Data
DataManager.cs
// *************************************************************************************
// SCICHART® Copyright SciChart Ltd. 2011-2021. All rights reserved.
//
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// Sales: [email protected]
//
// DataManager.cs is part of SCICHART®, High Performance Scientific Charts
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//
// This source code is protected by international copyright law. Unauthorized
// reproduction, reverse-engineering, or distribution of all or any portion of
// this source code is strictly prohibited.
//
// This source code contains confidential and proprietary trade secrets of
// SciChart Ltd., and should at no time be copied, transferred, sold,
// distributed or made available without express written permission.
// *************************************************************************************
using System;
using System.Collections.Generic;
using System.Globalization;
using System.IO;
using System.IO.Compression;
using System.Linq;
using System.Reflection;
using System.Threading.Tasks;
using System.Windows.Media;
using Lidar3DPointCloudDemo;
using SciChart.Examples.ExternalDependencies.Common;
namespace SciChart.Examples.ExternalDependencies.Data
{
public clast DataManager : IDataManager
{
private readonly IDictionary _dataSets = new Dictionary();
private readonly List _acousticPlotData = new List();
private static readonly DataManager _instance = new DataManager();
private IList _availableInstruments;
private IDictionary _availableTimeFrames;
private Random _random = new Random(0);
public static DataManager Instance
{
get { return _instance; }
}
private static string ResourceDirectory
{
get
{
return "SciChart.Examples.ExternalDependencies.Resources.Data";
}
}
public void SetRandomSeed(int seed)
{
_random = new Random(seed);
}
public double GetGaussianRandomNumber(double mean, double stdDev)
{
double u1 = _random.NextDouble(); //these are uniform(0,1) random doubles
double u2 = _random.NextDouble();
double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) *
Math.Sin(2.0 * Math.PI * u2); //random normal(0,1)
double randNormal =
mean + stdDev * randStdNormal; //random normal(mean,stdDev^2)
return randNormal;
}
public PriceSeries GetPriceData(string dataset, TimeFrame timeFrame)
{
return GetPriceData(string.Format("{0}_{1}", dataset, timeFrame));
}
public DoubleSeries GetDampedSinewave(double amplitude, double dampingFactor, int pointCount, int freq = 10)
{
return GetDampedSinewave(0, amplitude, 0.0, dampingFactor, pointCount, freq);
}
public double[] GetDampedSinewaveYData(double amplitude, double dampingFactor, int pointCount, int freq = 10)
{
return GetDampedSinewaveYData(0, amplitude, 0.0, dampingFactor, pointCount, freq);
}
public DoubleSeries GetSinewave(double amplitude, double phase, int pointCount, int freq = 10)
{
return GetDampedSinewave(0, amplitude, phase, 0.0, pointCount, freq);
}
public double[] GetSinewaveYData(double amplitude, double phase, int pointCount, int freq = 10)
{
return GetDampedSinewaveYData(0, amplitude, phase, 0.0, pointCount, freq);
}
public DoubleSeries GetNoisySinewave(double amplitude, double phase, int pointCount, double noiseAmplitude)
{
var sinewave = GetSinewave(amplitude, phase, pointCount);
// Add some noise
for (int i = 0; i < pointCount; i++)
{
sinewave[i].Y += (_random.NextDouble() * noiseAmplitude) - (noiseAmplitude * 0.5);
}
return sinewave;
}
public double[] GetNoisySinewaveYData(double amplitude, double phase, int pointCount, double noiseAmplitude)
{
var sinewave = GetSinewaveYData(amplitude, phase, pointCount);
// Add some noise
for (int i = 0; i < pointCount; i++)
{
sinewave[i] += (_random.NextDouble() * noiseAmplitude) - (noiseAmplitude * 0.5);
}
return sinewave;
}
