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Regions were stored as infix token streams including parenthesis and operator tokens. Evaluating a complex region scanned the tokens while tracking parenthesis depth, precedence was enforced by inserting parentheses, and bounding boxes required converting the expression to postfix on every call. Region specifications are now parsed with a recursive descent parser into an expression tree of intersections and unions with half-spaces as leaves. Nested operators of the same type are merged, so the depth of the tree is the number of alternations between intersection and union. The tree is stored in pre-order with the index of the end of each subtree and of the parent of each node, so contains_complex evaluates it in a single loop without recursion, skipping the rest of a subtree as soon as its value is known. The half-spaces of a region are also stored as a contiguous list, which is all a simple region needs and is used for distance calculations. Complements are removed while parsing by applying De Morgan's laws to the tree. Previously complement operators were removed by flipping the operators in the token stream before precedence was enforced, so the complement of an expression mixing intersection and union without inner parentheses, such as ~(1 2 | 3), was interpreted as -1 | (-2 -3) instead of (-1 | -2) -3. Expressions written by the Python API are fully parenthesized and were not affected. A test comparing cell lookup against the Python region parser for random expressions is added. Region strings written to the summary file are generated from the tree. They are equivalent to the previous strings, but redundant parentheses are no longer kept. n_surfaces now returns the number of half-spaces rather than the number of tokens including operators. Results are identical for the tested models. Transport time is unchanged for lattice and simple geometries, and reduced by 16% for a water tank containing 400 rods, where the water region is the tank minus the rods. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
CSGCell::find_left_parenthesis searched token streams and had no callers, the cell ID argument of Region::bounding_box was only used for error messages when converting the expression to postfix, and the <set> and <sstream> includes are no longer used in cell.cpp. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
Region::str() is now generated from the expression tree, in which nested operators of the same type are merged and redundant parentheses are not kept, so the expected string for the issue openmc-dev#3685 case changes from " ( ( -1 2 ( -3 4 ) ) | ( -5 6 ) )" to the equivalent " ( -1 2 -3 4 ) | ( -5 6 )". Add cases checking that complements of mixed expressions are applied after grouping. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
…ches A bounding box is computed for each CSG cell at initialization, enlarged slightly for roundoff, and the searches over the cells of a universe and over neighbor lists skip cells whose boxes do not contain the point before evaluating whether the cell contains it. Cells are checked in the same order as before, so the same cell is found, while expensive containment checks are replaced by a box test for cells that cannot contain the point. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
A simple region needs only its half-spaces, so the expression tree of a complex region is moved behind a pointer. This keeps Region, and the cells holding it, small for the common case of simple cells. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
The distance to the boundary of a complex region is found by stepping from one surface crossing to the next along the ray until crossing a surface changes whether the ray is in the region. Every step recomputed the distance to and the sense with respect to every half-space of the region, so a call with k virtual crossings cost (k + 1) N distance and up to (k + 2) N sense evaluations for N half-spaces, counting surfaces that appear several times in the expression once per appearance. The half-spaces in the expression tree of a complex region now refer to a list of the distinct surfaces of the region. Distances and senses are evaluated once per distinct surface per call and updated as the ray moves: distances to the other surfaces decrease by the distance moved, and only the surfaces at the new position are evaluated again. The updated distances are only used to select the next candidate surface; the distance to the candidate is recomputed from the current position, so the result is the same as before apart from the choice among surfaces at exactly the same distance. Membership is evaluated from the cached senses with the same tree evaluation as contains_complex. The cached distances and senses are kept in working space owned by each particle, next to its boundary information, and sized once for the region with the most surfaces, so that no memory is allocated during transport. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
Each particle keeps working space for finding boundaries in complex regions, sized for the region with the most surfaces. In event-based mode up to max_particles_in_flight particles exist at once, so a region with thousands of surfaces could need gigabytes. The total size of the working space of the particles in flight is now limited to 256 MB, and regions with more surfaces than it then holds are searched as before, without it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
