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AR-VMS-Seaman/vmssailor/studio/designer/rule_engine.py
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alro65 6ad76a89fa sprint-2: rule engine + auto-assigner + equipment editor + biblioteca
Wizard pasos 5-7 ahora funcionales (1-4 ya estaban en Sprint 1).

vmssailor/studio/designer/rule_engine.py
- RuleContext, RuleEngine, EquipmentProposal
- Lee library/rules/*.yaml y aplica reglas heuristicas
- Filtra por vessel_type, vessel_subtype, length_overall_m range
- Selecciona candidato segun condiciones 'when' (loa min/max)
- Genera tag_prefix con sustitucion {side}/{idx}

vmssailor/studio/designer/port_auto_assigner.py
- auto_assign() greedy: 1 bus Modbus RTU + tarjetas dedicadas para motores/gensets
- Tarjeta auxiliar compartida para resto de equipos
- Mapea SignalType -> ChannelType (AI/DI/DO/RPM)
- Genera TagBindings con scaling apropiado por tipo de senal
- Respeta capacidades 10/5/4/1 de AR-NMEA-IO-v1.0
- AssignmentReport con cards + tags + warnings

vmssailor/studio/wizard/step_05_equipment.py
- Tabla con propuestas del rule engine
- Checkboxes accept/reject + edicion inline de columnas
- Boton 'Regenerar' para re-aplicar reglas

vmssailor/studio/wizard/step_06_refinement.py
- Vista resumen de equipos aceptados

vmssailor/studio/wizard/step_07_topology.py
- Llama auto_assign sobre los equipos materializados
- Muestra tabla de tarjetas con uso por canal (DO/DI/AI/RPM)
- Lista warnings de capacidad

vmssailor/studio/editors/equipment_editor.py
- CRUD de Equipment del proyecto activo
- Tabla editable inline (tag_prefix, name, model_ref, system_id, coords, deck)
- Dialog modal para agregar equipos
- Senal projectMutated para refrescar canvas + sidebar

vmssailor/studio/main_window.py
- Layout actualizado: splitter vertical en panel derecho
  (canvas arriba + equipment editor abajo)
- _on_project_mutated() re-distribuye al sidebar y canvas

Biblioteca expandida (Sprint 2 brief: 5-7 yates, 10+ motores, gensets, bombas):
- vessels: + azimut_grande_32m, princess_y85, trawler_32m_offshore, patrol_coastal_30m (total: 6)
- engines: + cat_c32_acert, mtu_16v_2000_m96, yanmar_8lv_370 (total: 5)
- gensets: + kohler_28efkozd, onan_qd13500 (total: 3)
- pumps: + jabsco_36800, grundfos_cm10 (NUEVO categoria pumps)

Tests (tests/studio/test_designer.py, 10 nuevos, total 120/120):
- Rule engine: load default, propose engines, candidate picking por LOA
- auto_assign builds topology compatible with Project (Pydantic validation)
- Equipment editor smoke

VesselWizard.build_project() ahora materializa equipment + topology + tags
desde las propuestas y la asignacion automatica del paso 7.

Criterios Sprint 2:
- uv run vms-studio crea proyecto completo desde wizard con equipos + tags + topologia
- vms-validate-library: OK 6 vessels, 10 equipment, 1 rules
- 120/120 pytest verde, ruff clean

