134 lines
4.4 KiB
Python
134 lines
4.4 KiB
Python
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"""
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Mesh Converter Utility
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Converts Nastran BDF/OP2 files to GLTF for web visualization
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"""
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import json
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import numpy as np
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from pathlib import Path
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from typing import Optional, Dict, Any
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import trimesh
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from pyNastran.bdf.bdf import BDF
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from pyNastran.op2.op2 import OP2
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def convert_study_mesh(study_dir: Path) -> Optional[Path]:
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"""
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Convert the mesh and results of a study to GLTF format.
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Args:
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study_dir: Path to the study directory
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Returns:
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Path to the generated GLTF file, or None if conversion failed
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"""
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try:
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# Locate files
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setup_dir = study_dir / "1_setup" / "model"
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results_dir = study_dir / "2_results"
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vis_dir = study_dir / "3_visualization"
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vis_dir.mkdir(parents=True, exist_ok=True)
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# Find BDF/DAT file
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bdf_files = list(setup_dir.glob("*.dat")) + list(setup_dir.glob("*.bdf"))
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if not bdf_files:
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# Fallback: Generate placeholder if no BDF found
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return _generate_placeholder_mesh(vis_dir)
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bdf_path = bdf_files[0]
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# Find OP2 file (optional)
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op2_files = list(results_dir.glob("*.op2"))
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op2_path = op2_files[0] if op2_files else None
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# Load BDF
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model = BDF()
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model.read_bdf(bdf_path, xref=False)
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# Extract nodes and elements
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# This is a simplified extraction for shell/solid elements
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# A full implementation would handle all element types
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nodes = []
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node_ids = []
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for nid, node in model.nodes.items():
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nodes.append(node.get_position())
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node_ids.append(nid)
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nodes = np.array(nodes)
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node_map = {nid: i for i, nid in enumerate(node_ids)}
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faces = []
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# Process CQUAD4/CTRIA3 elements
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for eid, element in model.elements.items():
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if element.type == 'CQUAD4':
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n = [node_map[nid] for nid in element.nodes]
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faces.append([n[0], n[1], n[2]])
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faces.append([n[0], n[2], n[3]])
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elif element.type == 'CTRIA3':
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n = [node_map[nid] for nid in element.nodes]
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faces.append([n[0], n[1], n[2]])
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if not faces:
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# Fallback if no compatible elements found
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return _generate_placeholder_mesh(vis_dir)
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# Create mesh
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mesh = trimesh.Trimesh(vertices=nodes, faces=faces)
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# Map results if OP2 exists
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if op2_path:
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op2 = OP2()
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op2.read_op2(op2_path)
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# Example: Map displacement magnitude to vertex colors
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if 1 in op2.displacements:
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disp = op2.displacements[1]
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# Get last timestep
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t3 = disp.data[-1, :, :3] # Translation x,y,z
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mag = np.linalg.norm(t3, axis=1)
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# Normalize to 0-1 for coloring
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if mag.max() > mag.min():
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norm_mag = (mag - mag.min()) / (mag.max() - mag.min())
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else:
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norm_mag = np.zeros_like(mag)
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# Apply colormap (simple blue-to-red)
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colors = np.zeros((len(nodes), 4))
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colors[:, 0] = norm_mag # R
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colors[:, 2] = 1 - norm_mag # B
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colors[:, 3] = 1.0 # Alpha
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mesh.visual.vertex_colors = colors
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# Export to GLTF
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output_path = vis_dir / "model.gltf"
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mesh.export(output_path)
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# Save metadata
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metadata = {
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"node_count": len(nodes),
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"element_count": len(faces),
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"has_results": op2_path is not None
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}
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with open(vis_dir / "model.json", 'w') as f:
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json.dump(metadata, f, indent=2)
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return output_path
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except Exception as e:
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print(f"Mesh conversion error: {e}")
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# Fallback on error
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return _generate_placeholder_mesh(vis_dir)
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def _generate_placeholder_mesh(output_dir: Path) -> Path:
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"""Generate a simple box mesh for testing"""
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mesh = trimesh.creation.box(extents=[10, 10, 10])
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output_path = output_dir / "model.gltf"
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mesh.export(output_path)
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with open(output_dir / "model.json", 'w') as f:
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json.dump({"placeholder": True}, f)
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return output_path
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