public Vector3 estimate_num_graident(double x, double y, DerivativeEstimationMode mode)
{
//will need to add in edge cases. Ignore for now.
switch (mode)
{
case DerivativeEstimationMode.GFDM:
{
return(Vector3.Zero);
}
case DerivativeEstimationMode.WEIGHTFUNCTION:
{
double delta_x = (bounds.Xmax - bounds.Xmin) / (Xcount - 1);
double delta_y = (bounds.Ymax - bounds.Ymin) / (Ycount - 1);
double dzdx = (this.interpolate_at(x + delta_x, y) - this.interpolate_at(x - delta_x, y)) / (2 * delta_x);
double dzdy = (this.interpolate_at(x, y + delta_y) - this.interpolate_at(x, y - delta_y)) / (2 * delta_x);
return(new Vector3(dzdx, dzdy, 0));
}
default:
{
return(Vector3.Zero);
}
}
}
public Vector3 estimate_num_graident(int i, int j, DerivativeEstimationMode mode)
{
//will need to add in edge cases. Ignore for now.
switch (mode)
{
case DerivativeEstimationMode.GFDM:
{
//lacks implementation
return(Vector3.Zero);
}
case DerivativeEstimationMode.TAYLOR_SURPLUS_UPPER_RIGHT:
{
//clean this up???
NCAMRNode[] stencil =
{
nodes[i, j],
nodes[i + 1, j],
nodes[i, j + 1],
nodes[i - 1, j],
nodes[i, j - 1],
nodes[i + 1, j + 1]
};
double[] deltas_u =
{
stencil[1].Value - stencil[0].Value,
stencil[2].Value - stencil[0].Value,
stencil[3].Value - stencil[0].Value,
stencil[4].Value - stencil[0].Value,
stencil[5].Value - stencil[0].Value
};
double[] deltas_x =
{
stencil[1].X - stencil[0].X,
stencil[2].X - stencil[0].X,
stencil[3].X - stencil[0].X,
stencil[4].X - stencil[0].X,
stencil[5].X - stencil[0].X
};
double[] deltas_y =
{
stencil[1].Y - stencil[0].Y,
stencil[2].Y - stencil[0].Y,
stencil[3].Y - stencil[0].Y,
stencil[4].Y - stencil[0].Y,
stencil[5].Y - stencil[0].Y
};
double[] matrix_contents =
{
deltas_x[0], deltas_y[0], 0.5 * sq(deltas_x[0]), 0.5 * sq(deltas_x[0]), deltas_x[0] * deltas_y[0],
deltas_x[1], deltas_y[1], 0.5 * sq(deltas_x[1]), 0.5 * sq(deltas_x[1]), deltas_x[1] * deltas_y[1],
deltas_x[2], deltas_y[2], 0.5 * sq(deltas_x[2]), 0.5 * sq(deltas_x[2]), deltas_x[2] * deltas_y[2],
deltas_x[3], deltas_y[3], 0.5 * sq(deltas_x[3]), 0.5 * sq(deltas_x[3]), deltas_x[3] * deltas_y[3],
deltas_x[4], deltas_y[4], 0.5 * sq(deltas_x[4]), 0.5 * sq(deltas_x[4]), deltas_x[4] * deltas_y[4]
};
Matrix delta = new Matrix(5, 1);
return(Vector3.Zero);
}
case DerivativeEstimationMode.WEIGHTFUNCTION:
{
return(Vector3.Zero);
}
case DerivativeEstimationMode.NAIVE:
{
double delta_x = (bounds.Xmax - bounds.Xmin) / (Xcount - 1);
double delta_y = (bounds.Ymax - bounds.Ymin) / (Ycount - 1);
NCAMRNode node = nodes[i, j];
double dzdx = (this.interpolate_at(node.X + delta_x, node.Y) - this.interpolate_at(node.X - delta_x, node.Y)) / (2 * delta_x);
double dzdy = (this.interpolate_at(node.X, node.Y + delta_y) - this.interpolate_at(node.X, node.Y - delta_y)) / (2 * delta_x);
return(new Vector3(dzdx, dzdy, 0));
}
default:
{
return(Vector3.Zero);
}
}
}
