Port SimStadt library code from old/ into src/simstadtpy/

Add results.py (KPI, SimStadtResults ABC + HeatDemand/PV/GreenWater subclasses),
runner.py (workflow execution), workflows.py (high-level simulation helpers),
and utils.py. Add pytest-based test suite (46 tests, all passing).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

old/cgsc/lib/__init__.py

+import logging
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(levelname)s: %(message)s'
+)

old/cgsc/lib/parse_greenwater_results.py

+from pathlib import Path
+import logging
+import re
+
+import pandas as pd
+
+import matplotlib
+import matplotlib.pyplot as plt
+
+matplotlib.use('agg')
+log = logging.getLogger(__name__)
+
+RAIN_L = "Sum rain [L]"
+RUNOFF_L = "Sum runoff [L]"
+ETC_L = "Sum ETc [L]"
+SINGLE_TREE_ETC_L = "Single tree ETc [L]"
+SINGLE_TREE_MISSING_WATER_L = "Single tree missing water [L]"
+
+SINGLE_TREE_MISSING_WATER_MM = "Single tree missing water [mm]"
+RAIN_MM = "Average rain [mm]"
+RUNOFF_MM = "Average runoff [mm]"
+ET0_MM = "et0 [mm]"
+ETC_MM = "Average ETc [mm]"
+
+# NOTE: This code isn't used anywhere, it was just a proposal for diagrams
+
+
+def parse_green_water_results(csv_path: str |Path, year: int = 2005) -> pd.DataFrame:
+    times = pd.date_range(start=f'{year}-01-01 00:00', freq='1h', periods=8760)
+    df = pd.read_csv(csv_path,
+                     sep=';',
+                     header=0,
+                     skiprows=list(range(9)) + list(range(10, 14)),
+                     )
+    df = df.rename(columns={"#": "time",
+                            "Sum rain over trees [L]": RAIN_L,
+                            "Missing water [L]": SINGLE_TREE_MISSING_WATER_L,
+                            "ETc [L]": SINGLE_TREE_ETC_L
+                            })
+    with open(csv_path, encoding='utf-8') as csv:
+        for _ in range(5):
+            line = next(csv)
+        tree_area_header = re.split('[;,]', line.strip())
+        tree_area = float(tree_area_header[1])
+        for _ in range(6):
+            line = next(csv)
+        species = re.split(';+', line)[1]
+        line = next(csv)
+        single_tree_area = float(re.split('[;,]+', line)[1])
+
+    log.info('Total tree area : %g m²', tree_area)
+    log.info('Largest tree (%s): %g m²', species, single_tree_area)
+    sum_columns = [col for col in df if 'Sum' in col]
+    for sum_column in sum_columns:
+        new_column = sum_column.replace('Sum', 'Average').replace('[L]', '[mm]')
+        column_idx = list(df).index(sum_column)
+        df.insert(loc=column_idx + 1, column=new_column, value= df[sum_column] / tree_area)
+
+    single_tree_columns = [col for col in df if 'Single tree' in col]
+    df[SINGLE_TREE_MISSING_WATER_L] = -df[SINGLE_TREE_MISSING_WATER_L]
+    for single_tree_column in single_tree_columns:
+        new_column = single_tree_column.replace('[L]', '[mm]')
+        column_idx = list(df).index(single_tree_column)
+        df.insert(loc=column_idx + 1, column=new_column, value= df[single_tree_column] / single_tree_area)
+
+    df = df.set_index(times)
+    df = df.drop(columns=['time'])
+    return df
+
+def plot_greenwater(csv_path, description, output_dir=Path('output')):
+    df = parse_green_water_results(csv_path)
+    df['net_rain_sum'] = (df[RAIN_MM]-df[RUNOFF_MM]).cumsum()
+
+    ax = (df[[SINGLE_TREE_MISSING_WATER_MM, RAIN_MM, RUNOFF_MM]]).plot(grid=True)
+    title = f"Missing Water\n{description}"
+    plt.title(title)
+    ax.set_ylabel("[mm]")
+    png_path1 = output_dir / f"missing_water_{description}.png"
+    plt.savefig(png_path1, bbox_inches='tight')
+    plt.close()
+
+
+    ax = (df[[SINGLE_TREE_MISSING_WATER_MM, 'net_rain_sum']]).plot()
+    title = f"Missing Water\n{description}"
+    ax.set_ylabel("[mm]")
+    plt.title(title)
+    png_path2 = output_dir / f"missing_water_sum_{description}.png"
+    plt.savefig(png_path2,
+                bbox_inches='tight')
+    plt.close()
+
+
+    ax = df[[ETC_MM, RAIN_MM]].resample('1ME').sum().plot.bar()
+    title = f"Monthly ETc & Rain\n{description}"
+    ax.set_ylabel("[mm]")
+    month_labels = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
+    ax.set_xticklabels(month_labels)
+    plt.title(title)
+    png_path3 = output_dir / f"etc_{description}.png"
+    plt.savefig(png_path3,
+                bbox_inches='tight')
+    plt.close()
+    return png_path1, png_path2, png_path3

