public void Optimise(DateTime fromDate, DateTime toDate)
{
_stakingService.Evaluate(fromDate, toDate);
var history = _marketDataCache.TakeUntil(toDate).ToArray();
// Build 2d array where each cell is sized to has equal data points and probability
var xData = history.Select(_xSelector).ToArray();
var yData = history.Select(_ySelector).ToArray();
var grid = new Grid <List <decimal> >(xData, yData, _parameters.Partitions);
// Place each data point in appropriate cell
var marketDataValues = _ratingService.CalculateMarketDataValues(history);
foreach (var data in history)
{
var x = _xSelector(data);
var y = _ySelector(data);
var cell = grid[x, y];
marketDataValues.TryGetValue(data.Date, out var value);
cell.Add(value);
}
// Determine the average value of each cell
var averages = grid
.Where(x => x.Any())
.Select(GetAverage)
.Distinct()
.ToArray();
var minValue = Convert.ToInt32(Math.Round(averages.Min(), MidpointRounding.ToNegativeInfinity));
var maxValue = Convert.ToInt32(Math.Round(averages.Max(), MidpointRounding.ToPositiveInfinity));
var range = maxValue - minValue;
// Search for optimal buy threshold
var potentials = Enumerable.Range(minValue, range)
.SelectMany(t => Enumerable.Range(2, 8)
.Select(p => new ClusteringParameters
{
Partitions = p,
Threshold = -t,
Grid = grid
}));
var optimal = _searcher.Maximum(potentials, fromDate, toDate);
_parameters = (ClusteringParameters)optimal;
}