Datasets:
Formats:
json
Languages:
English
Size:
< 1K
Tags:
agentfem
finite-element-method
scientific-machine-learning
physics-ai
simulation
heat-transfer
License:
| """Plot heat inputs and recorded FEM temperatures. SPDX-License-Identifier: Apache-2.0 | |
| pip install numpy h5py matplotlib huggingface_hub | |
| python plot_heat.py | |
| python plot_heat.py --data test.h5 --sample 00016 --output heat.png | |
| This reads an existing FEM result, not a new simulation or neural prediction. | |
| Data: CC BY 4.0, Haoming Luo / AgentFEM-MultiSource-Heat-2D (2026). | |
| """ | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| import h5py | |
| import matplotlib | |
| matplotlib.use("Agg") | |
| import matplotlib.pyplot as plt | |
| import matplotlib.tri as mtri | |
| import numpy as np | |
| REPO = "HaomingLuo/AgentFEM-MultiSource-Heat-2D" | |
| REVISION = "7d19e509b4fdc33c767cbc469c9a669d817b11e4" | |
| def read_sample(path, sample_id=None): | |
| with h5py.File(path, "r") as handle: | |
| key = sample_id or sorted(handle)[0] | |
| if key not in handle: | |
| raise ValueError(f"Sample {key!r} not found. Available: {', '.join(sorted(handle))}") | |
| group = handle[key] | |
| parameters = json.loads(group.attrs["parameters_json"]) | |
| xy = group["coordinates"][:, :2] | |
| triangles = group["connectivity"][:] | |
| source = group["inputs/source_w_m3"][:] | |
| temperature = group["point/Temperature"][:] | |
| boundary = group["inputs/cooled_boundary"][:].astype(bool) | |
| if triangles.shape[1] != 3: | |
| raise ValueError("This recipe expects linear triangular elements.") | |
| if not all(np.isfinite(a).all() for a in (xy, source, temperature)): | |
| raise ValueError("Non-finite field values.") | |
| if not boundary.any(): | |
| raise ValueError("Missing cooled boundary nodes.") | |
| if not np.allclose(temperature[boundary], 300.0, atol=1e-7, rtol=0): | |
| raise ValueError("Boundary temperature differs from the documented 300 K.") | |
| return key, parameters, xy, triangles, source, temperature | |
| def main(): | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--data", type=Path, help="Existing split HDF5 file; otherwise download pinned test split") | |
| parser.add_argument("--sample", help="Sample ID, for example 00016") | |
| parser.add_argument("--output", type=Path, default=Path("heat-input-output.png")) | |
| args = parser.parse_args() | |
| path = args.data | |
| if path is None: | |
| from huggingface_hub import hf_hub_download | |
| path = hf_hub_download(REPO, "test.h5", repo_type="dataset", revision=REVISION) | |
| key, p, xy, triangles, source, temperature = read_sample(path, args.sample) | |
| peak = int(np.argmax(temperature)) | |
| report = { | |
| "sample": key, | |
| "conductivity_W_m_K": p["conductivity_w_m_k"], | |
| "peak_temperature_K": float(temperature[peak]), | |
| "peak_rise_K": float(temperature[peak] - 300), | |
| "peak_node_xy_mm": (xy[peak] * 1000).tolist(), | |
| "source": "Recorded finite-element result; not a new solve", | |
| } | |
| print(json.dumps(report, indent=2)) | |
| mesh = mtri.Triangulation(xy[:, 0] * 1000, xy[:, 1] * 1000, triangles) | |
| plt.rcParams.update({"font.family": "DejaVu Sans", "font.size": 10, | |
| "axes.spines.top": False, "axes.spines.right": False}) | |
| fig, axes = plt.subplots(1, 2, figsize=(11, 4.4)) | |
| fig.subplots_adjust(left=.065, right=.95, bottom=.21, top=.76, wspace=.34) | |
| fig.suptitle("Two heat sources. One temperature field.", x=.065, ha="left", y=.96, | |
| fontsize=19, fontweight="bold", color="#173a42") | |
| fig.text(.065, .855, f"AgentFEM / sample {key} / k = {p['conductivity_w_m_k']:.2f} W/(m K)" | |
| " / all edges at 300 K", color="#536a70") | |
| for ax, values, title, label, cmap in zip( | |
| axes, (source / 1e6, temperature - 300), | |
| ("Input: distributed heat generation", "Output: temperature rise"), | |
| ("q / MW m$^{-3}$", "T - 300 K / K"), ("magma", "inferno")): | |
| artist = ax.tripcolor(mesh, values, shading="gouraud", cmap=cmap, vmin=0) | |
| fig.colorbar(artist, ax=ax, fraction=.045, pad=.035, label=label) | |
| ax.set(title=title, xlabel="x / mm", ylabel="y / mm", aspect="equal") | |
| ax.set_xlim(0, p["length_m"] * 1000) | |
| ax.set_ylim(0, p["height_m"] * 1000) | |
| axes[1].plot(*(xy[peak] * 1000), "o", ms=5, mfc="none", mec="#66e4dc", mew=1.4) | |
| fig.text(.065, .08, f"Peak nodal rise: {temperature[peak] - 300:.3f} K. " | |
| "The hottest point need not coincide with the strongest source.", color="#173a42") | |
| fig.text(.065, .025, "Recorded FEM fields • source shown by nodal interpolation • data CC BY 4.0 • Haoming Luo / AgentFEM", | |
| fontsize=8, color="#536a70") | |
| args.output.parent.mkdir(parents=True, exist_ok=True) | |
| fig.savefig(args.output, dpi=180, facecolor="white") | |
| plt.close(fig) | |
| if __name__ == "__main__": | |
| main() | |