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-17 09:50:33 -04:00

197 lines
6.8 KiB
Python

"""Motor de reglas heurísticas — Studio Sprint 2.
Lee `vmssailor/library/rules/*.yaml` y, dado el contexto del wizard
(tipo de buque, subtipo, eslora, sistemas habilitados), produce una lista
de `EquipmentProposal` que el wizard muestra al integrador.
El integrador acepta/edita/rechaza cada propuesta antes de pasar al paso 6
(refinamiento manual).
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
from vmssailor.core.coords import ShipCoord
from vmssailor.core.enums import SystemId, VesselSubtype, VesselType
from vmssailor.library import load_library
@dataclass(slots=True)
class EquipmentProposal:
"""Una propuesta concreta de equipo para el integrador.
El integrador puede:
- aceptarla tal cual → se materializa en un Equipment del proyecto
- editarla (modelo distinto, ubicación distinta, prefix diferente)
- rechazarla
"""
system_id: SystemId
model_ref: str
"""ID de EquipmentModel de la biblioteca."""
tag_prefix: str
"""Prefijo de tags sugerido (ME_PORT, GEN_1, BILGE_FWD, etc.)."""
display_name: str
"""Nombre humano para el integrador."""
location_x_pp: float
location_y_cl: float
location_z_bl: float
rationale: str = ""
"""Por qué la regla propone este equipo."""
accepted: bool = True
"""El integrador puede desmarcar para rechazar."""
def to_ship_coord(self) -> ShipCoord:
return ShipCoord(
x_pp=self.location_x_pp, y_cl=self.location_y_cl, z_bl=self.location_z_bl
)
@dataclass(slots=True)
class RuleContext:
"""Input que el wizard pasa al rule engine."""
vessel_type: VesselType
vessel_subtype: VesselSubtype
length_overall_m: float
beam_max_m: float
draft_m: float
systems_enabled: list[SystemId] = field(default_factory=list)
class RuleEngine:
"""Carga reglas YAML y produce propuestas para un contexto dado."""
def __init__(self, rules: dict[str, dict[str, Any]] | None = None) -> None:
if rules is None:
try:
rules = load_library().rules
except Exception:
rules = {}
self._rules = rules
def applicable_rules(self, ctx: RuleContext) -> list[str]:
"""Lista de rule_ids cuyo `meta.applies_to` matchea el contexto."""
out: list[str] = []
for rid, data in self._rules.items():
applies = (data.get("meta") or {}).get("applies_to") or {}
v_types = applies.get("vessel_types") or []
v_subs = applies.get("vessel_subtypes") or []
loa_range = applies.get("length_overall_m") or {}
if v_types and ctx.vessel_type.value not in v_types:
continue
if v_subs and ctx.vessel_subtype.value not in v_subs:
continue
lo = loa_range.get("min")
hi = loa_range.get("max")
if lo is not None and ctx.length_overall_m < float(lo):
continue
if hi is not None and ctx.length_overall_m > float(hi):
continue
out.append(rid)
return out
def propose(self, ctx: RuleContext) -> list[EquipmentProposal]:
"""Genera la lista completa de propuestas para un contexto."""
proposals: list[EquipmentProposal] = []
for rid in self.applicable_rules(ctx):
proposals.extend(self._propose_from_rule(rid, ctx))
return proposals
# ----- internals --------------------------------------------------
def _propose_from_rule(
self, rule_id: str, ctx: RuleContext
) -> list[EquipmentProposal]:
rule = self._rules.get(rule_id) or {}
sys_proposals = rule.get("equipment_proposals") or {}
out: list[EquipmentProposal] = []
for sys_str, block in sys_proposals.items():
if not isinstance(block, dict):
continue
try:
sys_id = SystemId(sys_str)
except ValueError:
continue
if sys_id not in ctx.systems_enabled:
continue
count = int(block.get("count", 1))
candidates = block.get("candidates") or []
# Pick the first candidate whose `when` matches ctx
chosen = self._pick_candidate(candidates, ctx)
if not chosen:
continue
model_ref = chosen.get("model_ref", "")
rationale = chosen.get("rationale", "")
tag_template = block.get("tag_prefix_template", sys_str.upper())
sides = block.get("sides") or []
location_tpl = block.get("location_template") or {}
for idx in range(count):
if sides and idx < len(sides):
side = sides[idx]
prefix = tag_template.replace("{side}", side)
side_key = side.lower()
loc = location_tpl.get(side_key) or location_tpl.get("default") or {}
else:
prefix = tag_template.replace("{idx}", str(idx + 1))
loc = location_tpl.get("default") or {}
x_pp = self._resolve_x(loc, ctx)
y_cl = float(loc.get("y_cl", 0.0))
z_bl = float(loc.get("z_bl", 1.0))
out.append(
EquipmentProposal(
system_id=sys_id,
model_ref=model_ref,
tag_prefix=prefix,
display_name=f"{prefix} · {model_ref}",
location_x_pp=x_pp,
location_y_cl=y_cl,
location_z_bl=z_bl,
rationale=rationale,
)
)
return out
def _pick_candidate(
self, candidates: list[dict[str, Any]], ctx: RuleContext
) -> dict[str, Any] | None:
for c in candidates:
when = c.get("when") or {}
loa = when.get("length_overall_m") or {}
lo = loa.get("min")
hi = loa.get("max")
if lo is not None and ctx.length_overall_m < float(lo):
continue
if hi is not None and ctx.length_overall_m > float(hi):
continue
return c
# Si no matchea ninguno con `when`, devolver el primero sin condiciones
for c in candidates:
if not c.get("when"):
return c
return candidates[0] if candidates else None
def _resolve_x(self, loc: dict[str, Any], ctx: RuleContext) -> float:
if "x_pp" in loc:
return float(loc["x_pp"])
if "x_pp_pct" in loc:
return float(loc["x_pp_pct"]) * ctx.length_overall_m
return ctx.length_overall_m * 0.30
def apply_rules(ctx: RuleContext) -> list[EquipmentProposal]:
"""Conveniencia: aplica todas las reglas globales al contexto."""
return RuleEngine().propose(ctx)