old/cgsc/lib/run_simstadt_workflow.py

+r"""Tries to find simstadt, find a workflowstep, and run it with the specified
+CityGMLs.
+
+It could be useful in order to run the same workflows with many different CityGMLs, or with slightly different
+parameters.
+
+User config part will probably need to be updated.
+Corresponding workflows can be defined and saved in the SimStadt GUI.
+
+
+Example output with the current configuration:
+
+    # SimStadt found in C:\Users\eric.duminil\Desktop\SimStadt_0.10.0-SNAPSHOT_master_20230601_607b426
+
+    # Preparing 'Gruenbuehl_PhotovoltaicPotential&Financial' workflow (a.step):
+    * Adding Gruenbuehl_LOD2_ALKIS_1010.gml
+    * Adding Gruenbuehl_LOD2_ALKIS_1010_2buildings.gml
+
+    # Launching Gruenbuehl_PhotovoltaicPotential&Financial:
+    Workflow finished succesfuly!
+
+    # Listing written files :
+    * 'Gruenbuehl.proj\a.step\a.step\a.step\a.step\a.step\hourly_GHI_DHI_Ta.prn'
+    * 'Gruenbuehl.proj\a.step\a.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_2buildings_pvgis_SARAH_2005_2016_Hay_pv_potential.csv'
+    * 'Gruenbuehl.proj\a.step\a.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_pvgis_SARAH_2005_2016_Hay_pv_potential.csv'
+
+
+    # Preparing 'Gruenbuehl_HeatDemand' workflow (b.step):
+    * Adding Gruenbuehl_LOD2_ALKIS_1010.gml
+    * Adding Gruenbuehl_LOD2_ALKIS_1010_2buildings.gml
+
+    # Launching Gruenbuehl_HeatDemand:
+    Workflow finished succesfuly!
+
+    # Listing written files :
+    * 'Gruenbuehl.proj\b.step\a.step\a.step\a.step\a.step\hourly_GHI_DHI_Ta.prn'
+    * 'Gruenbuehl.proj\b.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_2buildings_DIN18599_HEATING.csv'
+    * 'Gruenbuehl.proj\b.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_2buildings_DIN18599_HEATING.log'
+    * 'Gruenbuehl.proj\b.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_DIN18599_HEATING.csv'
+    * 'Gruenbuehl.proj\b.step\a.step\a.step\a.step\a.step\a.step\a.step\Gruenbuehl_LOD2_ALKIS_1010_DIN18599_HEATING.log'
+"""
+
+import logging
+import os
+import platform
+import re
+import shutil
+import subprocess
+from pathlib import Path
+from xml.etree import ElementTree as et
+
+from dotenv import load_dotenv
+
+from lib.simstadt_results import SimStadtResults, create_simstadt_results
+from lib.utils import PROJECT_PATH, SCRIPT_DIR, chdir, random_id
+
+PARAMS = "params.xml"
+SIMSTADT2_GLOB = "SimStadt2_0.*/"
+TEMPLATE_PATH = SCRIPT_DIR / 'Template'
+load_dotenv()
+
+log = logging.getLogger(__name__)
+
+
+def find_simstadt(parent_folder: Path, simstadt_glob: str) -> Path:
+    try:
+        found = next(parent_folder.glob(simstadt_glob))
+        log.info("# SimStadt found in %s\n", found)
+        return found
+    except StopIteration as e:
+        log.error("Sorry, no SimStadt installation could be found in : %s/%s", parent_folder, simstadt_glob)
+        raise ValueError("SimStadt not found. Please define SIMSTADT_FOLDER environment variable.") from e
+
+
+def check_paths(repo_path: Path, workflow_path: Path):
+    if not repo_path.exists():
+        raise ValueError(f"Sorry, no Repository could be found in {repo_path}")
+
+    if not workflow_path.exists():
+        raise ValueError(f"Sorry, no workflow could be found in {workflow_path}")
+
+    if not (workflow_path / PARAMS).exists():
+        raise ValueError(f"Sorry, no workflow is defined in {workflow_path / PARAMS}")
+
+    proj_path = workflow_path.parent
+
+    for gml in proj_path.glob("*.gml"):
+        log.debug("  * Available citygml : %s", gml.name)
+
+
+def prepare_workflow(workflow_path: Path, citygmls: list[str]) -> str:
+    tree = et.parse(workflow_path / PARAMS)
+    root = tree.getroot()
+
+    node = root.find(".//void[@property='name']/string")
+    if node is None:
+        raise ValueError("Unknown workflow!")
+    name = node.text or "workflow"
+
+    log.info("# Preparing '%s' workflow (%s):", name, workflow_path.name)
+
+    citygml_node = root.find(".//void[@property='cityGmlFileNames']")
+
+    if citygml_node:
+        log.debug("  Removing old citygmls")
+        children = list(citygml_node)
+
+        for add_node in children:
+            citygml_node.remove(add_node)
+    else:
+        log.debug("  Add new XML node")
+        workflow_node = root.find(".//object[@class='eu.simstadt.workflows.CityGmlWorkflow']")
+        if workflow_node is None:
+            raise ValueError("Broken workflow!")
+        citygml_node = et.SubElement(workflow_node, "void")
+        citygml_node.set("property", "cityGmlFileNames")
+
+    for citygml in citygmls:
+        log.info("  * Adding %s", citygml)
+        add_node = et.SubElement(citygml_node, "void")
+        add_node.set("method", "add")
+        gml = et.SubElement(add_node, "string")
+        gml.text = citygml
+
+    tree.write(workflow_path / PARAMS)
+
+    return name
+
+
+def get_all_files(folder: Path) -> dict[Path, float]:
+    files = [f for f in folder.glob("**/*") if f.is_file() and f.name != PARAMS]
+    return {f: f.stat().st_mtime for f in files}
+
+
+def simstadt_script():
+    if platform.system().lower() == "windows":
+        return "SimStadt.bat"
+    return "./SimStadt.sh"
+
+
+def regionchooser_script():
+    if platform.system().lower() == "windows":
+        return "RegionChooser.bat"
+    return "./RegionChooser.sh"
+
+
+def run_simstadt(workflow_path: Path, name: str) -> str:
+    with chdir(get_simstadt_folder()):
+        log.info("Launching %s:", name)
+        result = subprocess.run([simstadt_script(), str(workflow_path)], text=True, capture_output=True, check=False)
+        if result.returncode != 0:
+            log.warning("  Workflow failed!\n%s", result.stdout)
+            raise ValueError("Workflow failed!")
+
+        log.debug(result.stdout)
+        log.info("  Workflow finished succesfuly!\n")
+
+        return result.stdout
+
+
+def run_regionchooser(*params: str):
+    with chdir(get_simstadt_folder()):
+        result = None
+        try:
+            log.info("Launching RegionChooser %s:", params)
+            result = subprocess.run([regionchooser_script(), *params], text=True, capture_output=True, check=True)
+            log.debug(result.stdout)
+            log.info("  RegionChooser finished succesfuly!\n")
+        except subprocess.CalledProcessError as e:
+            log.warning("  RegionChooser failed!\n")
+            log.info(e.stderr)
+            raise
+    return result.stdout
+
+
+def compare_written_files(repo_path: Path, before, after) -> list[Path]:
+    modified_files = []
+    log.info("# Listing written files :")
+    for result_file, modification_time in after.items():
+        before_time = before.get(result_file, 0)
+        if modification_time > before_time:
+            log.info("  * '%s'", result_file.relative_to(repo_path))
+            modified_files.append(result_file)
+    log.info("\n")
+    return modified_files
+
+
+def run_workflow(workflow_path: Path, citygmls: list[str]) -> list[Path]:
+    repo_path = workflow_path.parent.parent
+
+    check_paths(repo_path, workflow_path)
+
+    name = prepare_workflow(workflow_path, citygmls)
+
+    before = get_all_files(workflow_path)
+    run_simstadt(workflow_path, name)
+    after = get_all_files(workflow_path)
+
+    return compare_written_files(repo_path, before, after)
+
+
+def replace_params(workflow_path: Path, replaces: dict[str, str]):
+    param_files = workflow_path.glob(f"**/{PARAMS}")
+    replaced = False
+    for param_file in param_files:
+        with open(param_file, encoding="utf-8") as f:
+            content = f.read()
+            new_content = content
+            for old, new in replaces.items():
+                new_content = re.sub(old, new, new_content)
+
+            if new_content != content:
+                log.debug("Replacing parameters in %s", param_file)
+                replaced = True
+                with open(param_file, "w", encoding="utf-8") as f:
+                    f.write(new_content)
+    if not replaced:
+        log.warning("No parameter has been replaced! %r", replaces)
+
+
+def copy_workflow_from_template(
+    template_path: Path, project_path: Path, destination: str, replaces: dict | None = None
+) -> Path:
+    template_path = template_path.with_suffix(".flow")
+    workflow_path = (project_path / destination).with_suffix(".flow")
+
+    shutil.copytree(template_path, workflow_path, dirs_exist_ok=True)
+
+    if replaces:
+        replace_params(workflow_path, replaces)
+
+    return workflow_path
+
+
+def get_simstadt_folder():
+    if "SIMSTADT_FOLDER" in os.environ:
+        return Path(os.environ["SIMSTADT_FOLDER"])
+    return find_simstadt(Path.home() / "Desktop", SIMSTADT2_GLOB)
+
+
+def run_workflow_with_citygml(
+    template: str | Path,
+    citygml_path: Path,
+    replaces: dict | None = None,
+    description: str | None = None,
+    destination: str | None = None,
+) -> SimStadtResults:
+
+    if isinstance(template, str):
+        template_path = TEMPLATE_PATH / template
+    else:
+        template_path = template
+    template_name = template_path.stem
+
+    if destination is None:
+        # In order to avoid conflicts when two simulations are run as the same time
+        destination = random_id() + "_" + template_name.rsplit("_", 1)[-1]
+
+    project_path = citygml_path.parent
+
+    workflow_path = copy_workflow_from_template(
+        template_path,
+        project_path,
+        destination,
+        replaces,
+    )
+    output_files = run_workflow(workflow_path, [citygml_path.name])
+    if description is None:
+        description = f"{template_name} for {citygml_path.name}"
+    return create_simstadt_results(description, output_files)
+
+
+if __name__ == "__main__":
+    template_and_citygmls = [
+        ("101_HeatDemand", "Grombuehl_mini_Steinheilstrasse.gml"),
+        ("102_GreenWater", "Grombühl_mini_with_trees.gml"),
+        ("103_PV", "Grombühl_mini_with_trees.gml"),
+    ]
+
+    set_weather_file = {"<string>METEONORM_FILE</string>": f"<string>Wuerzburg-hour.csv</string>"}
+    for template, citygml in template_and_citygmls:
+        results = run_workflow_with_citygml(template, PROJECT_PATH / citygml, replaces=set_weather_file)
+
+        print(results.dataframe)
+        print(repr(results))

