamples - startIdx);
// save the structure as mat file using MatFileWriter
List <MLArray> mlList = new List <MLArray>();
double[][] d = new double[numsamples][];
double[][] t = new double[numsamples][];
double[][] aux = new double[numsamples][];
for (int j = startIdx; j < startIdx + numsamples; j++)
{
double[] dloc = new double[numch];
for (int i = 0; i < numch; i++)
{
dloc[i] = data.data[i][j];
}
try
{
if (naux > 0)
{
double[] aloc = new double[naux];
for (int ii = 0; ii < naux; ii++)
{
aloc[ii] = data.auxillaries[ii].data[j];
}
aux[j - startIdx] = aloc;
}
else
{
double[] aa = new double[1];
aa[0] = 0;
aux[j - startIdx] = aa;
}
}
catch
{
// Console.WriteLine("error writing aux");
double[] aa = new double[1];
aa[0] = 0;
aux[j - startIdx] = aa;
}
double[] tt = new double[1];
double[] ss = new double[1];
ss[0] = 0;
tt[0] = data.time[j];
t[j - startIdx] = tt;
d[j - startIdx] = dloc;
}
MLDouble mldata = new MLDouble("d", d);
mlList.Add(mldata);
MLDouble mlaux = new MLDouble("aux", aux);
mlList.Add(mlaux);
MLDouble mltime = new MLDouble("t", t);
mlList.Add(mltime);
double[][] s = new double[numsamples][];
for (int j = startIdx; j < startIdx + numsamples; j++)
{
double[] dloc = new double[data.stimulus.Count];
double thistime = data.time[j];
for (int i = 0; i < data.stimulus.Count; i++)
{
dloc[i] = 0;
for (int k = 0; k < data.stimulus[i].onsets.Count; k++)
{
double onset = data.stimulus[i].onsets[k];
double dur = data.stimulus[i].duration[k];
if (thistime >= onset & thistime <= onset + dur)
{
dloc[i] = data.stimulus[i].amplitude[k];
}
}
}
s[j - startIdx] = dloc;
}
MLDouble mls = new MLDouble("s", s);
mlList.Add(mls);
MLCell condNames = new MLCell("CondNames", new int[] { 1, data.stimulus.Count });
for (int i = 0; i < data.stimulus.Count; i++)
{
condNames[0, i] = new MLChar(null, data.stimulus[i].name);
}
mlList.Add(condNames);
// Probe
MLStructure mlSD = new MLStructure("SD", new int[] { 1, 1 });
List <string> datasubtype = new List <string>();
for (int i = 0; i < data.probe.numChannels; i++)
{
if (!datasubtype.Contains(data.probe.ChannelMap[i].datasubtype))
{
datasubtype.Add(data.probe.ChannelMap[i].datasubtype);
}
}
double[] lambda = new double[datasubtype.Count];
for (int i = 0; i < data.probe.numChannels; i++)
{
lambda[datasubtype.IndexOf(data.probe.ChannelMap[i].datasubtype)] = data.probe.ChannelMap[i].wavelength;
}
double[][] srcpos = new double[data.probe.numSrc][];
for (int j = 0; j < data.probe.numSrc; j++)
{
double[] slo = new double[3];
for (int i = 0; i < 2; i++)
{
slo[i] = data.probe.SrcPos[j, i];
}
slo[2] = 0;
srcpos[j] = slo;
}
double[][] detpos = new double[data.probe.numDet][];
for (int j = 0; j < data.probe.numDet; j++)
{
double[] dlo = new double[3];
for (int i = 0; i < 2; i++)
{
dlo[i] = data.probe.DetPos[j, i];
}
dlo[2] = 0;
detpos[j] = dlo;
}
mlSD["NumDet", 0] = new MLDouble("", new double[] { data.probe.numDet }, 1);
mlSD["NumSrc", 0] = new MLDouble("", new double[] { data.probe.numSrc }, 1);
mlSD["Lambda", 0] = new MLDouble("", lambda, 1);
mlSD["SrcPos", 0] = new MLDouble("", srcpos);
mlSD["DetPos", 0] = new MLDouble("", detpos);
if (data.probe.isregistered)
{
double[][] srcpos3d = new double[data.probe.numSrc][];
for (int j = 0; j < data.probe.numSrc; j++)
{
double[] slo = new double[3];
for (int i = 0; i < 3; i++)
{
slo[i] = data.probe.SrcPos3D[j, i];
}
srcpos3d[j] = slo;
}
double[][] detpos3d = new double[data.probe.numDet][];
for (int j = 0; j < data.probe.numDet; j++)
{
double[] dlo = new double[3];
for (int i = 0; i < 3; i++)
{
dlo[i] = data.probe.DetPos3D[j, i];
}
detpos3d[j] = dlo;
}
mlSD["SrcPos3D", 0] = new MLDouble("", srcpos3d);
mlSD["DetPos3D", 0] = new MLDouble("", detpos3d);
}
// fixes for HOMER2
mlSD["SpatialUnit"] = new MLChar("", "mm");
// Add demographics as a struct
MLStructure demo = new MLStructure("demographics", new int[] { 1, 1 });
for (int i = 0; i < data.demographics.Keys.Count; i++)
