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: [image: 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 < fipy@nist.gov> 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 <amine.aboufir...@gmail.com> 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 < > martinus.we...@ens-rennes.fr> 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 > >> > >> fipy@nist.gov > >> http://www.ctcms.nist.gov/fipy > >> > >> [ NIST internal ONLY: > >> https://email.nist.gov/mailman/listinfo/fipy > >> ] > >> > > > > > > _______________________________________________ > > fipy mailing list > > fipy@nist.gov > > http://www.ctcms.nist.gov/fipy > > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > _______________________________________________ > > fipy mailing list > > fipy@nist.gov > > http://www.ctcms.nist.gov/fipy > > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > > _______________________________________________ > fipy mailing list > fipy@nist.gov > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] >
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