/// <summary>
///
/// </summary>
/// <param name="data"></param>
public DescriptiveAnalysis(SampleMatrix data)
{
this.m_sourceData = data;
// Run analysis
this.m_mean = Statistics.Tools.Mean(data);
this.m_stdDev = Statistics.Tools.StandardDeviation(data, m_mean);
this.m_dScores = m_sourceData.Clone();
Statistics.Tools.Center(m_dScores, m_mean);
this.m_zScores = Statistics.Tools.ZScores(data, m_mean, m_stdDev);
this.m_median = Statistics.Tools.Median(data);
this.m_mode = Statistics.Tools.Mode(data);
this.m_variance = Statistics.Tools.Variance(data, m_mean);
this.m_covMatrix = Statistics.Tools.Covariance(data, m_mean);
this.m_corMatrix = Statistics.Tools.Covariance(m_zScores);
this.m_ranges = new DoubleRange[this.m_sourceData.Columns];
for (int i = 0; i < m_ranges.Length; i++)
{
this.m_ranges[i] = m_sourceData.GetColumn(i).Range;
}
// Create object-oriented structure to access data
DescriptiveMeasures[] measures = new DescriptiveMeasures[m_sourceData.Columns];
for (int i = 0; i < measures.Length; i++)
{
measures[i] = new DescriptiveMeasures(this, i);
}
this.m_measuresCollection = new DescriptiveMeasureCollection(measures);
}
public void TestJsonLongListInt()
{
var list1 = new SampleMatrix { M = new List<List<int>>() };
for (int i = 0; i < 300; ++i) {
list1.M.Add(new List<int>());
for (int j = 0; j < 400; ++j)
list1.M[i].Add(i * j * 97);
}
var js = new JsonSerializer();
var result1 = js.ToString(list1);
Assert.IsTrue(result1 != "");
var list2 = new SampleMatrix();
var jd = new JsonDeserializer();
jd.FromString(list2, result1);
Assert.AreEqual(list1.M.Count, list2.M.Count);
for (int i = 0; i < list1.M.Count; ++i) {
for (int j = 0; j < list1.M[i].Count; ++j)
Assert.AreEqual(list1.M[i][j], list2.M[i][j]);
}
var jdg = new SampleMatrix_JsonDeserializer();
var list3 = (SampleMatrix)jdg.FromString(result1);
Assert.AreEqual(list1.M.Count, list3.M.Count);
}
protected override void OnDoWork(System.ComponentModel.DoWorkEventArgs e)
{
int matrixHorizontalSize = 0;
double currentHorizontalPos = 0;
int counter = 0;
// Get Circle/Square fractions needed for round laser beam
double[,] fractions = CalcCircleSquareAreaFractions();
while (currentHorizontalPos < SampleSizeHor)
{
currentHorizontalPos = LaserBeamSize + (counter * ScanSpeed) / LaserFrequency;
counter++;
}
int[,] SampleOriginal = new int[SampleMatrix.GetLength(0), SampleMatrix.GetLength(1)];
SampleOriginal = SampleMatrix;
matrixHorizontalSize = counter;
double[,] ablatedSampleMatrix = new double
[(int)Math.Ceiling((double)SampleSizeVer / LineSpacing), // the vertical sample size divided by the LaserBeamSize
matrixHorizontalSize // the horizontal sample size divided by ScanSpeed and multiplied by LaserFrequency, to get the number of pulses in a line
]; // ** removed, i can calculate time if i need it; 1 for the resulting sum, and 1 for time
double horLocation = 0; // the horizontal, x, location of the laser beam (within a line)
int verLocation = 0; // the vertical, y, location of the laser beam (lines)
int laserPulseNumber = 0; // will be used to show which the current pulse is, within a single line scen
int lineNumber = 0; // will be used to show which the current line is
double localSum = 0; // initiation and declaration
// GasFlow * 0.01 is there because of 10 ms time precision
double ratio = (double)GasFlow * 0.01 / (double)ChamberVolume;
// now to sum up these exponential fall-out values in time, so we get a representation
// of how the concentration of ablated material/element changes in the gas with time
int maxTime = 0;
//Determine the approxiate washout time of the model, so we don't waste calculations
int washoutTime = (int)Math.Round(6.746 * Math.Pow(ratio * 100, -1.0661) * 100);
// If ratio is for example 1, (meaning 1 ml chamber, 100 ml/s gas flow), to keep the AUC for
// integrate A*e^((-t)*1) from 0 to (6.746*((1*100)^(-1.0661))*100)
// A, ergo peak, should be the ablated matrix value.
