/// <summary>
/// Drawing plot of a given regression
/// </summary>
/// <param name="container"></param>
private void DrawPlot(RegressionContainer container)
{
AbstractRegression regression = container.Regression;
Brush brush = colorValuePairs[container.BrushKeyValue];
int predictDays = container.PredictDays;
double min = regression.yVals.Min();
double max = regression.yVals.Max();
TopYLabel.Content = $"{max:f2}";
BottomYLabel.Content = $"{min:f2}";
double height = max - min;
MiddleYLabel.Content = $"{(min + max) / 2.0:f2}";
double predictCoefficient = 1 + (double)predictDays / regression.xVals.Length;
double width = regression.xVals.Length;
double heightCoefficient = PlotCanvas.ActualHeight / (height * predictCoefficient);
double widthCoefficient = PlotCanvas.ActualWidth / (width * predictCoefficient);
Line line = new Line
{
Y2 = Math.Min(PlotCanvas.ActualHeight,
PlotCanvas.ActualHeight - heightCoefficient * (regression.PredictY(0.1) - min)),
X2 = 0.1 * widthCoefficient,
HorizontalAlignment = HorizontalAlignment.Left,
VerticalAlignment = VerticalAlignment.Center,
StrokeThickness = 1.25,
Stroke = brush
};
for (double i = 0.1; i < regression.xVals.Length * predictCoefficient; i += 0.5)
{
double lastY = line.Y2;
double lastX = line.X2;
line = new Line
{
Y1 = lastY,
X1 = lastX,
Y2 = Math.Min(PlotCanvas.ActualHeight,
PlotCanvas.ActualHeight - heightCoefficient * (regression.PredictY(i) - min)),
X2 = i * widthCoefficient,
HorizontalAlignment = HorizontalAlignment.Left,
VerticalAlignment = VerticalAlignment.Center,
StrokeThickness = 1.25,
Stroke = brush
};
PlotCanvas.Children.Add(line);
}
}
/// <summary>
/// Drawing source values
/// </summary>
/// <param name="container"></param>
private void DrawPoints(RegressionContainer container)
{
AbstractRegression regression = container.Regression;
int predictDays = container.PredictDays;
double min = regression.yVals.Min();
double max = regression.yVals.Max();
TopYLabel.Content = $"{max:f2}";
BottomYLabel.Content = $"{min:f2}";
double height = max - min;
MiddleYLabel.Content = $"{(min + max) / 2.0:f2}";
double predictCoefficient = 1 + (double)predictDays / regression.xVals.Length;
double width = regression.xVals.Length;
double heightCoefficient = PlotCanvas.ActualHeight / (height * predictCoefficient);
double widthCoefficient = PlotCanvas.ActualWidth / (width * predictCoefficient);
for (int i = 0; i < regression.xVals.Length; i++)
{
Rectangle point = new Rectangle
{
HorizontalAlignment = HorizontalAlignment.Left,
VerticalAlignment = VerticalAlignment.Center,
Stroke = Brushes.Red,
Width = 2,
Height = 2,
Margin = new Thickness(regression.xVals[i] * widthCoefficient,
PlotCanvas.ActualHeight - heightCoefficient * (regression.yVals[i] - min),
regression.xVals[i] * widthCoefficient,
PlotCanvas.ActualHeight - heightCoefficient * (regression.yVals[i] - min))
};
PlotCanvas.Children.Add(point);
}
companyChanged = false;
}
/// <summary>
/// Opening a *.rgrs file
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void OpenButton_Click(object sender, RoutedEventArgs e)
{
OpenFileDialog fileDialog = new OpenFileDialog
{
Filter = "Regression file (*.rgrs)|*.rgrs"
};
if (fileDialog.ShowDialog() == true)
{
try
{
using (FileStream fs = new FileStream(fileDialog.FileName, FileMode.Open))
{
BinaryFormatter bf = new BinaryFormatter();
regressions = (List <RegressionContainer>)bf.Deserialize(fs);
}
}
catch (SerializationException)
{
MessageBox.Show("Сериалиазция не удалась");
ClearButton_Click(this, new RoutedEventArgs());
return;
}
PlotCanvas.Children.Clear();
if (regressions.Count == 0)
{
MessageBox.Show("Выходной файл пуст");
return;
}
foreach (RegressionContainer item in regressions)
{
DrawPlot(item);
}
RegressionContainer rc = regressions[0];
DrawPoints(rc);
int baseDays = rc.Regression.yVals.Length;
TopXLabel.Content = rc.Dates[0];
BottomXLabel.Content = rc.Dates[baseDays - 1];
MiddleXLabel.Content = rc.Dates[baseDays / 2];
BaseTextBox.Text = rc.Regression.xVals.Length.ToString();
PredictTextBox.Text = rc.PredictDays.ToString();
CompanyListBox.SelectedItem = CompanyListBox.Items[CompanyListBox.Items.IndexOf(rc.CompanyName)];
UncheckAll();
for (int i = 0; i < regressions.Count; i++)
{
if (regressions[i].Regression is ExponentialRegression)
{
ExponentialCheck.IsChecked = true;
continue;
}
if (regressions[i].Regression is LogarifmicRegression)
{
LogarifmicCheck.IsChecked = true;
continue;
}
if (regressions[i].Regression is HyperbolicRegression)
{
HyperbolicCheck.IsChecked = true;
continue;
}
if (regressions[i].Regression is SquareRegression)
{
SquareCheck.IsChecked = true;
continue;
}
if (regressions[i].Regression is CubicRegression)
{
CubicCheck.IsChecked = true;
continue;
}
}
}
}
