private static int GetBest(string method, Dictionary <string, IEnumerable <ForecastResult> > forecast, float actual)
{
if (forecast == null || !forecast.Any())
{
return(0);
}
ForecastResult best = null;
float minErr = float.MaxValue;
foreach (var fr in forecast[method])
{
// TODO: MAPE ?
var currErr = Math.Abs(fr.Result[0] - actual);
if (currErr < minErr)
{
minErr = currErr;
best = fr;
}
}
return(best?.WindowOffset ?? 0);
}
} // pure static class
/// <summary>
/// Raw-level ARIMA forecasting function.
/// </summary>
/// <param name="data"> UNMODIFIED, list of double numbers representing time-series with constant time-gap </param>
/// <param name="forecastSize"> integer representing how many data points AFTER the data series to be
/// forecasted </param>
/// <param name="params"> ARIMA parameters </param>
/// <returns> a ForecastResult object, which contains the forecasted values and/or error message(s) </returns>
//JAVA TO C# CONVERTER WARNING: 'final' parameters are not available in .NET:
//ORIGINAL LINE: public static TimeSeries.Forecast.TimeSeries.Arima.struct.ForecastResult forecast_arima(final double[] data, final int forecastSize, TimeSeries.Forecast.TimeSeries.Arima.struct.ArimaParams params)
public static ForecastResult forecast_arima(double[] data, int forecastSize, ArimaParams @params)
{
try
{
int p = @params.p;
int d = @params.d;
int q = @params.q;
int P = @params.P;
int D = @params.D;
int Q = @params.Q;
int m = @params.m;
ArimaParams paramsForecast = new ArimaParams(p, d, q, P, D, Q, m);
ArimaParams paramsXValidation = new ArimaParams(p, d, q, P, D, Q, m);
// estimate ARIMA model parameters for forecasting
ArimaModel fittedModel = ArimaSolver.estimateARIMA(paramsForecast, data, data.Length, data.Length + 1);
// compute RMSE to be used in confidence interval computation
double rmseValidation = ArimaSolver.computeRMSEValidation(data, ForecastUtil.testSetPercentage, paramsXValidation);
fittedModel.RMSE = rmseValidation;
ForecastResult forecastResult = fittedModel.Forecast(forecastSize);
// populate confidence interval
forecastResult.Sigma2AndPredicationInterval = fittedModel.Params;
// add logging messages
forecastResult.Log("{" + "\"Best ModelInterface Param\" : \"" + fittedModel.Params.summary() + "\"," + "\"Forecast Size\" : \"" + forecastSize + "\"," + "\"Input Size\" : \"" + data.Length + "\"" + "}");
// successfully built ARIMA model and its forecast
return(forecastResult);
}
catch (Exception ex)
{
// failed to build ARIMA model
throw new Exception("Failed to build ARIMA forecast: " + ex.Message);
}
}
private double[] CommonTestSimpleForecast(string name, double[] trainingData, double[] trueForecastData, int forecastSize, int p, int d, int q, int P, int D, int Q, int m)
{
//Make forecast
ForecastResult forecastResult = ArimaForecaster.forecast_arima(trainingData, forecastSize, new ArimaParams(p, d, q, P, D, Q, m));
//Get forecast data and confidence intervals
double[] forecast = forecastResult.Forecast;
double[] upper = forecastResult.ForecastUpperConf;
double[] lower = forecastResult.ForecastLowerConf;
//Building output
StringBuilder sb = new StringBuilder();
sb.Append(name).Append(" ****************************************************\n");
sb.Append("Input Params { ").Append("p: ").Append(p).Append(", d: ").Append(d).Append(", q: ").Append(q).Append(", P: ").Append(P).Append(", D: ").Append(D).Append(", Q: ").Append(Q).Append(", m: ").Append(m).Append(" }");
sb.Append("\n\nFitted Model RMSE: ").Append(dbl2str(forecastResult.RMSE));
sb.Append("\n\n TRUE DATA | LOWER BOUND FORECAST UPPER BOUND\n");
for (int i = 0; i < forecast.Length; ++i)
{
sb.Append(dbl2str(trueForecastData[i])).Append(" | ").Append(dbl2str(lower[i])).Append(" ").Append(dbl2str(forecast[i])).Append(" ").Append(dbl2str(upper[i])).Append("\n");
}
sb.Append("\n");
//Compute RMSE against true forecast data
double temp = 0.0;
for (int i = 0; i < forecast.Length; ++i)
{
temp += Math.Pow(forecast[i] - trueForecastData[i], 2);
}
double rmse = Math.Pow(temp / forecast.Length, 0.5);
sb.Append("RMSE = ").Append(dbl2str(rmse)).Append("\n\n");
Console.WriteLine(sb.ToString());
return(forecast);
}
public void test_run()
{
FinancialInstrument instr = controller.get_instrument("SPFB.Si_090101_091231.txt");
TradingStrategy strategy = controller.get_strategy("Test5").Originator;
