"""Parse a ``patterns.config`` programme into per-code space requirements. Only the ``spaces:`` section is read here. Generic codes (c/o/s) carry no explicit targets and are left unconstrained by the solver (they absorb slack). """ from __future__ import annotations from dataclasses import dataclass, field import yaml # Urb::Dom::Fitness defaults for optional params (ProgrammeDriven.default_params). _DEFAULT_WIDTH = (4.0, 1.0) _DEFAULT_PROPORTION = (1.5, 0.5) @dataclass class SpaceReq: code: str name: str = "" size: float = 0.0 # target floor area, m^2 size_sigma: float = 1.0 width: float = _DEFAULT_WIDTH[0] width_sigma: float = _DEFAULT_WIDTH[1] proportion: float = _DEFAULT_PROPORTION[0] # max length/width ratio proportion_sigma: float = _DEFAULT_PROPORTION[1] adjacency: list[str] = field(default_factory=list) level: int | None = None requires_below: str | None = None count: int = 1 # erc.3 §13.3 leaf-sharing grain (homemaker-py-x3b): how many rooms of this # code may collapse into one shared leaf. Default 1 = not shareable. Under the # global ``leaf_share_factor`` selector an explicit value overrides the global # grain (share:1 opts a code OUT, share:N>=2 sets that code's grain to N). share: int = 1 # 9o5 §7.5 veto hatch (homemaker-py-b3v): opt a code OUT of interchange-class # derivation. Default True = eligible. Set ``interchange: false`` in # patterns.config to let the architect suppress a harmful auto-derived # grouping (e.g. harbor-house's transitive 8-code chain) without disabling # superposition globally. interchange: bool = True # 1s3 §26 path b: codes this one may permanently co-locate on (fuse onto) # one leaf with. Explicit, architect-declared (unlike the auto-derived # interchange classes above) — a pair is only ever honoured if it *also* # passes interchangeable()'s S1-S4 bounds (see derive_colocate_pairs). co_locate: list[str] = field(default_factory=list) # Whether each quality param was explicitly in the config (not a default) has_size: bool = False has_width: bool = False has_proportion: bool = False has_share: bool = False def _pair(d: dict, key: str, default: tuple[float, float]) -> tuple[float, float]: v = d.get(key) if v is None: return default return float(v[0]), float(v[1]) # homemaker-py-ju3 (DESIGN.md §39.2): Urb's type system is prefix-based — a # leaf type starting with "c" is circulation, "o"/"s" is outside — and # programme room codes share that namespace. A code starting with one of these # letters is silently reinterpreted as a generic type, with three unannounced # consequences: ``graph.check_space_counts`` skips it entirely (so the room is # never required), ``Fitness.get_space_params`` returns the generic # ``*_circulation``/``*_outside`` parameters instead of the declared ones, and # ``dom.is_circulation``/``is_outside`` flip (changing value rate, crinkliness # treatment, and whether the leaf supplies daylight to neighbours). # # harbor-house shipped four such codes for years — ``cr1`` "Common Room with # Fireplace" had its declared 80 m² read as circulation's 0-30 m², and 14% of # the programme was silently optional. Refusing the code at load turns a silent # misread into a loud one. The other prefixes with semantics (l/k/b/t) are NOT # reserved: they only flavour adjacency heuristics and never discard a # requirement, so programme codes may use them freely. RESERVED_PREFIXES = ("c", "o", "s") def validate_codes(codes) -> None: """Raise ``ValueError`` if any programme code collides with a generic type. Called from both parse paths (``_parse_spaces`` and ``fitness.Fitness._load_programme``) so a colliding code cannot enter the system through either door. """ bad = sorted(c for c in codes if c and c[0].lower() in RESERVED_PREFIXES) if not bad: return raise ValueError( "programme code(s) collide with Urb's reserved generic type prefixes " f"{RESERVED_PREFIXES} (c=circulation, o/s=outside): {bad}. " "Such a code is silently treated as a generic type: it is dropped from " "the required-space check, its declared size/width/proportion are " "replaced by the generic circulation/outside parameters, and it is " "valued at the circulation/outside rate. Rename the code to start with " "another letter (the name: field is free text and need not change). " "See DESIGN.md §39.2 / homemaker-py-ju3." ) def _parse_spaces(conf: dict) -> dict[str, SpaceReq]: spaces = conf.get("spaces") or {} validate_codes(spaces) out: dict[str, SpaceReq] = {} for code, c in spaces.items(): size = _pair(c, "size", (0.0, 1.0)) width = _pair(c, "width", _DEFAULT_WIDTH) prop = _pair(c, "proportion", _DEFAULT_PROPORTION) out[code] = SpaceReq( code=code, name=c.get("name", ""), size=size[0], size_sigma=size[1], width=width[0], width_sigma=width[1], proportion=prop[0], proportion_sigma=prop[1], adjacency=list(c.get("adjacency") or []), level=c.get("level"), requires_below=c.get("requires_below"), count=int(c.get("count") or 1), share=int(c.get("share") or 1), interchange=bool(c.get("interchange", True)), co_locate=list(c.get("co_locate") or []), has_size="size" in c, has_width="width" in c, has_proportion="proportion" in c, has_share="share" in c, ) return out def load_programme(path: str) -> dict[str, SpaceReq]: with open(path) as fh: conf = yaml.safe_load(fh) return _parse_spaces(conf) # --------------------------------------------------------------------------- # # Interchange equivalence classes (homemaker-py-9o5, type superposition) # --------------------------------------------------------------------------- # # # A maximal group of codes whose leaf requirements are SIMILAR enough that one # leaf is genuinely substitutable for any in-class usage. Derived as a pure # function of the parsed programme (no hand-authored list on the happy path). # Used by the superposition+collapse search relaxation: a leaf typed to any # in-class code is left uncommitted during search and re-assigned to its best # in-class usage at scoring time (fitness.collapse_superposition). # # Thresholds are LOCKED defaults (Bruno 2026-06-29); conservative on purpose — # a missed grouping is cheap, a wrong one corrupts the relaxation. R_SIZE = 1.5 # larger area target <= 1.5x smaller R_WIDTH = 1.3 # clear-width targets vary less than areas; tighter band R_PROP = 1.5 # max length/width aspect targets within 1.5x CLASS_CAP = 4 # brute-force collapse <= C! assignments; beyond this use Hungarian def _ratio(x: float, y: float) -> float: """max/min of two positive magnitudes (inf if either is non-positive).""" lo, hi = min(abs(x), abs(y)), max(abs(x), abs(y)) return hi / lo if lo > 0 else float("inf") def interchangeable(a: SpaceReq, b: SpaceReq) -> bool: """True iff codes ``a`` and ``b`` satisfy the S1-S4 interchange relation (homemaker-py-9o5 §2). Symmetric.""" # S0 — architect veto (homemaker-py-b3v): either code opted out. if not a.interchange or not b.interchange: return False # S1 — both sized; generic circulation/outside never participate. if not (a.has_size and b.has_size) or a.size <= 0 or b.size <= 0: return False if a.code[0].lower() in ("c", "o", "s") or b.code[0].lower() in ("c", "o", "s"): return False # S2 — requirement similarity within bounded ratios (ALL three). if _ratio(a.size, b.size) > R_SIZE: return False if _ratio(a.width, b.width) > R_WIDTH: return False if _ratio(a.proportion, b.proportion) > R_PROP: return False # S3 — compatible level (equal or one None) and matching service stack. if a.level is not None and b.level is not None and a.level != b.level: return False if (a.requires_below or None) != (b.requires_below or None): return False # S4 — no direct adjacency edge (an adjacency pair are coexisting rooms). if b.code in a.adjacency or a.code in b.adjacency: return False return True def derive_interchange_classes(reqs: dict[str, SpaceReq]) -> list[frozenset[str]]: """Connected components of the interchange relation, size >= 2 (homemaker-py-9o5 §2). Each class is a set of mutually-substitutable codes. """ codes = [ c for c, r in reqs.items() if r.interchange and r.has_size and r.size > 0 and c[0].lower() not in ("c", "o", "s") ] edges: dict[str, set[str]] = {c: set() for c in codes} for i, a in enumerate(codes): for b in codes[i + 1:]: if interchangeable(reqs[a], reqs[b]): edges[a].add(b) edges[b].add(a) seen: set[str] = set() classes: list[frozenset[str]] = [] for c in codes: if c in seen: continue comp: set[str] = set() stack = [c] while stack: x = stack.pop() if x in comp: continue comp.add(x) seen.add(x) stack.extend(edges[x] - comp) if len(comp) >= 2: classes.append(frozenset(comp)) return classes # --------------------------------------------------------------------------- # # Co-location pairs (homemaker-py-1s3, §26 path b: permanent multi-use leaves) # --------------------------------------------------------------------------- # # # Unlike interchange classes (auto-derived, soft substitution), fusing two # codes onto one permanent leaf is architect-declared per-code (``co_locate``) # — but a declared pair is only ever honoured if it ALSO passes the existing # interchangeable() S1-S4 relation. This reuses the already-validated bounds # (size/width/proportion similarity, compatible level/service stack, no direct # adjacency edge) instead of inventing a second relation, and — because pairs # are kept individually rather than folded into connected components — sidesteps # the b3v transitive-chain failure mode (a nonsensical A-C fusion can never be # smuggled in via a declared A-B, B-C chain the way interchange classes could). def derive_colocate_pairs(reqs: dict[str, SpaceReq]) -> list[frozenset[str]]: """Valid co-location pairs: architect-declared AND interchangeable(). A code may declare ``co_locate: [other_code, ...]