Derived Fields
An extensible, catalog-driven library for computing derived fields from multi-component engineering data arrays
Overview
vcti.derived turns multi-component engineering result arrays — vectors,
6-DOF, symmetric stress/strain tensors — into derived fields such as
magnitude, von Mises, principal values and directions, and traction vectors.
It is pure numpy: plain arrays in, plain arrays out, with output dtype
following the input. Two faces sit over one implementation — bulk-first
kernels you call directly, and a catalog that enumerates which derived
fields exist per data family (with stable ids, display names, and parameters)
for driving menus and pipelines. Component order is handled explicitly, so
data from any solver (Abaqus, Nastran, Ansys, LS-Dyna) computes correctly
without reshuffling.
Installation
pip install vcti-derived
In requirements.txt
vcti-derived>=2.0.0
In pyproject.toml dependencies
dependencies = [
"vcti-derived>=2.0.0",
]
Quick Start
import numpy as np
from vcti.derived import ComponentOrder, DataFamily, catalogs, symtensor
stress = np.array([[100.0, 20.0, 5.0, 15.0, 0.0, 0.0]]) # (N, 6): xx yy zz xy yz xz
# Kernels directly:
vm = symtensor.von_mises(stress) # (N,) von Mises stress
s1 = symtensor.principals(stress)[:, -1] # (N,) max principal
# Data from a solver with a different component order (zero-copy):
vm = symtensor.von_mises(stress, order=ComponentOrder.ABAQUS)
# Or through the catalogs (organized by output kind):
entry = catalogs.get("symtensor3d.von_mises")
vm = entry.compute(stress)
for entry in catalogs.scalar.by_family(DataFamily.SYMTENSOR3D): # scalar-producing
print(entry.id, entry.display_name)
Dependencies
numpy only.
Documentation
| If you want to… | Read |
|---|---|
| Understand the architecture and design decisions | docs/design.md |
| Navigate and understand the source | docs/source-guide.md |
| See practical, real-world usage | docs/patterns.md |
| Extend the library | docs/extending.md |
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