choclo.point.kernel_e#
- choclo.point.kernel_e(easting_p, northing_p, upward_p, easting_q, northing_q, upward_q, distance)[source]#
Easting component of the gradient of the inverse of the distance
Important
The coordinates of the two points must be in Cartesian coordinates and have the same units.
- Parameters:
- easting_p
float
Easting coordinate of point \(\mathbf{p}\).
- northing_p
float
Northing coordinate of point \(\mathbf{p}\).
- upward_p
float
Upward coordinate of point \(\mathbf{p}\).
- easting_q
float
Easting coordinate of point \(\mathbf{q}\).
- northing_q
float
Northing coordinate of point \(\mathbf{q}\).
- upward_q
float
Upward coordinate of point \(\mathbf{q}\).
- distance
float
Euclidean distance between points \(\mathbf{p}\) and \(\mathbf{q}\).
- easting_p
- Returns:
- kernel
float
Value of the kernel function.
- kernel
Notes
Given two points \(\mathbf{p} = (x_p, y_p, z_p)\) and \(\mathbf{q} = (x_q, y_q, z_q)\) defined in a Cartesian coordinate system, compute the following kernel function:
\[k_x(\mathbf{p}, \mathbf{q}) = \frac{\partial}{\partial x} \left( \frac{1}{\lVert \mathbf{p} - \mathbf{q} \rVert_2} \right) = - \frac{ x_p - x_q }{ \lVert \mathbf{p} - \mathbf{q} \rVert_2 }\]where \(\lVert \cdot \rVert_2\) refer to the \(L_2\) norm (the Euclidean distance between \(\mathbf{p}\) and \(\mathbf{q}\)).