perfect-postcode/pipeline/transform/postcode_boundaries/process_oa.py
2026-05-28 21:48:35 +01:00

245 lines
7.8 KiB
Python

from collections import Counter, defaultdict
import numpy as np
from scipy.spatial import cKDTree
from shapely import STRtree, make_valid
from shapely.geometry import MultiPolygon, Polygon
from shapely.ops import unary_union
from .voronoi import compute_voronoi_regions
MIN_GEOM_AREA = 0.01
def process_oa(
oa_geom: Polygon | MultiPolygon,
points: np.ndarray,
postcodes: list[str],
inspire_candidates: list[Polygon],
) -> list[tuple[str, Polygon | MultiPolygon]]:
"""Process a single OA → list of (postcode, geometry) fragments."""
unique_pcs = set(postcodes)
if len(unique_pcs) == 1:
return [(next(iter(unique_pcs)), oa_geom)]
if len(points) == 0:
return []
valid_oa = _clean_polygonal(oa_geom)
if valid_oa is None:
return []
if inspire_candidates:
claimed = _claim_inspire_parcels(valid_oa, points, postcodes, inspire_candidates)
else:
claimed = {}
# Compute remaining area
if claimed:
all_claimed = unary_union(list(claimed.values()))
all_claimed = _clean_polygonal(all_claimed)
remaining = (
valid_oa.difference(all_claimed) if all_claimed is not None else valid_oa
)
remaining = _clean_polygonal(remaining)
else:
remaining = valid_oa
# Distribute non-parcel land via Voronoi
if remaining is not None and not remaining.is_empty and remaining.area > MIN_GEOM_AREA:
voronoi_result = compute_voronoi_regions(points, postcodes, remaining)
else:
voronoi_result = {}
# Combine claimed + voronoi
result: dict[str, list] = defaultdict(list)
for pc, geom in claimed.items():
result[pc].append(geom)
for pc, geom in voronoi_result.items():
result[pc].append(geom)
fragments = []
for pc, parts in result.items():
merged = _clean_polygonal(unary_union(parts))
if merged is not None:
fragments.append((pc, merged))
return fragments
def _claim_inspire_parcels(
valid_oa: Polygon | MultiPolygon,
points: np.ndarray,
postcodes: list[str],
inspire_candidates: list[Polygon],
) -> dict[str, Polygon | MultiPolygon]:
"""Assign INSPIRE parcels to postcodes before Voronoi fills non-parcel land."""
parcels = _prepare_inspire_parcels(valid_oa, inspire_candidates)
if not parcels:
return {}
cand_tree = STRtree(parcels)
from shapely import points as shp_points
uprn_pts = shp_points(points)
pt_idx, cand_idx = cand_tree.query(uprn_pts, predicate="within")
# First priority: parcels that physically contain UPRNs. Majority vote
# resolves blocks of flats or overlapping parcel data.
cand_postcodes: dict[int, list[str]] = defaultdict(list)
for pi, ci in zip(pt_idx, cand_idx):
cand_postcodes[ci].append(postcodes[pi])
contained_parts: dict[str, list] = defaultdict(list)
contained_scores: Counter[str] = Counter()
for ci, pc_list in cand_postcodes.items():
pc_counts = Counter(pc_list)
winner, votes = pc_counts.most_common(1)[0]
contained_parts[winner].append(parcels[ci])
contained_scores[winner] += votes
contained_claimed = _merge_parts_by_postcode(contained_parts)
contained_claims = sorted(
contained_claimed.items(),
key=lambda item: (-contained_scores[item[0]], -item[1].area, item[0]),
)