{
object val = data.demographics.get(data.demographics.Keys[i]);
string valstr = string.Format("{0}", val);
demo[data.demographics.Keys[i], 0] = new MLChar("", valstr);
}
mlList.Add(demo);
double[][] ml = new double[data.probe.numChannels][];
for (int i = 0; i < data.probe.numChannels; i++)
{
double[] m = new double[4];
m[0] = data.probe.ChannelMap[i].sourceindex + 1;
m[1] = data.probe.ChannelMap[i].detectorindex + 1;
m[2] = 0;
m[3] = 1 + datasubtype.IndexOf(data.probe.ChannelMap[i].datasubtype);
ml[i] = m;
}
MLDouble mlml = new MLDouble("ml", ml);
mlList.Add(mlml);
mlSD["MeasList", 0] = new MLDouble("", ml);
mlList.Add(mlSD);
MLStructure mlStim = new MLStructure("StimDesign", new int[] { data.stimulus.Count, 1 });
for (int i = 0; i < data.stimulus.Count; i++)
{
mlStim["name", i] = new MLChar("", data.stimulus[i].name);
double[] onset = new double[data.stimulus[i].onsets.Count];
for (int ii = 0; ii < data.stimulus[i].onsets.Count; ii++)
{
onset[ii] = data.stimulus[i].onsets[ii];
}
double[] dur = new double[data.stimulus[i].duration.Count];
for (int ii = 0; ii < data.stimulus[i].duration.Count; ii++)
{
dur[ii] = data.stimulus[i].duration[ii];
}
double[] amp = new double[data.stimulus[i].amplitude.Count];
for (int ii = 0; ii < data.stimulus[i].amplitude.Count; ii++)
{
amp[ii] = data.stimulus[i].amplitude[ii];
}
mlStim["onset", i] = new MLDouble("", onset, 1);
mlStim["dur", i] = new MLDouble("", dur, 1);
mlStim["amp", i] = new MLDouble("", amp, 1);
}
if (data.stimulus.Count > 0)
{
mlList.Add(mlStim);
}
new MatFileWriter(filename, mlList, false);
}
catch
{
Console.WriteLine("Unable to save .nirs file");
}
return;
}
/// <summary>
/// Reads <c>miMATRIX</c> from the input stream.
/// </summary>
/// <remarks>
/// If reading was not finished (which is normal for filtered results)
/// returns <c>null</c>.
/// </remarks>
/// <param name="buf">The <c>BinaryReader</c> input stream.</param>
/// <param name="isRoot">When <c>true</c> informs that if this is a top level
/// matrix.</param>
/// <returns><c>MLArray</c> or <c>null</c> if matrix does not match <c>filter</c></returns>
private MLArray ReadMatrix(Stream buf, bool isRoot)
{
// result
MLArray mlArray = null;
ISMatTag tag;
// read flags
int[] flags = ReadFlags(buf);
int attributes = (flags.Length != 0) ? flags[0] : 0;
int nzmax = (flags.Length != 0) ? flags[1] : 0;
int type = attributes & 0xff;
// read Array dimension
int[] dims = ReadDimension(buf);
// read Array name
string name = ReadName(buf);
// If this array is filtered out return immediately
if (isRoot && !_filter.Matches(name))
{
return(null);
}
// read data
switch (type)
{
case MLArray.mxSTRUCT_CLASS:
MLStructure mlStruct = new MLStructure(name, dims, type, attributes);
BinaryReader br = new BinaryReader(buf);
// field name length - this subelement always uses the compressed data element format
tag = new ISMatTag(br.BaseStream);
int maxlen = br.ReadInt32();
// Read fields data as Int8
tag = new ISMatTag(br.BaseStream);
// calculate number of fields
int numOfFields = tag.Size / maxlen;
// padding after field names
int padding = (tag.Size % 8) != 0 ? 8 - tag.Size % 8 : 0;
string[] fieldNames = new string[numOfFields];
for (int i = 0; i < numOfFields; i++)
{
byte[] names = new byte[maxlen];
br.Read(names, 0, names.Length);
fieldNames[i] = ZeroEndByteArrayToString(names);
}
br.ReadBytes(padding);
// read fields
for (int index = 0; index < mlStruct.M * mlStruct.N; index++)
{
for (int i = 0; i < numOfFields; i++)
{
// read matrix recursively
tag = new ISMatTag(br.BaseStream);
if (tag.Size > 0)
{
MLArray fieldValue = ReadMatrix(br.BaseStream, false);
mlStruct[fieldNames[i], index] = fieldValue;
}
else
{
mlStruct[fieldNames[i], index] = new MLEmptyArray();
}
}
}
mlArray = mlStruct;
//br.Close();
break;
case MLArray.mxCELL_CLASS:
MLCell cell = new MLCell(name, dims, type, attributes);
for (int i = 0; i < cell.M * cell.N; i++)
