/// <summary>
/// Export the raw data as well as the results of fitting the data.
/// </summary>
/// <param name="FullFileName">Name of file to write.</param>
/// <param name="GCC">Collection of GrowthCurves to export</param>
public static void ExportData(string FullFileName, GrowthCurveCollection GCC)
{
StreamWriter SW = new StreamWriter(FullFileName);
SW.WriteLine(String.Join(",", OutputColumnCollection.Select((x) => x.Name)));
foreach (GrowthCurve GR in GCC)
{
SW.WriteLine(String.Join(",", OutputColumnCollection.Select((x) => SafeGet(x.outFunc, GR))));
}
//Below assumes the time is the same for all of them
//Below assumes the time is the same for all of them
SW.WriteLine(Intermissionline);
SW.Write("DateTime,");
SW.WriteLine(String.Join(",", GCC.Select((x) => x.DataSetName + " OD,Flag")));
HashSet <DateTime> dtimes = new HashSet <DateTime>();
foreach (GrowthCurve gc in GCC)
{
foreach (DateTime dt in gc.Select((x) => x.time))
{
dtimes.Add(dt);
}
}
List <DateTime> DateTimesinFile = dtimes.Select((x) => x).ToList();
DateTimesinFile.Sort();
foreach (DateTime DT in DateTimesinFile)
{
string line = DT.ToString() + ",";
foreach (GrowthCurve GR in GCC)
{
int indexPos = -1;
DateTime[] timeValues = GR.Times;
if (SimpleFunctions.ValueInArray(timeValues, DT, ref indexPos))
{
//decide if this timepoint was included
line += GR.ODValues[indexPos].ToString() + ",";
double DateX = GR[indexPos].time_as_double;
if (GR.FittedXValues != null && SimpleFunctions.ValueInArray(GR.FittedXValues, DateX))//now decide if it made it into the fit
{
line += "0,";
}
else
{
line += "1,";
}
}
else
{
line += "-999,-999,";
}
}
SW.WriteLine(line);
}
SW.Close();
}
public GroupFitter(GrowthCurveCollection GCC)
{
var tmpHold = new List <LightWeightGC>();
HashSet <double> times = new HashSet <double>();
Random r = new Random();
foreach (GrowthCurve gc in GCC)
{
if (gc.ExpFit == null || gc.ExpFit.SuccessfulFit == false)
{
throw new Exception("Curve " + gc.DataSetName + " has not been fit with an exponential yet");
}
LightWeightGC tmp = new LightWeightGC()
{
Xvalues = gc.FittedXValues, YValues = gc.FittedYValues, Name = gc.DataSetName
};
tmpHold.Add(tmp);
NamesToCurves[gc.DataSetName] = tmp;
xl.AddRange(gc.FittedXValues);
yl.AddRange(gc.FittedYValues);
gc.FittedXValues.ToList().ForEach(x => times.Add(x));
gc.GroupFit = this;
}
//Now to make the data array
int ParameterArraySize = times.Count + 2 * tmpHold.Count;
var t2 = times.ToList();
data = tmpHold.ToArray();
t2.Sort();
Times = t2.ToArray();
//First items 1-n are the time point offsets, next are the GrowthRate,InitPop for the different guys
Parameters = new double[ParameterArraySize];
int ArrayStart = times.Count;
for (int i = 0; i < data.Length; i++)
{
if (i < Times.Length)
{
//Parameters[i] = 1e-3;
}
data[i].GrowthParameterStart = ArrayStart + (i * 2);
double v = r.NextDouble() < .5 ? -1.0:1.0;
Parameters[data[i].GrowthParameterStart] = GCC[i].ExpFit.GrowthRate; // +GCC[i].ExpFit.GrowthRate * (r.NextDouble() * .005) * v;
v = r.NextDouble() < .5 ? -1.0:1.0;
Parameters[data[i].GrowthParameterStart + 1] = GCC[i].ExpFit.InitialPopSize; // +GCC[i].ExpFit.InitialPopSize * (r.NextDouble() * .005) * v;
double minTime = data[i].Xvalues[0];
data[i].timeParameterStart = t2.IndexOf(minTime);
}
double val = ShoNS.Optimizer.GradTester.Test(new DiffFunc(GetDerivatives), Parameters);
double val3 = val + .01;
val3++;
FitModel();
}
/// <summary>
/// Exports data as a CSV file with the first column being the date/time encoded as a double.