public DoubleSeries GetDampedSinewave(int pad, double amplitude, double phase, double dampingFactor, int pointCount, int freq = 10)
{
var doubleSeries = new DoubleSeries();
for (int i = 0; i < pad; i++)
{
double time = 10 * i / (double)pointCount;
doubleSeries.Add(new XYPoint() { X = time });
}
for (int i = pad, j = 0; i < pointCount; i++, j++)
{
var xyPoint = new XYPoint();
double time = 10 * i / (double)pointCount;
double wn = 2 * Math.PI / (pointCount / (double)freq);
xyPoint.X = time;
xyPoint.Y = amplitude * Math.Sin(j * wn + phase);
doubleSeries.Add(xyPoint);
amplitude *= 1.0 - dampingFactor;
}
return doubleSeries;
}
public double[] GetDampedSinewaveYData(int pad, double amplitude, double phase, double dampingFactor, int pointCount, int freq = 10)
{
var yValues = new double[pointCount];
for (int i = 0; i < pad; i++)
{
yValues[i] = 0;
}
for (int i = pad, j = 0; i < pointCount; i++, j++)
{
double wn = 2 * Math.PI / (pointCount / (double)freq);
yValues[i] = amplitude * Math.Sin(j * wn + phase);
amplitude *= 1.0 - dampingFactor;
}
return yValues;
}
public DoubleSeries GetFourierSeriesZoomed(double amplitude, double phaseShift, double xStart, double xEnd, int count = 5000)
{
var data = GetFourierSeries(amplitude, phaseShift, count);
int index0 = 0;
int index1 = 0;
for (int i = 0; i < count; i++)
{
if (data.XData[i] > xStart && index0 == 0)
index0 = i;
if (data.XData[i] > xEnd && index1 == 0)
{
index1 = i;
break;
}
}
var result = new DoubleSeries();
var xData = data.XData.Skip(index0).Take(index1 - index0).ToArray();
var yData = data.YData.Skip(index0).Take(index1 - index0).ToArray();
for (int i = 0; i < xData.Length; i++)
{
result.Add(new XYPoint() {X = xData[i], Y = yData[i]});
}
return result;
}
private double GetFourierYValue(double amplitude, double phaseShift, int index, int count)
{
double wn = 2 * Math.PI / (count / 10);
return Math.PI * amplitude *
(Math.Sin(index * wn + phaseShift) +
(0.33 * Math.Sin(index * 3 * wn + phaseShift)) +
(0.20 * Math.Sin(index * 5 * wn + phaseShift)) +
(0.14 * Math.Sin(index * 7 * wn + phaseShift)) +
(0.11 * Math.Sin(index * 9 * wn + phaseShift)) +
(0.09 * Math.Sin(index * 11 * wn + phaseShift)));
}
public DoubleSeries GetFourierSeries(double amplitude, double phaseShift, int count = 5000)
{
var doubleSeries = new DoubleSeries();
for (int i = 0; i < count; i++)
{
doubleSeries.Add(new XYPoint
{
X = 10 * i / (double)count,
Y = GetFourierYValue(amplitude, phaseShift, i, count)
});
}
return doubleSeries;
}
public double[] GetFourierYData(double amplitude, double phaseShift, int count = 5000)
{
var yValues = new double[count];
for (int i = 0; i < count; i++)
{
yValues[i] = GetFourierYValue(amplitude, phaseShift, i, count);
}
return yValues;
}
public DoubleSeries GetFourierSeriesForMountainExample(double amplitude, double phaseShift, int count = 5000)
{
var series = this.GetFourierSeries(amplitude, phaseShift, count);
series.RemoveRange(0, 2);
series.Insert(0, new XYPoint { X = 0.002, Y = 0.02 });
series.Insert(0, new XYPoint { X = 0, Y = 0 });
series.RemoveRange(series.Count-2, 2);
series.Insert(series.Count, new XYPoint { X = 9.996, Y = -0.02 });
series.Insert(series.Count, new XYPoint { X = 9.998, Y = 0 });
return series;
}
public DoubleSeries GenerateEEG(int count, ref double startPhase, double phaseStep)
{
var doubleSeries = new DoubleSeries();
var rand = new Random((int)DateTime.Now.Ticks);
for (int i = 0; i < count; i++)
{
var xyPoint = new XYPoint();
var time = i / (double)count;
xyPoint.X = time;
//double mod = 0.2 * Math.Sin(startPhase);
xyPoint.Y = //mod * Math.Sin(startPhase / 4.9) +
0.05 * (rand.NextDouble() - 0.5) +
1.0;
doubleSeries.Add(xyPoint);
startPhase += phaseStep;
}
return doubleSeries;
}
public DoubleSeries GetSquirlyWave()
{
var doubleSeries = new DoubleSeries();
var rand = new Random(0);
const int COUNT = 1000;
for (int i = 0; i < COUNT; i++)
{
var xyPoint = new XYPoint();