strategy.subscribe_analyzer(new AnalyzerDirection());
ForecastingModule forecastingModule = new ForecastingModule(strategy, instr);
ForecastResult result = forecastingModule.run();
//result.print();
double profitExepted = -3419;
int numDeal = 5;
TypeDeal expType = TypeDeal.Buy;
DateTime expDateOpen = new DateTime(2009, 5, 13, 10, 49, 0);
DateTime expDateClose = new DateTime(2009, 5, 13, 10, 53, 0);
double expOpenPrice = 32110, expClosePrice = 32094;
TradeDeal tradeDeal = result.get_deal(numDeal);
double actOpenPrice = tradeDeal.OpeningPrice;
double actClosePrice = tradeDeal.ClosingPrice;
DateTime actDateTimeOpen = tradeDeal.DateTimeOpen;
DateTime actDateTimeClose = tradeDeal.DateTimeClose;
Assert.AreEqual(true,
profitExepted == result.CurProfit &&
tradeDeal.Opening == false &&
tradeDeal.Type == expType &&
actOpenPrice == expOpenPrice &&
actClosePrice == expClosePrice &&
actDateTimeOpen == expDateOpen &&
actDateTimeClose == expDateClose);
}
public async Task <IEnumerable <IForecastResult> > GetForecasts(IQuery <string, Forecast> currentQuery)
{
if (currentQuery == null)
{
throw new ArgumentNullException(ErrorMessages.ArgumentNullMessage(nameof(currentQuery)));
}
var tasksToExecute = currentQuery.Queries.Select(queryLocation => UrlProvider.SetLocation(queryLocation).GetUriAsString())
.Select(urlToCall => Client.GetForecastAsync(urlToCall));
var results = await Task.WhenAll(tasksToExecute).ConfigureAwait(false);
return(results.Where(response => response.Any())
.Select(response => response.Single())
.Select(response =>
{
var tempResult = new ForecastResult(response.City.DisplayName);
var Satisfied = response.Forecasts.Where(forecast => currentQuery.IsSatisfiedBy(forecast));
tempResult.AddRange(Satisfied);
return tempResult;
}).
Where(matchedForecast => matchedForecast.ForecastData.Any()) // Filter out, if no match was found
.ToList());
}
//public List<sp_Forecast_GetDailyAvereageProductTransactions_Result> GetDailyAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetDailyAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetDailyTimeSpecificAvereageProductTransactions_Result> GetDailyTimeSpecificAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetDailyTimeSpecificAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetWeeklyAverageTransactions_Result> GetWeeklyAverageTransactions()
//{
// var result = db.sp_Forecast_GetWeeklyAverageTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetWeeklyAvereageProductTransactions_Result> GetWeeklyAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetWeeklyAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountYearDayByProductId_Result> GetProductCountYearDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountYearDayByProductId(productId);
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountMonthDayByProductId_Result> GetProductCountMonthDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountMonthDayByProductId(productId);
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountDayByProductId_Result> GetProductCountDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountDayByProductId(productId);
// return result.ToList();
//}
#endregion
#region R_Related
public ForecastResult ForecastByMethod(int branchId, int productId, string method, string dataType, int periods)
{
ForecastResult forecastResult = new ForecastResult();
//Methods method1 = (Methods)Enum.Parse(typeof(Methods), method, true);
DataPeriod datatype1 = (DataPeriod)Enum.Parse(typeof(DataPeriod), dataType, true);
//int productId = 1;
//Methods method = Methods.rwf; //meanf(YYMMDD,MMDD,MMWWDD,DD), rtw, rtw(with Drift), Moving AVG,ets, Arima, HoltWinters, msts
//DataPeriod dataType = DataPeriod.Daily;
//int periods = 50;
var values = GetCorrespondingDataByPeriod(datatype1, productId);
//FFCEntities db = new FFCEntities();
//var list = db.sp_Forecast_GetProductCountYearDayByProductId(productId).ToList();
//List<double> values = list.Select(r => Double.Parse(r.Count.ToString())).ToList();
//REngine.SetEnvironmentVariables(@"C:\Program Files\R\R-2.13.1\bin\i386");
//SetupPath();
//Log();
REngine.SetEnvironmentVariables();
// There are several options to initialize the engine, but by default the following suffice:
REngine engine = REngine.GetInstance();
//engine.Initialize();
// .NET Framework array to R vector.
