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