public void PValueLogHistogram(CartesianChart chart)
{
int twentyPercent = 0;
int fortyPercent = 0;
int sixtyPercent = 0;
int eightyPercent = 0;
int oneHundrerdPercent = 0;
double popSize = (db.SubData[0].Genotype.Length) * (db.SubData[0].TraitValue.Length) * 1.0;
if (PValhistChart == null)
{
PValhistChart = new HistogramChart(chart);
}
PValhistChart.RemvoeColumnSeries();
PValhistChart.AxisXTitle = "-Log(P-Value)";
PValhistChart.AxisYTitle = "-Log(Proportion of Markers %)";
foreach (double d in pLogValues)
{
if (d >= 0.0 && d < 0.2)
{
twentyPercent++;
}
else if (d >= 0.2 && d < 0.4)
{
fortyPercent++;
}
else if (d >= 0.4 && d < 0.6)
{
sixtyPercent++;
}
else if (d >= 0.6 && d < 0.8)
{
eightyPercent++;
}
else if (d >= 0.8 && d <= 1.0)
{
oneHundrerdPercent++;
}
}
List <double> pValues = new List <double>();
pValues.Add((twentyPercent / popSize));
pValues.Add((fortyPercent / popSize));
pValues.Add((sixtyPercent / popSize));
pValues.Add((eightyPercent / popSize));
pValues.Add((oneHundrerdPercent / popSize));
List <string> pTitles = new List <string>();
pTitles.Add("0-20%");
pTitles.Add("20-40%");
pTitles.Add("40-60%");
pTitles.Add("60-80%");
pTitles.Add("80-100%");
PValhistChart.AddColumnSeries(pTitles, pValues, ColorConstants.highliteColor);
}
/// <summary>
/// 创建产品实例
/// </summary>
/// <param name="type"></param>
/// <returns></returns>
public static IChart GetChart(string type)
{
IChart chart = null;
switch (type)
{
case "histogram":
chart = new HistogramChart();
Console.WriteLine("初始化设置柱状图");
break;
case "pie":
chart = new PieChart();
Console.WriteLine("初始化设置饼状图");
break;
case "line":
chart = new LineChart();
Console.WriteLine("初始化设置折线图");
break;
default:
Console.WriteLine("当前类型不存在");
break;
}
return(chart);
}
private void ValuesRadioBtn_Checked(object sender, RoutedEventArgs e)
{
RadioButton radioButton = sender as RadioButton;
int[] histogram;
switch (radioButton.Name)
{
case "AveragedValuesRadioBtn":
histogram = averagedHistogram;
break;
case "RedValuesRadioBtn":
histogram = redHistogram;
break;
case "GreenValuesRadioBtn":
histogram = greenHistogram;
break;
case "BlueValuesRadioBtn":
histogram = blueHistogram;
break;
default:
throw new ArgumentOutOfRangeException();
}
HistogramChart.DisplayHistogram(histogram);
}
/// <summary>
/// Gets the SVG histogram.