# Second priority: remaining INSPIRE parcels with no contained UPRN. Assign
# each to the nearest UPRN/postcode so parcel boundaries carry more of the
# visible postcode shape; Voronoi is then limited to roads, parks, water, and
# any other non-parcel gaps.
points_f64 = points.astype(np.float64, copy=False)
contained_union = _union_claims(contained_claims)
nearest_tree = cKDTree(points_f64)
nearest_parts: dict[str, list] = defaultdict(list)
for i, parcel in enumerate(parcels):
if i in cand_postcodes:
continue
assignable = parcel
if contained_union is not None:
assignable = assignable.difference(contained_union)
for part in _polygon_parts(assignable):
part = _clean_polygonal(part)
if part is None:
continue
pc = _nearest_postcode(part, nearest_tree, postcodes)
nearest_parts[pc].append(part)
nearest_claimed = _merge_parts_by_postcode(nearest_parts)
nearest_claims = sorted(
nearest_claimed.items(),
key=lambda item: (-item[1].area, item[0]),
)
return _resolve_ordered_claims(contained_claims + nearest_claims)
def _prepare_inspire_parcels(
valid_oa: Polygon | MultiPolygon,
inspire_candidates: list[Polygon],
) -> list[Polygon | MultiPolygon]:
parcels: list[Polygon | MultiPolygon] = []
for candidate in inspire_candidates:
geom = _clean_polygonal(candidate)
if geom is None:
continue
if not geom.intersects(valid_oa):
continue
clipped = _clean_polygonal(geom.intersection(valid_oa))
if clipped is not None:
parcels.append(clipped)
return parcels
def _nearest_postcode(
geom: Polygon | MultiPolygon,
tree: cKDTree,
postcodes: list[str],
) -> str:
point = geom.representative_point()
_, idx = tree.query([point.x, point.y])
return postcodes[idx]
def _polygon_parts(geom) -> list[Polygon]:
geom = _clean_polygonal(geom)
if geom is None:
return []
if geom.geom_type == "Polygon":
return [geom]
return list(geom.geoms)
def _merge_parts_by_postcode(
parts_by_postcode: dict[str, list],
) -> dict[str, Polygon | MultiPolygon]:
merged: dict[str, Polygon | MultiPolygon] = {}
for pc, parts in parts_by_postcode.items():
geom = _clean_polygonal(unary_union(parts))
if geom is not None:
merged[pc] = geom
return merged
def _union_claims(
claims: list[tuple[str, Polygon | MultiPolygon]],
) -> Polygon | MultiPolygon | None:
if not claims:
return None
return _clean_polygonal(unary_union([geom for _, geom in claims]))
def _resolve_ordered_claims(
claims: list[tuple[str, Polygon | MultiPolygon]],
) -> dict[str, Polygon | MultiPolygon]:
"""Resolve overlapping parcel claims in priority order."""
resolved_parts: dict[str, list] = defaultdict(list)
used = None
for pc, geom in claims:
geom = _clean_polygonal(geom)
if geom is None:
continue
if used is not None:
geom = _clean_polygonal(geom.difference(used))
if geom is None:
continue
resolved_parts[pc].append(geom)
used = _clean_polygonal(geom if used is None else unary_union([used, geom]))
return _merge_parts_by_postcode(resolved_parts)
def _clean_polygonal(geom) -> Polygon | MultiPolygon | None:
if geom is None or geom.is_empty:
return None
if not geom.is_valid:
geom = make_valid(geom)
geom = _extract_polygonal(geom)
if geom is None or geom.is_empty or geom.area <= MIN_GEOM_AREA:
return None
return geom
def _extract_polygonal(geom) -> Polygon | MultiPolygon | None:
"""Extract only Polygon/MultiPolygon parts from a geometry.
make_valid can produce GeometryCollections containing lines and points;
this strips those away and returns only the polygonal component.
"""
if geom.geom_type in ("Polygon", "MultiPolygon"):
return geom
if geom.geom_type == "GeometryCollection":
polys = [g for g in geom.geoms if g.geom_type in ("Polygon", "MultiPolygon")]
if not polys:
return None
if len(polys) == 1:
return polys[0]
return MultiPolygon(
[
p
for g in polys
for p in (g.geoms if g.geom_type == "MultiPolygon" else [g])
]
)
return None