Heat Flux Interpolation Example¶

from interpcore.interpolator import Interpolator
from interpcore.config import InterpolationConfig, ColumnsConfig, QUERY_TYPE, INTERPOLATED_LOAD_TYPE
from interpcore.kernels import INTERPOLATION_KERNEL

# Create configuration for AVERAGE kernel with HEAT_FLUX load type
config = InterpolationConfig(
    method=QUERY_TYPE.K,
    param=3,
    max_distance=2.0,
    coincidence_tolerance=0.01,
    kernel=INTERPOLATION_KERNEL.AVERAGE,
    multithread=False,
    interpolated_load=INTERPOLATED_LOAD_TYPE.HEAT_FLUX
)

# Define column indices (including area column for integral computation)
columns = ColumnsConfig(id=0, dest_xyz=1, source_xyz=1, value=4, volume_area=4)

# Create interpolator
interpolator = Interpolator(
    path_to_src_folder="source_data",
    path_to_dest_mesh="destination_mesh.txt",
    config=config,
    columns=columns
)

# Run interpolation
interpolator.interpolate_all()
print("Interpolation completed!")

from tempfile import TemporaryDirectory

with TemporaryDirectory() as tmp_dir:
    interpolator.export_to_ansys(tmp_dir)  # the export command

    # Preview the exported file content
    with open(f"{tmp_dir}/interpolated_heat_flux_data.txt", "r") as f:
        for line in f.readlines()[:5]:
            print(line.strip())

import pyvista as pv
import matplotlib.pyplot as plt

interpolator.build_vtk_output(outdir=None) # set to an existing path to export vtk files

source_cloud = interpolator.src_vtk["heat_flux_data"]
dest_cloud = interpolator.dest_vtk["heat_flux_data"]

# Create a static plot comparing the two clouds side by side
fig, axes = plt.subplots(1, 2, figsize=(14, 6))

# Plot source cloud with gaussian points
plotter_src = pv.Plotter(off_screen=True)
plotter_src.add_mesh(source_cloud, scalars='Value', cmap='hot', point_size=10, 
                     render_points_as_spheres=False, style='points')
plotter_src.add_title('Source Cloud (Heat Flux Data)', font_size=12)
plotter_src.camera_position = 'xy'
img_src = plotter_src.screenshot(return_img=True)
plotter_src.close()

# Plot destination cloud with gaussian points
plotter_dest = pv.Plotter(off_screen=True)
plotter_dest.add_mesh(dest_cloud, scalars='Value', cmap='hot', point_size=10, 
                      render_points_as_spheres=False, style='points')
plotter_dest.add_title('Destination Cloud (Interpolated)', font_size=12)
plotter_dest.camera_position = 'xy'
img_dest = plotter_dest.screenshot(return_img=True)
plotter_dest.close()

# Display in matplotlib
axes[0].imshow(img_src)
axes[0].axis('off')
axes[0].set_title('Source Cloud', fontsize=14, fontweight='bold')

axes[1].imshow(img_dest)
axes[1].axis('off')
axes[1].set_title('Destination Cloud (Interpolated)', fontsize=14, fontweight='bold')

plt.tight_layout()
plt.show()

# Compute the total heat flux integral over the surface area
integrals = interpolator.compute_scalar_integrals()

print(f"{'='*60}")
print("Total Heat Flux Integrals")
print(f"{'='*60}")
for name, integral in integrals.items():
    print(f"\n{name}: {integral[0]:.6f} W (or units of heat_flux * area)")