/// </summary>
/// <param name="model">The histogram model</param>
/// <param name="is3D">if set to <c>true</c> it will be 3D</param>
/// <param name="depth">The depth.</param>
/// <returns></returns>
public static String GetSVGHistogram(this histogramModel model, Boolean is3D = false, short depth = 10)
{
if (!is3D)
{
HistogramChart output = new HistogramChart(500, 360, model.targetBins);
XmlDocument xml = output.GenerateChart(model.GetDataTableForFrequencies(), histogramModel.DEFAULT_COLUMN_NAME, histogramModel.DEFAULT_COLUMN_VALUE);
return(xml.OuterXml);
}
else
{
Histogram3DChart output = new Histogram3DChart(500, 360, model.targetBins, depth);
XmlDocument xml = output.GenerateChart(model.GetDataTableForFrequencies(), histogramModel.DEFAULT_COLUMN_NAME, histogramModel.DEFAULT_COLUMN_VALUE);
return(xml.OuterXml);
}
}
public static IChart GetChart(string name)
{
IChart chart = null;
if (string.Equals(name, "0", StringComparison.CurrentCultureIgnoreCase))
{
chart = new HistogramChart();
}
else if (string.Equals(name, "1", StringComparison.CurrentCultureIgnoreCase))
{
chart = new PieChart();
}
else if (string.Equals(name, "2", StringComparison.CurrentCultureIgnoreCase))
{
chart = new LineChart();
}
return(chart);
}
public static Chart GetChart(String type)
{
Chart chart = null;
if (type.Equals("histogram"))
{
chart = new HistogramChart();
Console.WriteLine("初始化设置柱状图");
}
else if (type.Equals("pie"))
{
chart = new PieChart();
Console.WriteLine("初始化设置饼状图");
}
else if (type.Equals("line"))
{
chart = new LineChart();
Console.WriteLine("初始化设置折线图");
}
return(chart);
}
public static IChartable GetChart(string type)
{
IChartable chart = null;
if (type.Equals("histogram", StringComparison.OrdinalIgnoreCase))
{
chart = new HistogramChart();
Console.WriteLine("初始化设置柱状图...");
}
else if (type.Equals("pie", StringComparison.OrdinalIgnoreCase))
{
chart = new PieChart();
Console.WriteLine("初始化设置饼状图...");
}
else if (type.Equals("line", StringComparison.OrdinalIgnoreCase))
{
chart = new PieChart();
Console.WriteLine("初始化设置折线图...");
}
return(chart);
}
// Acción que determina que clase utilitzar para crear los "Charts"
public void CrearChart(Button button, Label label = null)
{
ClearLastElements();
BaseChart.Chart.Series.RemoveAllSeries();
//Themes.RefreshTheme();
Themes.BasicAxes(BaseChart.Chart.Axes.Left, BaseChart.Chart.Axes.Right);
Themes.AplicarTheme(BaseChart);
switch (button.Text)
{
case "Line":
lineChart = new LineChart(BaseChart);
break;
case "Column Bar":
columnBarChart = new ColumnBarChart(BaseChart);
break;
case "Area":
areaChart = new AreaChart(BaseChart);
break;
case "Pie":
pieChart = new PieChart(BaseChart);
break;
case "Fast Line":
fastLineChart = new FastLineChart(BaseChart);
break;
case "Horizontal Area":
horizAreaChart = new HorizontalAreaChart(BaseChart);
break;
case "Horizontal Bar":
horizBarChart = new HorizontalBarChart(BaseChart);
break;
case "Horizontal Line":
horizLineChart = new HorizontalLineChart(BaseChart);
break;
case "Donut":
donutChart = new DonutChart(BaseChart);
break;
case "Bubble":
bubbleChart = new BubbleChart(BaseChart);
break;
case "Shape":
shapeChart = new ShapeChart(BaseChart);
break;
case "Gantt":
gantChart = new GanttChart(BaseChart);
break;
case "Point/Scatter":
point_scatterChart = new Point_ScatterChart(BaseChart);
break;
case "Interpolating Line":
interpolatingChart = new InterpolatingChartFeatures(BaseChart);
break;
case "Bar Styles":
coneBarChart = new BarStylesChartFeatures(BaseChart);
break;
case "Zoom & Panning":
zoomPaningArrowChart = new ZoomPanningChartFeatures(BaseChart);