/// Useful for loading data in Matlab.
/// </summary>
/// <param name="FullFileName"></param>
/// <param name="GCC"></param>
public static void ExportMatlabData(string FullFileName, GrowthCurveCollection GCC)
{
StreamWriter SW = new StreamWriter(FullFileName);
string TitleLine = "Time,";//this will hold the titles for everything below
HashSet <double> Times = new HashSet <double>();
foreach (GrowthCurve GC in GCC)
{
foreach (double d in GC.Select((x) => x.time_as_double))
{
Times.Add(d);
}
TitleLine += GC.ToString() + ",";
}
//Below assumes the time is the same for all of them
SW.WriteLine(TitleLine);
List <double> times = Times.ToList();
times.Sort();
foreach (double time in times)
{
string line = time.ToString() + ",";
foreach (GrowthCurve GR in GCC)
{
int indexPos = -1;
double[] timesGC = GR.TimeValues_As_Double;
if (SimpleFunctions.ValueInArray(timesGC, time, ref indexPos))
{
//decide if this timepoint was included
line += GR.ODValues[indexPos].ToString() + ",";
double DateX = GR[indexPos].time_as_double;
}
else
{
line += "-999,";
}
}
SW.WriteLine(line);
}
SW.Close();
}
public static void ExportDataDEPRECATED(string FullFileName, GrowthCurveCollection GCC)
{
bool LagData = false;
//FullFileName = "C:\\FullName.csv";
StreamWriter SW = new StreamWriter(FullFileName);
SW.WriteLine("Fitted Data Results");
SW.WriteLine("Name, Doubling Time(Hrs),Growth Rate, How Determined?,NumPoints,R2,RMSE, Maximum GrowthRate,MaxOD,Notes,Linear-Fit Slope,Reduction in absolute error from ExpFit,LagTime,Reduction in Sum of Squares from Exp Fit,TimeTill_OD_0.02,EndOD,TreatmentGroup");
string TitleLine = "Time,";//this will hold the titles for everything below
foreach (GrowthCurve GR in GCC)
{
LagData = false;
TitleLine += GR.ToString() + " OD," + "Flag,";
string newline = GR.ToString() + ",";
double ActualGrowth = Math.Log(2) / GR.GrowthRate.GrowthRate;
if (GR.ValidDataSet)
{
newline += ActualGrowth.ToString("n5") + "," + GR.GrowthRate.GrowthRate.ToString() + "," + GR.GrowthRate.FittingUsed + "," + GR.GrowthRate.NumPoints + "," + GR.GrowthRate.R2.ToString("n4") + ","
+ GR.GrowthRate.RMSE.ToString("n5") + "," + GR.MaxGrowthRate.MaxGrowthRate.ToString("n5") + "," + GR.ODValues.Max().ToString("n4") + "," + GR.GrowthRate.Notes;
if (GR.LinearModelFitted && GR.ExpModelFitted)
{
double dif = GR.LinFit.AbsError - GR.ExpFit.AbsError;
double dif2 = GR.LinFit.calculateResidualSumofSquares() - GR.ExpFit.calculateResidualSumofSquares();
newline += "," + GR.LinFit.Parameters[1].ToString("n5") + "," + dif.ToString("n5") + ",DEPRECATED," + dif2.ToString("n5") + ",";
}//+","+RMSEdiff.ToString("n5")+","+GR.LinFit.RMSE.ToString()+","+GR.ExpFit.RMSE.ToString(); }//report the linear fitted slope if possible
else
{
newline += ",No Exp Fit to Compare Against,";
}
newline += GR.HoursTillODReached(.02).ToString() + ",";
newline += GR.ODValues.Last().ToString() + ",";
}
else
{
newline += ",,Weird Data:Blank??,,,,,,,,,,,,,";
}
SW.WriteLine(newline);
}
//Below assumes the time is the same for all of them
