/// <summary>
/// The function gets the binsize
/// </summary>
/// <param name="scanfilesize">Size of the .scan file</param>
/// <param name="pointsInXDirection">Points in X Direction</param>
/// <param name="pointsInYDirection">Poitns in Y Direction</param>
private void GetBinSize(long scanfilesize, float pointsInXDirection, float pointsInYDirection)
{
// 1) We only want to do binning for files bigger than 100MB filesize > pathfilesize
string appPath = Application.StartupPath;
appPath += "\\ApplicationSettings.xml";
int filesizelimit = this.GetPathFileSizeLimit(appPath);
if (scanfilesize > filesizelimit)
{
// 2) Open up BinNumberWindow
MassRange massRange = this.msexperiment.Details.MassRangeInfo[0];
var fullScanMassRange = massRange as FullScanMassRange;
if (fullScanMassRange != null)
{
var binNumberWindow = new BinNumberWindow(pointsInXDirection, pointsInYDirection, this.masscal);
if (binNumberWindow.ShowDialog() == true)
{
if (binNumberWindow.BinSize > 0)
{
this.binsize = binNumberWindow.BinSize;
}
}
}
}
}
/// <summary>
/// Reads the Data file
/// </summary>
/// <param name="analysefilecontent">analyse file content Object</param>
/// <param name="filepath">Path of file </param>
/// <param name="analysefileheaderobject">Header Object</param>
protected override void Initialise(AnalyseFileContent analysefilecontent, string filepath, AnalyseFileHeaderObject analysefileheaderobject)
{
this.filePath = filepath;
this.analyseFileHeaderObject = analysefileheaderobject;
// 1) Make sure the path file exists
if (!File.Exists(this.filePath))
{
string header = "Missing File";
string error = string.Format("{0} is missing", this.filePath);
MessageBox.Show(error, header);
return;
}
// 2) ReadCalibrationFile (Calc MinMass, MaxMass, StepSize and MassSpecDataPoints)
this.ReadCalibrationFile();
// 3) Set Binsize
this.binsize = 1;
var fileinfo = new FileInfo(this.filePath);
long imgFileSize = fileinfo.Length;
string appPath = Application.StartupPath;
appPath += "\\ApplicationSettings.xml";
var filesizelimit = this.GetPathFileSizeLimit(appPath);
var minMassDp = 0;
var maxMassDp = (int)(this.massspecdatapoints - 1);
// We only want to do binning for files bigger than 100MB filesize > pathfilesize
if (imgFileSize != filesizelimit)
{
// Open up BinNumberWindow
var binNumberWindow = new BinNumberWindow(this.analyseFileHeaderObject.NumberOfXPoints, this.analyseFileHeaderObject.NumberOfYPoints, this.MassCal);
if (binNumberWindow.ShowDialog() == true)
{
this.binsize = binNumberWindow.BinSize;
minMassDp = binNumberWindow.MinMassDP;
maxMassDp = binNumberWindow.MaxMassDP;
}
}
this.massstepsize = 1;
// 4) Fill out meta rawdata
var metaData = new ImageMetaData();
try
{
metaData.Add("Sample Name", typeof(string), this.analyseFileHeaderObject.Name, false);
metaData.Add("Mass Range", typeof(string), this.massRangeName, false);
metaData.Add("Mass Step Size", typeof(string), 1, false);