//NumericVector testTs = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99, 1000 });
//NumericVector testTs = engine.CreateNumericVector(new double[] { 10, 20, 30, 40, 50 });
NumericVector data = engine.CreateNumericVector(values);
engine.SetSymbol("data", data);
//auto arima for monthly
engine.Evaluate("tsValue <- ts(data, frequency=160, start=c(2013.5))");
engine.Evaluate("library(forecast)");
engine.Evaluate(String.Format("Fit <- {0}(tsValue)", method.ToString())); // Fit <- Arima(tsValue)
//MethodManipulation(engine, method);
engine.Evaluate(String.Format("fcast <- forecast(Fit, h={0})", periods));
string image = PlotForecast(engine, method.ToString());
//var a = engine.Evaluate("fcast <- forecast(tsValue, h=5)").AsCharacter();
NumericVector forecasts = engine.Evaluate("fcast$mean").AsNumeric();
//NumericVector forecasts = engine.Evaluate("fcast$lower[,2]").AsNumeric();
forecastResult.BranchId = branchId;
forecastResult.ProductId = productId;
forecastResult.Method = db.Forecast_Methods.Where(r => r.ForecastIdentifier == method).Select(a => a.ForecastMethod).FirstOrDefault();
forecastResult.DatePeriod = datatype1.ToString();
forecastResult.ForecastPeriod = periods;
forecastResult.Values = forecasts.ToList();
forecastResult.ImagePath = "~/Content/Images/" + image;
//foreach (var item in forecasts)
//{
// Console.WriteLine(item);
//}
//engine.Dispose();
return(forecastResult);
}
/// <summary>
/// Gets the best weather of the forecast that is 5 times of three hours periods.
/// </summary>
/// <param name="json"></param>
/// <returns></returns>
public static ForecastResult GetBestWeather(string destination, string json, int daysrange)
{
var result = JsonConvert.DeserializeObject <WeatherForecast>(json);
WeatherForecast forecast = result;
ForecastResult bestweather = new ForecastResult();
var currentWeather = string.Empty;
var choosenWeather = string.Empty;
Dictionary <int, string> _storedWeather = new Dictionary <int, string>();
// Here we got the selected daysrange we have choosen by the slider in the frontend.
int timespan = FormatFunction.GetTimespan(daysrange);
// Here we get the weather of the forecast list from the json object and store it in a dictionary
for (var i = 0; i < timespan; i++)
{
if (forecast.list[i].weather[0].Main == WeatherType.Clear.ToString())
{
// Gets the current weather if weather is Clear
var key = i;
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
choosenWeather = currentWeather;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
else
{
if (forecast.list[i].weather[0].Main == WeatherType.Clouds.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Fog.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Drizzle.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Rain.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Thunderstorm.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Snow.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
}
}
if (choosenWeather != WeatherType.Clear.ToString())
{
var firstcloud = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Clouds.ToString());
//If best weather is cloads
if (firstcloud.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstcloud.Value)
{
choosenWeather = WeatherType.Clouds.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
if (choosenWeather != WeatherType.Clouds.ToString())
{
//If best weather is fog
var firstfog = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Fog.ToString());
if (firstfog.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstfog.Value)
{
choosenWeather = WeatherType.Fog.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
}
if (choosenWeather != WeatherType.Clouds.ToString())
{
if (choosenWeather != WeatherType.Fog.ToString())
{
//If best weather is drizzle
var firstdrizzle = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Drizzle.ToString());
if (firstdrizzle.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstdrizzle.Value)
{
choosenWeather = WeatherType.Drizzle.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
}
}
if (choosenWeather != WeatherType.Drizzle.ToString())
{
if (choosenWeather != WeatherType.Fog.ToString())
{
if (choosenWeather != WeatherType.Clouds.ToString())
{
//If best weather is rain