// If the ratio is 0.5, the peak should be twice the ablated matrix value.
double peakHeightFactor = ratio * 100;
double exp = Math.Exp(1);
int timeInCentiseconds = (int)Math.Floor((double)SampleSizeHor * 100 / ScanSpeed); // how much time it takes for one line to complete
double[,] finalBackmixedMatrix = new double[ablatedSampleMatrix.GetLength(0),
timeInCentiseconds];
// Calculate the number of required calculations, so we can display the percent done in the
// progress bar.
for (int i = 0; i < (ablatedSampleMatrix.GetLength(0)); i++)
{
for (int j = 0; j < (ablatedSampleMatrix.GetLength(1)); j++)
{
int offsetTime = (int)Math.Floor(((double)j / (double)LaserFrequency) * 100);
if ((offsetTime + washoutTime) < timeInCentiseconds)
{
maxTime = offsetTime + washoutTime;
}
else
{
maxTime = timeInCentiseconds;
}
HowManyCalculations += maxTime - offsetTime;
}
}
HowManyCalculations += ablatedSampleMatrix.GetLength(1) * ablatedSampleMatrix.GetLength(0);
// Simulate ablation (without backmixing)
//// Noise
Random random = new Random();
SimpleRNG.SetSeedFromSystemTime();
RNGCryptoServiceProvider secureRandom = new RNGCryptoServiceProvider();
byte[] randBytes = new byte[4];
double RSD = 3.009 * Math.Exp(-0.2293 * LaserBeamSize) + 0.0568;
/* Derived from MATLAB function fitting
* a = 3.009 (0.9428, 5.076)
* b = 0.2293 (0.1363, 0.3223)
* c = 0.0568 (0.00159, 0.112)
*/
while ((verLocation + LaserBeamSize) <= SampleSizeVer) // whole sample
{
if (CancellationPending)
{
e.Cancel = true;
return;
}
else
{
while ((horLocation + LaserBeamSize) <= SampleSizeHor) // one line
{
localSum = 0;
// this double for loop sums up the values within LaserBeamSize (down and right) of horLocation and verLocation
int LBS = LaserBeamSize;
for (int i = 0; i < LBS; i++)
{
for (int j = 0; j < LBS; j++)
{
// Square beam
if (BeamShape == false)
{
// Summation of values in the area of the matrix, that the laser ablates
localSum = localSum + SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)];
// Ablate the thin sample, so that nothing remains in the impact site
if (ThinSample)
{
SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] = 0;
}
// Ablate a certain fraction
else if (!ThinSample && !ThickSample)
{
SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] -= (int)Math.Round(SampleOriginal[i + verLocation, j + (int)Math.Floor(horLocation)] * (1 / (double)NumberOfShots));
}
}
// Round beam. Multiply border areas with calculated fractions.
