spacetransformer.core.relation_check

core.relation_check

Spatial relationship checking utilities for 3D medical image spaces.

This module provides functions for checking spatial relationships between different medical image spaces, including overlap detection, alignment checking, and geometric compatibility validation.

Example: Check if two spaces have overlapping regions:

>>> from spacetransformer.core import Space
>>> from spacetransformer.core.relation_check import find_tight_bbox
>>> source = Space(shape=(100, 100, 50), spacing=(1.0, 1.0, 2.0))
>>> target = Space(shape=(50, 50, 25), spacing=(2.0, 2.0, 4.0))
>>> bbox = find_tight_bbox(source, target)
>>> print(bbox.shape)
(3, 2)

Functions

Name	Description
find_tight_bbox	Calculate the tight bounding box of source space in target index coordinates.

find_tight_bbox

core.relation_check.find_tight_bbox(source, target)

Calculate the tight bounding box of source space in target index coordinates.

This function computes the minimal bounding box that contains all corners of the source space when transformed to the target space’s index coordinates. The bounding box uses half-open intervals [left, right).

Args: source: Source space to compute bounding box for target: Target space coordinate system

Returns: np.ndarray: Bounding box array of shape (3, 2) where bbox[:,0] contains left bounds and bbox[:,1] contains right bounds (exclusive)

Example: >>> from spacetransformer.core import Space >>> source = Space(shape=(100, 100, 50), spacing=(1.0, 1.0, 2.0)) >>> target = Space(shape=(50, 50, 25), spacing=(2.0, 2.0, 4.0)) >>> bbox = find_tight_bbox(source, target) >>> print(bbox) [[ 0 50] [ 0 50] [ 0 25]]