old/cgsc/lib/run_urbi.py

+import logging
+import subprocess
+from pathlib import Path
+
+from lib.utils import chdir
+
+log = logging.getLogger(__name__)
+
+
+def run_urbi(
+    urbi_folder: Path,
+    gml_path: Path,
+    path_config_urbi: Path,
+    urbi_output_folder: Path,
+    gui_activate: bool = False,
+):
+    if gui_activate:
+        gui = ["python", urbi_folder / "urbi.py", "--gui"]
+        try:
+            with chdir(urbi_folder):
+                process = subprocess.Popen(gui, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+                output, error = process.communicate()
+        except Exception as e:
+            log.error(f"Error starting process: {e}")
+        else:
+            log.info(f"Output: {output.decode()}")
+            log.info(f"Error: {error.decode()}")
+    else:
+        log.info("Urbi+ started without GUI")
+        no_gui = [
+            "python",
+            "urbi.py",
+            "--config",
+            path_config_urbi,
+            gml_path,
+            "--output",
+            urbi_output_folder,
+        ]
+
+        try:
+            with chdir(urbi_folder):
+                process = subprocess.Popen(no_gui, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+                output, error = process.communicate()
+            log.info("Urbi+ success")
+        except Exception as e:
+            log.error(f"Error starting process: {e}")
+

