/// <summary>
/// 拉伸
/// </summary>
/// <param name="data">图像</param>
/// <param name="band">波段：1~n</param>
public Stretch(byte[,,] data, int band)
{
_posibilities = new double[256];
_bandData = new byte[data.GetLength(1), data.GetLength(2)];
for (int i = 0; i < data.GetLength(1); i++)
{
for (int j = 0; j < data.GetLength(2); j++)
{
_bandData[i, j] = data[band, i, j];
}
}
HistoData hd = new HistoData(_bandData);
// 累计直方图255处为总像素数
long totalPixel = hd.GetAccHistogramData()[255];
for (int i = 0; i < _posibilities.Length; i++)
{
// 乘100化为百分比的值
_posibilities[i] = (100.0) * (hd.GetAccHistogramData()[i]) / (totalPixel * 1.0);
}
StretchImg();
}
/// <summary>
/// 拉伸
/// </summary>
/// <param name="data">图像</param>
/// <param name="band">波段：1~n</param>
public Stretch(byte[,,] data, int band)
{
_posibilities = new double[256];
_bandData = new byte[data.GetLength(1), data.GetLength(2)];
for (int i = 0; i < data.GetLength(1); i++)
{
for (int j = 0; j < data.GetLength(2); j++)
{
_bandData[i, j] = data[band, i, j];
}
}
HistoData hd = new HistoData(_bandData);
// 累计直方图255处为总像素数
long totalPixel = hd.GetAccHistogramData()[255];
for (int i = 0; i < _posibilities.Length; i++)
{
// 乘100化为百分比的值
_posibilities[i] = (100.0) * (hd.GetAccHistogramData()[i]) / (totalPixel * 1.0);
}
StretchImg();
}
public HistoEqualization(RsImage img, int band)
{
_bandData = img.GetPicData(band);
HistoData hd = new HistoData(img, band);
_accData = hd.GetAccHistogramData();
StartEqualization();
}
public HistoEqualization(RsImage img, int band)
{
_bandData = img.GetPicData(band);
HistoData hd = new HistoData(img, band);
_accData = hd.GetAccHistogramData();
StartEqualization();
}
private void PrepStretch()
{
_posibilities = new double[256];
HistoData hd = new HistoData(_bandData);
// 累计直方图255处为总像素数
long totalPixel = hd.GetAccHistogramData()[255];
for (int i = 0; i < _posibilities.Length; i++)
{
// 乘100化为百分比的值
_posibilities[i] = (100.0) * (hd.GetAccHistogramData()[i]) / (totalPixel * 1.0);
}
StretchImg();
}
private void PrepStretch()
{
_posibilities = new double[256];
HistoData hd = new HistoData(_bandData);
// 累计直方图255处为总像素数
long totalPixel = hd.GetAccHistogramData()[255];
for (int i = 0; i < _posibilities.Length; i++)
{
// 乘100化为百分比的值
_posibilities[i] = (100.0)*(hd.GetAccHistogramData()[i])/(totalPixel*1.0);
}
StretchImg();
}
/// <summary>
/// 按照波段号画图
/// </summary>
/// <param name="band">波段号</param>
private void DrawByBand(int band)
{
chart1.Series.Clear();
chart1.Titles.Clear();
HistoData histo = new HistoData(_image, band);
if (_type == 1)
{
chart1.ChartAreas[0].AxisY.Maximum = histo.GetHistogramData().Max() + 1000;
MadeChart(chart1, band, histo.GetHistogramData());
}
else
{
chart1.ChartAreas[0].AxisY.Maximum = histo.GetAccHistogramData().Max() + 1000;
MadeChart(chart1, band, histo.GetAccHistogramData());
}
}
private DataPoint HistoDataToDataPoint(HistoData pf)
{
return(new DataPoint(pf.Date.ToOADate(), pf.Price));
}
private void GetDataButton_Click(object sender, RoutedEventArgs e)
{
