Hi All,
I have some problems in figuring out a solution for an issue I am trying to solve. I have a 3D grid of dimension Nx, Ny, Nz; for every cell of this grid, I calculate the cell centroids (with the cell coordinates x, y, and z) and then I try to find which cell centroid is the closest to a specified point in 3D (which I supply). I still haven't figured out how to do this, even if I have some ideas (and suggestions for this problem are welcome :D ). But the problem is another one. When I find the closest centroid, I know only the cell ID of this centroid. The cell ID is (usually) defined as:
ID = (K1)*Nx*Ny + (J1)*Nx + I  1
Where I, J, K are the cell indexes. Now, the problem is, how can I calculate back the I, J, K indexes knowing only the cell ID? I am trying to solve this using numpy (as my grid is stored using a numpy array), but it's something akin to the Matlab function ind2sub...
Thank you for your suggestions.
Andrea.
"Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/
On Thu, Feb 28, 2008 at 1:47 PM, Andrea Gavana andrea.gavana@gmail.com wrote:
Hi All,
I have some problems in figuring out a solution for an issue I am trying to solve. I have a 3D grid of dimension Nx, Ny, Nz; for every cell of this grid, I calculate the cell centroids (with the cell coordinates x, y, and z) and then I try to find which cell centroid is the closest to a specified point in 3D (which I supply). I still haven't figured out how to do this, even if I have some ideas (and suggestions for this problem are welcome :D ). But the problem is another one. When I find the closest centroid, I know only the cell ID of this centroid. The cell ID is (usually) defined as:
ID = (K1)*Nx*Ny + (J1)*Nx + I  1
Where I, J, K are the cell indexes. Now, the problem is, how can I calculate back the I, J, K indexes knowing only the cell ID? I am trying to solve this using numpy (as my grid is stored using a numpy array), but it's something akin to the Matlab function ind2sub...
Thank you for your suggestions.
I think you are going to want to use mod (aka '%'). Something like:
def coord(id):
... return (id % NX + 1, id // NX % NY + 1, id // (NX*NY) + 1 )
should work. I believe there are a few things you could do to improve the efficiency here, but try this and see if it works for you before you worry about that.
Note that the above definition for cell ID is probably a little weird in the context of numpy where all of the indexing starts at zero.
Hi Timothy,
On Fri, Feb 29, 2008 at 12:16 AM, Timothy Hochberg wrote:
On Thu, Feb 28, 2008 at 1:47 PM, Andrea Gavana andrea.gavana@gmail.com wrote:
Hi All,
I have some problems in figuring out a solution for an issue I am trying to solve. I have a 3D grid of dimension Nx, Ny, Nz; for every cell of this grid, I calculate the cell centroids (with the cell coordinates x, y, and z) and then I try to find which cell centroid is the closest to a specified point in 3D (which I supply). I still haven't figured out how to do this, even if I have some ideas (and suggestions for this problem are welcome :D ). But the problem is another one. When I find the closest centroid, I know only the cell ID of this centroid. The cell ID is (usually) defined as:
ID = (K1)*Nx*Ny + (J1)*Nx + I  1
Where I, J, K are the cell indexes. Now, the problem is, how can I calculate back the I, J, K indexes knowing only the cell ID? I am trying to solve this using numpy (as my grid is stored using a numpy array), but it's something akin to the Matlab function ind2sub...
Thank you for your suggestions.
I think you are going to want to use mod (aka '%'). Something like:
def coord(id):
... return (id % NX + 1, id // NX % NY + 1, id // (NX*NY) + 1 )
should work. I believe there are a few things you could do to improve the efficiency here, but try this and see if it works for you before you worry about that.
Thank you for the suggestion. I was so concentrated on another kind of solution that I didn't even think about your approach, which is far more elegant than mine.
Note that the above definition for cell ID is probably a little weird in the context of numpy where all of the indexing starts at zero.
Yep, but actually this is perfect for my case as I have to input those numbers in a reservoir simulator where all of the indexing starts at 1 :D . It's perfect.
Thank you very much.
Andrea.
"Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/
participants (2)

Andrea Gavana

Timothy Hochberg