old/cgsc/lib/simstadt_results.py

+"""Tries to parse SimStadt results, with as few input information as possible,
+and as much output as possible, with a unified API, regardless of Workflows.
+It should work with HeatDemand, Photovoltaic, and GreenWater.
+
+Among others, it should offer dataframe, kpis, diagrams and csv_path
+"""
+
+import io
+import json
+import logging
+import re
+import zipfile
+from abc import ABC, abstractmethod
+from dataclasses import asdict, dataclass, field
+from enum import Enum
+from pathlib import Path
+from typing import ClassVar, Dict, Sequence, Type
+from xml.etree import ElementTree as et
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class KPI:
+    """Metric, with name, value, unit and precision."""
+
+    name: str
+    value: float
+    unit: str | None = None
+    precision: int = 2
+    NAME_AND_UNIT = re.compile(r"^(.*?) \[(.*?)\]$")
+
+    def __post_init__(self):
+        "Some columns have integrated units in key. Move them to unit value"
+        if match := self.NAME_AND_UNIT.match(self.name):
+            self.name, self.unit = match.groups()
+
+    def to_dict(self) -> dict:
+        return asdict(self)
+
+    @property
+    def rounded_value(self) -> float:
+        return round(self.value, self.precision)
+
+    def __str__(self):
+        s = f"{self.name:35s} : {self.value:.{self.precision}f}"
+        if self.unit:
+            s = f"{s} {self.unit}"
+        return s
+
+    def __repr__(self):
+        return str(self)
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "KPI":
+        return cls(**data)
+
+
+class Providers(str, Enum):
+    HEAT_DEMAND = "de.hftstuttgart.simstadtworkflows.energy.HeatDemandAnalysisWorkflowProvider"
+    HEAT_DEMAND_WITH_REFURBISHMENT = (
+        "de.hftstuttgart.simstadtworkflows.energy.HeatDemandAnalysisWithRefurbishmentStrategyWorkflowProvider"
+    )
+
+    HEAT_DEMAND_WITH_SHADOW = (
+        "de.hftstuttgart.simstadtworkflows.shadow.HeatDemandCalculationWithShadowProcessingProvider"
+    )
+    PHOTOVOLTAIC = "de.hftstuttgart.simstadtworkflows.energy.PhotovoltaicPotentialAnalysisWorkflowProvider"
+    PHOTOVOLTAIC_WITH_SHADOW = "de.hftstuttgart.simstadtworkflows.shadow.PVPotentialWithShadowProcessingProvider"
+    PHOTOVOLTAIC_FINANCE = (
+        "de.hftstuttgart.simstadtworkflows.economics.PhotovoltaicPotentialFinancialAnalysisWorkflowProvider"
+    )
+    GREEN_WATER = "de.hftstuttgart.simstadtworkflows.greenwater.GreenWaterWorkflowProvider"
+
+
+def detect_decimal(csv_path: Path, line_number: int, check: str = ""):
+    """Parse the line_number th line of csv_path, and tries to detect if ',' or '.' is used for decimals."""
+    with open(csv_path, encoding="utf-8") as csv:
+        for _ in range(line_number):
+            next(csv)
+        line = next(csv)
+        if check and (check not in line):
+            raise ValueError(f"Couldn't find '{check}' in '{line}'.")
+        possible_delimiters = [".", ","]
+        delimiter = next(delimiter for delimiter in possible_delimiters if delimiter in line)
+        logger.debug("Decimal for %s is '%s'", csv_path.name, delimiter)
+        return delimiter
+
+
+def get_workflow_provider(output_files):
+    """Determine the workflow provider from the output files"""
+    if len(output_files) == 0:
+        raise ValueError("No output files were provided!")
+    # Find the workflow path from the first output file
+    first_output_file = output_files[0]
+    workflow_path = next(d for d in first_output_file.parents if d.suffix == ".flow")
+    params_xml = workflow_path / "params.xml"
+
+    # Parse the params.xml file
+    tree = et.parse(params_xml)
+    root = tree.getroot()
+
+    element = root.find(".//void[@property='workflowProvider']/object")
+    assert element is not None, "workflowProvider element not found"
+
+    # Find the workflowProvider
+    return element.get("class", "UnknownWorkflowProvider")
+
+
+@dataclass
+class SimStadtResults(ABC):
+    """Base abstract class for SimStadt results"""
+
+    description: str
+    output_files: list[Path]
+
+    # List of providers this class supports
+    supported_providers: ClassVar[list[str]]
+
+    # A substring which should be found in the main CSV. Some workflows output more than 1 CSV
+    csv_identifier: ClassVar[str]
+
+    # Registry of concrete implementations
+    _registry: ClassVar[Dict[str, Type["SimStadtResults"]]] = {}
+
+    # Dataframe will hold most data.
+    # NOTE: For custom data which doesn't fit in the table, df.attrs can be used.
+    _df: pd.DataFrame | None = field(default=None, init=False, repr=False)
+
+    def __init_subclass__(cls, **kwargs):
+        """Register subclasses for factory pattern"""
+        super().__init_subclass__(**kwargs)
+        for provider in cls.supported_providers:
+            SimStadtResults._registry[provider] = cls
+
+    @abstractmethod
+    def _parse_results(self) -> pd.DataFrame:
+        pass
+
+    @property
+    def dataframe(self) -> pd.DataFrame:
+        if self._df is None:
+            self._df = self._parse_results()
+        return self._df
+
+    @property
+    def more_info(self) -> dict[str, list[KPI]]:
+        return {}
+
+    @property
+    @abstractmethod
+    def kpis(self) -> list[KPI]:
+        """Return KPIs for this workflow"""
+        pass
+
+    def kpi(self, name: str) -> KPI:
+        """Return KPI name 'name' for this workflow, if available"""
+        for kpi in self.kpis:
+            if kpi.name == name:
+                return kpi
+        raise ValueError(f"No '{name}' KPI found for {self}")
+
+    def _prepare_kpis(self, sums: Sequence, averages: Sequence) -> list[KPI]:
+        kpis = []
+        default_precision = 0
+
+        for item in sums:
+            name, unit, precision = (item + (default_precision,))[:3]
+            kpis.append(KPI(name, self.dataframe[name].sum(), unit, precision))
+
+        for item in averages:
+            name, unit, precision = (item + (default_precision,))[:3]
+            kpis.append(KPI(name, float(self.dataframe[name].mean()), unit, precision))
+
+        return kpis
+
+    def _params_xml(self) -> Path:
+        return self.workflow_path / "params.xml"
+
+    def _params(self) -> et.Element:
+        tree = et.parse(self._params_xml())
+        root = tree.getroot()
+        return root
+
+    def _params_element(self, xpath: str) -> et.Element:
+        element = self._params().find(xpath)
+        if element is None:
+            raise ValueError(f"'{xpath}' not found in XML")
+        return element
+
+    @property
+    def name(self) -> str:
+        return self._params_element(".//void[@property='name']/string").text or "Unknown"
+
+    @property
+    def short_name(self) -> str:
+        return self._params_element(".//void[@property='shortName']/string").text or "Unknown"
+
+    @property
+    def workflow_provider(self) -> str:
+        return self._params_element(".//void[@property='workflowProvider']/object").get("class", "Unknown provider")
+
+    @property
+    def workflow_path(self) -> Path:
+        first_output_file = self.output_files[0]
+        return first_output_file.parent.parent
+
+    @property
+    def citygml(self) -> str:
+        return self._params_element(".//void[@property='cityGmlFileNames']//string").text or "Unknown CityGML"
+
+    @property
+    def project_path(self) -> Path:
+        return self.workflow_path.parent
+
+    @property
+    def project(self) -> str:
+        return self.project_path.stem
+
+    @property
+    def repository(self) -> Path:
+        return self.project_path.parent
+
+    def relative_paths(self) -> list[str]:
+        workflow_path = self.workflow_path
+        return [f.relative_to(workflow_path).as_posix() for f in self.output_files]
+
+    def __str__(self) -> str:
+        return f"{self.description} ({self.class_name})"
+
+    def __repr__(self) -> str:
+        files_description = "\n".join(f"  - {f}" for f in self.relative_paths())
+        kpis = "\n".join(f"  {k}" for k in self.kpis)
+        return f"""{self.description} ({self.class_name}, {self.project}, {self.workflow_path.name}, {self.citygml})
+{files_description}\n{kpis}"""
+
+    @property
+    def class_name(self) -> str:
+        return type(self).__name__
+
+    @property
+    def csv_path(self) -> Path:
+        """Returns the last found CSV"""
+        csvs = self.get_all_by_extension(".csv")
+        relevant_csvs = [csv for csv in csvs if self.csv_identifier in csv.name]
+        if len(relevant_csvs) == 0:
+            raise ValueError("Workflow didn't seem to have returned any CSV file!")
+        if len(relevant_csvs) > 1:
+            logger.warning("Too many CSV results found for %s", self)
+        return relevant_csvs[-1]
+
+    def csv_content(self) -> bytes:
+        with open(self.csv_path, "rb") as f:
+            return f.read()
+
+    def get_all_by_extension(self, ext: str) -> list[Path]:
+        return [f for f in sorted(self.output_files) if f.suffix == ext]
+
+    @property
+    def diagrams(self) -> dict[str, Path]:
+        return {}
+
+    def log_content(self) -> bytes:
+        """Returns the content of log file, if available"""
+        logs = self.get_all_by_extension(".log")
+        if len(logs) == 0:
+            return b""
+        log = logs[-1]
+
+        with open(log, "rb") as f:
+            return f.read()
+
+    def zip_content(self) -> bytes:
+        zip_buffer = io.BytesIO()
+
+        with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED, False) as zf:
+            for file_path in self.output_files:
+                zf.write(file_path, arcname=file_path.name)
+
+        zip_buffer.seek(0)  # Rewind to the beginning of the buffer
+        zipped_content_bytes = zip_buffer.read()
+
+        return zipped_content_bytes
+
+    def to_dict(self):
+        """Convert instance to a dictionary with path objects converted to strings"""
+        # Start with a clean dictionary instead of using asdict
+        data = {
+            "description": self.description,
+            "output_files": [str(path) for path in self.output_files],
+            "_type": self.class_name,
+        }
+
+        # Force CSV parsing, and convert DataFrame to a dictionary representation
+        data["_df_dict"] = self.dataframe.to_dict("records")
+        # save metadata too
+        if self.dataframe.attrs:
+            data["_df_attrs"] = self.dataframe.attrs
+
+        return data
+
+    @classmethod
+    def from_dict(cls, data):
+        # Remove the type information before instantiation
+        data.pop("_type", None)
+
+        # Handle DataFrame serialization
+        df_dict = data.pop("_df_dict", None)
+        df_attrs = data.pop("_df_attrs", {})
+
+        # Convert paths back to Path objects
+        data["output_files"] = [Path(p) for p in data["output_files"]]
+
+        if cls is SimStadtResults:
+            # If it's a base class instantiation, detect the type from workflow_provider
+            provider = get_workflow_provider(data["output_files"])
+            result = cls.create(provider, **data)
+        else:
+            result = cls(**data)
+
+        result._df = pd.DataFrame(df_dict)
+        result._df.attrs = df_attrs
+
+        return result
+
+    def to_json(self):
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_json(cls, json_str):
+        return cls.from_dict(json.loads(json_str))
+
+    @classmethod
+    def create(cls, provider: str, **kwargs) -> "SimStadtResults":
+        """Factory method to create the correct subclass based on provider"""
+        if provider not in cls._registry:
+            raise ValueError(f"Unknown workflow provider: {provider}")
+        return cls._registry[provider](**kwargs)
+
+
+@dataclass(repr=False)
+class HeatDemandResults(SimStadtResults):
+    """Results for Heat Demand workflow"""