var firstrain = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Rain.ToString());
if (firstrain.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstrain.Value)
{
choosenWeather = WeatherType.Rain.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
}
}
}
if (choosenWeather != WeatherType.Rain.ToString())
{
if (choosenWeather != WeatherType.Drizzle.ToString())
{
if (choosenWeather != WeatherType.Fog.ToString())
{
if (choosenWeather != WeatherType.Clouds.ToString())
{
//If best weather is thunderstorm
var firstthunderstorm = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Thunderstorm.ToString());
if (firstthunderstorm.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstthunderstorm.Value)
{
choosenWeather = WeatherType.Thunderstorm.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
}
}
}
}
if (choosenWeather != WeatherType.Thunderstorm.ToString())
{
if (choosenWeather != WeatherType.Rain.ToString())
{
if (choosenWeather != WeatherType.Drizzle.ToString())
{
if (choosenWeather != WeatherType.Fog.ToString())
{
if (choosenWeather != WeatherType.Clouds.ToString())
{
//If best weather is snow
var firstsnow = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Snow.ToString());
foreach (var item in _storedWeather)
{
if (item.Value == firstsnow.Value)
{
choosenWeather = WeatherType.Snow.ToString();
var key = item.Key;
GetCurrentBestWeather(key, bestweather, forecast);
break;
}
}
}
}
}
}
}
}
return(bestweather);
}
/// <summary>
/// Gets the worst weather of the forecast that is 8 times of three hours periods.
/// </summary>
/// <param name="json"></param>
/// <returns></returns>
public static ForecastResult GetWorstWeather(string destination, string json, int daysrange)
{
var result = JsonConvert.DeserializeObject <WeatherForecast>(json);
WeatherForecast forecast = result;
ForecastResult worstweather = new ForecastResult();
var currentWeather = string.Empty;
var currentDescription = string.Empty;
var choosenWeather = string.Empty;
Dictionary <int, string> _storedWeather = new Dictionary <int, string>();
// Here we got the selected daysrange we have choosen by the slider in the frontend.
int timespan = FormatFunction.GetTimespan(daysrange);
// Here we get the weather of the forecast list from the json object and store it in a dictionary */
if (forecast != null)
{
for (var i = 0; i < timespan; i++)
{
if (forecast.list[i].weather[0].Main == WeatherType.Snow.ToString())
{
var key = i;
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
choosenWeather = currentWeather;
GetCurrentWorstWeather(key, worstweather, forecast);
}
else
{
if (forecast.list[i].weather[0].Main == WeatherType.Clear.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Clouds.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Fog.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Drizzle.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Rain.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
if (forecast.list[i].weather[0].Main == WeatherType.Thunderstorm.ToString())
{
currentWeather = string.Format("{0}", forecast.list[i].weather[0].Main);
_storedWeather.Add(i, currentWeather);
}
}
}
// If thunderstorm is the worst weather in the forecast
if (choosenWeather != WeatherType.Snow.ToString())
{
// Here we got the first thunderstorm in the forecast
var firstthunderstorm = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Thunderstorm.ToString());
if (firstthunderstorm.Value != null)
{
foreach (var item in _storedWeather)
{
// Here we will got the matching item to the first thunderstorm object in the forecast
if (item.Value == firstthunderstorm.Value)
{
// Now we set a value of choosenWeather
choosenWeather = WeatherType.Thunderstorm.ToString();
var key = item.Key;
// Here we sets the values to the returning object worstweather
GetCurrentWorstWeather(key, worstweather, forecast);
break;
}
}
}
}
// If rain is the worst weather in the forecast
if (choosenWeather != WeatherType.Snow.ToString())
{
if (choosenWeather != WeatherType.Thunderstorm.ToString())
{
var firstrain = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Rain.ToString());
if (firstrain.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstrain.Value)
{
choosenWeather = WeatherType.Rain.ToString();
var key = item.Key;
GetCurrentWorstWeather(key, worstweather, forecast);