string Intermissionline = "Complete Data Listing Below";
if (LagData)
{
Intermissionline += "-Initial OD Present";
}
;
SW.WriteLine(Intermissionline);
SW.WriteLine(TitleLine);
HashSet <DateTime> dtimes = new HashSet <DateTime>();
foreach (GrowthCurve gc in GCC)
{
foreach (DateTime dt in gc.Select((x) => x.time))
{
dtimes.Add(dt);
}
}
List <DateTime> DateTimesinFile = dtimes.Select((x) => x).ToList();
DateTimesinFile.Sort();
foreach (DateTime DT in DateTimesinFile)
{
string line = DT.ToString() + ",";
foreach (GrowthCurve GR in GCC)
{
int indexPos = -1;
DateTime[] timeValues = GR.Times;
if (SimpleFunctions.ValueInArray(timeValues, DT, ref indexPos))
{
//decide if this timepoint was included
line += GR.ODValues[indexPos].ToString() + ",";
double DateX = GR[indexPos].time_as_double;
if (GR.FittedXValues != null && SimpleFunctions.ValueInArray(GR.FittedXValues, DateX)) //now decide if it made it into the fit
{
line += "0,";
}
else
{
line += "1,";
}
}
else
{
line += "-999,-999,";
}
}
SW.WriteLine(line);
}
SW.Close();
}
public static GrowthCurveCollection importPreviousDataFile(string file)
{
StreamReader SR = new StreamReader(file);
GrowthCurveCollection GCC = new GrowthCurveCollection();
//drop header lines
SR.ReadLine();
string line = "";
List <string> FitSummaryLines = new List <string> ();
while ((line = SR.ReadLine()) != null)
{
if (!line.StartsWith("Complete Data Listing Below"))
{
FitSummaryLines.Add(line);
}
else
{
break;
}
}
//now to grab the more important data
List <string[]> CompleteDataListing = new List <string[]> ();
SR.ReadLine(); //blow through headerline
while ((line = SR.ReadLine()) != null)
{
if (line.Length > 3)
{
CompleteDataListing.Add(line.Split(','));
}
}
//now to add the datetimes to the file
DateTime[] AllDateTimes = new DateTime[CompleteDataListing.Count];
for (int i = 0; i < CompleteDataListing.Count; i++)
{
AllDateTimes [i] = (Convert.ToDateTime(CompleteDataListing [i] [0]));
}
//now to convert this into something useful
for (int i = 0; i < FitSummaryLines.Count; i++)
{
List <DateTime> DateTimeArray = new List <DateTime> ();
List <double> ODValuesArray = new List <double> ();
string name = (string)FitSummaryLines [i];
name = name.Split(',') [0];
string notes = (string)FitSummaryLines [i];
notes = notes.Split(',') [9];
int dataposition = 1 + i * 2;
int indexPos = 0;
List <int> IndexesToFit = new List <int> ();
for (int j = 0; j < CompleteDataListing.Count; j++)
{
if ((CompleteDataListing [j] as string[]) [dataposition] != "-999")
{
DateTimeArray.Add(Convert.ToDateTime(CompleteDataListing [j] [0]));
ODValuesArray.Add(Convert.ToDouble(CompleteDataListing [j] [dataposition]));
int flag = Convert.ToInt32(CompleteDataListing [j] [dataposition + 1]);
if (flag == 0)
{
IndexesToFit.Add(indexPos);
}
indexPos++;
}
}
DateTime[] Times = DateTimeArray.ToArray();
double[] ODvalues = ODValuesArray.ToArray();
GrowthCurve GD = new GrowthCurve(name, Times, ODvalues);
GD.SetFittedRangeFromIndexes(IndexesToFit);
GCC.Add(GD);
}
return(GCC);
}