Björn Steinhagen
551 lines
20 KiB
Python
551 lines
20 KiB
Python
from collections import defaultdict
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from pydantic import Field
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from speckle_automate import (
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AutomateBase,
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AutomationContext,
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execute_automate_function,
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)
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from typing import Dict, Generator, Any, List
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from src.domain.carbon.databases.enums import (
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SteelDatabase,
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TimberDatabase,
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ConcreteDatabase,
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)
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from src.infrastructure.logging import Logging
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from src.services.carbon_calculator import CarbonCalculator
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from src.services.element_processor import ElementProcessor
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from src.services.material_processor import MaterialProcessor
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def create_one_of_enum(enum_cls):
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"""
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Helper function to create a JSON schema from an Enum class.
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This is used for generating user input forms in the UI.
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"""
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return [{"const": item.value, "title": item.name} for item in enum_cls]
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class FunctionInputs(AutomateBase):
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"""User-defined function inputs."""
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steel_database: str = Field(
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default=SteelDatabase.Type350MPa,
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title="Steel Database",
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description="Database used for the GWP of steel objects",
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json_schema_extra={"oneOf": create_one_of_enum(SteelDatabase)},
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)
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timber_database: str = Field(
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default=TimberDatabase.Binderholz2019,
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title="Timber Database",
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description="Database used for the GWP of timber objects",
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json_schema_extra={"oneOf": create_one_of_enum(TimberDatabase)},
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)
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concrete_database: str = Field(
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default=ConcreteDatabase.GulLowAir.value,
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title="Concrete Database",
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description="Database used for the GWP of concrete objects",
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json_schema_extra={"oneOf": create_one_of_enum(ConcreteDatabase)},
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)
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country: str = Field(
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default="CAN",
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title="Country",
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description="Country for concrete strength units (CAN: MPa, USA: PSI)",
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json_schema_extra={
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"oneOf": [
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{"const": "CAN", "title": "Canada (MPa)"},
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{"const": "USA", "title": "United States (PSI)"},
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]
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},
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)
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# Add reinforcement rates based on Image 1
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reinforcement_grade_beam: float = Field(
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default=100.0,
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title="Grade Beam Reinforcement (kg/m³)",
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)
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reinforcement_slab_on_grade: float = Field(
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default=85.0,
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title="Slab on Grade Reinforcement (kg/m³)",
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)
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reinforcement_pad_footing: float = Field(
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default=100.0,
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title="Pad Footing Reinforcement (kg/m³)",
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)
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reinforcement_pile: float = Field(
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default=100.0,
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title="Pile Reinforcement (kg/m³)",
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)
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reinforcement_strip_footing: float = Field(
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default=100.0,
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title="Strip Footing Reinforcement (kg/m³)",
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)
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reinforcement_pile_cap: float = Field(
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default=100.0,
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title="Pile Cap Reinforcement (kg/m³)",
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)
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reinforcement_gravity_wall: float = Field(
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default=150.0,
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title="Gravity Wall Reinforcement (kg/m³)",
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)
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reinforcement_column: float = Field(
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default=450.0,
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title="Column Reinforcement (kg/m³)",
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)
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reinforcement_shear_wall: float = Field(
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default=150.0,
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title="Shear Wall Reinforcement (kg/m³)",
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)
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reinforcement_concrete_slab: float = Field(
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default=120.0,
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title="Concrete Slab Reinforcement (kg/m³)",
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)
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reinforcement_beam: float = Field(
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default=220.0,
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title="Beam Reinforcement (kg/m³)",
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)
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reinforcement_topping_slab: float = Field(
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default=85.0,
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title="Topping Slab Reinforcement (kg/m³)",
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)
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class RevitCarbonAnalyzer:
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"""Main application for analyzing carbon in Revit models."""
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def __init__(
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self,
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material_processor: MaterialProcessor,
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element_processor: ElementProcessor,
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carbon_calculator: CarbonCalculator,
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logger: Logging,
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):
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"""
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Initialize with injected dependencies.