break;
case "Bar Gradient":
gradientBarChart = new GradientBarChartFeatures(BaseChart);
break;
case "Bubble Transparent":
bubbleTranspChart = new BubbleTransparencyChartFeatures(BaseChart);
break;
case "Real Time":
fLineRealTimeChart = new FLineRealTimeChartFeatures(BaseChart);
break;
case "Stack Area":
stackAreaChart = new StackAreaChartFeatures(BaseChart);
break;
case "Multiple Pies":
multiPiesChart = new MultiplePiesChartFeatures(BaseChart);
break;
case "Semi-Pie":
semiPieChart = new Semi_PieChartFeatures(BaseChart);
break;
case "Semi-Donut":
semiDonutChart = new Semi_DonutChartFeatures(BaseChart);
break;
case "Arrow":
arrowChart = new ArrowChart(BaseChart);
break;
case "Polar":
polarChart = new PolarChart(BaseChart);
break;
case "Radar":
radarChart = new RadarChart(BaseChart);
break;
case "Pyramid":
pyramidChart = new PyramidChart(BaseChart);
break;
case "Candle":
candleChart = new CandleChart(BaseChart);
break;
case "Histogram":
histogramChart = new HistogramChart(BaseChart);
break;
case "Error":
errorChart = new ErrorChart(BaseChart);
break;
case "ErrorBar":
errorBarChart = new ErrorBarChart(BaseChart);
break;
case "Funnel":
funnelChart = new FunnelChart(BaseChart);
break;
case "Smith":
smithChart = new SmithChart(BaseChart);
break;
case "Bezier":
bezierChart = new BezierChart(BaseChart);
break;
case "HighLow":
highLowChart = new HighLowChart(BaseChart);
break;
case "Speed Time":
realTimeChart = new SpeedTimeChart(BaseChart);
break;
case "Waterfall":
waterfallChart = new WaterfallChart(BaseChart);
break;
case "Volume":
volumeChart = new VolumeChart(BaseChart);
break;
case "Color Grid":
colorGridChart = new ColorGridChart(BaseChart);
break;
case "Polar Bar":
polarBarChart = new PolarBarChart(BaseChart);
break;
case "Inverted Pyramid":
invertedPyramidChart = new InvertedPyramidChart(BaseChart);
break;
case "Horizontal Histogram":
horizHistogramChart = new HorizHistogramChart(BaseChart);
break;
case "Circular Gauge":
basicCircGaugeChart = new BasicCircularGaugeChart(BaseChart);
break;
case "Car Fuel":
carFuelChart = new CarFuelChart(BaseChart);
break;
case "Custom Hand":
custPointerGaugeChart = new CustomPointerChart(BaseChart);
break;
case "Acceleration":
accelerationCircularGaugeChart = new AccelerationCircularGaugeChart(BaseChart);
break;
case "Knob Gauge":
basicKnobGaugeChart = new BasicKnobGaugeChart(BaseChart);
break;
case "Temperature Knob":
temperatureKnobChart = new TemperatureKnobChart(BaseChart);
break;
case "Compass":
try { compassChart = new CompassChart(BaseChart); }
catch (Exception e) { }
break;
case "Map GIS":
mapGSIChart = new MapGISChart(BaseChart);
break;
case "World Map":
worldMapChart = new WorldMapChart(BaseChart);
break;
case "TreeMap":
treeMapChart = new TreeMapChart(BaseChart);
break;
case "Basic Clock":
basicClockChart = new BasicClockChart(BaseChart);
break;
case "Custom Clock":
customClockChart = new CustomClockChart(BaseChart);
break;
case "Organizational Chart":
basicOrganizationalChart = new BasicOrganizationalChart(BaseChart);
break;
case "Numeric Gauge":
numericGaugeChart = new NumericGaugeChart(BaseChart);
break;
case "Linear Gauge":
linearGaugeChart = new LinearGaugeChart(BaseChart);
break;
case "Scales":
scalesLinearChart = new ScalesLinearChart(BaseChart);
break;
case "SubLines":
moreLinesLinearChart = new MoreLinesLinearChart(BaseChart);
break;
case "Mobile Battery":
batteryLinearChart = new BatteryLinearChart(BaseChart);
break;
case "Basic Calendar":
basicCalendarChart = new BasicCalendarChart(BaseChart, label);
