public void CalculatePearsonsRSquaredTest()
{
System.Random random = new System.Random(31415);
int n = testData.GetLength(0);
int cols = testData.GetLength(1);
for (int c1 = 0; c1 < cols; c1++)
{
for (int c2 = c1 + 1; c2 < cols; c2++)
{
{
double c1Scale = random.NextDouble() * 1E7;
double c2Scale = random.NextDouble() * 1E7;
IEnumerable <double> x = from rows in Enumerable.Range(0, n)
select testData[rows, c1] * c1Scale;
IEnumerable <double> y = from rows in Enumerable.Range(0, n)
select testData[rows, c2] * c2Scale;
double[] xs = x.ToArray();
double[] ys = y.ToArray();
double r2_alglib = alglib.pearsoncorrelation(xs, ys, n);
r2_alglib *= r2_alglib;
var r2Calculator = new OnlinePearsonsRSquaredCalculator();
for (int i = 0; i < n; i++)
{
r2Calculator.Add(xs[i], ys[i]);
}
double r2 = r2Calculator.RSquared;
Assert.IsTrue(r2_alglib.IsAlmost(r2));
}
}
}
}
public void CalculatePearsonsRSquaredOfConstantTest()
{
System.Random random = new System.Random(31415);
int n = 12;
int cols = testData.GetLength(1);
for (int c1 = 0; c1 < cols; c1++)
{
double c1Scale = random.NextDouble() * 1E7;
IEnumerable <double> x = from rows in Enumerable.Range(0, n)
select testData[rows, c1] * c1Scale;
IEnumerable <double> y = (new List <double>()
{
150494407424305.47
})
.Concat(Enumerable.Repeat(150494407424305.47, n - 1));
double[] xs = x.ToArray();
double[] ys = y.ToArray();
double r2_alglib = alglib.pearsoncorrelation(xs, ys, n);
r2_alglib *= r2_alglib;
var r2Calculator = new OnlinePearsonsRSquaredCalculator();
for (int i = 0; i < n; i++)
{
r2Calculator.Add(xs[i], ys[i]);
}
double r2 = r2Calculator.RSquared;
Assert.AreEqual(r2_alglib.ToString(), r2.ToString());
}
}
public void CalculatePearsonsRSquaredTest() {
System.Random random = new System.Random(31415);
int n = testData.GetLength(0);
int cols = testData.GetLength(1);
for (int c1 = 0; c1 < cols; c1++) {
for (int c2 = c1 + 1; c2 < cols; c2++) {
{
double c1Scale = random.NextDouble() * 1E7;
double c2Scale = random.NextDouble() * 1E7;
IEnumerable<double> x = from rows in Enumerable.Range(0, n)
select testData[rows, c1] * c1Scale;
IEnumerable<double> y = from rows in Enumerable.Range(0, n)
select testData[rows, c2] * c2Scale;
double[] xs = x.ToArray();
double[] ys = y.ToArray();
double r2_alglib = alglib.pearsoncorrelation(xs, ys, n);
r2_alglib *= r2_alglib;
var r2Calculator = new OnlinePearsonsRSquaredCalculator();
for (int i = 0; i < n; i++) {
r2Calculator.Add(xs[i], ys[i]);
}
double r2 = r2Calculator.RSquared;
Assert.IsTrue(r2_alglib.IsAlmost(r2));
}
}
}
}
public void CalculatePearsonsRSquaredOfConstantTest() {
System.Random random = new System.Random(31415);
int n = 12;
int cols = testData.GetLength(1);
for (int c1 = 0; c1 < cols; c1++) {
double c1Scale = random.NextDouble() * 1E7;
IEnumerable<double> x = from rows in Enumerable.Range(0, n)
select testData[rows, c1] * c1Scale;
IEnumerable<double> y = (new List<double>() { 150494407424305.47 })
.Concat(Enumerable.Repeat(150494407424305.47, n - 1));
double[] xs = x.ToArray();
double[] ys = y.ToArray();
double r2_alglib = alglib.pearsoncorrelation(xs, ys, n);
r2_alglib *= r2_alglib;
var r2Calculator = new OnlinePearsonsRSquaredCalculator();
for (int i = 0; i < n; i++) {
r2Calculator.Add(xs[i], ys[i]);
}
double r2 = r2Calculator.RSquared;
Assert.AreEqual(r2_alglib.ToString(), r2.ToString());
}
}
