Visualization

Postprocessing of Fluent results can be done with either built-in Fluent postprocessing capabilities, PyVista, or Matplotlib integration.

Fluent TUI command example

Here visualization objects are constructed within Fluent. You can use standard Fluent commands to write graphics to a file.

solver_session.tui.display.objects.contour['contour-1'] = {'boundary_values': True, 'color_map': {'color': 'field-velocity', 'font_automatic': True, 'font_name': 'Helvetica', 'font_size': 0.032, 'format': '%0.2e', 'length': 0.54, 'log_scale': False, 'position': 1, 'show_all': True, 'size': 100, 'user_skip': 9, 'visible': True, 'width': 6.0}, 'coloring': {'smooth': False}, 'contour_lines': False, 'display_state_name': 'None', 'draw_mesh': False, 'field': 'pressure', 'filled': True, 'mesh_object': '', 'node_values': True, 'range_option': {'auto_range_on': {'global_range': True}}, 'surfaces_list': [2, 5]}
solver_session.tui.display.objects.contour['contour-1']()
solver_session.tui.display.objects.contour['contour-1'].field.set_state('velocity-magnitude')
solver_session.tui.display.objects.contour['contour-1'].field()
solver_session.tui.display.objects.contour['contour-1'].color_map.size.set_state(80.0)
solver_session.tui.display.objects.contour['contour-1'].color_map.size()
solver_session.tui.display.objects.contour['contour-1'].rename('my-contour')
del solver_session.tui.display.objects.contour['my-contour']

PyVista example (graphics)

Here field data is extracted from the Fluent session into the Python environment. PyVista is then used to visualize the extracted data.

# import module
from ansys.fluent.visualization.pyvista import Graphics

# get the graphics objects for the session

graphics_session1 = Graphics(solver_session)
mesh1 = graphics_session1.Meshes["mesh-1"]
contour1 = graphics_session1.Contours["contour-1"]
contour2 = graphics_session1.Contours["contour-2"]
surface1 = graphics_session1.Surfaces["surface-1"]

# set graphics objects properties

# mesh
mesh1.show_edges = True
mesh1.surfaces_list = ['symmetry']

# contour
contour1.field = "velocity-magnitude"
contour1.surfaces_list = ['symmetry']

contour2.field = "temperature"
contour2.surfaces_list = ['symmetry', 'wall']

# copy
graphics_session1.Contours["contour-3"] = contour2()

# update
contour3 = graphics_session1.Contours["contour-3"]
contour3.update(contour1())

# delete
del graphics_session1.Contours["contour-3"]

# loop
for name, _ in graphics_session1.Contours.items():
    print(name)

# iso surface
surface1.surface.iso_surface.field= "velocity-magnitude"
surface1.surface.iso_surface.rendering= "contour"

# display
contour1.display()
mesh1.display()
surface1.display()

# To display in specific window e.g. window-2
contour1.display("window-2")

Matplotlib example (XY plots)

Here plot data is extracted from the Fluent session into the Python environment. Matplotlib is then used to plot data.

# import module
from ansys.fluent.visualization.matplotlib import Plots

# get the plots object for the session
plots_session1 = Plots(solver_session)

#get xyplot object
plot1=plots_session1.XYPlots["plot-1"]

#set properties
plot1.surfaces_list = ["symmetry"]
plot1.y_axis_function = "temperature"

#Draw plot
plot1.plot("window-1")

solver_session.exit()