pyAEDT, Icepak and pyVista

[lorenzovecchietti]

After a discussion with @Leunamedaking on the possibilities of exporting data from (py)AEDT and handling everything in pyVista, I explored a few possibilities for Icepak. An important note is that due to native APIs limitation, this is quite slow and inefficient, especially when dealing with multiple quantities on large volumes.

(py)AEDT

Export data

First, we need to export the fields we are interested in and the model geometry from AEDT. To export the plot, it needs to be active.

ipk = Icepak(dest_file, version=242, non_graphical=True)

start_time_export_data = time.time()
# Export Geometry
objs = ipk.post.export_model_obj(export_path=temp_dir, export_as_single_objects=False)

# Export Temperature Solution
fp = ipk.post.create_fieldplot_volume(["Region"], "Temperature")
air_temp_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")
fp = ipk.post.create_fieldplot_volume(["Region"], "Ux")
air_ux_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")
fp = ipk.post.create_fieldplot_volume(["Region"], "Uy")
air_uy_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")
fp = ipk.post.create_fieldplot_volume(["Region"], "Uz")
air_uz_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")

fp = ipk.post.create_fieldplot_surface(["ALPHA_MAIN_PCB"], "Temperature")
pcb_temp_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")

plane = ipk.modeler.create_plane(plane_base_z="10mm", plane_normal_z="11mm")
fp = ipk.post.create_fieldplot_cutplane(plane.name, "Temperature")
cutplane_case = ipk.post.export_field_plot(fp.name, output_dir=temp_dir, file_format="case")
ipk.close_desktop()

Then we can work entirely on pyvista.

pyVista

Temperature on an Object (PCB)

pl = pyvista.Plotter(off_screen=True, window_size=(3840, 2160))
for filename in objs:
    if not filename[0].endswith("ALPHA_MAIN_PCB.obj"):
        reader = pyvista.get_reader(filename[0])
        mesh = reader.read()
        pl.add_mesh(
            mesh, smooth_shading=True, split_sharp_edges=True, ambient=0.05, opacity=0.2
        )
mesh = pyvista.read(pcb_temp_case)
pl.add_mesh(
    mesh,
    scalars="Temperature",
    lighting=False,
    scalar_bar_args={"title": "PCB Temperature"},
    cmap="hot",
)
pl.enable_ssao(kernel_size=128, radius=15, bias=0.5)
pl.enable_anti_aliasing("ssaa")
pl.view_xy()
pl.screenshot(os.path.join(original_folder, "pcb_temperature.png"))

Temperature cutplane

pl = pyvista.Plotter(off_screen=True, window_size=(3840, 2160))
for filename in objs:
    if not filename[0].endswith("ALPHA_MAIN_PCB.obj"):
        reader = pyvista.get_reader(filename[0])
        mesh = reader.read()
        pl.add_mesh(
            mesh, smooth_shading=True, split_sharp_edges=True, ambient=0.05, opacity=0.2
        )
reader = pyvista.get_reader(cutplane_case)
mesh = reader.read()
pl.add_mesh(
    mesh,
    scalars="Temperature",
    lighting=False,
    scalar_bar_args={"title": "Temperature"},
    cmap="hot",
)
pl.enable_ssao(kernel_size=128, radius=15, bias=0.5)
pl.enable_anti_aliasing("ssaa")
pl.view_xy()
pl.screenshot(os.path.join(original_folder, "pcbtemp.png"))

Streamlines

Here the code is slightly more complex, as we need to read the different ensight case files (and every time we reload the mesh, even if it's the same - see the warning at the beginning of the post), merge the data together and then proceed to plotting.

# Load the scalar fields from Ensight case files
mesh_ux = pyvista.read(air_ux_case)
mesh_uy = pyvista.read(air_uy_case)
mesh_uz = pyvista.read(air_uz_case)
mesh_temp = pyvista.read(air_temp_case)  # Load the temperature case
temp_block = mesh_temp[0]  # First block for temperature
# Extract the actual mesh (assuming it's the first block in MultiBlock)
ux_block = mesh_ux[0]  # First block
uy_block = mesh_uy[0]  # First block
uz_block = mesh_uz[0]  # First block
ux = ux_block.point_data.values()[0]
uy = uy_block.point_data.values()[0]
uz = uz_block.point_data.values()[0]
temperature = temp_block.point_data.values()[0]  # Temperature data
velocity = np.column_stack((ux, uy, uz))
ux_block.point_data["Velocity"] = velocity
ux_block.point_data["Temperature"] = temperature
seed = pyvista.Box(bounds=(-90, -85, 20, 60, 1, 28), level=10)
streamlines = ux_block.streamlines_from_source(
    seed, max_time=200.0, integration_direction="both"
)
pl = pyvista.Plotter(off_screen=True, window_size=(3840, 2160))
for filename in objs:
    reader = pyvista.get_reader(filename[0])
    mesh = reader.read()
    pl.add_mesh(
        mesh,
        smooth_shading=True,
        split_sharp_edges=True,
        ambient=0.05,
    )
pl.add_mesh(streamlines, line_width=4, scalars="Temperature", cmap="coolwarm")
pl.enable_ssao(kernel_size=128, radius=15, bias=0.5)
pl.enable_anti_aliasing("ssaa")
pl.screenshot(os.path.join(original_folder, "streamlines.png"))

Streamlines (animated)

p = pyvista.Plotter(off_screen=True, window_size=(3840, 2160))
p.enable_ssao(kernel_size=128, radius=15, bias=0.5)
p.enable_anti_aliasing("ssaa")
p.open_gif(os.path.join(original_folder, "streamlines.gif"))

for filename in objs:
    reader = pyvista.get_reader(filename[0])
    mesh = reader.read()
    p.add_mesh(
        mesh,
        smooth_shading=True,
        split_sharp_edges=True,
        ambient=0.05,
    )
p.show(auto_close=False)

nframes = 50
for i in range(nframes):
    streamlines = ux_block.streamlines_from_source(
        seed, max_time=0.1 + 200 / nframes * i, integration_direction="forward"
    )
    actor = p.add_mesh(streamlines, line_width=12, scalars="Temperature", clim=[20, 45])
    p.write_frame()
    p.remove_actor(actor)
    print(f"Frame {i}")

p.close()

Volumetric Render

This is the slowest plot.

pl = pyvista.Plotter(off_screen=True, window_size=(3840, 2160))
for filename in objs:
    reader = pyvista.get_reader(filename[0])
    mesh = reader.read()
    pl.add_mesh(
        mesh,
        smooth_shading=True,
        split_sharp_edges=True,
        ambient=0.05,
    )
opac = np.zeros(20)
opac[1:] = np.geomspace(1e-7, 0.01, 19)
opac[-15:] = [
    0.005,
    0.01,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
    0.05,
]
pl.add_volume(
    mesh_temp,
    opacity=opac,
    cmap="reds",
    clim=[0, 50],
    show_scalar_bar=True,
    scalar_bar_args={"title": "Temperature"},
    ambient=0.05,
)

pl.enable_ssao(kernel_size=128, radius=15, bias=0.5)
pl.enable_anti_aliasing("ssaa")

pl.add_point_labels(
    points=[-37.0, 43.0, 3.0],
    labels=[f"Max Temp 61.9 °C"],
    point_size=20,
    font_size=30,
    text_color="red",
)
pl.screenshot(os.path.join(original_folder, "volume.png"))

---

⚠️ NOTE

These lines:

pl.enable_ssao(kernel_size=128, radius=15, bias=0.5)
pl.enable_anti_aliasing("ssaa")

are there just to have the final image a bit cooler ;)