Differencing

This code computes all the edges of a block or block face

plot3d.differencing.find_edges(X: ndarray, Y: ndarray, Z: ndarray)[source]
Check if the edges of both blocks that are parallel. Takes into account the whole block and not a single face

if edges are parallel then their vertices might intersect.

Parameters:

  • X (np.ndarray) – Multi-dimensional array (3 dimensions IMAX,JMAX,KMAX ) representing values of X for the block/face domain

  • Y (np.ndarray) – Multi-dimensional array (3 dimensions IMAX,JMAX,KMAX ) representing values of Y for the block/face domain

  • Z (np.ndarray) – Multi-dimensional array (3 dimensions IMAX,JMAX,KMAX ) representing values of Z for the block/face domain

Returns:

Dataframe with columns i,j,k,di,dj,dk where di,dj,dk are each tuples containing (dx_b,dy_b,dz_b),(dx_f,dy_f,dz_f)

_f = forward differencing

Return type:

pandas.DataFrame

plot3d.differencing.find_face_edges(X: ndarray, Y: ndarray, Z: ndarray)[source]
Check if the edges of both faces to see if they are parallel. Face can be in any direction (I,J) (I,K) etc.

if edges are parallel then their vertices might intersect Find edges will always deal with faces and not something that is in 3D

Parameters:

  • X (np.ndarray) – Multi-dimensional array (2 dimensions PMAX,QMAX ) representing values of X for the block domain

  • Y (np.ndarray) – Multi-dimensional array (2 dimensions PMAX,QMAX ) representing values of Y for the block domain

  • Z (np.ndarray) – Multi-dimensional array (2 dimensions PMAX,QMAX ) representing values of Z for the block domain

Returns:

with columns p,q,dp,dq where dp, dq are each tuples containing (dx_b,dy_b,dz_b),(dx_f,dy_f,dz_f)

Return type:

pandas.DataFrame