+
+    MAX_FLAT_ROOF_DIFFERENCE = 0.1  # [m]
+    TOTAL_DEMAND = "Total Yearly Heating + DHW demand"
+
+    supported_providers: ClassVar[list[str]] = [
+        Providers.HEAT_DEMAND,
+        Providers.HEAT_DEMAND_WITH_SHADOW,
+        Providers.HEAT_DEMAND_WITH_REFURBISHMENT,
+    ]
+    csv_identifier = "DIN18599"
+
+    def _parse_results(self) -> pd.DataFrame:
+        csv_decimal = detect_decimal(self.csv_path, 5, "Latitude")
+        df = pd.read_csv(self.csv_path, skiprows=list(range(19)) + [20], sep=";", decimal=csv_decimal)
+
+        logger.debug("Looking for flat roofs")
+        df["has_flat_roof"] = (
+            df["Ridge/mean Height"] - df["Eaves/mean Height"] < self.MAX_FLAT_ROOF_DIFFERENCE
+        ).fillna(False)
+
+        df.attrs["Heating"] = "Yearly Heating demand" in df.columns
+        df.attrs["Cooling"] = "Yearly Cooling demand" in df.columns
+
+        return df
+
+    @property
+    def kpis(self):
+        df = self.dataframe
+        custom_kpis = [
+            KPI("Number of buildings", df.shape[0], precision=0),
+        ]
+        sums = [
+            ("Heated area", "m²"),
+            ("Footprint area", "m²"),
+        ]
+
+        if df.attrs["Heating"]:
+            specific_heat_demand = df[self.TOTAL_DEMAND].sum() / df["Heated area"].sum()
+            heated_buildings = int((df[self.TOTAL_DEMAND] > 10_000).sum())
+            custom_kpis.extend(
+                [
+                    KPI("Number of heated buildings", heated_buildings, precision=0),
+                    KPI("Specific Heating Demand", specific_heat_demand, "kWh / (m² · a)", precision=0),
+                ]
+            )
+            sums.extend(
+                [
+                    ("Yearly Heating demand", "kWh / a"),
+                    (self.TOTAL_DEMAND, "kWh / a"),
+                ]
+            )
+
+        if df.attrs["Cooling"]:
+            specific_cooling_demand = df["Yearly Cooling demand"].sum() / df["Heated area"].sum()
+            custom_kpis.append(KPI("Specific Cooling Demand", specific_cooling_demand, "kWh / (m² · a)", precision=0))
+            sums.extend(
+                [
+                    ("Yearly Cooling demand", "kWh / a"),
+                ]
+            )
+
+        averages = [("Mean Uvalue", "W / (m² · K)", 1), ("Year of construction", None), ("Storey number", None)]
+        return custom_kpis + self._prepare_kpis(sums, averages)
+
+    @property
+    def diagrams(self) -> dict[str, Path]:
+        heat_png = self.workflow_path / "heating.png"
+        ax = self.monthly_df().plot.bar(
+            rot=0,
+            ylabel="[MWh]",
+            width=0.8,
+            color={"Monthly Heating Demand": "darkred", "Monthly Cooling Demand": "darkblue"},
+        )
+        plt.savefig(heat_png, bbox_inches="tight", dpi=300)
+        plt.close(ax.figure)
+        return {"Monthly demands": heat_png}
+
+    def monthly_df(self) -> pd.DataFrame:
+        months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
+        df = self.dataframe
+
+        monthly_df = pd.DataFrame([], index=pd.Index(months))
+
+        modes = ["Heating", "Cooling"]
+        for mode in modes:
+            search_str = f"{mode} demand"
+            found_cols = [
+                col for col in df.columns if search_str in col and ("Yearly" not in col) and ("Specific" not in col)
+            ]
+            if found_cols:
+                monthly_df[f"Monthly {mode} Demand"] = (df[found_cols].sum() / 1000).values
+
+        return monthly_df
+
+
+@dataclass(repr=False)
+class PhotovoltaicResults(SimStadtResults):
+    """Results for Photovoltaic workflow"""
+
+    supported_providers: ClassVar[list[str]] = [
+        Providers.PHOTOVOLTAIC,
+        Providers.PHOTOVOLTAIC_FINANCE,
+        Providers.PHOTOVOLTAIC_WITH_SHADOW,
+    ]
+    csv_identifier = "_pv_potential"
+
+    def _count_header_lines(self) -> int:
+        count = 0
+        with open(self.csv_path) as csv:
+            for line in csv:
+                if line.startswith("Building ID"):
+                    return count
+                count += 1
+        raise ValueError(f"Header not found in {self.csv_path}")
+
+    def _parse_results(self) -> pd.DataFrame:
+        csv_decimal = detect_decimal(self.csv_path, 4, "Latitude")
+
+        header_length = self._count_header_lines()
+
+        df = pd.read_csv(
+            self.csv_path, skiprows=list(range(header_length)) + [header_length + 1], sep=";", decimal=csv_decimal
+        )
+        df = df.rename(columns={"Area": "Roof area for PV"})
+        # Remove unused Finance columns
+        return df.dropna(axis=1, how="all")
+
+    @property
+    def kpis(self):
+        sums = [("Roof area for PV", "m²"), ("PV potential nominal power", "kWp"), ("PV potential yield", "MWh / a")]
+        averages = [("Irradiance in module plane", "W / m²"), ("PV specific yield", "kWh / (kWp · a)")]
+        return self._prepare_kpis(sums, averages)
+
+
+@dataclass(repr=False)
+class GreenWaterResults(SimStadtResults):
+    """Results for GreenWater workflow"""
+
+    csv_identifier = "_greenwater"
+    supported_providers: ClassVar[list[str]] = [Providers.GREEN_WATER]
+    RAIN_L = "Sum rain [L]"
+    SINGLE_TREE_ETC_L = "Single tree ETc [L]"
+    SINGLE_TREE_MISSING_WATER_L = "Single tree missing water [L]"
+
+    def _parse_results(self) -> pd.DataFrame:
+        csv_decimal = detect_decimal(self.csv_path, 5, "tree area")
+        df = pd.read_csv(
+            self.csv_path, sep=";", header=[0, 1], skiprows=list(range(8)) + list(range(10, 13)), decimal=csv_decimal
+        )
+
+        # First row should be forward-filled, since species are not repeated
+        cols = df.columns.tolist()
+
+        new_cols = []
+        current_species = "All"
+        species = []
+
+        for col in cols:
+            # Sadly, multiindex columns cannot be saved to JSON, so we flatten them
+            level0, level1 = col
+
+            if pd.notna(level0) and not level0.startswith("Unnamed") and not level0.startswith("#"):
+                current_species = level0
+                species.append(current_species)
+
+            if current_species == "All":
+                new_cols.append(level1)
+            else:
+                new_cols.append(f"{current_species} - {level1}")
+
+        df.columns = new_cols
+
+        ########################
+        #    Parse headers     #
+        ########################
+        with open(self.csv_path, encoding="utf-8") as csv:
+            line = ""
+            for _ in range(5):
+                line = next(csv)
+            tree_count = int(line.split(";")[1])
+            line = next(csv)
+            tree_area_header = re.split("[;,]", line.strip())
+            total_tree_area = float(tree_area_header[1].replace(",", "."))
+            if tree_count == 0:
+                raise ValueError(f"CityGML {self.citygml} does not have any tree!")
+            for _ in range(5):
+                line = next(csv)
+            species_count = [int(c) for c in re.split(";+", line.strip())[1:-1]]
+
+            line = next(csv)
+            species_area = [float(c.replace(",", ".")) for c in re.split(";+", line.strip())[1:-1]]
+
+        species.pop(0)
+
+        df.attrs = {
+            "species": {
+                name: {"count": count, "area": area} for name, count, area in zip(species, species_count, species_area)
+            },
+            "tree count": tree_count,
+            "tree area": total_tree_area,
+        }
+
+        return df
+
+    def df_with_time(self):
+        # NOTE: DateTimeIndex is somehow not serializable, so it has to be created dynamically
+        df = self.dataframe
+        year = 2005
+        times = pd.date_range(start=f"{year}-01-01 00:00", freq="1h", periods=8760)
+        df = df.set_index(times)
+        df = df.drop(columns=["#"])
+        return df
+
+    @property
+    def kpis(self):
+        df = self.dataframe
+
+        rain = df["Rain [mm]"].sum()
+        etc = df["Average ETc [mm]"].sum()
+
+        cooling = df["Evaporative cooling [kWh/h]"].sum() / 1000
+
+        irrigation_mm = df["Average irrigation [mm]"].sum()
+        tree_area = df.attrs["tree area"]
+        irrigation_m3 = irrigation_mm * tree_area / 1000
+
+        return [
+            KPI("Number of trees", df.attrs["tree count"], precision=0),
+            KPI("Projected tree area", tree_area, "m²", precision=1),
+            KPI("Rain", rain, "mm / a", precision=0),
+            KPI("Average ETc", etc, "mm / a", precision=0),
+            KPI("Irrigation", irrigation_m3, "m³ / a", precision=0),
+            KPI("Evaporative cooling", cooling, "MWh / a", precision=0),
+        ]
+
+    @property
+    def more_info(self) -> dict[str, list[KPI]]:
+        df = self.dataframe
+
+        all_info = {}
+        species = df.attrs["species"]
+        for name, info in species.items():
+            count = info["count"]
+            area = info["area"]
+            irrigation_mm = df[f"{name} - Average irrigation [mm]"].sum()
+            average_area = area / count
+            species_kpis = [
+                KPI(
+                    "Number of trees",
+                    value=count,
+                    precision=0,
+                ),
+                KPI(
+                    "Average tree area",
+                    value=average_area,
+                    unit="m²",
+                    precision=1,
+                ),
+                KPI(
+                    "Average ETc",
+                    value=df[f"{name} - Average ETc [mm]"].sum(),
+                    unit="mm / a",
+                    precision=0,
+                ),
+                KPI(
+                    "Irrigation",
+                    value=irrigation_mm,
+                    unit="mm / a",
+                    precision=0,
+                ),
+                KPI(
+                    "Average irrigation",
+                    value=average_area * irrigation_mm / 1000,
+                    unit="m³ / a",
+                    precision=0,
+                ),
+            ]
+
+            all_info[f"_{name}_"] = species_kpis
+
+        return all_info
+
+    @property
+    def diagrams(self) -> dict[str, Path]:
+        rain_irrigation_png = self.workflow_path / "rain_and_irrigation.png"
+
+        df_months = self.df_with_time()[["Rain [mm]", "Average irrigation [mm]"]].resample("ME").sum()
+        fig, ax = plt.subplots()
+        df_months = df_months.rename(
+            columns={"Rain [mm]": "Niederschlag", "Average irrigation [mm]": "Künstliche Bewässerung"}
+        )
+        df_months.plot(kind="bar", stacked=True, ax=ax, ylabel="[mm]", figsize=(13, 6))
+        ax.set_xticklabels([x.strftime("%b") for x in df_months.index], rotation=0)
+
+        plt.savefig(rain_irrigation_png, bbox_inches="tight", dpi=300)
+        plt.close(fig)
+
+        return {"Rain and Irrigation": rain_irrigation_png}
+
+
+# Factory function for convenience
+def create_simstadt_results(description: str, output_files: list[Path]) -> SimStadtResults:
+    """Create appropriate SimStadtResults object based on workflow provider"""
+    provider = get_workflow_provider(output_files)
+    return SimStadtResults.create(provider, description=description, output_files=sorted(output_files))
+
+
+if __name__ == "__main__":
+    output_files = [
+        Path(
+            "Repository/CGSC.proj/101_HeatDemand.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn"
+        ),
+        Path(
+            "Repository/CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.csv"
+        ),
+        Path(
+            "Repository/CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.log"
+        ),
+    ]
+    results = create_simstadt_results("Heat demand simulation for Grombühl", output_files)
+    print(repr(results))