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Args:
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material_processor: Service for processing raw materials
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element_processor: Service for processing Revit elements
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carbon_calculator: Service for calculating carbon emissions
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logger: Logging service
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"""
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self.material_processor = material_processor
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self.element_processor = element_processor
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self.carbon_calculator = carbon_calculator
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self.logger = logger
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def analyze_model(self, model_root) -> dict:
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"""Analyze a Revit model for carbon emissions."""
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results = {
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"processed_elements": [],
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"skipped_elements": [],
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"errors": [],
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"total_carbon": 0.0,
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"missing_factors": {"timber": [], "steel": [], "concrete": []},
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}
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# Process each element
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for element in self._iterate_elements(model_root):
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try:
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element_result = self._process_single_element(element)
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if element_result["status"] == "processed":
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results["processed_elements"].append(element_result)
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results["total_carbon"] += element_result["total_carbon"]
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elif element_result["status"] == "skipped":
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results["skipped_elements"].append(element_result)
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else:
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results["errors"].append(element_result)
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except Exception as e:
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results["errors"].append(
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{
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"id": getattr(element, "id", "unknown"),
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"error": str(e),
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"status": "error",
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}
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)
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# Get missing factors
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(
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missing_timber,
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missing_steel,
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missing_concrete,
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) = self.carbon_calculator.get_missing_factors()
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results["missing_factors"]["timber"] = missing_timber
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results["missing_factors"]["steel"] = missing_steel
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results["missing_factors"]["concrete"] = missing_concrete
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# Log missing factors
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if missing_timber:
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print(f"Missing timber factors ({len(missing_timber)}):")
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for item in missing_timber:
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print(f" - {item}")
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if missing_steel:
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print(f"Missing steel factors ({len(missing_steel)}):")
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for item in missing_steel:
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print(f" - {item}")
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if missing_concrete:
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print(f"Missing concrete factors ({len(missing_concrete)}):")
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for item in missing_concrete:
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print(f" - {item}")
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return results
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def _process_single_element(self, element: Dict) -> Dict:
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"""Process a single element and return its results."""
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element_id = getattr(element, "id", "unknown")
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# Process element
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processed_element = self.element_processor.process_element(element)
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if not processed_element:
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return {
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"id": element_id,
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"status": "skipped",
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"reason": "Invalid element structure",
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}
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# Calculate carbon
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try:
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carbon_results = self.carbon_calculator.calculate_carbon(processed_element)
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# Initialize Embodied Carbon Calculation dictionary
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embodied_carbon_data = {}
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for material_name, result in carbon_results.items():
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# Create a dictionary for each material instead of an array
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material_data = {}
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if result.category == "Wood":
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# For timber - use name/value/units format as dictionary entries
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material_data = {
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"volume": {
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"name": "volume",
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"value": result.quantity,
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"units": "m³",
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},
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"database": {
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"name": "database",
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"value": result.database,
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"units": None,
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},
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"ecf": {
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"name": "ecf",
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"value": result.factor,
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"units": "kgCO₂e/m³",
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},
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"embodied carbon": {
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"name": "embodied carbon",
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"value": result.total_carbon,
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"units": "kgCO₂e",
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},
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}
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elif result.category == "Concrete":
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# For concrete (include both concrete and reinforcement)
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material_data = {
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"volume": {
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"name": "volume",
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"value": result.concrete_volume,
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"units": "m³",
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},
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"database": {
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"name": "database",
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"value": result.database,
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"units": None,
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},
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"ecf": {
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"name": "ecf",
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"value": result.factor,
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"units": "kgCO₂e/m³",
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},
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"concrete carbon": {
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"name": "concrete carbon",
