User guide

You can use PyFluent-Visualization for postprocessing of Fluent results to display graphics objects and plot data.

Graphics operations

Examples follow for graphics operations that PyFluent-Visualization supports.

Display mesh

This example shows how you can display a mesh:

import ansys.fluent.core as pyfluent
from ansys.fluent.core import examples
from ansys.fluent.visualization import set_config
from ansys.fluent.visualization import Plots
from ansys.fluent.visualization import Graphics
from ansys.fluent.visualization.contour import Contour

set_config(blocking=True, set_view_on_display="isometric")

import_case = examples.download_file(
    file_name="exhaust_system.cas.h5", directory="pyfluent/exhaust_system"
)

import_data = examples.download_file(
    file_name="exhaust_system.dat.h5", directory="pyfluent/exhaust_system"
)

solver_session = pyfluent.launch_fluent(precision="double", processor_count=2, mode="solver")

solver_session.tui.file.read_case(import_case)
solver_session.tui.file.read_data(import_data)

graphics = Graphics(session=solver_session)
mesh1 = graphics.Meshes["mesh-1"]
mesh1.show_edges = True
mesh1.surfaces = [
    "in1",
    "in2",
    "in3",
    "out1",
    "solid_up:1",
    "solid_up:1:830",
    "solid_up:1:830-shadow",
]
mesh1.display("window-1")

Display iso-surface

This example shows how you can display an iso-surface:

surf_outlet_plane = graphics.Surfaces["outlet-plane"]
surf_outlet_plane.surface.type = "iso-surface"
iso_surf1 = surf_outlet_plane.surface.iso_surface
iso_surf1.field = "y-coordinate"
iso_surf1.iso_value = -0.125017
surf_outlet_plane.display("window-2")

Display contour

This example shows how you can display a contour:

temperature_contour_manifold = graphics.Contours["contour-temperature-manifold"]
temperature_contour_manifold.field = "temperature"
temperature_contour_manifold.surfaces = [
    "in1",
    "in2",
    "in3",
    "out1",
    "solid_up:1",
    "solid_up:1:830",
]
temperature_contour_manifold.display("window-3")

Instantiate a contour object with or without a solver session, using a field name and a list of surfaces, as follows. Target is either a Graphics object or a solver session.

temperature_contour_manifold = Contour(field="temperature",
                                       surfaces=["in1", "in2", "in3", "out1", "solid_up:1", "solid_up:1:830",])

temperature_contour_manifold = Contour(field="temperature",
                                       surfaces=["in1", "in2", "in3", "out1", "solid_up:1", "solid_up:1:830",],
                                       solver=solver_session)

# Create and render contour object on client side.
temperature_contour = temperature_contour_manifold.draw(solver=solver_session, target=Graphics(solver_session))

# Create and render contour object on server side.
temperature_contour = temperature_contour_manifold.draw(solver=solver_session, target=solver_session)

Display vector

This example shows how you can display a vector:

velocity_vector = graphics.Vectors["velocity-vector"]
velocity_vector.surfaces = ["outlet-plane"]
velocity_vector.scale = 1
velocity_vector.display("window-4")

Plot operations

Examples follow for plot operations that PyFluent-Visualization supports.

Display plot

This example shows how you can display the XY plot:

plots_session_1 = Plots(solver_session)
xy_plot = plots_session_1.XYPlots["xy-plot"]
xy_plot.surfaces = ["outlet"]
xy_plot.y_axis_function = "temperature"
xy_plot.plot("window-5")

Display solution residual plot

This example shows how you can display the solution residual plot:

matplotlib_plots1 = Plots(solver_session)
residual = matplotlib_plots1.Monitors["residual"]
residual.monitor_set_name = "residual"
residual.plot("window-6")

Display solution monitors plot

This example shows how you can display the solution monitors plot:

solver_session.tui.solve.initialize.hyb_initialization()
solver_session.tui.solve.set.number_of_iterations(50)
solver_session.tui.solve.iterate()
solver_session.monitors_manager.get_monitor_set_names()
matplotlib_plots1 = Plots(solver_session)
mass_bal_rplot = matplotlib_plots1.Monitors["mass-bal-rplot"]
mass_bal_rplot.monitor_set_name = "mass-bal-rplot"
mass_bal_rplot.plot("window-7")