/// <summary>
/// Generate the monthly returns plot using the python libraries.
/// </summary>
public override string Render()
{
var backtestPoints = ResultsUtil.EquityPoints(_backtest);
var livePoints = ResultsUtil.EquityPoints(_live);
var backtestSeries = new Series <DateTime, double>(backtestPoints.Keys, backtestPoints.Values);
var liveSeries = new Series <DateTime, double>(livePoints.Keys, livePoints.Values);
// Equivalent to python pandas line: `backtestSeries.resample('M').apply(lambda x: x.pct_change().sum())`
var backtestMonthlyReturns = backtestSeries.ResampleEquivalence(date => new DateTime(date.Year, date.Month, 1).AddMonths(1).AddDays(-1))
.Select(kvp => kvp.Value.PercentChange().Sum());
var liveMonthlyReturns = liveSeries.ResampleEquivalence(date => new DateTime(date.Year, date.Month, 1).AddMonths(1).AddDays(-1))
.Select(kvp => kvp.Value.PercentChange().Sum());
var base64 = "";
using (Py.GIL())
{
var backtestResults = new PyDict();
foreach (var kvp in backtestMonthlyReturns.GroupBy(kvp => kvp.Key.Year).GetObservations())
{
var key = kvp.Key.ToStringInvariant();
var values = (kvp.Value * 100).Values.ToList();
while (values.Count != 12)
{
values.Add(double.NaN);
}
backtestResults.SetItem(key.ToPython(), values.ToPython());
}
var liveResults = new PyDict();
foreach (var kvp in liveMonthlyReturns.GroupBy(kvp => kvp.Key.Year).GetObservations())
{
var key = kvp.Key.ToStringInvariant();
var values = (kvp.Value * 100).Values.ToList();
while (values.Count != 12)
{
values.Add(double.NaN);
}
liveResults.SetItem(key.ToPython(), values.ToPython());
}
base64 = Charting.GetMonthlyReturns(backtestResults, liveResults);
}
return(base64);
}
/// <summary>
/// Generate the monthly returns plot using the python libraries.
/// </summary>
public override string Render()
{
var backtestPoints = ResultsUtil.EquityPoints(_backtest);
var livePoints = ResultsUtil.EquityPoints(_live);
var backtestSeries = new Series <DateTime, double>(backtestPoints.Keys, backtestPoints.Values);
var liveSeries = new Series <DateTime, double>(livePoints.Keys, livePoints.Values);
// Equivalent to python pandas line: `backtestSeries.resample('M').apply(lambda x: x.pct_change().sum())`
var backtestMonthlyReturns = backtestSeries.ResampleEquivalence(date => new DateTime(date.Year, date.Month, 1).AddMonths(1).AddDays(-1))
.Select(kvp => kvp.Value.TotalReturns());
var liveMonthlyReturns = liveSeries.ResampleEquivalence(date => new DateTime(date.Year, date.Month, 1).AddMonths(1).AddDays(-1))
.Select(kvp => kvp.Value.TotalReturns());
var base64 = "";
using (Py.GIL())
{
var backtestResults = new PyDict();
foreach (var kvp in backtestMonthlyReturns.GroupBy(kvp => kvp.Key.Year).GetObservations())
{
var key = kvp.Key.ToStringInvariant();
var monthlyReturns = kvp.Value * 100;
var values = new List <double>();
for (var i = 1; i <= 12; i++)
{
var returns = monthlyReturns.Where(row => row.Key.Month == i);
if (!returns.IsEmpty)
{
values.Add(returns.FirstValue());
continue;
}
values.Add(double.NaN);
}
backtestResults.SetItem(key.ToPython(), values.ToPython());
}
var liveResults = new PyDict();
foreach (var kvp in liveMonthlyReturns.GroupBy(kvp => kvp.Key.Year).GetObservations())
{
var key = kvp.Key.ToStringInvariant();
var monthlyReturns = kvp.Value * 100;
var values = new List <double>();
for (var i = 1; i <= 12; i++)
{
var returns = monthlyReturns.Where(row => row.Key.Month == i);
if (!returns.IsEmpty)
{
values.Add(returns.FirstValue());
continue;
}
values.Add(double.NaN);
}
liveResults.SetItem(key.ToPython(), values.ToPython());
}
base64 = Charting.GetMonthlyReturns(backtestResults, liveResults);
}
return(base64);
}