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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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