FiPy can have completely general polyhedral cells, whereas VTK is more restrictive. In principle, VTK_CONVEX_POINT_SET allows the same generality, but as you've seen, this cell type is not implemented by many tools using VTK.
General 2D meshes know to export VTK_POLYGONs, which are widely understood. 2D grids bypass this specialization for historical reasons and so just get the default VTK_CONVEX_POINT_SET. We've never had any call to render 2D grids with VTK tools, so we've not noticed this before. Grid meshes should be exported as VTK_PIXEL or VTK_VOXEL. Fixing in this in FiPy is likely to happen sooner than getting any of those other packages to support VTK_CONVEX_POINT_SET. I have a (stalled) development that does a better job with mesh io, but higher priority tasks have gotten in the way. > On Jan 22, 2020, at 10:11 AM, A A <[email protected]> wrote: > > > This is somewhat related to my last comment about visualizing meshes. I'm > noticing that both CylindricalGrid2D and Grid2D default to a cell type of 41 > which according to VTK is a VTK_CONVEX_POINT_SET (see > https://vtk.org/doc/nightly/html/vtkCellType_8h_source.html). Interestingly, > the mesh generated in fipy's circle diffusion example using gmesh capability > results in a mesh of cell type 7 which is a VTK_POLYGON. I'm suspecting that > the third party libraries I'm using to plot these meshes might be limited to > cell types with numbers ranging from 0 to 35 thus not including fipy's choice > of cell type 41. > > Is the choice of the cell type intentional or important here? If so it might > be worth convincing those libraries to add cell type 41 plotting and i/o > capabilities. > ---------- Forwarded message --------- > From: A A <[email protected]> > Date: Wed, Jan 22, 2020 at 12:22 PM > Subject: Re: Some questions on the viewer > To: Guyer, Jonathan E. Dr. (Fed) <[email protected]>, <[email protected]> > > > Hi Jonathan, > > The lines do remain dashed on successive calls. I guess the viewer keeps > pointing to the right objects even if their properties are retroactively > modified. > > Here's what I mean about the diffusion term: > > <Untitled.png> > > On another note, I've posted some stuff on github which may be of interest > regarding the circle diffusion example. I had a hard time visualizing the > mesh so I went with some third-party packages (pyvista, pygmsh) and the > result looks quite nice. https://github.com/usnistgov/fipy/issues/693 > > I'm now experimenting with cylindrical coordinates as I would like to try to > solve the heat equation in radial terms. I tried repeating the above > procedure to visualize CylindricalGrid1D and CylindricalGrid2D objects but > without much luck. Here's what I'm doing: > > from fipy import Variable, FaceVariable, CellVariable, Grid1D, > CylindricalGrid1D, CylindricalGrid2D, ExplicitDiffusionTerm, TransientTerm, > DiffusionTerm, Viewer > from fipy.tools import numerix > import numpy as np > import pyvista > > mesh = CylindricalGrid2D(dr=0.1, dz=0.25, nr=3, nz=0.1) > ugrid= pyvista.UnstructuredGrid(mesh.VTKCellDataSet._vtk_obj) > plotter = pyvista.Plotter() > plotter.set_background('white') > plotter.add_mesh(ugrid, style='wireframe', color='black') > plotter.add_bounding_box(color='red') > plotter.show_grid(color="red") > plotter.view_xy() > plotter.show() > > I only get the red bounding box/grid but no cylindrical mesh. Is there > something I'm missing regarding the nature of CylindricalGrid objects? It > seems that fipy is working with/using VTK under the hood so it would be nice > to be able to recover it and take a look at what I'm working with... > > Regards, > > Amine > > On Tue, Jan 21, 2020 at 3:55 PM Guyer, Jonathan E. Dr. (Fed) via fipy > <[email protected]> wrote: > I'm curious. Do the lines remain dashed on successive calls to plot()? > > As to the third question, where are you seeing exponent n and subscript i? > I'm not suggesting we don't use them, just that I don't know where. > > Is the discussion at > https://www.ctcms.nist.gov/fipy/documentation/numerical/discret.html#higher-order-diffusion > helpful? > > > On Jan 21, 2020, at 1:25 AM, A A <[email protected]> wrote: > > > > Hi Martin, > > > > Thanks for your response. That's strange that such a "dummy" command would > > be necessary. > > > > I was able to answer the second question myself. It is possible to > > retroactively change line and axis properties. For the mesh1D example I did > > the following: > > > > viewer = Viewer(vars=(phi, phi_analytical), datamin=-6.0, datamax=6.0) > > ax = viewer.axes > > ax.lines[-1].set_dashes((3.5,3.5,3.5,3.5)) > > ax.grid() > > viewer.plot() > > > > Which seemed to work quite well. > > > > With regards to the third question, I think the terms in the general > > conservation equation are explained reasonably well in the fipy docs, > > except for the diffusion term. It is unclear what the exponent n and > > subscript i represent and how they are related to one another. Is the > > exponent an arithmetic exponent? Is i part of a sum? I had trouble > > expanding the diffusion term to n>=4. > > > > Regards, > > > > Amine > > > > On Mon, Jan 20, 2020 at 5:23 PM Martinus WERTS > > <[email protected]> wrote: > > Dear Amine, > > > > Concerning your second question, I think that this a normal (but in this > > case, annoying) feature of the Jupyter notebook. > > > > You might trying adding an extra (dummy) command to the cell, after the > > line in which the Viewer() is instantiated. For example: ``print('Ready')``. > > > > Best, > > Martin > > > > On 20/01/2020 17:01, A A wrote: > >> Dear All, > >> > >> I'm just getting back into using fipy after a few months hiatus. I'm > >> getting more familiar with how it works, but I have a couple of questions > >> about the viewer: > >> • Is it possible to control linestyle (specifically dashes) of the > >> cellVariable objects tied to each specific viewer? I'd like to avoid the > >> possibility of superimposing very similar plots and thinking they are the > >> same > >> • I am primarily using jupyter notebook to practice some basic > >> concepts. What I've found is that simply instantiating the viewer in > >> interactive mode will generate a plot. This renders a viewer.plot() call > >> redundant. When I run the whole notebook in non-interactive mode I get the > >> expected behavior, namely one plot with a .plot() call. Am I missing > >> something here? Why does viewer instantiation generate a plot in jupyter > >> notebook? > >> Thanks for your help and look forward to your reply. > >> > >> Regards, > >> > >> Amine Aboufirass > >> > >> > >> _______________________________________________ > >> fipy mailing list > >> > >> [email protected] > >> http://www.ctcms.nist.gov/fipy > >> > >> [ NIST internal ONLY: > >> https://email.nist.gov/mailman/listinfo/fipy > >> ] > >> > > > > > > _______________________________________________ > > fipy mailing list > > [email protected] > > http://www.ctcms.nist.gov/fipy > > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > _______________________________________________ > > fipy mailing list > > [email protected] > > http://www.ctcms.nist.gov/fipy > > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > > _______________________________________________ > fipy mailing list > [email protected] > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > _______________________________________________ > fipy mailing list > [email protected] > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] _______________________________________________ fipy mailing list [email protected] http://www.ctcms.nist.gov/fipy [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ]