break;
case "Special Dates":
specialDatesChart = new SpecialDatesChart(BaseChart, label);
break;
case "TagCloud":
tagCloudChart = new TagCloudChart(BaseChart);
break;
case "Add":
addStdFunctionsChart = new AddStdFunctionsChart(BaseChart);
break;
case "Subtract":
subtStdFunctionsChart = new SubtStdFunctionsChart(BaseChart);
break;
case "Multiply":
multStdFunctionsChart = new MultStdFunctionsChart(BaseChart);
break;
case "Divide":
divStdFunctionsChart = new DivStdFunctionsChart(BaseChart);
break;
case "Count":
countStdFunctionsChart = new CountStdFunctionsChart(BaseChart);
break;
case "Average":
avgStdFunctionsChart = new AvgStdFunctionsChart(BaseChart);
break;
case "High":
highStdFunctionsChart = new HighStdFunctionsChart(BaseChart);
break;
case "Low":
lowStdFunctionsChart = new LowStdFunctionsChart(BaseChart);
break;
case "Median Function":
medianStdFunctionsChart = new MedianStdFunctionsChart(BaseChart);
break;
case "Percent Change":
percentStdFunctionsChart = new PercentStdFunctionsChart(BaseChart);
break;
case "ADX":
adxProFunctionChart = new ADXProFunctionChart(BaseChart);
break;
case "AC":
acProFunctionChart = new ACProFunctionChart(BaseChart);
break;
case "Alligator":
alligatorProFunctionChart = new AlligatorProFunctionChart(BaseChart);
break;
case "AO":
aoProFunctionChart = new AOProFunctionChart(BaseChart);
break;
case "ATR":
atrProFunctionChart = new ATRProFunctionChart(BaseChart);
break;
case "Bollinger Bands":
bollingerProFunctionChart = new BollingerProFunctionChart(BaseChart);
break;
case "CCI":
cciProFunctionChart = new CCIProFunctionChart(BaseChart);
break;
case "CLV":
clvProFunctionChart = new CLVProFunctionChart(BaseChart);
break;
case "Compression OHLC":
compressionOHLCProFunctionChart = new CompressionOHLCProFunctionChart(BaseChart);
break;
case "Exp. Average":
expAverageProFunctionChart = new ExpAverageProFunctionChart(BaseChart);
break;
case "Exp. Moving Average":
expMovAverageProFunctionChart = new ExpMovAverageProFunctionChart(BaseChart);
break;
case "Gator Oscillator":
gatorOscillProFunctionChart = new GatorOscillProFunctionChart(BaseChart);
break;
case "Kurtosis":
kurtosisProFunctionChart = new KurtosisProFunctionChart(BaseChart);
break;
case "MACD":
macdProFunctionChart = new MACDProFunctionChart(BaseChart);
break;
case "Momentum":
momentumProFunctionChart = new MomentumProFunctionChart(BaseChart);
break;
case "Momentum Div.":
momentumDivProFunctionChart = new MomentumDivProFunctionChart(BaseChart);
break;
case "Money Flow":
moneyFlowProFunctionChart = new MoneyFlowProFunctionChart(BaseChart);
break;
case "OBV":
obvProFunctionChart = new OBVProFunctionChart(BaseChart);
break;
case "PVO":
pvoProFunctionChart = new PVOProFunctionChart(BaseChart);
break;
case "RSI":
rsiProFunctionChart = new RSIProFunctionChart(BaseChart);
break;
case "RVI":
rviProFunctionChart = new RVIProFunctionChart(BaseChart);
break;
case "Slope":
slopeProFunctionChart = new SlopeProFunctionChart(BaseChart);
break;
case "Smoothed Mov Avg":
smoothMovAvgProFunctionChart = new SmoothMovAvgProFunctionChart(BaseChart);
break;
case "S.A.R.":
sarProFunctionChart = new SARProFunctionChart(BaseChart);
break;
case "Cross Point":
crossPointsProFunctionsChart = new CrossPointsProFunctionsChart(BaseChart);
break;
case "Correlation":
correlationProFunctionChart = new CorrelationProFunctionChart(BaseChart);
break;
case "Cumulative":
cumulativeProFunctionChart = new CumulativeProFunctionChart(BaseChart);
break;
case "Custom Function":
calculateEventProFunctionChart = new CalculateEventProFunctionChart(BaseChart);
