On Jan 15, 2014, at 5:03 PM, Eric Bruning <[email protected]> wrote:
> In the case of a simple thunderstorm charge distribution (see > https://twitter.com/deeplycloudy/status/423575182997876736/photo/1), the > vectors are so large between the charge layers that the vector plot is rather > noisy and hard to interpret. Hence my desire for a simpler way to visualize > the magnitude. Understood. I've run into the same issues. You might try the MatplotlibStreamViewer. You can use the `color` and/or `linewidth` arguments to illustrate the magnitude. Nice illustration, btw. > > > An average of the values at each face for each cell of the underlying mesh > > would be fine. > > That basically describes a plot of phi.grad.mag. Let us know if that doesn't > do what you want. > > I was having some misgivings about the first- vs. second-order > discretization, hence my preference for phi.faceGrad, although you're correct > that phi.grad would do what I want. phi.grad is lower order, but an average of the bounding face values is exactly what it is. For the purposes of visualization, I don't think you need to worry about the order of accuracy. > More generally, I like to be able to understand the underlying coordinate > geometry so I can do other things with the solution values. Got you. _______________________________________________ fipy mailing list [email protected] http://www.ctcms.nist.gov/fipy [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ]