var time = i / (double)COUNT;
xyPoint.X = time;
xyPoint.Y = time * Math.Sin(2 * Math.PI * i / (double)COUNT) +
0.2 * Math.Sin(2 * Math.PI * i / (COUNT / 7.9)) +
0.05 * (rand.NextDouble() - 0.5) +
1.0;
doubleSeries.Add(xyPoint);
}
return doubleSeries;
}
public IEnumerable AvailableInstruments
{
get
{
if (_availableInstruments == null)
{
lock (typeof(DataManager))
{
if (_availableInstruments == null)
{
var astembly = typeof (DataManager).astembly;
_availableInstruments = new List();
foreach (var resourceString in astembly.GetManifestResourceNames())
{
if (resourceString.Contains("_"))
{
string instrumentString = GetSubstring(resourceString, ResourceDirectory + ".", "_");
var instr = Instrument.Parse(instrumentString);
if (!_availableInstruments.Contains(instr))
{
_availableInstruments.Add(instr);
}
}
}
}
}
}
return _availableInstruments;
}
}
private string GetSubstring(string input, string before, string after)
{
int beforeIndex = string.IsNullOrEmpty(before) ? 0 : input.IndexOf(before) + before.Length;
int afterIndex = string.IsNullOrEmpty(after) ? input.Length : input.IndexOf(after) - beforeIndex;
return input.Substring(beforeIndex, afterIndex);
}
public IEnumerable GetAvailableTimeFrames(Instrument forInstrument)
{
if (_availableTimeFrames == null)
{
lock (typeof (DataManager))
{
if (_availableTimeFrames == null)
{
// Initialise the Timeframe dictionary
_availableTimeFrames = new Dictionary();
foreach (var instr in AvailableInstruments)
{
_availableTimeFrames[instr] = new List();
}
var astembly = typeof (DataManager).astembly;
foreach (var resourceString in astembly.GetManifestResourceNames())
{
if (resourceString.Contains("_"))
{
var instrument = Instrument.Parse(GetSubstring(resourceString, ResourceDirectory + ".", "_"));
var timeframe = TimeFrame.Parse(GetSubstring(resourceString, "_", ".csv.gz"));
_availableTimeFrames[instrument].Add(timeframe);
}
}
}
}
}
return _availableTimeFrames[forInstrument];
}
public DoubleSeries GetAcousticChannel(int channelNumber)
{
if (channelNumber > 7)
throw new InvalidOperationException("Only channels 0-7 allowed");
if (_acousticPlotData.Count != 0)
{
return _acousticPlotData[channelNumber];
}
// e.g. resource format: SciChart.Examples.ExternalDependencies.Resources.Data.EURUSD_Daily.csv
var csvResource = string.Format("{0}.{1}", ResourceDirectory, "AcousticPlots.csv.gz");
var ch0 = new DoubleSeries(100000);
var ch1 = new DoubleSeries(100000);
var ch2 = new DoubleSeries(100000);
var ch3 = new DoubleSeries(100000);
var ch4 = new DoubleSeries(100000);
var ch5 = new DoubleSeries(100000);
var ch6 = new DoubleSeries(100000);
var ch7 = new DoubleSeries(100000);
var astembly = typeof(DataManager).astembly;
using (var stream = astembly.GetManifestResourceStream(csvResource))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
line = streamReader.ReadLine();
while (line != null)
{
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
double x = double.Parse(tokens[0], NumberFormatInfo.InvariantInfo);
double y0 = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
double y1 = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
double y2 = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
double y3 = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
double y4 = double.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
double y5 = double.Parse(tokens[6], NumberFormatInfo.InvariantInfo);
double y6 = double.Parse(tokens[7], NumberFormatInfo.InvariantInfo);
double y7 = double.Parse(tokens[8], NumberFormatInfo.InvariantInfo);
ch0.Add(new XYPoint() { X = x, Y = y0 });
ch1.Add(new XYPoint() { X = x, Y = y1 });
ch2.Add(new XYPoint() { X = x, Y = y2 });
ch3.Add(new XYPoint() { X = x, Y = y3 });
ch4.Add(new XYPoint() { X = x, Y = y4 });
ch5.Add(new XYPoint() { X = x, Y = y5 });
ch6.Add(new XYPoint() { X = x, Y = y6 });