bool securityFilled = ((v_ticker1.Text != "") && (v_ticker2.Text != "") && (v_ticker3.Text != "")) ? true : false; // TRUE if v_ticker fields have been indicated
// We first check if dates are correct (dateFrom < dateTo)
if ((DateTime.Compare(Convert.ToDateTime(dateFrom.Text), Convert.ToDateTime(dateTo.Text)) < 0) && (DateTime.Compare(Convert.ToDateTime(dateTo.Text), Convert.ToDateTime(DateTime.Now)) < 0))
{
if (securityFilled)
{
// Then if all number of shares are positive
if ((Convert.ToInt32(v_nbShares1.Text) > 0) && (Convert.ToInt32(v_nbShares2.Text) > 0) && (Convert.ToInt32(v_nbShares3.Text) > 0) &&
(v_nbShares1.Text != "") && (v_nbShares2.Text != "") && (v_nbShares3.Text != ""))
{
try
{
BlgWrapper wrap = new BlgWrapper();
List <string> tickers = new List <string>();
List <string> fields = new List <string>();
List <int> nbShares = new List <int>();
MainModel mm = GridMain.DataContext as MainModel;
ResultModel rm = GridResult.DataContext as ResultModel;
rm.DateTo = Convert.ToDateTime(dateTo.Text);
rm.DateFrom = Convert.ToDateTime(dateFrom.Text);
// Adding security & number of shares to the list of data we will download
tickers.Add(v_ticker1.Text);
tickers.Add(v_ticker2.Text);
tickers.Add(v_ticker3.Text);
nbShares.Add(Convert.ToInt32(v_nbShares1.Text));
nbShares.Add(Convert.ToInt32(v_nbShares2.Text));
nbShares.Add(Convert.ToInt32(v_nbShares3.Text));
fields.Add("PX_LAST"); // Data obtain from this Bloomberg fields will be plotted on the reporting
Dictionary <string, Dictionary <string, List <HistoData> > > res_histo2 = new Dictionary <string, Dictionary <string, List <HistoData> > >();
List <string> _ticker;
List <List <HistoData> > histoPX = new List <List <HistoData> >();
// Download data for each security
foreach (string ticker in tickers)
{
_ticker = new List <string>();
_ticker.Add(ticker);
if (wrap.GetHistoricalData(_ticker, fields, BlgPeriodOpt.periodicity_sel, BlgPeriods.daily, rm.DateFrom, rm.DateTo))
{
res_histo2 = wrap.ResultHisto;
List <HistoData> result = res_histo2[fields.First()].Values.First();
histoPX.Add(result);
}
else
{
MessageBox.Show("No data collected for the security " + ticker);
return;
}
}
// Get the number of rows of the smallest List<HistoData>
int numberOfRows = histoPX[0].Count;
foreach (List <HistoData> hd in histoPX)
{
if (hd.Count < numberOfRows)
{
numberOfRows = hd.Count;
}
}
#region COMPUTING THE PERFORMANCE OF THE PORTFOLIO FOR GRAPH
List <double> value_portfolio = new List <double>();
double sum = 0;
for (int i = 0; i < numberOfRows; i++)
{
sum = 0;
for (int j = 0; j < histoPX.Count; j++) //histoPX.Count = number of tickers
{
sum += histoPX[j][i].Price * nbShares[j];
}
value_portfolio.Add(sum);
}
List <double> perf_portfolio = new List <double>();
perf_portfolio.Add(0);
//compute the perf of the portfolio
for (int i = 1; i < numberOfRows; i++)
{
perf_portfolio.Add((value_portfolio[i] / value_portfolio[i - 1]) - 1);
}
rm.Donnees1 = new List <HistoData>();
for (int i = 0; i < perf_portfolio.Count; i++)
{
HistoData data = new HistoData(res_histo2[fields.First()].Values.First()[i].Date, perf_portfolio[i]);
