public void GetOpenCloseHighLow(string symbl, DateTime start, DateTime end, out TimeSeries open, out TimeSeries close, out TimeSeries high, out TimeSeries low)
{
var a = new Quote(symbl);
XDocument doc = null;
if (Properties.Settings.Default.PollWebAPI) {
doc = a.Fetch(start.Date, end);
if (doc == null) {
throw new Exception();
}
}
open = new TimeSeries(symbl);
close = new TimeSeries(symbl);
high = new TimeSeries(symbl);
low = new TimeSeries(symbl);
if (!Properties.Settings.Default.PollWebAPI) {
open = Open(symbl, start, end, 1);
high = Open(symbl, start, end, 2);
low = Open(symbl, start, end, 3);
close = Open(symbl, start, end, 4);
return;
}
foreach (var quote in doc.Descendants("quote")) {
open.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Open").Value));
close.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Close").Value));
high.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("High").Value));
low.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Low").Value));
}
}
public Histogram(TimeSeries data, double binSize)
{
this.binSize = binSize;
for (int i = 0; i < data.Count(); i++) {
IncrementAt((int)Math.Floor(data[i] / binSize));
}
}
/// <summary>Uses Scott's choice algorithm to assign bin width:
/// http://en.wikipedia.org/wiki/Histogram#Number_of_bins_and_width</summary>
public Histogram(TimeSeries data)
{
var bS = (3.5 * data.StandardDeviation) / Math.Pow(data.Count(), .33333333333333);
if (bS <= 0)
bS = .01;
this.binSize = bS;
for (int i = 0; i < data.Count(); i++) {
IncrementAt((int)Math.Floor(data[i] / binSize));
}
}
public TimeSeries DailyReturns(int i, DateTime start, DateTime end)
{
var r = getReader(i);
TimeSeries ts = new TimeSeries(getTitle(i));
double lastVal = double.NaN;
foreach (var p in r.readData(0, 6, start, end)) {
double y = p.Y / lastVal - 1;
if (lastVal == double.NaN) y = 0;
ts.Add(p.X, y);
lastVal = p.Y;
}
return ts;
}
public TimeSeries Open2(string symbl, DataType type, DateTime start, DateTime end)
{
var a = new Quote(symbl);
XDocument doc = null;
if (Properties.Settings.Default.PollWebAPI) {
doc = a.Fetch(start.Date, end);
if (doc == null) {
throw new Exception();
}
}
TimeSeries ts = new TimeSeries(symbl);
if (type == DataType.AdjClose) {
if (!Properties.Settings.Default.PollWebAPI) {
return Open(symbl, start, end, 6);
}
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Adj_Close").Value));
}
}
if (type == DataType.Volume) {
if (!Properties.Settings.Default.PollWebAPI) {
return Open(symbl, start, end, 5);
}
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Volume").Value));
}
}
if (type == DataType.Close) {
if (!Properties.Settings.Default.PollWebAPI) {
return Open(symbl, start, end, 4);
}
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Close").Value));
}
}
if (type == DataType.Open) {
if (!Properties.Settings.Default.PollWebAPI) {
return Open(symbl, start, end, 1);
}
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Open").Value));
}
}
if (type == DataType.High) {
if (!Properties.Settings.Default.PollWebAPI) {
return Open(symbl, start, end, 2);
}
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("High").Value));
}
}
if (type == DataType.Low) {
foreach (var quote in doc.Descendants("quote")) {
ts.Add(DateTimeAxis.ToDouble(DateTime.Parse(quote.Element("Date").Value)),
