pyfieldml Quickstart¶

Five-minute demo: install, load a dataset, inspect, evaluate, and export.

Install¶

This notebook assumes pyfieldml is already installed:

pip install pyfieldml[meshio]

In [ ]:

from pyfieldml import datasets

doc = datasets.load_unit_cube()
print("Version :", doc.source_version)
print("Region  :", doc.region.name)

from pyfieldml import datasets doc = datasets.load_unit_cube() print("Version :", doc.source_version) print("Region :", doc.region.name)

Inspect the evaluator graph¶

In [ ]:

for name, ev in doc.evaluators.items():
    print(f"{name:30s}  {type(ev).__name__}")

for name, ev in doc.evaluators.items(): print(f"{name:30s} {type(ev).__name__}")

Extract coordinates as NumPy¶

In [ ]:

coords_ev = doc.evaluators["coordinates"]
xyz = coords_ev.as_ndarray()
print("coords shape:", xyz.shape)
print("coords:")
print(xyz)

coords_ev = doc.evaluators["coordinates"] xyz = coords_ev.as_ndarray() print("coords shape:", xyz.shape) print("coords:") print(xyz)

Evaluate the coordinate field at the element centroid¶

In [ ]:

coords = doc.field("coordinates")
centroid = coords.evaluate(element=1, xi=(0.5, 0.5, 0.5))
print("centroid:", centroid)

coords = doc.field("coordinates") centroid = coords.evaluate(element=1, xi=(0.5, 0.5, 0.5)) print("centroid:", centroid)

Export to meshio (requires [meshio] extra)¶

In [ ]:

try:
    m = doc.to_meshio()
    print("meshio cell type:", m.cells[0].type, "count:", len(m.cells[0].data))
except ImportError as exc:
    print("meshio not installed; install with: pip install pyfieldml[meshio]")
    print(exc)

try: m = doc.to_meshio() print("meshio cell type:", m.cells[0].type, "count:", len(m.cells[0].data)) except ImportError as exc: print("meshio not installed; install with: pip install pyfieldml[meshio]") print(exc)

Next steps¶

• See 02_evaluator_graph.ipynb for a tour of the evaluator hierarchy.
• See 04_muscle_fibers.ipynb for a fiber-field workflow.