else if (BeamShape == true)
{
// Summation of values in the area of the matrix, that the laser ablates
localSum = localSum + SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] * fractions[i, j];
// Ablate the thin sample, so that nothing remains in the impact site
if (ThinSample)
{
SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] -= (int)Math.Round(SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] * fractions[i, j]);
}
else if (!ThinSample && !ThickSample)
{
SampleMatrix[i + verLocation, j + (int)Math.Floor(horLocation)] -= (int)Math.Round(SampleOriginal[i + verLocation, j + (int)Math.Floor(horLocation)] * fractions[i, j] * (1 / (double)NumberOfShots));
}
}
}
}
// Introduce ablation noise
secureRandom.GetBytes(randBytes);
double currentRandom = Math.Abs((double)BitConverter.ToInt32(randBytes, 0));
double noise2 = 0;
double noise = 0;
// noise = AblationNoise * localSum * ((random.NextDouble() - 0.5) * 2);
if (AblationNoise != 0)
{
noise = localSum * SimpleRNG.GetNormal(0, AblationNoise);
noise2 = SimpleRNG.GetNormal(0, AblationNoise);
}
ablatedSampleMatrix[lineNumber, laserPulseNumber] = Math.Abs(noise2 + localSum);
// resultingMatrix[lineNumber, laserPulseNumber, 1] = (int)Math.Floor((double)laserPulseNumber * 100/ LaserFrequency); // time at which the laser beam pulse had happened (in 1/100 seconds)
laserPulseNumber++;
CurrentCalc++;
horLocation = ScanSpeed * laserPulseNumber * (1 / (double)LaserFrequency);
// the next horizontal location equals the current one + how much the laser moves in one pulse
}
}
// the next vertical location is the current one + the width of the laser (LaserBeamSize); moves down one width to the next line
ReportProgress((int)(CurrentCalc * 100 / HowManyCalculations), "Simulating ... (1/3 - Sample ablation)");
lineNumber++;
laserPulseNumber = 0;
horLocation = 0;
verLocation = verLocation + LineSpacing;
// progressBar.Value = (int)(100 * ((double)verLocation / (double)SampleSizeVer));
// progressBar.Update();
}
// commented because we are putting everything in a single function
// return ablatedSampleMatrix;
// }
// this is an inherent physical property of the LA (and ICP-MS?) machine, not its technical function
// public double[,] SampleBackmix(ref double[,] ablatedSampleMatrix, ref System.Windows.Forms.ProgressBar progressBar, ref System.Windows.Forms.Label timeRemaining)
// {
//Report second step - sample backmixing
// progressReport.Text = "Simulating ... (2/3 - Sample backmixing)";
// form.Refresh();
for (int i = 0; i < (ablatedSampleMatrix.GetLength(0)); i++)
{
if (CancellationPending)
{
e.Cancel = true;
return;
}
else
{
for (int j = 0; j < (ablatedSampleMatrix.GetLength(1)); j++)
{
int offsetTime = (int)Math.Ceiling(((double)j / (double)LaserFrequency) * 100);
if ((offsetTime + washoutTime) < timeInCentiseconds)
{
maxTime = offsetTime + washoutTime;
}
else
{
maxTime = timeInCentiseconds;
}
for (int k = offsetTime; k < maxTime; k++)
{
// so it starts the curve at the right point,*100 time precision
double noise = 0;
noise = TransferNoise * ((random.NextDouble() - 0.5) * 2);
finalBackmixedMatrix[i, k] += Math.Abs(noise + (ablatedSampleMatrix[i, j] * peakHeightFactor * Math.Pow(exp, (-(k - offsetTime)) * ratio)));
