Dear Mike, Thank you for your answer! I implemented your suggestions and I don’t have the error anymore. The code starts running, but then goes crazy with absolutely random values of composition (as opposed to an expected periodic variation). I don’t know if this still come from the spline.. I remember I was advised to not set the diffusion coefficient as a variable, but I have to admit I don’t remember why. I don’t know if that could be the problem.
Any idea, anyone?
Thank you!
Clara
> On 09 Aug 2017, at 18:13, Michael J. Waters <waters.mik...@gmail.com> wrote:
>
> Hi Clara,
>
> Is your spline function returning a numpy array? I think what is happening
> is that FiPy is seeing it as a tensor diffusion coefficient rather than just
> a list of the values throughout your simulation. I'm a little rusty with FiPy
> these days, but I think you could so something like this:
>
> Diff = CellVariable(mesh=mesh)
>
> Diff.setValue(d2G(Xf))
>
> and then update the value in the loop like this:
> while time < duration:
> res0 = eq.sweep(X_var, dt=dt, solver=solver)
>
>
> Diff.setValue(d2G(Xf))
>
>
> Maybe 'Diff' should be FaceVariable? whichever way it should be, it should be
> fine in the equation definition then.
>
> Best,
> -Mike
>
>
>
>
> On 8/9/17 4:48 PM, Clara Maurel wrote:
>> Hello,
>>
>> I would like to model the Cahn Hilliard equation with a diffusion
>> coefficient that depends on the cell variable (concentration X) and time.
>> The diffusion coefficient (Diff) is proportional to the second derivative of
>> the free energy (d2G), for which I have the values in an external file, for
>> a range of concentrations.
>> Initially I interpolated d2G with a polynomial function and could easily
>> express Diff as a function of Xf = X.arithmeticFaceValue
>>
>> However, I realised that this interpolation was not appropriate in my case.
>> The only way I found to obtain a correct interpolation of d2G is to use a
>> B-spline interpolation, with scipy.interpolate.UnivariateSpline. The piece
>> of code is as follows (d2G_fit is the array of values that I imported from
>> an external file):
>>
>>
>> X = np.arange(0.011,1.0,0.001)
>>
>> X_var = CellVariable(name=r"$X_{at}$", mesh=mesh, hasOld=True)
>>
>> noise = GaussianNoiseVariable(mesh=mesh, mean=X_mean, variance=1.0e-7).value
>> X_var[:] = noise
>> X_var.updateOld()
>> Xf = X_var.arithmeticFaceValue
>>
>> d2G = UnivariateSpline(X, d2G_fit[id_mean_spino], k=3, s=0)
>> Diff = d2G(Xf)
>>
>>
>> My problem is that when I start looping with:
>>
>> while time < duration:
>> res0 = eq.sweep(X_var, dt=dt, solver=solver)
>>
>> I have the error message:
>>
>> IndexError: diffusion coefficent tensor is not an appropriate shape for this
>> mesh
>>
>>
>> I also tried:
>>
>> Diff = Variable(value=d2G(Xf))
>> and
>> Diff = d2G(Xf)*Variable(list(d2G(Xf)))
>>
>> but I have the same error.
>>
>> Could you tell me how I could work this out? Additional comment: Diff
>> evolves with time, I update it at selected timestep in the loop.
>>
>>
>> Any hint would be greatly appreciated!
>>
>> Thank you in advance!
>> Clara
>>
>>
>>
>>
>>
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