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I am currently using fipy but am still relatively new to the nuiances associated with the package. While I have been able to regenerate the desired heatmap from the examples folder in for the mesh20x20 diffusion example using the command line, I have struggled to replicate it within a Spyder IDE. I am using python version 3.8 . It is simple enough to generate it using the "examples" folder from the command line the command line image generated, however, when I attempt to "re-program" it I end up with iterations of the following. the following result. I am hoping to be able to regenerate the smooth color transition from the examples folder, as opposed to the discrete dichromatic option that I have been limited to at present. I believe there is some issues with the viewer in some capacity I believe some related issues may have cropped up in the past for others, potentially as it relates to colorbar reformatting, though I have not yet been capable of effectively implementing these workarounds to generate the desired imagery. datamin and datamax in Viewer() did not work

I would be greatly indebted for any assitance the community could provide.

from fipy.terms.transientTerm import TransientTerm
from fipy.terms.implicitDiffusionTerm import ImplicitDiffusionTerm
from fipy.terms.explicitDiffusionTerm import ExplicitDiffusionTerm
from fipy.meshes.nonUniformGrid2D import NonUniformGrid2D
from fipy.variables.cellVariable import CellVariable
from fipy.viewers.matplotlibViewer.matplotlib2DViewer import Matplotlib2DViewer


####
#Global Inputs
D=1
steps=10


#Dimensional Inputs
nx=20
dx=1
ny=20
dy=1
L=dx*nx

#Temporal Inputs
#nt=20
#dt=1

#cell variable initial values
value=0

#construct mesh from dimensional pts
mesh=NonUniformGrid2D(nx=nx, dx=dx, ny=ny, dy=dy)


#construct term variables phi with name, mesh design
phi=CellVariable(name="solutionvariable", mesh=mesh, value=0)


#construct boundary conditions
#dirichlet ---> we can an automatic application of neumann to top right and bottom left
valueTopLeft=0
valueBottomRight=1

#assign boundary conditions to a face or cell
X, Y=mesh.faceCenters
facesTopLeft=((mesh.facesLeft & (Y > L/2 )) | (mesh.facesTop &( X < L/2)))
facesBottomRight=((mesh.facesRight & (Y < L/2)) | (mesh.facesBottom & (X > L/2)))


#constrain variables
phi.constrain(valueTopLeft, facesTopLeft)
phi.constrain(valueBottomRight, facesBottomRight)


#equation construction
eq=TransientTerm()==ExplicitDiffusionTerm(coeff=D)


#equation solving and either viewing and/or extraction
timestepduration=0.9 *(dx**2)/(2*D)
for step in range(steps):
    eq.solve(var=phi, dt=timestepduration)
    print(phi[step])
    viewer=Matplotlib2DViewer(vars=phi, datamin=0, datamax=1)
    viewer.axes.set_title("Solutionvbl(Step %d)" % (step+1,))
user13708466
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1 Answers1

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Figured it out I think. I was using ExplicitDiffusion and the example utilizes ImplicitDiffusion. When I tried this all I got back was a blank monochromatic image (and returned zeros for my phi[step] at the end. I am happy to report that once a "kickstart" value is provided in the value section for cellVariable (I used 0.001), and utilized in conjunction with ImplicitDiffusion, and the timestepduration is increased from its limit of 0.9x**2/2D to the utilized 9x**2/2D used in the example documentation it more or less adheres to the image generated when run from the command line. Grateful to have this sorted. Hope this provides assistance to anyone else who might run into a similar problem.

user13708466
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