public PartyPollingResultsSet(
string party,
bool isConstituency,
List <OpinionPoll> polls
)
{
PartyAbbreviation = party;
IsConstituency = isConstituency;
PollingResults = new List <PollingResult>();
_startDate = null;
_splineParameters = null;
// loop through the polls getting the polling values
SetupPollingResults(party, isConstituency, polls);
// get the x and y values
double[] xValues = PollingResults.Select(x => (double)x.DaysSinceStart).ToArray();
double[] yValues = PollingResults.Select(x => (double)x.Percentage).ToArray();
// fit the curves
if (xValues.Length > 0 && yValues.Length > 0)
{
alglib.spline1dfitpenalized(
xValues,
yValues,
yValues.Length,
1d,
out _,
out alglib.spline1dinterpolant splineParameters,
out alglib.spline1dfitreport _);
_splineParameters = splineParameters;
}
}
private void InitInterpolantModel()
{
var xData = ProbabilityFunctionValues.Select(p => p.X).ToArray();
var yData = ProbabilityFunctionValues.Select(p => p.Y).ToArray();
alglib.spline1dinterpolant spline1Dinterpolant;
alglib.spline1dbuildcubic(xData, yData, out spline1Dinterpolant);
InterpolantModel = spline1Dinterpolant;
}
/// <summary>
/// Spline Interpolation using a math/stats assembly from http://www.alglib.net/download.php
/// Interpolation method mimics UofI disaggregation method of taking a 31 day window and interpolating
/// the values in index numbers 11 - 21
/// Lots of magic numbers...
/// </summary>
private static Series SplineCalc(Series sOrig)
{
// Magic numbers to assign index values to the data points
double[] X = new double[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 };
// Magic numbers for values to be overwritten with interpolated values
double[] evalpts = new double[] { 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 };
// Generates values from the input series corresponding with 'X'
List <double> tempVals = new List <double>();
for (int i = 0; i < 10; i++)
{
tempVals.Add(sOrig[i].Value);
}
for (int i = 21; i < 31; i++)
{
tempVals.Add(sOrig[i].Value);
}
double[] Y = tempVals.ToArray();
//This Cubic Spline replicates the Excel output used by UofI's A.Acharya and Dr.Ryu.
alglib.spline1dinterpolant C = new alglib.spline1dinterpolant();
var results = new List <double>();
for (int i = 0; i < evalpts.Length; i++)
{
double evalpt = evalpts[i];
alglib.spline1dbuildcubic(X, Y, out C);
double s = alglib.spline1dcalc(C, evalpt);
results.Add(s);
}
// Loop to populate interpolated series.
Series sNewInterp = new Series();
for (int j = 0; j < sOrig.Count; j++)
{
if (j >= 10 && j <= 20)
{ // Assigns interpolated value to the new series so long as the interpolated value is > 0
if (results[j - 10] > 0)
{
sNewInterp.Add(sOrig[j].DateTime, results[j - 10], sOrig[j].Flag);
}
else
{
sNewInterp.Add(sOrig[j]);
}
}
else
{
sNewInterp.Add(sOrig[j]);
}
}
return(sNewInterp);
}
private static List <PointD> GetMiddle(List <PointD> points)
{
var size = points.Count;
var middle = new List <PointD>(size);
var maxPoints = GetLocalMaximums(points);
var minPoints = GetLocalMinimums(points);
if (maxPoints.Count > 1 && minPoints.Count > 1)
{
alglib.spline1dinterpolant splineMax = new alglib.spline1dinterpolant();
alglib.spline1dinterpolant splineMin = new alglib.spline1dinterpolant();
alglib.spline1dbuildcubic(
maxPoints.Select(p => p.X).ToArray(),
maxPoints.Select(p => p.Y).ToArray(),
out splineMax);
alglib.spline1dbuildcubic(
minPoints.Select(p => p.X).ToArray(),
minPoints.Select(p => p.Y).ToArray(),
out splineMin);
for (int i = 0; i < size; i++)
{
var xValue = points[i].X;
var yMaxValue = alglib.spline1dcalc(splineMax, xValue);
var yMinValue = alglib.spline1dcalc(splineMin, xValue);
middle.Add(new PointD
{
X = xValue,
Y = (yMaxValue + yMinValue) / 2.0
});
}
}
return(middle);
}
/// <summary>
/// Spline Interpolation using a math/stats assembly from http://www.alglib.net/download.php
/// Interpolation method mimics UofI disaggregation method of taking a 31 day window and interpolating
/// the values in index numbers 11 - 21
/// Lots of magic numbers...
/// </summary>
private static Series SplineCalc(Series sOrig)
{
// Magic numbers to assign index values to the data points
double[] X = new double[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 };
// Magic numbers for values to be overwritten with interpolated values
double[] evalpts = new double[] { 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 };
// Generates values from the input series corresponding with 'X'
List<double> tempVals = new List<double>();
for (int i = 0; i < 10; i++) { tempVals.Add(sOrig[i].Value); }
for (int i = 21; i < 31; i++) { tempVals.Add(sOrig[i].Value); }
double[] Y = tempVals.ToArray();
//This Cubic Spline replicates the Excel output used by UofI's A.Acharya and Dr.Ryu.
alglib.spline1dinterpolant C = new alglib.spline1dinterpolant();
var results = new List<double>();
for (int i = 0; i < evalpts.Length; i++)
{
double evalpt = evalpts[i];
alglib.spline1dbuildcubic(X, Y, out C);
double s = alglib.spline1dcalc(C, evalpt);
results.Add(s);
}
// Loop to populate interpolated series.
Series sNewInterp = new Series();
for (int j = 0; j < sOrig.Count; j++)
{
if (j >= 10 && j <= 20)
{ // Assigns interpolated value to the new series so long as the interpolated value is > 0
if (results[j - 10] > 0)
{ sNewInterp.Add(sOrig[j].DateTime, results[j - 10],sOrig[j].Flag); }
else { sNewInterp.Add(sOrig[j]); }
}
else { sNewInterp.Add(sOrig[j]); }
}
return sNewInterp;
}