/// <summary>
/// Returns a signal's Y axis minimum bound
/// </summary>
/// <param name="Signal"> The signal to return Y axis bounds for </param>
/// <param name="woBias"> True if the returned bounds assumes 0 DC </param>
/// <param name="LoadedEDFFile"> The EDF File with all the signal's values in it </param>
/// <param name="sm"> The settings model containing the bounds </param>
/// <returns> The min y axis bounds of a signal</returns>
public static double GetMinSignalValue(string Signal, bool woBias, EDFFile LoadedEDFFile, SettingsModel sm)
{
// Check if the Y Bounds have already been calculated
SignalYAxisExtremes find = sm.SignalsYAxisExtremes.Find(temp => temp.SignalName.Trim() == Signal.Trim());
if (find != null) // If the Y Bounds have been calculated
{
if (!Double.IsNaN(find.yMin) && !Double.IsNaN(find.yAvr)) // Double check if the Y Bounds have been calculated
{
// Remove DC bias?
if (woBias) // Yes
{
return(find.yMin - find.yAvr);
}
else // No
{
return(find.yMin);
}
}
else // Calculate Y Bounds
{
SetYBounds(Signal, LoadedEDFFile, sm);
return(GetMinSignalValue(Signal, woBias, LoadedEDFFile, sm));
}
}
else // Calculate Y Bounds
{
SetYBounds(Signal, LoadedEDFFile, sm);
return(GetMinSignalValue(Signal, woBias, LoadedEDFFile, sm));
}
}
/// <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
});
}
}