break;
case "Exponential Trend":
exponentialTrendProFunctionChart = new ExponentialTrendProFunctionChart(BaseChart);
break;
case "Fitting Linearizable":
fittingProFunctionChart = new FittingProFunctionChart(BaseChart);
break;
case "Performance":
performanceProFunctionChart = new PerformanceProFunctionChart(BaseChart);
break;
case "Perimeter":
perimeterProFunctionChart = new PerimeterProFunctionChart(BaseChart);
break;
case "Finding Coefficients":
findCoeffProFunctionChart = new FindCoeffProFunctionChart(BaseChart);
break;
case "Down Sampling":
downSamplingProFunctionChart = new DownSamplingProFunctionChart(BaseChart);
break;
case "RMS":
rmsProFunctionChart = new RMSProFunctionChart(BaseChart);
break;
case "Smoothing Function":
smoothingProFunctionChart = new SmoothingProFunctionChart(BaseChart);
break;
case "Standard Deviation":
stdDeviationProFunctionChart = new StdDeviationProFunctionChart(BaseChart);
break;
case "Trendline":
trendlineProFunctionChart = new TrendlineProFunctionChart(BaseChart);
break;
case "Variance":
varianceProFunctionChart = new VarianceProFunctionChart(BaseChart);
break;
case "SPC":
spcProFunctionChart = new SPCProFunctionChart(BaseChart);
break;
case "Cumulative Histogram":
cumulativeHistogProFunctionChart = new CumulativeHistogProFunctionChart(BaseChart);
break;
case "Skewness":
skewnessProFunctionChart = new SkewnessProFunctionChart(BaseChart);
break;
}
Themes.AplicarOptions(BaseChart);
}
public void ChiSquaredHistogramChart(CartesianChart chart)
{
if (histChartChi == null)
{
histChartChi = new HistogramChart(chart);
}
histChartChi.AxisXTitle = "Chi^2 statistic";
histChartChi.AxisYTitle = "Proportion of markers";
double chiVal = 0;
double chiExpected = 0;
double counterN0 = 0, counterN1 = 0;
int twentyPercent = 0;
int fortyPercent = 0;
int sixtyPercent = 0;
int eightyPercent = 0;
int oneHundrerdPercent = 0;
double popSize = this.db.SubData[0].Genotype.Length * 1.0;
// this is our 100%
//we iterate over all the population
for (int i = 0; i < this.db.SubData[0].Genotype.Length; i++)
{
counterN0 = 0;
counterN1 = 0;
chiVal = 0;
chiExpected = 0;
//we iterate over the genotype of each person
for (int j = 0; j < this.db.SubData.Count; j++)
{
if (this.db.SubData[j].Genotype[0, i] == 0)
{
counterN0++;
}
else if (this.db.SubData[j].Genotype[0, i] == 1)
{
counterN1++;
}
}
//we finished going over the persons genotype divide by the 100 percent and add to the relevant bucket
chiExpected = (counterN0 + counterN1) / 2;
chiVal = (Math.Pow((counterN0 - chiExpected), 2.0) + Math.Pow((counterN1 - chiExpected), 2.0)) / chiExpected;
if (chiVal >= 0.0 && chiVal < 0.2)
{
twentyPercent++;
}
else if (chiVal >= 0.2 && chiVal < 0.4)
{
fortyPercent++;
}
else if (chiVal >= 0.4 && chiVal < 0.6)
{
sixtyPercent++;
}
else if (chiVal >= 0.6 && chiVal < 0.8)
{
eightyPercent++;
}
else if (chiVal >= 0.8 && chiVal <= 1.0)
{
oneHundrerdPercent++;
}
}
List <double> pValues = new List <double>();
pValues.Add((twentyPercent / popSize));
pValues.Add((fortyPercent / popSize));
pValues.Add((sixtyPercent / popSize));
pValues.Add((eightyPercent / popSize));
pValues.Add((oneHundrerdPercent / popSize));
List <string> pTitles = new List <string>();
pTitles.Add("0-20%");
pTitles.Add("20-40%");
pTitles.Add("40-60%");
pTitles.Add("60-80%");
pTitles.Add("80-100%");
histChartChi.AddColumnSeries(pTitles, pValues, ColorConstants.highliteColor);
}
public void TraitDistributionHistogram(int traitIndex, CartesianChart chart)
{
if (traitHistogramDist == null)
{
traitHistogramDist = new HistogramChart(chart);
