public Nonlinearity(NormalDistribution frequencyOfRawStimuli, NormalDistribution frequencyOfSpikeTriggeredStimuli, int points)
{
_frequencyOfRawStimuli = frequencyOfRawStimuli;
_frequencyOfSpikeTriggeredStimuli = frequencyOfSpikeTriggeredStimuli;
_points = points;
_parameterChanged = true;
}
private void PlotNormalDistribution(double[] data, Histogram histogram, string distributionName, Color color)
{
if (data == null || histogram == null)
return;
var points = 50;
var normalDistribution = new NormalDistribution(data.Average(), Math.Variance(data), points, histogram.LowerBound, histogram.UpperBound);
//var normalDistribution = new NormalDistribution(histogram.Mean(), histogram.Variance(), points, histogram.LowerBound, histogram.UpperBound);
var densityCurve = normalDistribution.DensityCurve;
var xValues = new double[points];
var yValues = new double[points];
for (var index = 0; index < points; index++)
{
xValues[index] = densityCurve[index, 0];
yValues[index] = densityCurve[index, 1];
}
// Add data sources.
var yDataSource = new EnumerableDataSource<double>(yValues);
yDataSource.SetYMapping(Y => Y);
yDataSource.AddMapping(ShapeElementPointMarker.ToolTipTextProperty, Y => string.Format("Normal Value \n\n{0}", Y));
var xDataSource = new EnumerableDataSource<double>(xValues);
xDataSource.SetXMapping(X => X);
var compositeDataSource = new CompositeDataSource(xDataSource, yDataSource);
// MatchValuePlotter.Viewport.Restrictions.Add(new PhysicalProportionsRestriction { ProportionRatio = 500000 });
var graph = ChartPlotter.AddLineGraph(compositeDataSource, color, 0.5, distributionName);
// Cache for later usage (e.g. change visibility).
if (graph != null)
_histogramGraphs.Add(graph);
}
private void GetSTAResponseHistogramPlotData(out Histogram rawStimuliSTAResponseHistogram, out double[] rawStimuliSTAMatchValues, out Histogram spikeTriggeredStimuliSTAResponseDiagram, out double[] spikeTriggeredStimuliSTAMatchValues, out Nonlinearity nonlinearity, bool recalcData = true)
{
rawStimuliSTAResponseHistogram = null;
rawStimuliSTAMatchValues = null;
spikeTriggeredStimuliSTAResponseDiagram = null;
spikeTriggeredStimuliSTAMatchValues = null;
nonlinearity = null;
if (_spikes == null)
return;
// caching
if (!recalcData)
{
rawStimuliSTAResponseHistogram = _rawStimuliSTAResponseHistogram;
spikeTriggeredStimuliSTAResponseDiagram = _spikeTriggeredStimuliSTAResponseDiagram;
nonlinearity = _nonlinearity;
return;
}
var spikes = new List<double[][]>();
if (Cell1CheckBox.IsChecked != null && Cell1CheckBox.IsChecked.Value)
spikes.Add(_spikes[0]);
if (Cell2CheckBox.IsChecked != null && Cell2CheckBox.IsChecked.Value)
spikes.Add(_spikes[1]);
if (Cell3CheckBox.IsChecked != null && Cell3CheckBox.IsChecked.Value)
spikes.Add(_spikes[2]);
if (Cell4CheckBox.IsChecked != null && Cell4CheckBox.IsChecked.Value)
spikes.Add(_spikes[3]);
if (spikes.Count == 0)
return;
int offset;
if (!int.TryParse(OffsetTextbox.Text, out offset))
offset = 13;
int maxTime;
if (!int.TryParse(TimeTextbox.Text, out maxTime))
maxTime = 13;
var rawStimuliHistogramBuckets = MatchValuesForRawStimuliBucketsUpDown.Value != null ? MatchValuesForRawStimuliBucketsUpDown.Value.Value : 200;
var spikeTriggeredStimuliHistogramBuckets = MatchValuesForSpikeTriggeredStimuliBucketsUpDown.Value != null ? MatchValuesForSpikeTriggeredStimuliBucketsUpDown.Value.Value : 200;
double[,] smoothKernel = null;
bool useDynamicDivisorForEdges = false;
GetSmoothKernel(out smoothKernel, out useDynamicDivisorForEdges);
SpikeTriggeredAnalysis.CalculateSTAResponseHistogram(_stimuli, spikes.ToArray(), false, offset, maxTime, smoothKernel, useDynamicDivisorForEdges, rawStimuliHistogramBuckets, out rawStimuliSTAMatchValues, out rawStimuliSTAResponseHistogram);
SpikeTriggeredAnalysis.CalculateSTAResponseHistogram(_stimuli, spikes.ToArray(), true, offset, maxTime, smoothKernel, useDynamicDivisorForEdges, spikeTriggeredStimuliHistogramBuckets, out spikeTriggeredStimuliSTAMatchValues, out spikeTriggeredStimuliSTAResponseDiagram);
_rawStimuliSTAResponseHistogram = rawStimuliSTAResponseHistogram;
_rawStimuliSTAMatchValues = rawStimuliSTAMatchValues;
_spikeTriggeredStimuliSTAResponseDiagram = spikeTriggeredStimuliSTAResponseDiagram;
_spikeTriggeredStimuliSTAMatchValues = spikeTriggeredStimuliSTAMatchValues;
var frequencyRawStimuli = new NormalDistribution(rawStimuliSTAMatchValues.Average(), Math.Variance(rawStimuliSTAMatchValues), 10, rawStimuliSTAResponseHistogram.LowerBound, rawStimuliSTAResponseHistogram.UpperBound);
var frequencySpikeTriggeredStimuli = new NormalDistribution(spikeTriggeredStimuliSTAMatchValues.Average(), Math.Variance(spikeTriggeredStimuliSTAMatchValues), 10, spikeTriggeredStimuliSTAResponseDiagram.LowerBound, spikeTriggeredStimuliSTAResponseDiagram.UpperBound);
nonlinearity =
// caching
_nonlinearity = new Nonlinearity(frequencyRawStimuli, frequencySpikeTriggeredStimuli, 100);
}