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"value": result.concrete_carbon,
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"units": "kgCO₂e",
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},
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"reinforcement mass": {
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"name": "reinforcement mass",
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"value": result.reinforcement_mass,
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"units": "kg",
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},
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"reinforcement rate": {
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"name": "reinforcement rate",
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"value": result.reinforcement_rate,
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"units": "kg/m³",
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},
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"reinforcement ecf": {
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"name": "reinforcement ecf",
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"value": result.reinforcement_factor,
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"units": "kgCO₂e/kg",
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},
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"reinforcement carbon": {
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"name": "reinforcement carbon",
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"value": result.reinforcement_carbon,
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"units": "kgCO₂e",
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},
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"embodied carbon": {
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"name": "embodied carbon",
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"value": result.total_carbon,
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"units": "kgCO₂e",
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},
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}
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elif result.category == "Metal":
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# For metal
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material_data = {
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"mass": {
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"name": "mass",
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"value": result.quantity,
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"units": "kg",
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},
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"database": {
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"name": "database",
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"value": result.database,
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"units": None,
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},
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"ecf": {
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"name": "ecf",
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"value": result.factor,
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"units": "kgCO₂e/kg",
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},
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"embodied carbon": {
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"name": "embodied carbon",
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"value": result.total_carbon,
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"units": "kgCO₂e",
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},
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}
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# Add this material's data to the main dictionary
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embodied_carbon_data[material_name] = material_data
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# Attach the data to the original element
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if hasattr(element, "properties"):
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element.properties["Embodied Carbon Calculation"] = embodied_carbon_data
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return {
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"id": element_id,
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"status": "processed",
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"level": processed_element.level,
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"category": processed_element.category.value,
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"materials": [
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{
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"name": m.properties.name,
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"type": m.type.value,
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"volume": m.properties.volume,
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}
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for m in processed_element.materials
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],
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"carbon_results": carbon_results,
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"total_carbon": sum(r.total_carbon for r in carbon_results.values()),
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}
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except Exception as e:
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return {
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"id": element_id,
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"status": "error",
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"error": f"Carbon calculation failed: {str(e)}",
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}
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@staticmethod
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def _iterate_elements(model_data) -> Generator[Dict, None, None]:
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"""Iterate through all elements in the model."""
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for level in getattr(model_data, "elements", []):
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for type_group in getattr(level, "elements", []):
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for element_group in getattr(type_group, "elements", []):
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for element in getattr(element_group, "elements", []):
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yield element
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def automate_function(
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automate_context: AutomationContext,
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function_inputs: FunctionInputs,
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) -> None:
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"""Program entry point."""
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try:
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# Get string values from enums if needed
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steel_db = function_inputs.steel_database
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timber_db = function_inputs.timber_database
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concrete_db = function_inputs.concrete_database
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country = function_inputs.country
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# Ensure we're working with string values, not enum objects
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if hasattr(steel_db, "value"):
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steel_db = steel_db.value
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if hasattr(timber_db, "value"):
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timber_db = timber_db.value
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if hasattr(concrete_db, "value"):
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concrete_db = concrete_db.value
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# Create custom reinforcement rates dictionary
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custom_reinforcement_rates = {
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"Grade Beam": function_inputs.reinforcement_grade_beam,
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"Slab on Grade": function_inputs.reinforcement_slab_on_grade,
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"Pad Footing": function_inputs.reinforcement_pad_footing,
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"Pile": function_inputs.reinforcement_pile,
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"Strip Footing": function_inputs.reinforcement_strip_footing,
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"Pile Cap": function_inputs.reinforcement_pile_cap,
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"Walls - wind/gravity": function_inputs.reinforcement_gravity_wall,
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"Column": function_inputs.reinforcement_column,
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"Shear Walls": function_inputs.reinforcement_shear_wall,
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"Concrete Slabs": function_inputs.reinforcement_concrete_slab,
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"Beams": function_inputs.reinforcement_beam,
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"Topping Slabs": function_inputs.reinforcement_topping_slab,
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}
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# Create dependencies with proper DI