The working space for finding boundaries in complex regions was sized in the constructor of every geometry state, including the temporary ones used only to locate a point, such as when checking whether a sampled source site is in the source's domain. With a complex region of thousands of surfaces, each of these allocated and zeroed tens of kilobytes; a fixed source constrained to a small cell ran 7 times slower than before. The working space is now sized when a particle is constructed. Other geometry states have none, and search complex regions without it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
A region that is the intersection of many children, such as the water around rods or the matrix around TRISO particles, was evaluated by testing every child, both to determine whether it contains a point and to find the distance to its boundary. When enough of the children are false only within finite boxes, the children with boxes are now put in a bounding volume hierarchy, and only the children whose boxes contain the point, or whose boxes the ray enters before the nearest boundary found so far, are evaluated. A region that is an intersection of half-spaces, such as the space outside of many spheres, is searched the same way. The tree is used when at least 32 children have finite boxes and a point is in at most an eighth of the boxes on average, as estimated from their volumes. Children without finite boxes that are single half-spaces, such as the walls of a vessel made of many planes, are searched together in one pass over their surfaces, as in a simple region. Other regions are evaluated as before. Results are unchanged apart from roundoff in the distance to a boundary reached after virtual crossings. The surfaces of each child are stored consecutively, so that a child is searched with working space for its own surfaces only. In event-based mode, where the working space of each particle may be too small for all of the surfaces of the region, the children are still searched with it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
Finding the cell containing a point checks the cells of a universe in order, skipping cells whose bounding boxes do not contain the point. In a universe with many cells, such as the layers of many TRISO particles placed directly in a matrix, testing every bounding box is itself the cost, and neighbor lists grow to hold most of the cells. A universe whose cells have finite bounding boxes that rarely overlap is now searched with a bounding volume hierarchy over the boxes, using the same tree and the same rule as regions outside of many objects: at least 32 boxes, and a point in at most an eighth of them on average. Of the cells whose boxes contain the point, the first in the universe that contains it is found, as in a search of all of the cells, so the cell found is unchanged. Neighbor lists in such a universe hold at most eight cells, so that a cell next to many others, such as a matrix around many particles, has its neighbors found with the tree, while a cell with few neighbors is still found from its neighbor list. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
In a universe searched with a tree, neighbor lists hold at most eight cells. A cell next to many others, such as the water around many rods, fills its list, and every search from it then checked the eight cells in the list before searching the tree. Such a list is now marked as full, and searches from its cell go to the tree directly. Cells with few neighbors still find them from their lists. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RN7JroEkrbkLKVHbMDap9
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Description
This PR is stacked on the region tree PR (#4167) and on #4163. Only the last two commits are new.
Finding the cell containing a point checks the cells of a universe in order. With #4163, cells whose bounding boxes do not contain the point are skipped. In a universe with many cells, such as the layers of many TRISO particles placed directly in a matrix, testing every bounding box is itself the cost. Neighbor lists don't help either: the matrix's list grows to hold most of the cells.
With this PR, a universe whose cells have finite bounding boxes that rarely overlap is searched with a bounding volume hierarchy over the boxes. It uses the same tree, and the same rule, as the region tree PR: at least 32 boxes, and a point in at most an eighth of them on average.
The rule for using a tree moves to
box_treeso that regions and universes share it, and the geometry methods documentation describes the search.Results
Transport time, single thread, median of interleaved runs (3 to 6 per build), compared with the region tree PR (#4167). Results are bit-identical on every model.
Flat models no longer need lattices to be fast. On the same machine:
developWith delta tracking (#3971 merged with this PR):
Adversarial model checked against
develop:developfind each new cell in one or two checks. 0.90 times the time ofdevelop. Before neighbor lists were kept in tree universes, this model was 1.2 times slower.Testing
test_cell_search.py(from Skip cells whose bounding boxes do not contain the point in cell searches #4163) now runs through the tree: cells found for random points agree with Python's evaluation of the regions.develop.Checklist