2011/2/8 Julien Derr <julien.d...@gmail.com> > Thanks very much Benny for the explanation, but what do you mean by > working in chunks ? > > I have a variable newphi which is defined on a newmesh and phi the old > variable which was defined in the original mesh. > > how can I copy phi to newphi by "chunk" ? In any case the huge array needs > to be created no ? >
The problem is not in the final array, but in the intermediate ones. I see this in the error: nearestCellIDs = self.getMesh()_getNearestCellID(points) So my guess is that every new point has to be compared with all meshpoints to extract the neareast one. If you do one point at the time, this is doable, if you 10 points also, ..., but not all points in one go. In a rectangular regular grid, this is also easy, but not in an unstructured one. Benny > Julien > > > > > > On Tue, Feb 8, 2011 at 2:47 PM, Benny Malengier <benny.maleng...@gmail.com > > wrote: > >> You do >> >> ... value=phi(mesh.getCellCenters())) >> >> This is what causes the problem. You can probably work around it by >> creating value yourself. >> Fipy uses some vectorized algorithms, which works great, but have the >> disadvantage that there must be enough memory to allocate the required >> arrays. >> In this case, by working in chunks to create value, you can work around >> this (I believe, did not try anything). >> >> Benny >> >> 2011/2/8 Julien Derr <julien.d...@gmail.com> >> >> Hi everyone, >>> >>> I am dealing with an irregular mesh done between a big circle and a small >>> polygone. >>> >>> looks like I have memory issues when the polygone becomes more than a few >>> hundreds sides. Is that a typical limitation by fipy ? Is there a way to >>> deal with big polygonial shapes? >>> >>> see error bellow, if you understand it ? >>> >>> Traceback (most recent call last): >>> File "growth.py", line 175, in <module> >>> newphi = CellVariable(name = "solution variable", mesh = mesh, >>> value=phi(mesh.getCellCenters())) >>> File "/usr/lib/pymodules/python2.6/fipy/variables/cellVariable.py", >>> line 197, in __call__ >>> nearestCellIDs = self.getMesh()_getNearestCellID(points) >>> File "/usr/lib/pymodules/python2.6/fipy/meshes/common/mesh.py", line >>> 772, in _getNearestCellID >>> return numerix.argmin(numerix.dot(tmp, tmp, axis = 0), axis=0) >>> File "/usr/lib/pymodules/python2.6/fipy/tools/numerix.py", line 844, in >>> dot >>> return sum(a1*a2, axis) >>> File "/usr/lib/pymodules/python2.6/fipy/tools/numerix.py", line 241, in >>> sum >>> return NUMERIX.sum(arr, axis) >>> File "/usr/lib/python2.6/dist-packages/numpy/core/fromnumeric.py", line >>> 1252, in sum >>> return sum(axis, dtype, out) >>> MemoryError >>> >>> thanks for your help ! >>> >>> Julien >>> >>> PS I am trying to reproduce a typical DLA/saffman taylor problem. so I >>> guess the alternative would be to use a simple rectangular lattice, and to >>> use a phase parameter to determine what is solid and what is not (like in >>> the dendritic solidification example of the fipy help). >>> but the issue then is to make some diffusion happen (for another field >>> c) only on the space where phi=0. is that possible ? >>> >>> >>> >> >