double.Parse(quote.Element("Low").Value));
}
}
return ts;
}
public TimeSeries Open(int i, DateTime start, DateTime end, int fieldIdx = 6)
{
TimeSeries ts = new TimeSeries(getTitle(i));
var r = getReader(i);
try {
foreach (var p in r.readData(0, fieldIdx, start, end)) {
ts.Add(p.X, p.Y);
}
}
catch{
}
return ts;
}
public TimeSeries Open(string symbol, DateTime start, DateTime end, int fieldIdx = 6)
{
TimeSeries ts = new TimeSeries(symbol);
var r = getReader(symbol);
try {
foreach (var p in r.readData(0, fieldIdx, start, end)) {
ts.Add(p.X, p.Y);
}
} catch {
}
return ts;
}
public TimeSeries Open(string symbl, DataType type, DateTime start, DateTime end)
{
this.start = start;
this.end = end;
symbl = symbl.ToUpper();
var a = new Quote(symbl);
//var doc = a.Fetch(DateTime.Parse("2010-03-5").Date, DateTime.Parse("2011-03-5"));
TimeSeries ts = new TimeSeries(symbl);
if (type == DataType.AdjClose) {
return Open(symbolIndex[symbl], start, end, 6);
}
if (type == DataType.Volume) {
return Open(symbolIndex[symbl], start, end, 5);
}
if (type == DataType.Close) {
return Open(symbolIndex[symbl], start, end, 4);
}
//if (type == DataType.DailyReturns) {
// return DailyReturns(symbolIndex[symbl], start, end);
//}
throw new Exception();
}
public TimeSeries GetDiffs()
{
double lastVal = double.NaN;
TimeSeries ts = new TimeSeries(this.Name);
///Notice that this for loop iterates forward in time
for (int i = domain.Count() - 1; i >= 0; i--) {
double y = range[i] / lastVal - 1;
if (double.IsNaN(lastVal)) y = 0;
ts.Add(domain[i], y);
lastVal = range[i];
}
return ts;
}
public ScatterSeries CorrelateDailyReturns(TimeSeries ts2)
{
ScatterSeries ss = new ScatterSeries() { MarkerSize = .8, MarkerStroke = OxyColors.Blue, MarkerFill = OxyColors.Blue };
int i = this.DailyReturns.Count() - 1;
int j = ts2.DailyReturns.Count() - 1;
while (i >= 0 && j >= 0) {
double domaini = this.DailyReturns.domain[i];
double domainj = ts2.DailyReturns.domain[j];
if (domaini != domainj) {
if (domaini > domainj) {
i--;
} else { j--; }
continue;
} else {
ss.Points.Add(new ScatterPoint(this.DailyReturns.range[i], ts2.DailyReturns.range[j]));
i--;
j--;
}
}
return ss;
}
public ScatterSeries Correlate2(TimeSeries ts2)
{
ScatterSeries ss = new ScatterSeries() { MarkerSize = .8, MarkerStroke = OxyColors.Blue, MarkerFill = OxyColors.Blue };
bool axis1Direction = this.domain[1] - this.domain[0] > 0;
bool axis2Direction = ts2.domain[1] - ts2.domain[0] > 0;
int i, j;
if (axis1Direction) {
i = this.Count() - 1;
} else {
i = 0;
}
if (axis2Direction) {
j = ts2.Count() - 1;
} else {
j = 0;
}
while (i >= 0 && j >= 0 && i < this.Count() && j < ts2.Count()) {
double domaini = this.domain[i];
double domainj = ts2.domain[j];
if (domaini != domainj) {
if (domaini > domainj) {
//Move i
if (axis1Direction) {
i--;
} else {
i++;
}
} else {
//Move j
if (axis2Direction) {
j--;
} else {
j++;
}
}
continue;
} else {
ss.Points.Add(new ScatterPoint(this.range[i], ts2.range[j]));
//Move both
if (axis1Direction) {
i--;
} else {
i++;
}
if (axis2Direction) {
j--;
} else {
j++;
}
}
}
return ss;
}
private LineSeries getSeries(TimeSeries ts)
{
if (LogarithmicX) {
ts.LogarithmicX();
}
if (LogarithmicY) {
ts.LogarithmicY();
}
if (this.Normalize0) {
return ts.Normalize0();
} else if (this.Normalize1) {
return ts.Normalize1();
} else {
return ts.GetLineSeries();
}
}