``; declaration is symmetric (either side declaring is sufficient). Returns one frozenset per valid pair (size always 2); an entry with no interchangeable() partner is silently dropped, never merged into a larger group. """ pairs: list[frozenset[str]] = [] seen: set[frozenset[str]] = set() for code, req in reqs.items(): for other in req.co_locate: if other not in reqs or other == code: continue key = frozenset((code, other)) if key in seen: continue seen.add(key) if interchangeable(reqs[code], reqs[other]): pairs.append(key) return pairs def n_storeys_required(reqs: dict[str, SpaceReq]) -> int: """Number of storeys the programme implies, from the highest ``level:`` key. Level-free rooms (no ``level``) do not force extra storeys — they are distributed across whatever storeys the level-constrained rooms require. """ levels = [r.level for r in reqs.values() if r.level is not None] return (max(levels) + 1) if levels else 1 def partition_rooms_by_storey( reqs: dict[str, SpaceReq], n_storeys: int, rng, ) -> list[dict[str, int]]: """Per-storey required-room multisets (DESIGN.md §11.3 staging). Level-constrained rooms land on their required storey; level-free rooms are distributed round-robin over a shuffled order across all storeys. Generic circulation/outside/sahn codes are excluded (they are added per storey at construction time). Mirrors the inline partition in ``operators.constructive_topology`` so Stage 1 (base) and Stage 2 (upper deltas) draw from one consistent partition. Returns a list of length ``n_storeys``; each entry maps room code -> count. """ buckets: list[dict[str, int]] = [{} for _ in range(n_storeys)] def _add(li: int, code: str) -> None: buckets[li][code] = buckets[li].get(code, 0) + 1 free: list[str] = [] for code, req in reqs.items(): if code[0].lower() in ("c", "o", "s"): continue for _ in range(req.count): if req.level is not None and req.level < n_storeys: _add(req.level, code) else: free.append(code) free = [free[i] for i in rng.permutation(len(free))] for i, code in enumerate(free): _add(i % n_storeys, code) return buckets def write_stage1_programme( full_dir: str | Path, out_dir: str | Path, base_codes: dict[str, int], ) -> Path: """Derive a single-storey base-floor programme (DESIGN.md §11.3 Stage 1). Filters the full merged ``patterns.config`` down to the rooms assigned to the base floor (``base_codes``: code -> count), drops their ``level:`` keys, prunes each kept space's ``adjacency`` to references that survive (retained codes or generic c/o/s), and forces single-storey building constraints. The result is written as a *self-contained* ``patterns.config`` in ``out_dir`` so ``fitness.load_config``'s parent-dir merge contributes nothing — keep ``out_dir`` outside the corpus tree (e.g. a tempdir). Returns ``out_dir`` as a ``Path``. """ from pathlib import Path as _Path from . import fitness as _fit out_dir = _Path(out_dir) out_dir.mkdir(parents=True, exist_ok=True) conf, _cost = _fit.load_config(full_dir) keep = set(base_codes) src_spaces = conf.get("spaces") or {} new_spaces: dict = {} for code, count in base_codes.items(): if code not in src_spaces: continue spec = dict(src_spaces[code]) spec.pop("level", None) spec["count"] = count adj = spec.get("adjacency") if adj is not None: spec["adjacency"] = [ r for r in adj if r in keep or r[0].lower() in ("c", "o", "s") ] new_spaces[code] = spec new_conf = {k: v for k, v in conf.items() if k != "spaces"} new_conf["spaces"] = new_spaces new_conf.update( storey_minimum=1, storey_limit=1, staircase_min=1, staircase_max=1, ) with open(out_dir / "patterns.config", "w") as fh: yaml.safe_dump(new_conf, fh, sort_keys=False, default_flow_style=False) return out_dir def _load_merged_conf(directory: "str | Path") -> dict: """Merge ``../patterns.config`` then the local one (mirrors load_config).""" from pathlib import Path as _Path directory = _Path(directory) conf: dict = {} for p in (directory.parent / "patterns.config", directory / "patterns.config"): if p.is_file(): with open(p) as fh: conf.update(yaml.safe_load(fh) or {}) return conf def load_programme_dir(directory: str | Path) -> dict[str, SpaceReq]: """Load programme from a directory, merging parent patterns.config as base. Mirrors urb-evolve.pl: ../patterns.config loaded first, then the local file's top-level keys override it (same shallow-merge as fitness.load_config). """ return _parse_spaces(_load_merged_conf(directory)) def storey_minimum(directory: str | Path) -> int: """Minimum storey count the programme requires (``storey_minimum`` key). Independent of ``level:`` keys: a programme can demand N storeys via ``storey_minimum`` without pinning any room to an upper floor (e.g. programme-house: ``storey_minimum: 2`` but all rooms ``level: 0``). The constructive seeder and the staged/plain dispatch must honour it, else the seed is built one storey short and fitness fires a ``storey minimum`` fail the search has to repair structurally (DESIGN.md §12.2). """ return int(_load_merged_conf(directory).get("storey_minimum") or 1) def n_storeys_for(directory: str | Path) -> int: """Storeys the programme implies: the max of level-derived and storey_minimum.""" reqs = load_programme_dir(directory) return max(n_storeys_required(reqs), storey_minimum(directory))