ch7.Add(new XYPoint() { X = x, Y = y7 });
line = streamReader.ReadLine();
}
}
_acousticPlotData.AddRange(new[] { ch0, ch1, ch2, ch3, ch4, ch5, ch6, ch7});
return _acousticPlotData[channelNumber];
}
public PriceSeries GetPriceData(string dataset)
{
if (_dataSets.ContainsKey(dataset))
{
return _dataSets[dataset];
}
// e.g. resource format: SciChart.Examples.ExternalDependencies.Resources.Data.EURUSD_Daily.csv
var csvResource = string.Format("{0}.{1}", ResourceDirectory, Path.ChangeExtension(dataset, "csv.gz"));
var priceSeries = new PriceSeries();
priceSeries.Symbol = dataset;
var astembly = typeof(DataManager).astembly;
// Debug.WriteLine(string.Join(", ", astembly.GetManifestResourceNames()));
using (var stream = astembly.GetManifestResourceStream(csvResource))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
var priceBar = new PriceBar();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
priceBar.DateTime = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo);
priceBar.Open = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
priceBar.High = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
priceBar.Low = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
priceBar.Close = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
priceBar.Volume = long.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
priceSeries.Add(priceBar);
line = streamReader.ReadLine();
}
}
_dataSets.Add(dataset, priceSeries);
return priceSeries;
}
public IEnumerable GetTicks()
{
// e.g. resource format: SciChart.Examples.ExternalDependencies.Resources.Data.EURUSD_Daily.csv
var csvResourceZipped = string.Format("{0}.{1}", ResourceDirectory, "TickData.csv.gz");
var ticks = new List();
var astembly = typeof(DataManager).astembly;
// Debug.WriteLine(string.Join(", ", astembly.GetManifestResourceNames()));
using (var stream = astembly.GetManifestResourceStream(csvResourceZipped))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
var tick = new Tick();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
tick.DateTime = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo) +
TimeSpan.Parse(tokens[1], DateTimeFormatInfo.InvariantInfo);
tick.Open = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
tick.High = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
tick.Low = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
tick.Close = double.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
tick.Volume = long.Parse(tokens[7], NumberFormatInfo.InvariantInfo);
ticks.Add(tick);
line = streamReader.ReadLine();
}
}
return ticks;
}
public IList GetVitalSignsData()
{
var csvResourceZipped = string.Format("{0}.{1}", ResourceDirectory, "VitalSignsTrace.csv.gz");
var vitalSignsData = new List();
var astembly = typeof(DataManager).astembly;
using (var stream = astembly.GetManifestResourceStream(csvResourceZipped))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
// Line Format:
// XValue, HeartRate, BloodPressure, BloodVolume, BloodOxygenation
// 3.12833, 0.873118, 0.625403, 0.209285, 0.100243
var tokens = line.Split(',');
vitalSignsData.Add(new VitalSignsData
{
XValue = double.Parse(tokens[0], NumberFormatInfo.InvariantInfo),
ECGHeartRate = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo),
BloodPressure = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo),
BloodVolume = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo),
BloodOxygenation = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo)
});
line = streamReader.ReadLine();
}
}
return vitalSignsData;
}
public IList ComputeMovingAverage(IList prices, int length)
{
double[] result = new double[prices.Count];
for (int i = 0; i < prices.Count; i++)
{
if (i < length)
{
result[i] = double.NaN;
continue;
}
result[i] = AverageOf(prices, i - length, i);
}
return result;
}
private static double AverageOf(IList prices, int from, int to)
{