old/cgsc/lib/simstadt_workflows.py

+from pathlib import Path
+
+from lib.run_simstadt_workflow import run_workflow_with_citygml
+from lib.simstadt_results import SimStadtResults
+from lib.utils import PROJECT_PATH, remove_random_id, set_random_seed
+
+
+################################################################################
+#      Simulation functions, for callbacks, testing and optimization           #
+################################################################################
+def set_weather_file(meteonorm_filename: str) -> dict[str, str]:
+    # Input filename sometimes contains just the basename, sometimes the whole path
+    return {"<string>METEONORM_FILE</string>": f"<string>{Path(meteonorm_filename).name}</string>"}
+
+
+def set_calculation_mode(calculation_mode: str) -> dict[str, str]:
+    allowed_modes = ["HEATING", "COOLING", "HEATING_AND_COOLING"]
+
+    if calculation_mode not in allowed_modes:
+        raise ValueError(f"{calculation_mode} should be in {allowed_modes}")
+
+    return {"<string>CALCULATION_MODE</string>": f"<string>{calculation_mode}</string>"}
+
+
+def set_refurbishment(geg_ratio: float) -> dict[str, str]:
+    return {"<double>GEG_RATIO</double>": f"<double>{geg_ratio}</double>"}
+
+
+def photovoltaic_simulation(
+    gml_filename: str,
+    meteonorm_filename: str,
+    roof_percentage: float = 100.0,  # [%]
+    pv_share_flat: float = 40,  # [%]
+    pv_share_tilted: float = 50,  # [%]
+    min_roof_insolation: float = 1000,  # [kWh / (m² . a)]
+    hourly_pv: bool = False,
+    with_shadows: bool = True,
+    description="🌤️ Photovoltaik",
+) -> SimStadtResults:
+    set_weather_file_and_pv_share = set_weather_file(meteonorm_filename) | {
+        "<int>PV_SHARE_FLAT_ROOF</int>": f"<int>{pv_share_flat}</int>",
+        "<int>PV_SHARE_TILTED_ROOF</int>": f"<int>{pv_share_tilted}</int>",
+        "<int>MIN_ROOF_INSOLATION</int>": f"<int>{min_roof_insolation}</int>",
+        "<boolean>HOURLY_PV</boolean>": f"<boolean>{str(hourly_pv).lower()}</boolean>",
+    }
+
+    template = "105_PVWithShadow" if with_shadows else "103_PV"
+
+    pv_results = run_workflow_with_citygml(
+        template,
+        PROJECT_PATH / gml_filename,
+        replaces=set_weather_file_and_pv_share,
+        description=description,
+    )
+
+    set_random_seed(remove_random_id(gml_filename))
+    # Only keep roof_percentage of rows
+    pv_results._df = pv_results.dataframe.sample(frac=roof_percentage / 100.0)
+
+    return pv_results
+
+
+def heatdemand_simulation(
+    gml_filename: str,
+    meteonorm_filename: str,
+    with_shadows: bool = True,
+    calculation_mode: str = "HEATING",
+    refurbishment_ratio: float = 0.0,
+    description="🏡🌤️ Wärmebedarf",
+) -> SimStadtResults:
+
+    template = "104_HeatDemandWithShadow" if with_shadows else "101_HeatDemand"
+
+    return run_workflow_with_citygml(
+        template,
+        PROJECT_PATH / gml_filename,
+        replaces=set_weather_file(meteonorm_filename)
+        | set_calculation_mode(calculation_mode)
+        | set_refurbishment(refurbishment_ratio),
+        description=description,
+    )
+
+
+def greenwater_simulation(
+    gml_filename: str, meteonorm_filename: str, irrigation_ratio: float, description="🌱 Grün & Wasser"
+) -> SimStadtResults:
+    # irrigation_ratio 1.0 : Irrigation when needed
+    # irrigation_ratio 0.0 : No irrigation
+    set_weather_file_and_irrigation = set_weather_file(meteonorm_filename) | {
+        "<double>MAX_WATER_STRESS</double>": f"<double>{1 - irrigation_ratio}</double>",
+    }
+
+    return run_workflow_with_citygml(
+        "102_GreenWater",
+        PROJECT_PATH / gml_filename,
+        replaces=set_weather_file_and_irrigation,
+        description=description,
+    )

old/cgsc/tests/TestRepo/.gitignore

+*.png

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/00_ImportCityGml.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.citygml.steps.ImportCityGml" id="ImportCityGml0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>startStep</string>
+   <void method="set">
+    <object idref="ImportCityGml0"/>
+    <boolean>true</boolean>
+   </void>
+  </void>
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="ImportCityGml0"/>
+    <string>01_Preprocessing.step</string>
+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/01_Preprocessing.step/00_GeometricPreprocessor.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.GeometricPreprocessorStep" id="GeometricPreprocessorStep0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>startStep</string>
+   <void method="set">
+    <object idref="GeometricPreprocessorStep0"/>
+    <boolean>true</boolean>
+   </void>
+  </void>
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="GeometricPreprocessorStep0"/>
+    <string>01_GeometricEstimator.step</string>
+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/01_Preprocessing.step/01_GeometricEstimator.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.GeometricEstimatorStep" id="GeometricEstimatorStep0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="GeometricEstimatorStep0"/>
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+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/01_Preprocessing.step/02_PhysicsPreprocessor.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.PhysicsPreprocessorStep" id="PhysicsPreprocessorStep0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="PhysicsPreprocessorStep0"/>
+    <string>03_UsagePreprocessor.step</string>
+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/01_Preprocessing.step/03_UsagePreprocessor.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.UsagePreprocessorStep">
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/01_Preprocessing.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.Preprocessing" id="Preprocessing0">
+  <void class="de.hftstuttgart.hierarchicworkflow.Workflow" method="getField">
+   <string>selectedStartStepPath</string>
+   <void method="set">
+    <object idref="Preprocessing0"/>
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+   </void>
+  </void>
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
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+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

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+0	0	2.00
+0	0	1.80
+0	0	1.60
+0	0	1.50
+0	0	1.30
+0	0	1.00
+0	0	0.80
+0	0	0.60
+0	0	0.50
+0	0	0.50
+0	0	0.40
+0	0	0.40
+0	0	0.30
+4	4	0.60
+87	41	3.00
+163	60	5.30
+196	87	7.00
+219	83	8.40
+171	94	8.80
+128	67	8.70
+56	37	7.70
+1	1	6.30
+0	0	5.50
+0	0	4.80
+0	0	4.10
+0	0	3.40
+0	0	2.60
+0	0	1.90
+0	0	1.20
+0	0	0.20
+0	0	-0.80
+0	0	-1.90
+0	0	-2.50
+0	0	-3.10
+0	0	-3.70
+0	0	-4.10
+0	0	-4.50
+4	4	-4.50
+102	36	-2.20
+193	42	-0.10
+253	45	1.60
+274	45	2.70
+247	44	3.30
+172	40	3.10
+77	32	1.90
+1	1	0.30
+0	0	0.10
+0	0	-0.10
+0	0	-0.40
+0	0	-0.60
+0	0	-0.90
+0	0	-1.10
+0	0	-1.40

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/02_WeatherProcessor.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.WeatherProcessorStep" id="WeatherProcessorStep0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="WeatherProcessorStep0"/>
+    <string>03_IrradianceProcessor.step</string>
+   </void>
+  </void>
+  <void property="inputFilename">
+   <string>Wuerzburg-hour.csv</string>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+  <void property="weatherDataSource">
+   <object class="java.lang.Enum" method="valueOf">
+    <class>de.hft.stuttgart.simstadt2.weather.WeatherDataSourceType</class>
+    <string>TMY3_HOURLY_FILE</string>
+   </object>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/03_IrradianceProcessor.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.IrradianceProcessorStep" id="IrradianceProcessorStep0">
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>selectedNextStepPath</string>
+   <void method="set">
+    <object idref="IrradianceProcessorStep0"/>
+    <string>04_MonthlyEnergyBalance.step</string>
+   </void>
+  </void>
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.csv