}
traitHistogramDist.AxisXTitle = "Trait Values";
traitHistogramDist.AxisYTitle = "Proportion of Individuals";
traitHistogramDist.RemvoeColumnSeries();
double max, min;
max = db.SubData[0].TraitValue[0, traitIndex];
min = db.SubData[0].TraitValue[0, traitIndex];
double popSize = 0.0;
// make sure that our population is according to the size of the traits that we actually have info about them
foreach (DataIndividualsAndTraits ind in db.SubData)
{
if (ind.TraitValueOk[0, traitIndex] == true)
{
popSize++;
}
}
for (int i = 0; i < db.SubData.Count; i++)
{
if (db.SubData[i].TraitValue[0, traitIndex] > max && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
max = db.SubData[i].TraitValue[0, traitIndex];
}
}
double twentyPrecent = 0.0, fortyPrecent = 0.0, sixtyPrecent = 0.0, eightPrecent = 0.0, onehundredPrecent = 0.0;
for (int i = 0; i < this.db.SubData.Count; i++)
{
double temp = db.SubData[i].TraitValue[0, traitIndex];
temp = temp / max;
if (temp >= 0.0 && temp < 0.2 && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
twentyPrecent++;
}
else if (temp >= 0.2 && temp < 0.4 && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
fortyPrecent++;
}
else if (temp >= 0.4 && temp < 0.6 && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
sixtyPrecent++;
}
else if (temp >= 0.6 && temp < 0.8 && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
eightPrecent++;
}
else if (temp >= 0.8 && temp < 1.0 && db.SubData[i].TraitValueOk[0, traitIndex] == true)
{
onehundredPrecent++;
}
}
//get the proportion of the indivivuals
List <string> titles = new List <string>();
titles.Add("0.0-" + (max * 0.2).ToString("0.00"));
titles.Add((max * 0.2).ToString("0.00") + "-" + (max * 0.4).ToString("0.00"));
titles.Add((max * 0.4).ToString("0.00") + "-" + (max * 0.6).ToString("0.00"));
titles.Add((max * 0.6).ToString("0.00") + "-" + (max * 0.8).ToString("0.00"));
titles.Add((max * 0.8).ToString("0.00") + "-" + (max).ToString("0.00"));
List <double> values = new List <double>();
values.Add(twentyPrecent / popSize);
values.Add(fortyPrecent / popSize);
values.Add(sixtyPrecent / popSize);
values.Add(eightPrecent / popSize);
values.Add(onehundredPrecent / popSize);
traitHistogramDist.AddColumnSeries(titles, values, ColorConstants.highliteColor);
}
public void PValueHistogram(CartesianChart chart)
{
if (PValhistChart == null)
{
PValhistChart = new HistogramChart(chart);
}
PValhistChart.AxisXTitle = "P-Value";
PValhistChart.AxisYTitle = "Proportion of Markers %";
PValhistChart.RemvoeColumnSeries();
int twentyPercent = 0;
int fortyPercent = 0;
int sixtyPercent = 0;
int eightyPercent = 0;
int oneHundrerdPercent = 0;
double temp = 0.0;
double popSize = (db.SubData[0].Genotype.Length) * (db.SubData[0].TraitValue.Length) * 1.0;
//go over all the individuals of first marker and first trait and calculate p value
//get the answer and put it in the correct bin
for (int i = 0; i < this.db.SubData[0].Genotype.Length; i++)
{
//we get the wanted genotype index
for (int j = 0; j < this.db.SubData[0].TraitValue.Length; j++)
{
//we get the wanted trait index
List <double> no = new List <double>();
List <double> n1 = new List <double>();
for (int k = 0; k < this.db.SubData.Count; k++)
{
if (this.db.SubData[k].Genotype[0, i] == 0)
{
no.Add(this.db.SubData[k].TraitValue[0, j]);
}
else if (this.db.SubData[k].Genotype[0, i] == 1)
{
n1.Add(this.db.SubData[k].TraitValue[0, j]);
}
//iterate over all the people and gather two groups of n0 and n1
}
//calculate the pvalue for trait and genotype and put in the correct bin