double result = 0.0;
for (int i = from; i < to; i++)
{
result += prices[i];
}
return result / (to - from);
}
public DoubleSeries GetStraightLine(double gradient, double yIntercept, int pointCount)
{
var doubleSeries = new DoubleSeries(pointCount);
for (int i = 0; i < pointCount; i++)
{
double x = i + 1;
double y = (gradient * x) + yIntercept;
doubleSeries.Add(new XYPoint { X = x, Y = y });
}
return doubleSeries;
}
public double[] GetStraightLineYData(double gradient, double yIntercept, int pointCount)
{
var yValues = new double[pointCount];
for (int i = 0; i < pointCount; i++)
{
yValues[i] = (gradient * (i + 1)) + yIntercept;
}
return yValues;
}
public DoubleSeries GetExponentialCurve(double power, int pointCount)
{
var doubleSeries = new DoubleSeries(pointCount);
double x = 0.00001;
const double fudgeFactor = 1.4;
for(int i = 0; i < pointCount; i++)
{
x *= fudgeFactor;
double y = Math.Pow((double)i + 1, power);
doubleSeries.Add(new XYPoint() {X = x, Y = y});
}
return doubleSeries;
}
public DoubleSeries GetLissajousCurve(double alpha, double beta, double delta, int count=200)
{
// From http://en.wikipedia.org/wiki/Lissajous_curve
// x = Asin(at + d), y = Bsin(bt)
var doubleSeries = new DoubleSeries(count);
for (int i = 0; i < count; i++)
{
double x = Math.Sin(alpha*i*0.1 + delta);
double y = Math.Sin(beta*i*0.1);
doubleSeries.Add(new XYPoint() {X = x, Y = y});
}
return doubleSeries;
}
public DoubleSeries GetButterflyCurve(int count=2000)
{
// From http://en.wikipedia.org/wiki/Butterfly_curve_%28transcendental%29
// x = sin(t) * (e^cos(t) - 2cos(4t) - sin^5(t/12))
// y = cos(t) * (e^cos(t) - 2cos(4t) - sin^5(t/12))
var temp = 0.01;
var doubleSeries = new DoubleSeries(count);
for (int i = 0; i < count; i++)
{
var t = i*temp;
double multiplier = Math.Pow(Math.E, Math.Cos(t)) - 2*Math.Cos(4*t) - Math.Pow(Math.Sin(t/12), 5);
double x = Math.Sin(t)*multiplier;
double y = Math.Cos(t) * multiplier;
doubleSeries.Add(new XYPoint {X = x, Y = y});
}
return doubleSeries;
}
public IEnumerable Offset(IList inputList, double offset)
{
foreach(double value in inputList)
{
yield return value + offset;
}
}
public DoubleSeries GetRandomDoubleSeries(int pointCount)
{
var doubleSeries = new DoubleSeries();
double amplitude = _random.NextDouble() + 0.5;
double freq = Math.PI * (_random.NextDouble() + 0.5) * 10;
double offset = _random.NextDouble() - 0.5;
for(int i = 0; i < pointCount; i++)
{
doubleSeries.Add(new XYPoint() { X=i, Y=offset + amplitude*Math.Sin(freq*i) });
}
return doubleSeries;
}
public double[] GetRandomDoubleData(int pointCount)
{
var doubleData = new double[pointCount];
double amplitude = _random.NextDouble() + 0.5;
double freq = Math.PI * (_random.NextDouble() + 0.5) * 10;
double offset = _random.NextDouble() - 0.5;
for(int i = 0; i < pointCount; i++)
{
doubleData[i] = offset + (amplitude * Math.Sin(freq * i));
}
return doubleData;
}
public Color GetRandomColor()
{
return Color.FromArgb(0xFF, (byte)_random.Next(255), (byte)_random.Next(255), (byte)_random.Next(255));
}
public PriceSeries GetRandomTrades(out List trades, out List news)
{
var priceSeries = new PriceSeries();
trades = new List();
news = new List();
var startDate = new DateTime(2012, 01, 01);
double randomWalk = 0.0;
// Note: Change the value below to increase or decrease the point count and trade frequency
const int Count = 1000;
const uint TradeFrequency = 14;
// Generate the X,Y data with sequential dates on the X-Axis and slightly positively biased random walk on the Y-Axis
for (int i = 0; i < Count; i++)
{
randomWalk += (_random.NextDouble() - 0.498);
priceSeries.Add(new PriceBar(startDate.AddMinutes(i*10), randomWalk, randomWalk, randomWalk, randomWalk, 0));
}
// The random walk is a truly random series, so it may contain negative values. Here we find the minimum and offset it
// so it is always positive.
