Dear Dario,
I am currently using Fipy for a slightly different diffusion-reaction
problem.
I use a CellVariable on the same grid for the (spatially-dependent) rate
constant. One can set its values in a "numpy-vectorized" fashion by
accessing the "value" property of the CellVariable.
By using a Boolean expression for indexing the "value" vector one can
address individual elements.
Here are bits of code that illustrate the approach. It sets the "capture
rate" to Kcap inside a sphere of radius R. Outside the sphere, "capture
rate" is zero.
# create grid (one octant, using symmetry)
mesh = UniformGrid3D(nx=Nx, ny=Ny, nz=Nz,
dx=sx/Nx, dy=sy/Ny, dz=sz/Nz,
origin=[[0.],[0.],[0.]] )
X,Y,Z = mesh.cellCenters
# variables
u = CellVariable(name="particles",
mesh=mesh,
value=0.)
k = CellVariable(name="capture rate",
mesh=mesh,
value=0.)
# equation
eq = TransientTerm(var = u) == DiffusionTerm(coeff = Dcoeff, var =
u) - k*u
# I skip the boundary conditions here to keep this message compact
# initial conditions for u; setting value for rate constant
u.value=Ceq
k.value[(X**2 + Y**2 + Z**2< Rcap**2)] = Kcap
I also found that it is possible to access the elements on this regular
3D grid via a "reshaped" version of the array
uvol = u.value.reshape(Nz,Ny,Nx)
(...)
uvol[:,0,:] += np.sum(vvol, axis=1)
This approach, however, requires that one does the book-keeping of the
coordinate system oneself, and relies on the specific way that the data
is organized by FiPy.
Best wishes,
Martin
On 08/04/2019 17:30, Dario Panada wrote:
Hello,
Many thanks for your reply.
Yes, let me provide a bit more context.
I two initial numpy grids (n*n*n) where each value corresponds to a
source/sink. Eg: Given my source grid and coordinates (1,2,3) having
value 5, I want to set such value as a source in FiPy. Currently I am
dong that by, for each such coordinate, finding the corresponding
ravelled index and setting it in _array, as snippet in my previous
message;
/i = np.ravel_multi_index([coordinate[0], coordinate[1],
coordinate[2]], (20, 20, 20))/
/
/
/ sourceGrid._array[i] = sourceRate/
/ sinkGrid._array[i] = sinkRate/
/
/
I suppose I could build the entire vector of sources before and then
doing a single assignment to _array, but again you correctly mentioned
that relying on that is bad practice.
You mention:
/sourceGrid[..., i] = sourceRate/
/
/
Can I just please confirm what data type sourceGrid is? In the context
of defining the equation
/eq = TransientTerm() == DiffusionTerm(coeff=D) + sourceGrid - sinkGrid/
/
/
Can sourceGrid/sinkGrid just be numpy arrays or even simple python
lists? I was under the impression they had to be CellVariable objects
but could be wrong.
Kind Regards,
Dario
On Mon, Apr 8, 2019 at 3:04 PM Guyer, Jonathan E. Dr. (Fed) via fipy
<fipy@nist.gov <mailto:fipy@nist.gov>> wrote:
Iterating over a mesh with a Python `for` loop is, as you've
found, an incredibly inefficient way to do things. FiPy, like
numpy it relies on, is intended to be used with vectorized
operations.
As far as your approach, things that start with `_` in Python are
internal implementation details and you should not depend on them.
If you find cases in FiPy that absolutely require that you access
`some._propertyName` or `some._methodName()`, then please file an
issue explaining your need so that we can provide a public interface.
In this case, there's no need to access `_array`. Just write
>>> sourceGrid[..., i] = sourceRate
>>> sinkGrid[..., i] = sinkRate
HOWEVER, you are still relying on an internal implementation
detail, specifically that a Grid is an array with known fastest
and slowest varying axes. We have in FiPy's history switched from
Fortran to C ordering, and we might conceivably switch back at
some point. Further, if you every wanted to run your script on an
unstructured mesh, then your system wouldn't work at all.
`sourceCoords` presumably comes from some definition in terms of
geometry rather than discrete mesh indices. FiPy is intended to
work best with those geometric descriptions. If you described
where `sourceCoords` came from, we could help with a more FiPyish
way to get what you want.
> On Apr 6, 2019, at 9:02 AM, Dario Panada <dario.pan...@gmail.com
<mailto:dario.pan...@gmail.com>> wrote:
>
> Good Afternoon (Morning) to all,
>
> I have an equation of type
>
> eq = TransientTerm() == DiffusionTerm(coeff=D) + sourceGrid -
sinkGrid
>
> Where sourceGrid and sinkGrid are derived from values in a 3D grid.
>
> Is there any downside to declaring the grids as
>
> sourceGrid = CellVariable(name="source", mesh=Grid3D(dx=1, dy=1,
dz=1, nx=20, ny=20, nz=20))
> sinkGrid = CellVariable(name="sink", mesh=Grid3D(dx=1,
dy=1, dz=1, nx=20, ny=20, nz=20))
>
> And populating them as:
>
> i = np.ravel_multi_index([coordinate[0], coordinate[1],
coordinate[2]], (20, 20, 20))
>
> sourceGrid._array[i] = sourceRate
> sinkGrid._array[i] = sinkRate
>
> The original procedure I was using (given below) where I called
.setValue on each coordinate is extremely time-consuming. Results
seem to align, but of course this doesn't mean it's right... Or if
it's wrong, any specific advice on how to achieve this?
>
> Thanks,
> Dario
>
> Original approach (and there is an equivalent function for
setupSinkGrid):
> def setupSourceGrid_(self, sourceCoords, mesh):
> sourceGrid = CellVariable(name="source", mesh=mesh, value=0)
> sourceGrid.setValue(0.)
> for pos, v in sourceCoords.iteritems():
> tmpGrid = [False for _ in range(8000)]
> i = np.ravel_multi_index([pos[0], pos[1], pos[2]],
(20, 20, 20))
> tmpGrid[i] = True
> sourceGrid.setValue(v, where=tmpGrid)
>
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