+## SimStadt DIN18599 Monthly Energy Balance
+#
+# Weather data source;meteonorm tmy3 file 2000-2009
+# Location;Wuerzburg
+# Coordinate reference system;EPSG:25832
+# Latitude;49,77;°
+# Longitude;9,97;°
+# Radiation model;meteonorm_Hay
+# Calculation Mode;HEATING
+# Consumer behaviour;IWU_NUTZUNG
+#
+# Building physics library;German Building Typology Library IWU (http://www.iwu.de)
+# Building usage library;Germany (based on UsageLibrary.xlsx, sheet: Germany)
+# Has custom building usage codes?;false
+#
+# SimStadt version;0.14.0-SNAPSHOT (develop, rev. a5cbb2b, 20250317)
+# Created at;2025/04/23 09:41:31
+# Cache version;7
+#
+GMLId;ParentGMLId;Latitude;Longitude;X-coordinate;Y-coordinate;LOD;Year of construction;Year of refurbishment;Refurbishment Variant;ALKIS code;PrimaryUsageZoneType;PrimaryUsageZoneArea;SecondaryUsageZoneType;SecondaryUsageZoneArea;BuildingType;Footprint area;Total wall thermal area above ground;Total wall thermal area below ground;Total outwall area;Total shared wall area;Total roof area;Gross volume;Is Gross volume approximated?;Heated volume;Ridge/mean Height;Eaves/mean Height;Storey number;Average Storey Height;Number of households;Number of occupants;Attic Heating;Basement Heating;Basement ceiling height above ground;Surface area to volume ratio;Heated area;Mean Uvalue;Specific domestic hot water demand;Domestic hot water demand;Specific space heating demand;Yearly Heating demand;Total Yearly Heating + DHW demand;January Heating demand;February Heating demand;March Heating demand;April Heating demand;May Heating demand;June Heating demand;July Heating demand;August Heating demand;September Heating demand;October Heating demand;November Heating demand;December Heating demand
+[-];[-];[°];[°];[?];[?];LOD;[YYYY];[YYYY];[-];[-];[-];[m²];[-];[m²];[-];[m²];[m²];[m²];[m²];[m²];[m²];[m³];[0/1];[m³];[m];[m];[-];[m];[-];[-];[-];[-];[m];[m⁻¹];[m²];[W/(m²·K)];[kWh/(m²·a)];[kWh/a];[kWh/(m²·a)];[kWh/a];[kWh/a];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh];[kWh]
+DEBY_LOD2_604868;;49,80340;9,94771;568195,65;5517202,94;LOD_2;1973;;Original;31001_1000;residential;658,3;none;0,0;GMH;139,5;385,7;0,0;414,3;308,0;156,8;2196,6;false;2057,1;17,0;14,47;6;2,7;6;19;HEATED;NOT_HEATED;1,0;0,324;658,3;1,20;15,8;10427,0;74,5;49073;59500;10945;8297;5868;2017;175;3;0;0;385;3222;7460;10702
+DEBY_LOD2_604870;;49,80340;9,94729;568165,37;5517202,14;LOD_2;1960;;Original;31001_1000;residential;912,4;none;0,0;GMH;184,1;573,4;0,0;616,8;192,3;250,3;3035,3;false;2851,2;19,2;14,17;7;2,6;9;18;HEATED;NOT_HEATED;1,0;0,346;912,4;1,28;15,8;14452,0;86,3;78709;93161;17271;13206;9629;3531;336;5;0;0;750;5375;11798;16808
+DEBY_LOD2_604869;;49,80340;9,94676;568127,19;5517202,25;LOD_2;2014;;Original;31001_1000;residential;864,4;none;0,0;GMH;179,3;566,3;0,0;609,2;180,9;225,8;2880,6;false;2701,3;18,6;14,11;7;2,5;8;18;HEATED;NOT_HEATED;1,0;0,352;864,4;0,40;15,8;13692,0;32,2;27835;41527;6804;4944;3024;545;11;0;0;0;44;1384;4416;6662
+DEBY_LOD2_604871;;49,80340;9,94697;568142,65;5517202,19;LOD_2;1978;;Original;31001_1000;residential;825,2;none;0,0;GMH;179,8;529,0;0,0;571,6;180,9;225,9;2758,5;false;2578,8;17,7;13,43;6;2,8;8;12;HEATED;NOT_HEATED;1,0;0,354;825,2;1,20;15,8;13071,0;78,4;64691;77762;14652;10977;7606;2331;186;2;0;0;447;4177;9981;14333
+DEBY_LOD2_604872;;49,80319;9,94676;568127,23;5517178,83;LOD_2;1974;;Original;31001_1000;residential;782,4;none;0,0;GMH;179,5;506,9;0,0;549,7;168,6;220,2;2624,4;false;2445,0;16,9;12,82;6;2,7;7;10;HEATED;NOT_HEATED;1,0;0,362;782,4;1,19;15,8;12393,0;82,3;64359;76752;14356;10877;7723;2621;222;3;0;0;520;4268;9767;14002
+DEBY_LOD2_604874;;49,80318;9,94749;568180,49;5517178,18;LOD_2;1990;;Original;31001_1000;residential;720,6;none;0,0;GMH;164,4;417,0;0,0;451,5;249,7;205,3;2416,4;false;2252,0;16,8;12,61;6;2,6;7;13;HEATED;NOT_HEATED;1,0;0,340;720,6;0,81;15,8;11415,0;56,5;40720;52135;9243;6955;4826;1460;94;1;0;0;247;2583;6269;9043
+DEBY_LOD2_604873;;49,80319;9,94697;568142,69;5517178,70;LOD_2;1960;;Original;31001_1000;residential;763,1;none;0,0;GMH;178,0;491,8;0,0;534,1;168,6;219,1;2562,7;false;2384,7;16,6;12,59;6;2,6;7;11;HEATED;NOT_HEATED;1,0;0,363;763,1;1,27;15,8;12088,0;87,7;66901;78989;14860;11269;8075;2719;248;3;0;0;568;4502;10166;14490
+DEBY_LOD2_604876;;49,80318;9,94728;568165,25;5517178,28;LOD_2;1922;;Original;31001_1000;residential;785,3;none;0,0;GMH;172,0;524,6;0,0;530,5;161,3;216,0;2478,0;false;2453,9;16,6;12,57;6;2,8;7;15;HEATED;NOT_HEATED;0,1;0,371;785,3;1,57;15,8;12439,0;104,5;82097;94536;18223;13935;10124;3420;185;1;0;0;556;5545;12398;17712
+DEBY_LOD2_604875;;49,80339;9,94751;568181,00;5517202,13;LOD_2;1916;;Original;31001_1000;residential;896,3;none;0,0;GMH;171,9;450,0;0,0;481,7;362,2;225,8;2972,7;false;2800,8;19,7;14,70;7;2,7;8;12;HEATED;NOT_HEATED;1,0;0,296;896,3;1,80;15,8;14197,0;96,2;86184;100381;19335;14656;10459;3426;175;1;0;0;520;5627;13139;18847
+DEBY_LOD2_604877;;49,80340;9,94791;568209,80;5517202,83;LOD_2;1988;;Original;31001_1000;residential;722,0;none;0,0;GMH;138,1;416,7;0,0;445,6;324,2;180,3;2394,5;false;2256,4;19,4;15,27;7;2,6;7;9;HEATED;NOT_HEATED;1,0;0,319;722,0;0,82;15,8;11437,0;53,8;38842;50279;8840;6638;4580;1424;91;1;0;0;226;2409;5975;8659
+DEBY_LOD2_604878;;49,80339;9,94810;568223,83;5517202,73;LOD_2;1956;;Original;31001_1000;residential;894,8;none;0,0;GMH;138,6;593,0;0,0;597,4;170,0;180,7;2392,0;false;2375,7;19,3;15,18;8;2,4;8;15;HEATED;NOT_HEATED;0,1;0,383;894,8;1,39;15,8;14174,0;82,7;73961;88135;16514;12477;8864;2948;261;4;0;0;595;4902;11277;16121
+DEBY_LOD2_604879;;49,80317;9,94790;568209,32;5517177,33;LOD_2;1968;;Original;31001_1000;residential;616,0;none;0,0;GMH;137,5;411,6;0,0;443,2;235,4;154,8;2062,6;false;1925,1;16,3;13,73;6;2,5;6;8;HEATED;NOT_HEATED;1,0;0,357;616,0;1,28;15,8;9758,0;89,8;55308;65066;12044;9253;6806;2577;269;4;0;0;560;3822;8253;11720
+DEBY_LOD2_604880;;49,80316;9,94809;568223,38;5517177,20;LOD_2;1937;;Original;31001_1000;residential;557,8;none;0,0;GMH;138,8;494,9;0,0;532,1;147,3;156,7;2075,2;false;1936,4;16,2;13,66;5;3,0;5;10;HEATED;NOT_HEATED;1,0;0,399;557,8;1,57;15,8;8836,0;117,9;65781;74617;14962;11282;7868;2321;111;0;0;0;330;4224;10112;14572
+DEBY_LOD2_604882;;49,80317;9,94770;568195,11;5517177,45;LOD_2;1882;;Original;31001_1000;residential;363,9;none;0,0;RH;142,2;231,7;0,0;260,7;176,6;142,2;1279,5;false;1137,3;9,0;9,00;3;2,7;5;8;NO_ROOM;NOT_HEATED;1,0;0,426;363,9;1,31;15,8;5765,0;107,5;39128;44893;8497;6561;4898;1915;150;1;0;0;332;2694;5822;8259
+DEBY_LOD2_605659;;49,80331;9,94669;568122,33;5517191,87;LOD_2;1966;;Original;31001_2000;commercial;12,5;none;0,0;EFH;15,6;45,3;0,0;49,5;0,0;15,7;45,7;false;39,0;3,1;2,75;1;2,5;0;0;NOT_HEATED;NOT_HEATED;0,3;1,769;12,5;1,23;73,0;912,0;258,7;3231;4143;799;574;360;88;0;0;0;0;2;145;488;775
+DEBY_LOD2_605660;;49,80331;9,94722;568160,33;5517192,29;LOD_2;1976;;Original;31001_2000;commercial;14,4;none;0,0;RH;17,4;30,7;0,0;33,6;15,9;17,4;49,3;false;45,1;2,8;2,84;1;2,6;0;0;NO_ROOM;NOT_HEATED;0,2;1,384;14,4;1,15;73,0;1054,0;225,0;3247;4301;765;565;379;108;4;0;0;0;12;188;491;736
+DEBY_LOD2_605661;;49,80330;9,94700;568144,89;5517191,77;LOD_2;1991;;Original;31001_2000;commercial;23,9;none;0,0;EFH;29,9;71,7;0,0;79,6;0,0;30,0;87,3;false;74,7;3,0;2,79;1;2,5;0;0;NOT_HEATED;NOT_HEATED;0,3;1,599;23,9;0,59;73,0;1745,0;140,1;3349;5094;807;574;356;97;7;0;0;0;15;180;521;793
+DEBY_LOD2_605664;;49,80327;9,94722;568160,29;5517188,10;LOD_2;1953;;Original;31001_2000;commercial;26,5;none;0,0;RH;29,3;43,1;0,0;48,3;15,9;29,4;86,7;false;70,2;3,2;2,72;1;2,4;0;0;NOT_HEATED;NOT_HEATED;0,3;1,233;26,5;1,21;73,0;1932,0;185,1;4898;6830;1190;847;527;138;6;0;0;0;15;253;759;1164
+DEBY_LOD2_605665;;49,80327;9,94805;568220,45;5517189,01;LOD_2;1918;;Original;31001_2000;commercial;15,1;none;0,0;RH;18,2;31,4;0,0;41,5;19,4;18,2;62,4;false;47,3;3,4;3,43;1;2,6;0;0;NO_ROOM;NOT_HEATED;0,8;1,249;15,1;1,33;73,0;1105,0;246,9;3735;4840;878;657;449;133;2;0;0;0;8;204;558;846
+DEBY_LOD2_605663;;49,80332;9,94747;568178,23;5517193,67;LOD_2;1984;;Original;31001_2000;commercial;27,7;none;0,0;RH;34,6;40,9;0,0;56,5;24,8;34,6;119,4;false;86,5;3,5;3,45;1;2,5;0;0;NO_ROOM;NOT_HEATED;1,0;1,052;27,7;0,66;73,0;2021,0;134,0;3709;5730;859;631;420;126;12;0;0;0;25;226;571;838
+DEBY_LOD2_605662;;49,80327;9,94744;568176,42;5517187,76;LOD_2;2002;;Original;31001_2000;commercial;31,1;none;0,0;EFH;38,9;53,7;0,0;54,0;8,8;38,9;97,8;false;97,3;2,5;2,51;1;2,5;0;0;NO_ROOM;NOT_HEATED;0,0;1,347;31,1;0,39;73,0;2273,0;94,2;2934;5207;672;497;335;105;12;0;0;0;23;181;451;658
+DEBY_LOD2_605668;;49,80326;9,94815;568227,84;5517187,71;LOD_2;2007;;Original;31001_2000;commercial;14,2;none;0,0;RH;17,8;24,0;0,0;32,1;26,4;17,8;59,6;false;44,5;3,4;3,35;1;2,5;0;0;NO_ROOM;NOT_HEATED;0,9;1,135;14,2;0,41;73,0;1040,0;87,9;1251;2291;297;212;132;38;5;0;0;0;7;67;198;296
+DEBY_LOD2_605669;;49,80327;9,94810;568223,57;5517188,98;LOD_2;1935;;Original;31001_2000;commercial;14,9;none;0,0;RH;16,9;18,1;0,0;22,9;37,2;16,9;58,9;false;46,5;3,5;3,49;1;2,8;0;0;NO_ROOM;NOT_HEATED;0,7;0,962;14,9;1,26;73,0;1086,0;203,1;3022;4108;684;520;372;131;7;0;0;0;15;183;449;662
+DEBY_LOD2_605670;;49,80329;9,94816;568227,85;5517190,95;LOD_2;1965;;Original;31001_2000;commercial;14,4;none;0,0;RH;18,0;24,1;0,0;28,4;22,6;18,0;52,9;false;44,9;2,9;2,94;1;2,5;0;0;NO_ROOM;NOT_HEATED;0,4;1,216;14,4;1,29;73,0;1049,0;244,5;3514;4563;808;609;430;134;5;0;0;0;15;216;523;774