//temp=result of p value
temp = StatisticCalculations.PValueTStatistic(no, n1);
pLogValues.Add((-1.0 * Math.Log(temp)));
if (temp >= 0.0 && temp < 0.2)
{
twentyPercent++;
}
else if (temp >= 0.2 && temp < 0.4)
{
fortyPercent++;
}
else if (temp >= 0.4 && temp < 0.6)
{
sixtyPercent++;
}
else if (temp >= 0.6 && temp < 0.8)
{
eightyPercent++;
}
else if (temp >= 0.8 && temp <= 1.0)
{
oneHundrerdPercent++;
}
}
}
List <double> pValues = new List <double>();
pValues.Add(twentyPercent / popSize);
pValues.Add(fortyPercent / popSize);
pValues.Add(sixtyPercent / popSize);
pValues.Add(eightyPercent / popSize);
pValues.Add(oneHundrerdPercent / popSize);
List <string> pTitles = new List <string>();
pTitles.Add("0-20%");
pTitles.Add("20-40%");
pTitles.Add("40-60%");
pTitles.Add("60-80%");
pTitles.Add("80-100%");
PValhistChart.AddColumnSeries(pTitles, pValues, ColorConstants.highliteColor);
}
public void SegregationMarkerHistogram(CartesianChart chart)
{
HistogramChart histChart = new HistogramChart(chart);
histChart.AxisXTitle = " n0/(n1+n0)";
histChart.AxisYTitle = "Proportion of Markers %";
int twentyPercent = 0, fortyPercent = 0, sixtyPercent = 0, eightyPercent = 0, oneHundrerdPercent = 0;
double temp, counterN0 = 0, counterN1 = 0;
double genotypeSize = db.SubData[0].Genotype.Length;
//we iterate over all the population
for (int i = 0; i < this.db.SubData[0].Genotype.Length; i++)
{
counterN0 = 0;
counterN1 = 0;
//we iterate over the genotype of each person
for (int j = 0; j < this.db.SubData.Count; j++)
{
if (this.db.SubData[j].Genotype[0, i] == 0)
{
counterN0++;
}
else if (this.db.SubData[j].Genotype[0, i] == 1)
{
counterN1++;
}
}
//we finished going over the persons genotype divide by the 100 percent and add to the relevant bucket
temp = counterN0 / (counterN1 + counterN0);
if (temp >= 0.0 && temp < 0.2)
{
twentyPercent++;
}
else if (temp >= 0.2 && temp < 0.4)
{
fortyPercent++;
}
else if (temp >= 0.4 && temp < 0.6)
{
sixtyPercent++;
}
else if (temp >= 0.6 && temp < 0.8)
{
eightyPercent++;
}
else if (temp >= 0.8 && temp <= 1.0)
{
oneHundrerdPercent++;
}
}
List <string> titles = new List <string>();
titles.Add("0-20%");
titles.Add("20-40%");
titles.Add("40-60%");
titles.Add("60-80%");
titles.Add("80-100%");
List <double> values = new List <double>();
values.Add(twentyPercent / genotypeSize);
values.Add(fortyPercent / genotypeSize);
values.Add(sixtyPercent / genotypeSize);
values.Add(eightyPercent / genotypeSize);
values.Add(oneHundrerdPercent / genotypeSize);
histChart.AddColumnSeries(titles, values, ColorConstants.highliteColor);
}
public void MarkerQualityHistogram(CartesianChart chart)
{
HistogramChart histChart = new HistogramChart(chart);
histChart.AxisXTitle = " Missing Data %";
histChart.AxisYTitle = "Proportion of Markers %";
// find out which markers are:
//0-20%
//20-40%
//40-60%
//60-80%
//80-100%
int twentyPercent = 0;
int fortyPercent = 0;
int sixtyPercent = 0;
int eightyPercent = 0;
int oneHundrerdPercent = 0;
double popSize = db.SubData.Count * 1.0;
double temp;
double counter = 0;
// this is our 100%
double genotypeSize = db.SubData[0].Genotype.Length;
//we iterate over all the population
for (int i = 0; i < this.db.SubData.Count; i++)
{
counter = 0;
//we iterate over the genotype of each person
for (int j = 0; j < this.db.SubData[i].Genotype.Length; j++)
{
if (this.db.SubData[i].GenotypeOk[0, j] == true)
{
counter++;
}
}
//we finished going over the persons genotype divide by the 100 percent and add to the relevant bucket
temp = counter / genotypeSize;
