/// <summary>
/// From a signal, returns a series of X,Y values for use with a PlotModel
/// Also returns y axis information and the sample_period of the signal
/// </summary>
/// <param name="sample_period"> Variable to contain the sample period of the signal </param>
/// <param name="Signal"> The input signal name </param>
/// <param name="StartTime"> The input start time to be contained in the series </param>
/// <param name="EndTime"> The input end time to be contained in the series </param>
/// <returns> The series of X,Y values to draw on the plot </returns>
public LineSeries GetSeriesFromSignalName(out float sample_period, string Signal, DateTime StartTime, DateTime EndTime)
{
// Variable To Return
LineSeries series = new LineSeries();
// Check if this signal needs filtering
bool filter = false;
FilteredSignal filteredSignal = sm.FilteredSignals.Find(temp => temp.SignalName == Signal);
if (filteredSignal != null)
{
filter = true;
Signal = sm.FilteredSignals.Find(temp => temp.SignalName == Signal).OriginalName;
}
// Get Signal
if (EDFAllSignals.Contains(Signal))
{
// Get Signal
EDFSignal edfsignal = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == Signal);
// Determine Array Portion
sample_period = (float)LoadedEDFFile.Header.DurationOfDataRecordInSeconds / (float)edfsignal.NumberOfSamplesPerDataRecord;
// Get Array
List <float> values = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal, StartTime, EndTime);
// Add Points to Series
for (int y = 0; y < values.Count; y++)
{
series.Points.Add(new DataPoint(DateTimeAxis.ToDouble(StartTime + new TimeSpan(0, 0, 0, 0, (int)(sample_period * (float)y * 1000))), values[y]));
}
}
else // Derivative Signal
{
// Get Signals
DerivativeSignal deriv_info = sm.DerivedSignals.Find(temp => temp.DerivativeName == Signal);
EDFSignal edfsignal1 = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == deriv_info.Signal1Name.Trim());
EDFSignal edfsignal2 = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == deriv_info.Signal2Name.Trim());
// Get Arrays and Perform Resampling if needed
List <float> values1;
List <float> values2;
if (edfsignal1.NumberOfSamplesPerDataRecord == edfsignal2.NumberOfSamplesPerDataRecord) // No resampling
{
values1 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal1, StartTime, EndTime);
values2 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal2, StartTime, EndTime);
sample_period = (float)LoadedEDFFile.Header.DurationOfDataRecordInSeconds / (float)edfsignal1.NumberOfSamplesPerDataRecord;
}
else if (edfsignal1.NumberOfSamplesPerDataRecord > edfsignal2.NumberOfSamplesPerDataRecord) // Upsample signal 2
{
values1 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal1, StartTime, EndTime);
values2 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal2, StartTime, EndTime);
values2 = Utils.MATLAB_Resample(values2.ToArray(), edfsignal1.NumberOfSamplesPerDataRecord / edfsignal2.NumberOfSamplesPerDataRecord);
sample_period = (float)LoadedEDFFile.Header.DurationOfDataRecordInSeconds / (float)edfsignal1.NumberOfSamplesPerDataRecord;
}
else // Upsample signal 1
{
values1 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal1, StartTime, EndTime);
values2 = Utils.retrieveSignalSampleValuesMod(LoadedEDFFile, edfsignal2, StartTime, EndTime);
values1 = Utils.MATLAB_Resample(values1.ToArray(), edfsignal2.NumberOfSamplesPerDataRecord / edfsignal1.NumberOfSamplesPerDataRecord);
sample_period = (float)LoadedEDFFile.Header.DurationOfDataRecordInSeconds / (float)edfsignal2.NumberOfSamplesPerDataRecord;
}
// Add Points to Series
for (int y = 0; y < Math.Min(values1.Count, values2.Count); y++)
{
series.Points.Add(new DataPoint(DateTimeAxis.ToDouble(StartTime + new TimeSpan(0, 0, 0, 0, (int)(sample_period * (float)y * 1000))), values1[y] - values2[y]));
}
}
if (filter == true)
{
if (filteredSignal.LowPass_Enabled)
{
series = Utils.ApplyLowPassFilter(series, filteredSignal.LowPassCutoff, sample_period);
