//Main code for creating chart.
//Note: the argument chartIndex is unused because this demo only has 1 chart.
public void createChart(WinChartViewer viewer, int chartIndex)
{
//
// This example demonstrates creating a histogram with a bell curve from raw data. About
// half of the code is to sort the raw data into slots and to generate the points on the
// bell curve. The remaining half of the code is the actual charting code.
//
// Generate a random guassian distributed data series as the input data for this
// example.
RanSeries r = new RanSeries(66);
double[] samples = r.getGaussianSeries(200, 100, 10);
//
// Classify the numbers into slots. In this example, the slot width is 5 units.
//
int slotSize = 5;
// Compute the min and max values, and extend them to the slot boundary.
ArrayMath m = new ArrayMath(samples);
double minX = Math.Floor(m.min() / slotSize) * slotSize;
double maxX = Math.Floor(m.max() / slotSize) * slotSize + slotSize;
// We can now determine the number of slots
int slotCount = (int)((maxX - minX + 0.5) / slotSize);
double[] frequency = new double[slotCount];
// Count the data points contained in each slot
for (int i = 0; i < samples.Length; ++i)
{
int slotIndex = (int)((samples[i] - minX) / slotSize);
frequency[slotIndex] = frequency[slotIndex] + 1;
}
//
// Compute Normal Distribution Curve
//
// The mean and standard deviation of the data
double mean = m.avg();
double stdDev = m.stdDev();
// The normal distribution curve (bell curve) is a standard statistics curve. We need to
// vertically scale it to make it proportion to the frequency count.
double scaleFactor = slotSize * samples.Length / stdDev / Math.Sqrt(6.2832);
// In this example, we plot the bell curve up to 3 standard deviations.
double stdDevWidth = 3.0;
// We generate 4 points per standard deviation to be joined with a spline curve.
int bellCurveResolution = (int)(stdDevWidth * 4 + 1);
double[] bellCurve = new double[bellCurveResolution];
for (int i = 0; i < bellCurveResolution; ++i)
{
double z = 2 * i * stdDevWidth / (bellCurveResolution - 1) - stdDevWidth;
bellCurve[i] = Math.Exp(-z * z / 2) * scaleFactor;
}
//
// At this stage, we have obtained all data and can plot the chart.
//
// Create a XYChart object of size 600 x 360 pixels
XYChart c = new XYChart(600, 360);
// Set the plotarea at (50, 30) and of size 500 x 300 pixels, with transparent
// background and border and light grey (0xcccccc) horizontal grid lines
c.setPlotArea(50, 30, 500, 300, Chart.Transparent, -1, Chart.Transparent, 0xcccccc);
// Display the mean and standard deviation on the chart
c.addTitle("Mean = " + c.formatValue(mean, "{value|1}") + ", Standard Deviation = " +
c.formatValue(stdDev, "{value|2}"), "Arial");
// Set the x and y axis label font to 12pt Arial
c.xAxis().setLabelStyle("Arial", 12);
c.yAxis().setLabelStyle("Arial", 12);
// Set the x and y axis stems to transparent, and the x-axis tick color to grey
// (0x888888)
c.xAxis().setColors(Chart.Transparent, Chart.TextColor, Chart.TextColor, 0x888888);
c.yAxis().setColors(Chart.Transparent);
// Draw the bell curve as a spline layer in red (0xdd0000) with 2-pixel line width
SplineLayer bellLayer = c.addSplineLayer(bellCurve, 0xdd0000);
bellLayer.setXData2(mean - stdDevWidth * stdDev, mean + stdDevWidth * stdDev);
bellLayer.setLineWidth(2);
// No tooltip is needed for the spline layer
bellLayer.setHTMLImageMap("{disable}");
// Draw the histogram as bars in blue (0x6699bb) with dark blue (0x336688) border
BarLayer histogramLayer = c.addBarLayer(frequency, 0x6699bb);
histogramLayer.setBorderColor(0x336688);
// The center of the bars span from minX + half_bar_width to maxX - half_bar_width
histogramLayer.setXData2(minX + slotSize / 2.0, maxX - slotSize / 2.0);
// Configure the bars to touch each other with no gap in between
histogramLayer.setBarGap(Chart.TouchBar);
// Use rounded corners for decoration
histogramLayer.setRoundedCorners();
// Tool tip for the histogram
histogramLayer.setHTMLImageMap("", "", "title='{value}'");
// ChartDirector by default will extend the x-axis scale by 0.5 unit to cater for the
// bar width. It is because a bar plotted at x actually occupies (x +/- half_bar_width),
// and the bar width is normally 1 for label based x-axis. However, this chart is using
// a linear x-axis instead of label based. So we disable the automatic extension and add
// a dummy layer to extend the x-axis scale to cover minX to maxX.
c.xAxis().setIndent(false);
c.addLineLayer2().setXData(minX, maxX);
// For the automatic y-axis labels, set the minimum spacing to 40 pixels.
c.yAxis().setTickDensity(40);
// Output the chart
viewer.Chart = c;
// Include tool tip for the chart
viewer.ImageMap = c.getHTMLImageMap("clickable");
}
