public void Test_PlottableBar2_SingleSeries()
{
double[,] values = new double[, ] {
{ 7, 12, 40, 40, 100, 125, 172, 550, 560, 600, 2496, 2789 }
};
string[] rowLabels = new string[] { null };
string[] colLabels = new string[] { "ant", "bird", "mouse", "human", "cat", "dog", "frog", "lion", "elephant", "horse", "shark", "hippo" };
Assert.AreEqual(values.GetLength(0), rowLabels.Length);
Assert.AreEqual(values.GetLength(1), colLabels.Length);
var plt = new ScottPlot.Plot(400, 300);
// create and add an experimental plottable (not in the ScottPlot namespace)
var pltBar = new PlottableBar2(rowLabels, colLabels, values);
plt.Add(pltBar);
plt.Title("Body-to-Brain Mass Ratio");
plt.XTicks(colLabels);
plt.Axis(-1, colLabels.Length, 0, null);
plt.Grid(enableVertical: false);
// customize ticks to display better at high density
plt.Ticks(useMultiplierNotation: false);
plt.Ticks(xTickRotation: 45);
plt.Layout(xLabelHeight: 40);
TestTools.SaveFig(plt);
}
public void Test_PlottableBar2_MultiSeries()
{
double[,] values = new double[, ] {
{ 15, 22, 45, 17 }, { 37, 21, 29, 13 }
};
string[] rowLabels = new string[] { "men", "women" };
string[] colLabels = new string[] { "always", "regularly", "sometimes", "never" };
Assert.AreEqual(values.GetLength(0), rowLabels.Length);
Assert.AreEqual(values.GetLength(1), colLabels.Length);
var plt = new ScottPlot.Plot(400, 300);
// create and add an experimental plottable (not in the ScottPlot namespace)
var pltBar = new PlottableBar2(rowLabels, colLabels, values);
plt.Add(pltBar);
plt.Title("How often do you read reviews?");
plt.XTicks(colLabels);
plt.Ticks(useMultiplierNotation: false);
plt.Axis(-1, colLabels.Length, 0, null);
plt.Grid(enableVertical: false);
TestTools.SaveFig(plt);
}
public void AxisVSpan_ExtremeZoomIn_FullScreenIsSpanColor()
{
var plt = new ScottPlot.Plot();
var axSpan = new VSpan()
{
Y1 = 1, Y2 = 10, Color = System.Drawing.Color.Green
};
plt.Add(axSpan);
// Initial zoom to fill full plot with span color
plt.AxisZoom(1, 10);
var smallZoomBmp = TestTools.GetLowQualityBitmap(plt);
var smallZoom = new MeanPixel(smallZoomBmp);
// Extreme zoom to prove that full plot filled with span Color
plt.AxisZoom(1, 10_000_000);
var extremeZoomBmp = TestTools.GetLowQualityBitmap(plt);
var extremeZoom = new MeanPixel(extremeZoomBmp);
// Compare mean pixel with delta, because different ticks
// Y Ticks has more affect on mean pixel
Assert.AreEqual(smallZoom.RGB, extremeZoom.RGB, 20);
}
public void Test_AxisSpan_ChangesPosition()
{
var plt = new ScottPlot.Plot();
// start with default settings
var axSpan = new HSpan()
{
X1 = 1.23, X2 = 2.34
};
plt.Add(axSpan);
var bmp1 = TestTools.GetLowQualityBitmap(plt);
// change the plottable
axSpan.X2 += 1;
var bmp2 = TestTools.GetLowQualityBitmap(plt);
// measure what changed
//TestTools.SaveFig(bmp1, "1");
//TestTools.SaveFig(bmp2, "2");
var before = new MeanPixel(bmp1);
var after = new MeanPixel(bmp2);
Console.WriteLine($"Before: {before}");
Console.WriteLine($"After: {after}");
Assert.That(after.IsDarkerThan(before));
}
public void Test_ManualPolygon_Render()
{
Random rand = new Random(0);
var plt = new ScottPlot.Plot();
for (int i = 0; i < 5; i++)
{
var color = plt.GetSettings(false).GetNextColor();
var plottable = new ScottPlot.Plottable.Polygon(
xs: ScottPlot.DataGen.Random(rand, 3, 100),
ys: ScottPlot.DataGen.Random(rand, 3, 100))
{
Label = $"polygon {i + 1}",
LineWidth = 2,
LineColor = color,
Fill = true,
FillColor = color,
};
plt.Add(plottable);
}
plt.Title("Polygon Example");
plt.Legend(location: ScottPlot.Alignment.LowerLeft);
TestTools.SaveFig(plt);
}
public void Test_ManualPolygon_Render()
{
Random rand = new Random(0);
var plt = new ScottPlot.Plot();
for (int i = 0; i < 5; i++)
{
var color = plt.GetSettings(false).GetNextColor();
var plottable = new ScottPlot.PlottablePolygon(
xs: ScottPlot.DataGen.Random(rand, 3, 100),