rm.Donnees1.Add(data);
}
graph_perf.ItemsSource = null;
graph_perf.Items.Clear();
graph_perf.ItemsSource = rm.DonneesChartable;
#endregion
#region COMPUTING THE VOLATILITY OF THE PORTFOLIO FOR GRAPH
rm.Donnees1 = new List <HistoData>();
for (int i = 0; i < numberOfRows; i++)
{
HistoData data = new HistoData(res_histo2[fields.First()].Values.First()[i].Date, Volatility(histoPX, nbShares, i));
rm.Donnees1.Add(data);
}
graph_volat.ItemsSource = null;
graph_volat.Items.Clear();
graph_volat.ItemsSource = rm.DonneesChartable;
#endregion
#region COMPUTING PERFOMANCE OF EACH SECURITY FOR GRAPH
// Perf of first security
rm.Donnees1 = new List <HistoData>();
HistoData hdTMP = new HistoData(histoPX[0][0].Date, 0);
rm.Donnees1.Add(hdTMP);
for (int i = 1; i < histoPX[0].Count; i++)
{
hdTMP = new HistoData(histoPX[0][i].Date, (histoPX[0][i].Price / histoPX[0][i - 1].Price) - 1);
rm.Donnees1.Add(hdTMP);
}
graph_1.ItemsSource = null;
graph_1.Items.Clear();
graph_1.ItemsSource = rm.DonneesChartable;
// Perf of second security
rm.Donnees1 = new List <HistoData>();
hdTMP = new HistoData(histoPX[1][0].Date, 0);
rm.Donnees1.Add(hdTMP);
for (int i = 1; i < histoPX[1].Count; i++)
{
hdTMP = new HistoData(histoPX[1][i].Date, (histoPX[1][i].Price / histoPX[1][i - 1].Price) - 1);
rm.Donnees1.Add(hdTMP);
}
graph_2.ItemsSource = null;
graph_2.Items.Clear();
graph_2.ItemsSource = rm.DonneesChartable;
// Perf of third security
rm.Donnees1 = new List <HistoData>();
hdTMP = new HistoData(histoPX[2][0].Date, 0);
rm.Donnees1.Add(hdTMP);
for (int i = 1; i < histoPX[2].Count; i++)
{
hdTMP = new HistoData(histoPX[2][i].Date, (histoPX[2][i].Price / histoPX[2][i - 1].Price) - 1);
rm.Donnees1.Add(hdTMP);
}
graph_3.ItemsSource = null;
graph_3.Items.Clear();
graph_3.ItemsSource = rm.DonneesChartable;
#endregion
#region COMPUTING THE INITIAL AND LAST VALUES OF THE PORTFOLIO AND THE P&L
double price_portfolio_begin = 0;
for (int i = 0; i < histoPX.Count; i++)
{
price_portfolio_begin += histoPX[i][0].Price * nbShares[i];
}
double price_portfolio_end = price_portfolio_begin;
for (int i = 0; i < perf_portfolio.Count; i++)
{
price_portfolio_end *= 1 + perf_portfolio[i];
}
v_priceportofolio_end.Text = Math.Round(price_portfolio_end, 2).ToString(); // We keep two significant digits
v_priceportofolio_begin.Text = Math.Round(price_portfolio_begin, 2).ToString();
// Compute P&L = Last_value - Initial_value
v_pl.Text = Math.Round(price_portfolio_end - price_portfolio_begin, 2).ToString();
if (price_portfolio_begin - price_portfolio_end >= 0)
{
v_pl.Background = Brushes.Red; // Case of negative P&L
}
else
{
v_pl.Background = Brushes.Green; // Case of postivie P&L
}
#endregion
// Once the reporting is complete, we can print it
PrintButton.IsEnabled = true;
}
catch (Exception error)
{
MessageBox.Show(error.Message);
}
}
else
{
MessageBox.Show("Enter positive values for the number of parts !");
}
}
else
{
MessageBox.Show("Please fill in all the required fields");
}
}
else
{
MessageBox.Show("Please verify dates");
}
}