}
CurrentCalc += maxTime - offsetTime;
}
}
ReportProgress((int)(CurrentCalc * 100 / HowManyCalculations), "Simulating ... (2/3 - Sample backmixing)");
}
double[,] ICPMSMatrix = new double[finalBackmixedMatrix.GetLength(0),
(int)Math.Ceiling(finalBackmixedMatrix.GetLength(1) / (AcqTime * 100))]; // time precision ( the * 100 part)
// Detector Noise generation
// Random detectorNoise = new Random();
// double strength = AmountNoise * 1 / (AdvancedNoiseSettings[10] * AdvancedNoiseSettings[11]);
// Complete noise generation
Random holisticNoise = new Random();
// ICP-MS Acquisition
for (int i = 0; i < ICPMSMatrix.GetLength(0); i++)
{
int j = 0; // raw data counter
int k = 0; // final data counter
double localSum1 = 0;
while (j < finalBackmixedMatrix.GetLength(1))
{
// adds up all the raw data within an acquisition time
// localSum1 += finalBackmixedMatrix[i, j] + strength*detectorNoise.NextDouble();
// Trapezoidal rule of approximating integration
if ((j + 1 < finalBackmixedMatrix.GetLength(1)) && ((j + 1) % (AcqTime * 100) != 0))
{
localSum1 += ((finalBackmixedMatrix[i, j] + finalBackmixedMatrix[i, j + 1]) / 2) * 0.01;
}
else
{
localSum1 += finalBackmixedMatrix[i, j] * 0.01;
}
j++;
// writes the data to the final array
if ((j % (AcqTime * 100) == 0) || j == finalBackmixedMatrix.GetLength(1)) // time precision (the * 100 part)
{
double noise = DetectorNoise * ((random.NextDouble() - 0.5) * 2);
//ICPMSMatrix[i, k] = localSum1 + holisticNoise.NextDouble()*AmountNoise ;
//ICPMSMatrix[i, k] = localSum1;
ICPMSMatrix[i, k] = Math.Abs(noise + localSum1);
localSum1 = 0;
k++;
}
}
}
ReportProgress((int)(CurrentCalc * 100 / HowManyCalculations), "Simulating ... (3/3 - ICPMS acquisition)");
e.Result = ICPMSMatrix;
}
public void TestMatrix()
{
var src = "{\"M\":[[1,2,3],[4,5],[6],[]]}";
var v = new SampleMatrix();
(new JsonDeserializer()).FromString(v, src);
Assert.AreEqual(4, v.M.Count);
CollectionAssert.AreEqual(new int[] { 1, 2, 3 }, v.M[0]);
CollectionAssert.AreEqual(new int[] { 4, 5 }, v.M[1]);
CollectionAssert.AreEqual(new int[] { 6 }, v.M[2]);
Assert.AreEqual(0, v.M[3].Count);
v = (SampleMatrix)SampleMatrix_JsonDeserializer.Instance.FromString(src);
Assert.AreEqual(4, v.M.Count);
CollectionAssert.AreEqual(new int[] { 1, 2, 3 }, v.M[0]);
CollectionAssert.AreEqual(new int[] { 4, 5 }, v.M[1]);
CollectionAssert.AreEqual(new int[] { 6 }, v.M[2]);
Assert.AreEqual(0, v.M[3].Count);
var js = new JsonSerializer();
js.JsonOptions.FieldSeparator = "";
js.JsonOptions.Indent = "";
Assert.AreEqual(src, js.ToString(v));
}
public void TestMatrix()
{
var src =
"20 01 00 " + XS(typeof(SampleMatrix)) + " 01 00 " + XS("M") + " 21 21 05 01 00 " +
"04 00 00 00 03 00 00 00 01 00 00 00 02 00 00 00 03 00 00 00 " +
"02 00 00 00 04 00 00 00 05 00 00 00 " +
"01 00 00 00 06 00 00 00 00 00 00 00 00 00";
var w = new SampleMatrix();
CheckDeserializers(bd => {
bd.FromBytes(w, SX(src));
Assert.AreEqual(4, w.M.Count);
CollectionAssert.AreEqual(new int[] { 1, 2, 3 }, w.M[0]);
CollectionAssert.AreEqual(new int[] { 4, 5 }, w.M[1]);
CollectionAssert.AreEqual(new int[] { 6 }, w.M[2]);
Assert.AreEqual(0, w.M[3].Count);
});
var bs = new BinarySerializer();
Assert.AreEqual(src, XS(bs.ToBytes(w)));
}