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.log

+======================== Summary ========================
+
+
+
+================ Excluded buildings lists ===============
+

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/params.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflowsteps.MonthlyEnergyBalanceStep">
+  <void property="name">
+   <string>Base</string>
+  </void>
+ </object>
+</java>

old/cgsc/tests/TestRepo/CGSC.proj/101_HeatDemand.flow/params.xml

+<java version="1.8.0_422" class="java.beans.XMLDecoder">
+ <object class="eu.simstadt.workflows.CityGmlWorkflow" id="CityGmlWorkflow0">
+  <void class="de.hftstuttgart.hierarchicworkflow.Workflow" method="getField">
+   <string>selectedStartStepPath</string>
+   <void method="set">
+    <object idref="CityGmlWorkflow0" />
+    <string>00_ImportCityGml.step</string>
+   </void>
+  </void>
+  <void class="de.hftstuttgart.hierarchicworkflow.WorkflowStep" method="getField">
+   <string>startStep</string>
+   <void method="set">
+    <object idref="CityGmlWorkflow0" />
+    <boolean>true</boolean>
+   </void>
+  </void>
+  <void property="name">
+   <string>CGSC_HeatDemand</string>
+  </void>
+  <void property="shortName">
+   <string>HeatDemand</string>
+  </void>
+  <void property="workflowProvider">
+   <object class="de.hftstuttgart.simstadtworkflows.energy.HeatDemandAnalysisWorkflowProvider" />
+  </void>
+ <void property="cityGmlFileNames"><void method="add"><string>Grombuehl_mini_Steinheilstrasse.gml</string></void></void></object>
+</java>
\ No newline at end of file