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logger = Logging()
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material_processor = MaterialProcessor()
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element_processor = ElementProcessor(
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material_processor=material_processor, logger=logger
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)
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carbon_calculator = CarbonCalculator(
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steel_database=steel_db,
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timber_database=timber_db,
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concrete_database=concrete_db,
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country=country,
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custom_reinforcement_rates=custom_reinforcement_rates,
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)
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# Initialize analyzer with injected dependencies
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analyzer = RevitCarbonAnalyzer(
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material_processor=material_processor,
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element_processor=element_processor,
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carbon_calculator=carbon_calculator,
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logger=logger,
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)
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# Get commit root
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version_id = automate_context.automation_run_data.triggers[0].payload.version_id
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commit_root = automate_context.speckle_client.commit.get(
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automate_context.automation_run_data.project_id, version_id
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)
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# Get model root
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model_root = automate_context.receive_version()
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# Validate Revit source
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if not _validate_revit_source(commit_root):
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automate_context.mark_run_failed("Model must be from Revit")
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return
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# Run analysis - convert Speckle model to dict for processing
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results = analyzer.analyze_model(model_root)
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# Process results
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_process_automation_results(automate_context, results)
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# Prepare detailed success message
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success_message = (
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f"🚀 Analysis complete.\n\n\tProcessed:\t\t{len(results['processed_elements'])} elements\n\t"
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f"Total carbon:\t{results['total_carbon']:.2f} kgCO₂e\n"
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)
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# Add missing factors to message if any
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missing_timber = results["missing_factors"]["timber"]
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missing_steel = results["missing_factors"]["steel"]
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if missing_timber or missing_steel:
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success_message += "\nMissing emission factors detected:\n"
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if missing_timber:
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success_message += (
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f"- Timber ({len(missing_timber)}): {', '.join(missing_timber[:5])}"
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)
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if len(missing_timber) > 5:
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success_message += f" and {len(missing_timber) - 5} more"
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success_message += "\n"
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if missing_steel:
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success_message += (
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f"- Steel ({len(missing_steel)}): {', '.join(missing_steel[:5])}"
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)
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if len(missing_steel) > 5:
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success_message += f" and {len(missing_steel) - 5} more"
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success_message += "\n"
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success_message += "\nThese materials were assigned zero carbon. Consider updating the database."
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else:
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success_message += (
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"\nNOTE: All materials successfully matched with emission factors."
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)
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# Upload mutated model
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automate_context.create_new_version_in_project(
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model_root, f"{commit_root.branchName}_embodied_carbon"
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)
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# Mark success with detailed message
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automate_context.mark_run_success(success_message)
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except Exception as e:
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automate_context.mark_run_failed(f"Analysis failed: {str(e)}")
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raise
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def _validate_revit_source(commit_root: Any) -> bool:
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"""Validate that the model is from Revit."""
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source_app = getattr(commit_root, "sourceApplication", "").lower()
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return source_app.startswith("revit")
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def _process_automation_results(
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automate_context: AutomationContext, results: dict
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) -> None:
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"""Process results and attach them to the automation context."""
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# Group results by category
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successes: Dict[str, List[str]] = defaultdict(list)
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warnings: Dict[str, List[str]] = defaultdict(list)
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errors: Dict[str, List[str]] = defaultdict(list)
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# Group successful elements
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for element in results["processed_elements"]:
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successes["Carbon Analysis"].append(element["id"])
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# Group skipped elements
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for element in results["skipped_elements"]:
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warnings["Skipped Elements"].append(element["id"])
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# Group errors
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for element in results["errors"]:
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errors["Processing Errors"].append(element["id"])
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# Attach grouped results
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for category, object_ids in successes.items():
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automate_context.attach_success_to_objects(
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category=category,
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object_ids=object_ids,
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message="Carbon calculations completed successfully for these elements!",
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)
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for category, object_ids in warnings.items():
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automate_context.attach_warning_to_objects(
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category=category,
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object_ids=object_ids,
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message="Elements requiring careful review.",
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)
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for category, object_ids in errors.items():
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automate_context.attach_error_to_objects(
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category=category,
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object_ids=object_ids,
|
|
message="Failure processing the following elements.",
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
execute_automate_function(automate_function, FunctionInputs)
|