double yOffset = -priceSeries.CloseData.Min() + _random.NextDouble();
for (int i = 0; i < Count; i++)
{
// Now update with the offset so it is never negative
priceSeries[i].Close += yOffset;
// Every N'th tick create a random trade
if (i % TradeFrequency == 0)
{
var trade = new Trade();
// randomize buy or sell
trade.BuySell = _random.NextDouble() > 0.48 ? BuySell.Buy : BuySell.Sell;
// Set dealprice and date
trade.DealPrice = priceSeries[i].Close;
trade.TradeDate = priceSeries[i].DateTime;
// Set instrument and quansaty
trade.Instrument = Instrument.CrudeOil;
trade.Quansaty = _random.Next(100, 500);
trades.Add(trade);
}
// Every N'th tick create a random news event
if (_random.Next(0, 99) > 95)
{
var newsEvent = new NewsEvent();
newsEvent.EventDate = priceSeries[i].DateTime;
newsEvent.Headline = "OPEC meeting minutes";
newsEvent.Body = "The Organization of the Petroleum Exporting Countries voted today to increase production of Crude oil from its member states";
news.Add(newsEvent);
}
}
return priceSeries;
}
public DoubleSeries GenerateSpiral(double xCentre, double yCentre, double maxRadius, int count)
{
var doubleSeries = new DoubleSeries();
double radius = 0;
double x, y;
double deltaRadius = maxRadius/count;
for (int i = 0; i < count; i++)
{
double sinX = Math.Sin(2*Math.PI*i*0.05);
double cosX = Math.Cos(2*Math.PI*i*0.05);
x = xCentre + radius * sinX;
y = yCentre + radius*cosX;
doubleSeries.Add(new XYPoint() { X = x, Y = y});
radius += deltaRadius;
}
return doubleSeries;
}
public DoubleSeries GetClusteredPoints(double xCentre, double yCentre, double deviation, int count)
{
var doubleSeries = new DoubleSeries();
for (int i = 0; i < count; i++)
{
double x = GetGaussianRandomNumber(xCentre, deviation);
double y = GetGaussianRandomNumber(yCentre, deviation);
doubleSeries.Add(new XYPoint() { X = x, Y = y});
}
return doubleSeries;
}
public IEnumerable GetTradeticks()
{
var dataSource = new List();
var asm = astembly.GetExecutingastembly();
var csvResource = asm.GetManifestResourceNames().Single(x => x.ToUpper(CultureInfo.InvariantCulture).Contains("TRADETICKS.CSV.GZ"));
using (var stream = asm.GetManifestResourceStream(csvResource))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
var data = new TradeData();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
data.TradeDate = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo);
data.TradePrice = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
data.TradeSize = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
dataSource.Add(data);
line = streamReader.ReadLine();
}
}
return dataSource;
}
public List LoadWeatherData()
{
var values = new List();
var asm = astembly.GetExecutingastembly();
var resourceString = asm.GetManifestResourceNames().Single(x => x.Contains("WeatherData.txt.gz"));
using (var stream = asm.GetManifestResourceStream(resourceString))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
var tokens = line.Split(',');
values.Add(new WeatherData
{
// ID, Date, MinTemp, MaxTemp, Rainfall, Sunshine, UVIndex, WindSpd, WindDir, Forecast, LocalStation
ID = int.Parse(tokens[0], NumberFormatInfo.InvariantInfo),
Date = DateTime.Parse(tokens[1], DateTimeFormatInfo.InvariantInfo),
MinTemp = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo),
MaxTemp = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo),
Rainfall = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo),
Sunshine = double.Parse(tokens[5], NumberFormatInfo.InvariantInfo),
UVIndex = int.Parse(tokens[6], NumberFormatInfo.InvariantInfo),
WindSpeed = int.Parse(tokens[7], NumberFormatInfo.InvariantInfo),
WindDirection = (WindDirection) Enum.Parse(typeof(WindDirection), tokens[8]),
Forecast = tokens[9],
LocalStation = bool.Parse(tokens[10])
});
line = streamReader.ReadLine();
}
}
return values;
}
public double[] LoadWaveformData()
{
var values = new List();
var asm = astembly.GetExecutingastembly();
var resourceString = asm.GetManifestResourceNames().Single(x => x.Contains("Waveform.txt.gz"));
using (var stream = asm.GetManifestResourceStream(resourceString))
using (var gz = new GZipStream(stream, CompressionMode.Decompress))
using (var streamReader = new StreamReader(gz))
{
string line = streamReader.ReadLine();
while (line != null)
{
values.Add(double.Parse(line, NumberFormatInfo.InvariantInfo));
line = streamReader.ReadLine();
}
}
return values.ToArray();
}
public async Task GetAscDataAsync(Func colorMapFunction)
{
const string resourceName = "LIDARtq3080DSM2M.asc.gz";
return await AscReader.ReadResourceToAscData(resourceName, colorMapFunction);
}
}
}