if (temp >= 0.0 && temp < 0.2)
{
twentyPercent++;
}
else if (temp >= 0.2 && temp < 0.4)
{
fortyPercent++;
}
else if (temp >= 0.4 && temp < 0.6)
{
sixtyPercent++;
}
else if (temp >= 0.6 && temp < 0.8)
{
eightyPercent++;
}
else if (temp >= 0.8 && temp <= 1.0)
{
oneHundrerdPercent++;
}
}
//we have all the data now we arrange it in the format the histogram has to accept
List <string> titles = new List <string>();
titles.Add("0-20%");
titles.Add("20-40%");
titles.Add("40-60%");
titles.Add("60-80%");
titles.Add("80-100%");
List <double> values = new List <double>();
values.Add(twentyPercent / popSize);
values.Add(fortyPercent / popSize);
values.Add(sixtyPercent / popSize);
values.Add(eightyPercent / popSize);
values.Add(oneHundrerdPercent / popSize);
histChart.AddColumnSeries(titles, values, ColorConstants.highliteColor);
}
private void Button1_Click(object sender, EventArgs e)
{
DialogResult dialogResult = openFileDialog1.ShowDialog();
if (dialogResult.Equals(DialogResult.OK))
{
StreamReader fileIN;
// fileName = openFileDialog1.FileName;
fileIN = new StreamReader(fileName);
string tableTitle = fileIN.ReadLine();
string[] values;
while (fileIN.Peek() != -1)
{
values = fileIN.ReadLine().Split(',');
vehicleType.Add(values[0]);
vehicleYear2018Sales.Add(Int32.Parse(values[1]));
vehicleYear2019Sales.Add(Int32.Parse(values[2]));
}
fileIN.Close();
}
// Plotting the Data in a graph
//salesBarGraph.Titles.Add(tableName);
//salesBarGraph.Series.Add("2019");
//salesBarGraph.Series[0].Points.DataBindY(vehicleYear2018Sales);
//salesBarGraph.Series[0].LegendText = "2018";
//salesBarGraph.Series[1].Points.DataBindY(vehicleYear2019Sales);
//for (int i = 0; i < vehicleType.Count; i++)
// salesBarGraph.Series[0].Points[i].AxisLabel = vehicleType[i];
//salesBarGraph.SaveImage("VehicleSales.emf", ChartImageFormat.Emf);
//mktShareChart.Titles.Add("Market Share of Vehicles 2019");
//mktShareChart.Series[0].Points.DataBindY(vehicleYear2019Sales);
//mktShareChart.Series[0].LegendText = "2019";
//for (int i=0; i<vehicleType.Count; i++)
//mktShareChart.Series[0].Points[i].AxisLabel = vehicleType[i];
//mktShareChart.SaveImage("Market Share of 2019.emf", ChartImageFormat.Emf);
//Convert Charts To SVG
DataTable table1 = new DataTable("Vehicle Sales 2018 & 2019"), table2 = new DataTable("2019 Market Share");
//table1 = ConvertToDataTable(vehicleYear2018Sales);
//table2 = ConvertToDataTable(vehicleYear2019Sales);
table1.Columns.Add("Type", typeof(string));
table1.Columns.Add("Quantity", typeof(double));
table2.Columns.Add("Type", typeof(string));
table2.Columns.Add("Quantity", typeof(double));
for (int i = 0; i < vehicleYear2018Sales.Count; i++)
{
table1.Rows.Add("2018 " + vehicleType[i], vehicleYear2018Sales[i].ToString());
table1.Rows.Add("2019 " + vehicleType[i], vehicleYear2019Sales[i].ToString());
table2.Rows.Add(vehicleType[i], vehicleYear2019Sales[i].ToString());
}
SVGObject svg = new SVGObject();
HistogramChart his = new HistogramChart(300, 300, table1.Rows.Count);
//his.
// Credits to Gerard Viader
XmlDocument xml = his.GenerateChart(table1, table1.Columns["Type"].ToString(), table1.Columns["Quantity"].ToString());
xml.Save("2018 & 2019 Vehicle Sales.svg");
PieChart pie = new PieChart(500, 500, table2.Rows.Count);
xml = pie.GenerateChart(table2, table2.Columns["Type"].ToString(), table2.Columns["Quantity"].ToString());
xml.Save("2019 Market Share.svg");
//xml = his.GenerateChart(table1, table1.Columns["Type"].ToString(), table1.Columns["2019"].ToString());
//xml.Save("2019 Market Share.svg");
Application.Exit();
}
