Neutron flux in a graphite stack

User Support
21

Seems to be working now, thank you for helping

22

Wanted to ask about the differences between uses matplotlib vs your openmc-mesh-plotter

graphite flux mesh_plotter Thermal Neutrons
graphite flux log mesh_plotter Thermal Neutrons
Above is using mesh_plotter

graphite flux log Thermal Neutrons matplotlib
graphite flux Thermal Neutrons matplotlib
Above is matplotlib

Not sure how to interpret the differences between these two, maybe to do with my having resize my slice array for the pyplot?

23

The plotter does use matplotlib behind the scenes so you should be able to look at the source code and slice, reshape etc in the same way with matplotlib. I plan to add plotly functionality at some point

1 Like
24

I figured out why my matplotlib direct plots looks weird was that I was resizing the data to a mesh dimension that it already was.

What I don’t understand is why my plots seem completely incorrect when using matplotlib directly. Your regular mesh plotter package gives accurately that the thermal neutron flux for my geometry but through how I plot it manually through matplotlib it seems to be upside down? I know that your mesh plotting package takes into account the geometry of the model so I wonder if it’s something to do with that.
image

Thank you again for all the help so far

matplotlib code snippet

    my_slice = my_tally.get_slice(scores=['flux']) # don't need to resize, resolution is the same
    plt.figure(1)
    plt.imshow(my_slice.mean, extent=mesh.bounding_box.extent['xz'], norm=colors.LogNorm())
    plt.xlabel('x [cm]')
    plt.ylabel('z [cm]')
    plt.title(f'Flux in {material_choice} (log scale) - {energy}')
    plt.savefig(f'{material_choice} flux log {energy} matplotlib.png')
    plt.figure(2)
    plt.imshow(my_slice.mean, extent=mesh.bounding_box.extent['xz'])
    plt.xlabel('x [cm]')
    plt.ylabel('z [cm]')
    plt.title(f'Flux in {material_choice} - {energy}')
    plt.savefig(f'{material_choice} flux {energy} matplotlib.png')