metaData.Add("X1 (mm)", typeof(string), (Math.Abs(this.analyseFileHeaderObject.X1 - (int)this.analyseFileHeaderObject.X1) < Epsilon) ? this.analyseFileHeaderObject.X1.ToString("0.0") : this.analyseFileHeaderObject.X1.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Y1 (mm)", typeof(string), (Math.Abs(this.analyseFileHeaderObject.Y1 - (int)this.analyseFileHeaderObject.Y1) < Epsilon) ? this.analyseFileHeaderObject.Y1.ToString("0.0") : this.analyseFileHeaderObject.Y1.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("X2 (mm)", typeof(string), (Math.Abs(this.analyseFileHeaderObject.X2 - (int)this.analyseFileHeaderObject.X2) < Epsilon) ? this.analyseFileHeaderObject.X2.ToString("0.0") : this.analyseFileHeaderObject.X2.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Y2 (mm)", typeof(string), (Math.Abs(this.analyseFileHeaderObject.Y2 - (int)this.analyseFileHeaderObject.Y2) < Epsilon) ? this.analyseFileHeaderObject.Y2.ToString("0.0") : this.analyseFileHeaderObject.Y2.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Data Points in X", typeof(string), this.analyseFileHeaderObject.NumberOfXPoints.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Data Points in Y", typeof(string), this.analyseFileHeaderObject.NumberOfYPoints.ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Point Width (mm)", typeof(string), Math.Round(this.analyseFileHeaderObject.Dx, 2).ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Point Height (mm)", typeof(string), Math.Round(this.analyseFileHeaderObject.Dy, 2).ToString(CultureInfo.InvariantCulture), false);
metaData.Add("Bin Size", typeof(string), this.binsize.ToString(CultureInfo.InvariantCulture), false);
}
catch (Exception e)
{
Util.ReportException(e);
}
// 5) Declare Median List
var valuesForMedian = new List <float>();
this.minIntensityValue = 0;
this.maxIntensityValue = 0;
var minIntList = new float[maxMassDp - minMassDp + 1];
var maxIntList = new float[maxMassDp - minMassDp + 1];
// 6) Declare and Initialise the dataTic
var dataTic = new float[analysefileheaderobject.NumberOfXPoints][];
for (int i = 0; i < dataTic.Length; i++)
{
dataTic[i] = new float[analysefileheaderobject.NumberOfYPoints];
}
// 7) Declare mass spectrum datat list
this.massspecdatalist = new List <float[][]>();
// 8) Declare and Initialise the dataList
var data = new float[analysefileheaderobject.NumberOfXPoints][];
for (int pointOnXAxis = 0; pointOnXAxis < analysefileheaderobject.NumberOfXPoints; pointOnXAxis++)
{
data[pointOnXAxis] = new float[analysefileheaderobject.NumberOfYPoints];
}
this.massspecdatalist.Add(data);
// 9) Declare and populate the image data list - Fill it with some default data - this will be over written later
Cursor.Current = Cursors.WaitCursor;
AppContext.ProgressStart("Generating Empty Imagelist...");
var imageDataList = new List <ImageData>();
try
{
for (int massSpecDataPt = 0; massSpecDataPt < ((maxMassDp - minMassDp + 1) / this.binsize); massSpecDataPt++)
{
var specData = new float[analysefileheaderobject.NumberOfXPoints][];
for (int i = 0; i < specData.Length; i++)
{
specData[i] = new float[analysefileheaderobject.NumberOfYPoints];
}
// ok, now create the imageData and add to list...