break;
}
}
}
}
}
if (choosenWeather != WeatherType.Snow.ToString())
{
if (choosenWeather != WeatherType.Thunderstorm.ToString())
{
if (choosenWeather != WeatherType.Rain.ToString())
{
// If Drizzle is the worst weather in the forecast
var firstDrizzle = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Drizzle.ToString());
if (firstDrizzle.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstDrizzle.Value)
{
choosenWeather = WeatherType.Drizzle.ToString();
var key = item.Key;
GetCurrentWorstWeather(key, worstweather, forecast);
break;
}
}
}
}
}
}
if (choosenWeather != WeatherType.Snow.ToString())
{
if (choosenWeather != WeatherType.Thunderstorm.ToString())
{
if (choosenWeather != WeatherType.Rain.ToString())
{
if (choosenWeather != WeatherType.Drizzle.ToString())
{
// If fog is the worst weather at the forecast
var firstFog = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Fog.ToString());
if (firstFog.Value != null)
{
foreach (var item in _storedWeather)
{
if (item.Value == firstFog.Value)
{
choosenWeather = WeatherType.Fog.ToString();
var key = item.Key;
GetCurrentWorstWeather(key, worstweather, forecast);
break;
}
}
}
}
}
}
}
if (choosenWeather != WeatherType.Snow.ToString())
{
if (choosenWeather != WeatherType.Thunderstorm.ToString())
{
if (choosenWeather != WeatherType.Rain.ToString())
{
if (choosenWeather != WeatherType.Drizzle.ToString())
{
if (choosenWeather != WeatherType.Fog.ToString())
{
// If it is clouds as the worst weather at the forecast
var firstcloud = _storedWeather.FirstOrDefault(x => x.Value == WeatherType.Clouds.ToString());
foreach (var item in _storedWeather)
{
if (item.Value == firstcloud.Value)
{
choosenWeather = WeatherType.Clouds.ToString();
var key = item.Key;
GetCurrentWorstWeather(key, worstweather, forecast);
break;
}
}
}
}
}
}
}
}
return(worstweather);
}
public ForecastResult Forecast(DateTime forecastDate)
{
int year = forecastDate.Year;
State[] states = GetStates().ToArray();
Poll[] polls = GetPolls(forecastDate).ToArray();
Candidate[] candidates = GetCandidates(year).ToArray();
StateElectionHistory[] history = GetElectionHistory().ToArray();
(decimal partisanSwing, string currentPartisanship) =
GenerateSwing(forecastDate, GetElectionDate(forecastDate));
Dictionary <string, int> votes = candidates.ToDictionary(candidate => candidate.Name, candidate => 0);
var finalResult = new ForecastResult();
foreach (State state in states)
{
StateElectionHistory stateHistory = history.FirstOrDefault(h => h.State == state.Name);
if (stateHistory != null)
{
IEnumerable <StateElectionHistory.Election> elections =
stateHistory.Elections.Where(e => e.Year < year).ToArray();
var stateLean = new Dictionary <string, decimal>();
foreach (Candidate candidate in candidates)
{
decimal runningTotal = 0;
decimal totalWeight = 0;
foreach (StateElectionHistory.Election election in elections)
{
var weight = (decimal)System.Math.Pow(10.0 / (year - election.Year), 2);
totalWeight += weight;
runningTotal +=
(election.Results.FirstOrDefault(r => r.Party == candidate.Party)?.Pct ?? 0) * weight;
}
Poll[] statePolls = polls.Where(p => p.State == state.Name).ToArray();
if (statePolls.Any())
{
foreach (Poll poll in statePolls)
{
(decimal result, decimal weight) = GetGuassian(poll, candidate.Name, forecastDate);
runningTotal += result;
totalWeight += weight;
}
}
decimal endPct = runningTotal / totalWeight;
endPct += currentPartisanship == candidate.Party ? partisanSwing : -partisanSwing;
stateLean.Add(candidate.Party, endPct);
}
string winningParty = stateLean.FirstOrDefault(l => l.Value == stateLean.Values.Max()).Key;
Candidate winner = candidates.FirstOrDefault(c => c.Party == winningParty);
if (winner != null)
{
votes[winner.Name] += state.EcVotes;
finalResult.Results.Add(new CandidateResult
{
State = state.Name,
Candidate = winner.Name,
WinPercent = 100
});
}
}
}
finalResult.Results.Add(new CandidateResult
{
State = "",
Candidate = votes.FirstOrDefault(v => v.Value == votes.Values.Max()).Key,
WinPercent = 100
});
return(finalResult);
}
private static void ShowForecast(ForecastResult result)
{
Console.WriteLine($"Date: {result.Date} Temperature: {result.TemperatureC} Summary: {result.Summary} Golfable? {(result.CanYouPlayGolf ? "Yes" : "No")}");
}