}
if (filteredSignal.Average_Enabled)
{
float LENGTH;
LENGTH = Math.Max(filteredSignal.Average_Length / (sample_period * 1000), 1);
series = Utils.ApplyAverageFilter(series, (int)LENGTH);
}
}
return(series);
}
/// <summary>
/// Given a settings model and edf file, sets the Y axis bounds of a given signal
/// </summary>
/// <param name="Signal"> The signal to set the bounds for </param>
/// <param name="LoadedEDFFile"> The EDF file with the signal's values </param>
/// <param name="sm"> The settings model that bounds are stored in </param>
public static void SetYBounds(string Signal, EDFFile LoadedEDFFile, SettingsModel sm)
{
// Save Signal Name
string OrigName = Signal;
// Check to see if the Signal Y Bounds have already been calculated
SignalYAxisExtremes find = sm.SignalsYAxisExtremes.Find(temp => temp.SignalName.Trim() == Signal.Trim());
// If the Signal Y Bounds have not been calculated
if (find == null)
{
List <float> values = new List <float>();
// Check if this signal needs filtering
FilteredSignal filteredSignal = sm.FilteredSignals.Find(temp => temp.SignalName == Signal);
if (filteredSignal != null)
{
Signal = sm.FilteredSignals.Find(temp => temp.SignalName == Signal).OriginalName;
}
if (LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == Signal) != null) // Regular Signal
{
// Get the EDF Signal Values
EDFSignal edfsignal = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == Signal);
values = LoadedEDFFile.retrieveSignalSampleValues(edfsignal);
}
else // Derivative Signal
{
// Get Signals
DerivativeSignal deriv_info = sm.DerivedSignals.Find(temp => temp.DerivativeName == Signal);
EDFSignal edfsignal1 = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == deriv_info.Signal1Name.Trim());
EDFSignal edfsignal2 = LoadedEDFFile.Header.Signals.Find(temp => temp.Label.Trim() == deriv_info.Signal2Name.Trim());
// Get Arrays and Perform Resampling if needed
List <float> values1;
List <float> values2;
if (edfsignal1.NumberOfSamplesPerDataRecord == edfsignal2.NumberOfSamplesPerDataRecord) // No resampling
{
values1 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal1);
values2 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal2);
}
else if (edfsignal1.NumberOfSamplesPerDataRecord > edfsignal2.NumberOfSamplesPerDataRecord) // Upsample signal 2
{
values1 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal1);
values2 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal2);
values2 = Utils.MATLAB_Resample(values2.ToArray(), edfsignal1.NumberOfSamplesPerDataRecord / edfsignal2.NumberOfSamplesPerDataRecord);
}
else // Upsample signal 1
{
values1 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal1);
values2 = LoadedEDFFile.retrieveSignalSampleValues(edfsignal2);
values1 = Utils.MATLAB_Resample(values1.ToArray(), edfsignal2.NumberOfSamplesPerDataRecord / edfsignal1.NumberOfSamplesPerDataRecord);
}
for (int x = 0; x < Math.Min(values1.Count, values2.Count); x += 1)
{
values.Add(values1[x] - values2[x]);
}
}
// Remove repeated values
int last_unique = 0;
for (int x = 0; x < values.Count; x++)
{
if (x > 0 && values[x] == values[last_unique])
{
values[x] = float.NaN;
}
else
{
last_unique = x;
}
}
values.RemoveAll(temp => float.IsNaN(temp));
// Find the high and low percentiles of the signal and the average value of the signal
values.Sort();
int high_index = (int)(percent_high / 100 * (values.Count - 1));
int low_index = (int)(percent_low / 100 * (values.Count - 1));
float range = values[high_index] - values[low_index];
float high_value = values[high_index] + range * (100 - (float)percent_high) / 100;
float low_value = values[low_index] - range * ((float)percent_low) / 100;
float av_value = values.Average();
// Save the values so that they do not have to be recalculated
sm.SignalsYAxisExtremes.Add(new SignalYAxisExtremes(OrigName)
{
yMax = high_value, yMin = low_value, yAvr = av_value
});
}
}