public void CouldReadVariantSeries()
{
var sm = new SortedMap <int, string>();
for (int i = 0; i < 100; i++)
{
sm.Add(i, (i * 100).ToString());
}
var vs = new VariantSeries <int, string>(sm);
foreach (var item in vs)
{
System.Console.WriteLine(item.Key.Get <int>() + ": " + item.Value.Get <string>());
}
Assert.AreEqual(Variant.Create(0), vs.First.Key);
Assert.AreEqual(Variant.Create("0"), vs.First.Value);
Assert.AreEqual(Variant.Create(99), vs.Last.Key);
Assert.AreEqual(Variant.Create("9900"), vs.Last.Value);
var cursorSeries = new CursorSeries <int, string>(sm);
Assert.AreEqual(0, cursorSeries.First.Key);
}
public static Series <DateTime, Matrix <double> > MovingRegression(this Series <DateTime, double> y, Series <DateTime, double[]> xs, uint window, uint step = 1)
{
var xpx = xs.Zip(y, (dt, xrow, yrow) =>
{
// first x row transposed
var xt = Matrix <double> .Build.DenseOfColumnArrays(new[] { xrow });
var xpxi = xt.Multiply(xt.Transpose());
var xpy = xt.Multiply(yrow);
var tuple =
new ValueTuple <Matrix <double>, Matrix <double> >(xpxi, xpy);
//return xpxi;
return(tuple);
});
// then we need to sum xpxi and xpy over a window, make inverse of the first and multiply
// - the result is betas
var dim = xs.First.Value.Length;
var cursorFactory = new Func <ScanLagAllowIncompleteCursor <DateTime, ValueTuple <Matrix <double>, Matrix <double> >, ValueTuple <Matrix <double>, Matrix <double> > > >(() =>
new ScanLagAllowIncompleteCursor <DateTime, ValueTuple <Matrix <double>, Matrix <double> >, ValueTuple <Matrix <double>, Matrix <double> > >(
xpx.GetCursor, window, step,
() => new ValueTuple <Matrix <double>, Matrix <double> >(Matrix <double> .Build.Dense(dim, dim), Matrix <double> .Build.Dense(dim, 1)),
(st, add, sub, cnt) =>
{
var cov = st.Value1.Add(add.Value.Value1);
if (sub.Value.Value1 != null)
{
cov = cov.Subtract(sub.Value.Value1);
}
var variance = st.Value2.Add(add.Value.Value2);
if (sub.Value.Value2 != null)
{
variance = variance.Subtract(sub.Value.Value2);
}
return(new ValueTuple <Matrix <double>, Matrix <double> >(cov, variance));
}, false));
Series <DateTime, Matrix <double> > betas;
betas = new CursorSeries <DateTime, ValueTuple <Matrix <double>, Matrix <double> > >(cursorFactory).Map(
tpl =>
{
return(tpl.Value1.Inverse().Multiply(tpl.Value2));
});
return(betas);
}