var imageData = new ImageData(
analysefilecontent.Document,
specData,
this.analyseFileHeaderObject.Name,
metaData,
0,
10000,
1000,
1000,
this.analyseFileHeaderObject.Dx,
this.analyseFileHeaderObject.Dy,
this.masscal,
this.analyseFileHeaderObject.ExperimentType);
// Add the imageData to the list
imageDataList.Add(imageData);
AppContext.ProgressSetValue(100.0 * massSpecDataPt / ((maxMassDp - minMassDp + 1) / this.binsize));
}
}
catch (Exception e)
{
Util.ReportException(e);
}
finally
{
AppContext.ProgressClear();
Cursor.Current = Cursors.Default;
}
// 10) Read binary file
Cursor.Current = Cursors.WaitCursor;
AppContext.ProgressStart("Populating ImageList...");
using (var imgReader = new BinaryReader(File.Open(this.filePath, FileMode.Open)))
{
int xp = analysefileheaderobject.NumberOfXPoints;
int yp = analysefileheaderobject.NumberOfYPoints;
int dp = (maxMassDp - minMassDp + 1) / this.binsize;
int dd = this.binsize;
int dl = minMassDp;
int xf = analysefileheaderobject.NumberOfXPoints;
int df = this.masscal.Length;
int ps = this.analyseFileHeaderObject.DataByteSize;
int y;
var meanSumList = new double[dp];
for (int i = 0; i < dp; i++)
{
minIntList[i] = float.MaxValue;
maxIntList[i] = float.MinValue;
meanSumList[i] = 0.0;
}
for (y = 0; y < yp; y++)
{
// for the progress bar
AppContext.ProgressSetValue(y * 100 / yp);
// refresh counter here;
for (int x = 0; x < xp; x++)
{
long fp = ((((y * xf) + x) * df) + dl) * ps;
imgReader.BaseStream.Position = fp;
for (int d = 0; d < dp; d++)
{
float average = 0;
for (int di = 0; di < dd; di++)
{
float intensity;
switch (this.analyseFileHeaderObject.DataType)
{
case 4:
intensity = imgReader.ReadInt16();
break;
case 8:
case 16:
intensity = imgReader.ReadInt32();
break;
case 64:
intensity = imgReader.ReadInt64();
break;
default:
intensity = imgReader.ReadInt32();
break;
}
average += intensity;
}
average = average / dd;
imageDataList[d].Data[x][y] = average;
dataTic[x][y] += average;
if (average < minIntList[d])
{
minIntList[d] = average;
}
if (average > maxIntList[d])
{
maxIntList[d] = average;
}
// mean and median calculation... sum up the value to calculate the mean
meanSumList[d] += average;
}
}
}
// and cleanup
imgReader.Close();
}
AppContext.ProgressClear();
Cursor.Current = Cursors.Default;
// 11) create new masscal array
var newmasscal = new float[(maxMassDp - minMassDp + 1) / this.binsize];
for (int i = 0; i < ((maxMassDp - minMassDp + 1) / this.binsize); i++)
{
newmasscal[i] = this.masscal[minMassDp + (i * this.binsize)];
}
this.masscal = newmasscal;
// 12) Mean/Median for Tic
double meanSum = 0.0;
int numDataPoint = dataTic.Length;
for (int y = 0; y < analysefileheaderobject.NumberOfYPoints; y++)
{
for (int x = 0; x < analysefileheaderobject.NumberOfXPoints; x++)
{
float intensity = dataTic[x][y];
meanSum += intensity;
valuesForMedian.Add(intensity);
if (intensity < this.minIntensityValue)
{
this.minIntensityValue = intensity;
}
if (intensity > this.maxIntensityValue)
{
this.maxIntensityValue = intensity;
}
}
}
if (numDataPoint != 0)
{
this.meanValue = (float)(meanSum / numDataPoint);
}
valuesForMedian.Sort();
this.medianValue = ((valuesForMedian.Count % 2) == 0)
? (valuesForMedian[(valuesForMedian.Count / 2) - 1]
+ valuesForMedian[valuesForMedian.Count / 2]) / 2.0f
: valuesForMedian[valuesForMedian.Count / 2];
// 13) Fill out imageTic
var imageTic = new ImageData(
analysefilecontent.Document,
dataTic,
this.analyseFileHeaderObject.Name,
metaData,
this.minIntensityValue,
this.maxIntensityValue,
this.meanValue,
this.medianValue,
this.analyseFileHeaderObject.Dx,
this.analyseFileHeaderObject.Dy,
this.masscal,
this.analyseFileHeaderObject.ExperimentType);
// 14) Fill out ImageSpectrumData and add to analysefilecontent
analysefilecontent.Add(
new ImageSpectrumData(
analysefilecontent.Document,
this.analyseFileHeaderObject.Name,
metaData,
this.masscal,
imageDataList,
this.analyseFileHeaderObject.ExperimentType)
{
ImageTic = imageTic
});
}
