vcti-nptree 1.0.0

Vectorized, numpy-backed tree: parent-id topology and user-defined fields in one growable structured array, with vectorized operations over node ids.

vcti-nptree

Vectorized, numpy-backed tree: parent-index topology and user-defined fields in one growable structured array, with vectorized operations over node indices.

Overview

vcti-nptree provides NpTree, a single-rooted tree whose structure and per-node data live together in one growable numpy structured array (backed by GrowableArray from vcti-nputils):

• One record per node, addressed by its integer row index. The record carries parent_index, a flags column (active / locks), and any fixed-width user fields declared at construction.
• parent_index is the structure. Children and siblings are vectorized scans of that column (parent_index == n), ancestors are a short parent-chain walk, and per-node fields roll up with np.bincount(parent_index, weights=field).
• Soft deletion clears the ACTIVE bit and leaves the row in place — nothing is moved or renumbered, so node indices stay stable for the life of the tree and every vectorized operation keeps working with deletions present. delete(..., fill=...) optionally writes a per-field "inactive" / "na" / zero / custom value so aggregations stay branchless without even consulting the mask.

It is built for vectorized operations over sets of nodes — aggregating, masking, or rolling up fields across many nodes at once, rather than walking the tree one node at a time. Nodes are addressed by integer indices and index-arrays (not opaque handles), which is what lets those operations be plain numpy.

The design and rationale are documented in docs/design.md.

Installation

pip install vcti-nptree

In requirements.txt

vcti-nptree>=1.0.0

In pyproject.toml dependencies

dependencies = [
    "vcti-nptree>=1.0.0",
]

---

Quick Start

import numpy as np
from vcti.nptree import FieldSpec, NpTree

# Declare fixed-width user fields: a schema dtype plus the per-field default and
# inactive values (unspecified fields default to zero).
spec = FieldSpec.create(
    np.dtype([("mass", "f8")]), default={"mass": 0.0}, inactive={"mass": 0.0}
)

tree = NpTree(spec)                # the root is node 0
p1 = tree.create_child(tree.root)
p2 = tree.create_child(tree.root)

# Bulk-create a level of elements under the parts (one vectorized append).
tree.create_children(np.array([p1, p1, p2]), mass=np.array([3.0, 4.0, 10.0]))

# Vectorized roll-up: every node's subtree total in one pass.
totals = tree.subtree_sum("mass")
assert totals[tree.root] == 17.0           # whole tree

# Soft-delete a subtree; aggregations still work and node indices stay valid.
tree.delete(p1)
assert tree.subtree_sum("mass")[tree.root] == 10.0

---

Dependencies

• vcti-nputils >=1.6.0 — GrowableArray storage backing.
• vcti-multi-valued-array >=1.5.0 — the CSR / ragged container for the parent→children index.
• numpy>=1.26 — structured-array storage and vectorized operations.
• numba>=0.59 — compiles the per-node kernels (DFS walk orders, ordered ancestor chains).