{
tag = new ISMatTag(buf);
if (tag.Size > 0)
{
MLArray cellmatrix = ReadMatrix(buf, false);
cell[i] = cellmatrix;
}
else
{
cell[i] = new MLEmptyArray();
}
}
mlArray = cell;
break;
case MLArray.mxDOUBLE_CLASS:
mlArray = new MLDouble(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <double>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <double>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxSINGLE_CLASS:
mlArray = new MLSingle(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <float>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <float>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT8_CLASS:
mlArray = new MLUInt8(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <byte>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <byte>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT8_CLASS:
mlArray = new MLInt8(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <sbyte>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <sbyte>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT16_CLASS:
mlArray = new MLUInt16(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <ushort>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <ushort>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT16_CLASS:
mlArray = new MLInt16(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <short>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <short>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT32_CLASS:
mlArray = new MLUInt32(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <uint>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <uint>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT32_CLASS:
mlArray = new MLInt32(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <int>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <int>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxUINT64_CLASS:
mlArray = new MLUInt64(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <ulong>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <ulong>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxINT64_CLASS:
mlArray = new MLInt64(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <long>)mlArray).RealByteBuffer,
(IByteStorageSupport)mlArray);
// read complex
if (mlArray.IsComplex)
{
tag = new ISMatTag(buf);
tag.ReadToByteBuffer(((MLNumericArray <long>)mlArray).ImaginaryByteBuffer,
(IByteStorageSupport)mlArray);
}
break;
case MLArray.mxCHAR_CLASS:
MLChar mlchar = new MLChar(name, dims, type, attributes);
//read real
tag = new ISMatTag(buf);
char[] ac = tag.ReadToCharArray();
for (int i = 0; i < ac.Length; i++)
{
mlchar.SetChar(ac[i], i);
}
mlArray = mlchar;
break;
case MLArray.mxSPARSE_CLASS:
MLSparse sparse = new MLSparse(name, dims, attributes, nzmax);
// read ir (row indices)
tag = new ISMatTag(buf);
int[] ir = tag.ReadToIntArray();
// read jc (column indices)
tag = new ISMatTag(buf);
int[] jc = tag.ReadToIntArray();
// read pr (real part)
tag = new ISMatTag(buf);
double[] ad1 = tag.ReadToDoubleArray();
int n = 0;
for (int i = 0; i < ir.Length; i++)
{
if (i < sparse.N)
{
n = jc[i];
}
sparse.SetReal(ad1[i], ir[i], n);
}
//read pi (imaginary part)
if (sparse.IsComplex)
{
tag = new ISMatTag(buf);
double[] ad2 = tag.ReadToDoubleArray();
int n1 = 0;
for (int i = 0; i < ir.Length; i++)
{
if (i < sparse.N)
{
n1 = jc[i];
}
sparse.SetImaginary(ad2[i], ir[i], n1);
}
}
mlArray = sparse;
break;
default:
throw new MatlabIOException("Incorrect Matlab array class: " + MLArray.TypeToString(type));
}
return(mlArray);
}
private static MLCell CreateCellArrayCustom(string name, string[] items)
{
var cell = new MLCell(name, new int[] { items.Length, 1 });
int i = 0;
foreach (var item in items)
{
double ans = 0;
if (double.TryParse(items[i], out ans))
{
cell[i] = new MLDouble(null, new double[] { ans }, 1);
i++;
continue;
}
cell[i] = new MLChar(null, (string)items[i].Trim());
i++;
}
return cell;
}
