public void TestDerivative(double point, double expected)
{
Derivative = new Derivative(TypicalFunction);
var got = Derivative.GetDerivative(point);
// delta подбирается эмпирическим путём
Assert.AreEqual(expected, got, 1E-09);
}
public void Execute(int index)
{
var bufferNoiseEntity = BufferNoiseEntities[index];
var fromIndex = bufferNoiseEntity.Fraction * Size;
for (var i = 0; i < PartSize; i++)
{
var currentIndex = fromIndex + i * 4;
var position = Location.Position(Location.NextIndexes(currentIndex), Resolution);
UnsafeUtility.WriteArrayElementWithStride(
Normals.GetUnsafePtr(),
currentIndex,
UnsafeUtility.SizeOf <float3>(),
Derivative.GetDerivative(Vertices, position, Resolution)
);
}
}
private Vector3 getNormalAnalitic(string xExpr, string yExpr, string zExpr, string u, string v)
{
var d = ":" + u + ";" + v;
var xonu = Derivative.GetDerivative(xExpr, u, false);
var xonv = Derivative.GetDerivative(xExpr, v, false);
var yonu = Derivative.GetDerivative(yExpr, u, false);
var yonv = Derivative.GetDerivative(yExpr, v, false);
var zonu = Derivative.GetDerivative(zExpr, u, false);
var zonv = Derivative.GetDerivative(zExpr, v, false);
var v1 = new Vector3(xonu + d, yonu + d, zonu + d);
var v2 = new Vector3(xonv + d, yonv + d, zonv + d);
var normalNotNormalized = (v1 ^ v2);
var len = (CommonFunction)("sqrt(" + (normalNotNormalized * normalNotNormalized).Print() + ")" + d);
return(normalNotNormalized / len);
}