ys: ScottPlot.DataGen.Random(rand, 3, 100),
label: $"polygon {i + 1}",
lineWidth: 2,
lineColor: color,
fill: true,
fillColor: color,
fillAlpha: .5
);
plt.Add(plottable);
}
plt.Title("Polygon Example");
plt.Legend(location: ScottPlot.legendLocation.lowerLeft);
TestTools.SaveFig(plt);
}
public void Test_Scatter_Mutable()
{
var plt = new ScottPlot.Plot();
var scatter = new ScottPlot.Plottable.ScatterPlotList();
plt.Add(scatter);
TestTools.SaveFig(plt, "no_points");
scatter.Add(1, 1);
plt.AxisAuto();
TestTools.SaveFig(plt, "one_point");
scatter.Add(2, 2);
plt.AxisAuto();
TestTools.SaveFig(plt, "two_points");
scatter.AddRange(new double[] { 3, 4, 5 }, new double[] { 1, 6, 3 });
plt.AxisAuto();
TestTools.SaveFig(plt, "many_points");
}
//[Test]
public void Test_DocPlottables_CreateAndAdd()
{
double[] xs = { 1, 2, 3, 4, 5 };
double[] ys = { 1, 4, 9, 16, 25 };
var plt = new ScottPlot.Plot(400, 300);
var scatter = new ScottPlot.Plottable.ScatterPlot(xs, ys)
{
Color = Color.Green,
LineWidth = 2
};
plt.Add(scatter);
TestTools.SaveFig(plt);
string thisHash = ScottPlot.Tools.BitmapHash(plt.Render());
createHash ??= thisHash;
Assert.AreEqual(createHash, thisHash);
}
public void Test_Annotation_Plottable()
{
var plottable = new ScottPlot.PlottableAnnotation(
xPixel: 50,
yPixel: 10,
label: "seems like it works",
fontSize: 16,
fontName: "Arial Narrow",
fontColor: Color.Magenta,
fill: true,
fillColor: Color.Green,
lineWidth: 2,
lineColor: Color.Blue,
shadow: true
);
var plt = new ScottPlot.Plot(400, 300);
plt.Add(plottable);
TestTools.SaveFig(plt);
}
public static void Main(string[] args)
{
const int maxDepth = 7;
const int minDepth = 1;
const int popSize = 250;
const uint maxGenerations = 250;
const uint elitism = 5;
const uint tournamentSize = 50;
const float growTerminalChance = .5f;
const float pCrossover = .3f;
const float pMutation = .5f;
string[] terminals = new string[] { "1", "0.5" };
string[] functions = new string[] { "add", "mul", "sub", "div", "pow" };
List <Tuple <List <float>, float> > Data = new List <Tuple <List <float>, float> >();
using (StreamReader sr = new StreamReader("concrete.txt"))
{
string line;
while ((line = sr.ReadLine()) != null)
{
var strData = line.Replace("\t", "").Split(' ', StringSplitOptions.RemoveEmptyEntries);
List <float> inputs = new List <float>();
for (int i = 0; i < strData.Length - 1; i++)
{
terminals = terminals.Append("x" + i).ToArray();
inputs.Add(float.Parse(strData[i], System.Globalization.NumberStyles.Float, System.Globalization.CultureInfo.InvariantCulture));
}
Data.Add(new Tuple <List <float>, float>(inputs,
(float.Parse(strData[strData.Length - 1], System.Globalization.NumberStyles.Float, System.Globalization.CultureInfo.InvariantCulture))));
}
}
var plt = new ScottPlot.Plot();
for (int i = 0; i < Data.Count; i++)
{
for (int j = 0; j < Data[0].Item1.Count; j++)
{
plt.PlotPoint(Data[i].Item1[j], Data[i].Item2, Color.Red, label: "Original Data");
}
}
Population <string> pop = new Population <string>(popSize, tournamentSize, pCrossover, pMutation, elitism, maxDepth, minDepth, functions, terminals, growTerminalChance);
pop.Init();
pop.Individuals = CalculateFitness(Data, pop.Individuals, terminals);
for (int i = 0; i < maxGenerations; i++)
{
pop.Evolve();
pop.Individuals = CalculateFitness(Data, pop.Individuals, terminals);
if (pop.Individuals.Any(i => i.Fitness <= 0))
{
Console.WriteLine("Solution reached in generation: " + i);
break;
}
}
Console.WriteLine("Fitness: " + pop.Individuals[0].Fitness);
pop.Individuals[0].PrintTree();
var op = Evaluate(pop.Individuals[0], terminals);
for (int i = 0; i < Data.Count; i++)
{
for (int j = 0; j < Data[0].Item1.Count; j++)
{
plt.Add(plt.PlotPoint(Data[i].Item1[j], op.Compute(Data[i].Item1.Select(d => (double)d).ToArray()), Color.Blue, label: "Estimate"));
}
}
plt.SaveFig("output.png");
}
