验收四路模型并优化拓扑求解性能
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from __future__ import annotations
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import argparse
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import json
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Mapping
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from app.simulation.components.amesim.flow.pipes import AmesimPnl0002
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from app.simulation.reporting.amesim_results import (
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AmesimResults,
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load_test_mql_amesim_results,
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)
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@dataclass(frozen=True, slots=True)
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class Pnl0002ReplayPaths:
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"""AMESim data paths needed to replay one PNL0002 resistance."""
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center_pressure: str
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center_temperature: str
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port_1_pressure: str
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port_1_temperature: str
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port_1_mass_flow: str
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port_2_pressure: str
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port_2_temperature: str
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port_2_mass_flow: str
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reynolds: str
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friction_factor: str
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PNL83_REPLAY_PATHS = Pnl0002ReplayPaths(
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center_pressure="pctr@pneumatic_83",
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center_temperature="tctr@pneumatic_83",
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port_1_pressure="press1@pnnode4_16",
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port_1_temperature="temp1@pnnode4_16",
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port_1_mass_flow="dm1@pneumatic_83",
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port_2_pressure="press3@pnnode4_17",
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port_2_temperature="temp3@pnnode4_17",
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port_2_mass_flow="dm2@pneumatic_83",
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reynolds="re@pneumatic_83",
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friction_factor="ff@pneumatic_83",
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)
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def _required_series(
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results: AmesimResults,
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path: str,
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) -> tuple[float, ...]:
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try:
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values = results.series(path)
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except KeyError as exc:
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raise ValueError(f"AMESim replay variable is not saved: {path}") from exc
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if len(values) != len(results.times):
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raise ValueError(f"AMESim replay variable has an invalid length: {path}")
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return values
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def _metric_summary(
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rows: list[dict[str, float]],
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key: str,
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) -> dict[str, float]:
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values = [float(row[key]) for row in rows]
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max_index = max(range(len(values)), key=lambda index: abs(values[index]))
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return {
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"maxAbs": abs(values[max_index]),
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"maxAbsTime": rows[max_index]["time"],
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"finalSigned": values[-1],
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}
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def replay_pnl0002_amesim_states(
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pipe: AmesimPnl0002,
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results: AmesimResults,
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paths: Pnl0002ReplayPaths,
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*,
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amesim_mass_flow_scale: float = -1.0e-3,
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) -> dict[str, object]:
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"""Replay saved AMESim states through current PNL0002 flow functions.
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This is a calibration-only, no-integration calculation. It does not write
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states into the pipe or alter the production simulation path.
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"""
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series_by_field = {
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field: _required_series(results, getattr(paths, field))
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for field in paths.__dataclass_fields__
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}
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rows: list[dict[str, float]] = []
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for index, time_s in enumerate(results.times):
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center_pressure = series_by_field["center_pressure"][index]
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center_temperature = series_by_field["center_temperature"][index]
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port_1_pressure = series_by_field["port_1_pressure"][index]
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port_2_pressure = series_by_field["port_2_pressure"][index]
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observed_flow_1 = (
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amesim_mass_flow_scale
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* series_by_field["port_1_mass_flow"][index]
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)
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observed_flow_2 = (
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amesim_mass_flow_scale
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* series_by_field["port_2_mass_flow"][index]
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)
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upstream_temperature_1 = (
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series_by_field["port_1_temperature"][index]
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if observed_flow_1 >= 0.0
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else center_temperature
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)
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upstream_temperature_2 = (
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series_by_field["port_2_temperature"][index]
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if observed_flow_2 >= 0.0
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else center_temperature
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)
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predicted_flow_1 = pipe.mass_flow(
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port_1_pressure,
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center_pressure,
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upstream_temperature_1,
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)
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predicted_flow_2 = pipe.mass_flow(
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port_2_pressure,
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center_pressure,
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upstream_temperature_2,
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)
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reynolds_1 = pipe.reynolds_number(
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observed_flow_1,
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upstream_temperature_1,
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)
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reynolds_2 = pipe.reynolds_number(
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observed_flow_2,
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upstream_temperature_2,
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)
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friction_1 = pipe.friction_factor(reynolds_1)
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friction_2 = pipe.friction_factor(reynolds_2)
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replay_reynolds = 0.5 * (reynolds_1 + reynolds_2)
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replay_friction = 0.5 * (friction_1 + friction_2)
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rows.append(
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{
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"time": float(time_s),
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"centerPressure": center_pressure,
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"centerTemperature": center_temperature,
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"port1Pressure": port_1_pressure,
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"port2Pressure": port_2_pressure,
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"observedPort1MassFlow": observed_flow_1,
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"observedPort2MassFlow": observed_flow_2,
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"predictedPort1MassFlow": predicted_flow_1,
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"predictedPort2MassFlow": predicted_flow_2,
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"port1MassFlowError": predicted_flow_1 - observed_flow_1,
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"port2MassFlowError": predicted_flow_2 - observed_flow_2,
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"amesimReynolds": series_by_field["reynolds"][index],
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"replayReynolds": replay_reynolds,
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"reynoldsError": (
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replay_reynolds - series_by_field["reynolds"][index]
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),
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"amesimFrictionFactor": series_by_field["friction_factor"][index],
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"replayFrictionFactor": replay_friction,
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"frictionFactorError": (
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replay_friction
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- series_by_field["friction_factor"][index]
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),
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}
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)
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metric_keys = (
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"port1MassFlowError",
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"port2MassFlowError",
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"reynoldsError",
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"frictionFactorError",
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)
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return {
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"mode": "amesim-state-replay-no-integration",
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"component": pipe.name,
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"pointCount": len(rows),
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"massFlowScale": amesim_mass_flow_scale,
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"paths": {
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field: getattr(paths, field)
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for field in paths.__dataclass_fields__
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},
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"parameters": dict(pipe.parameter_values),
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"summary": {
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key: _metric_summary(rows, key)
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for key in metric_keys
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},
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"rows": rows,
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}
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def _compile_project_pipe(
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project_path: Path,
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component_name: str,
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) -> AmesimPnl0002:
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from app.main import (
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ReactFlowProjectPayload,
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_compile_xml_document_or_422,
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_validated_xml_document_or_422,
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build_reactflow_system_xml,
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validate_system_xml_document,
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)
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payload = ReactFlowProjectPayload.model_validate_json(
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project_path.read_text(encoding="utf-8")
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)
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xml_bytes = build_reactflow_system_xml(payload)
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document = _validated_xml_document_or_422(
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validate_system_xml_document(xml_bytes)
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)
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_project, network = _compile_xml_document_or_422(document)
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try:
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component = network.components[component_name]
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except KeyError as exc:
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raise ValueError(f"Project component does not exist: {component_name}") from exc
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if not isinstance(component, AmesimPnl0002):
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raise ValueError(f"Project component is not PNL0002: {component_name}")
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return component
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def _paths_from_arguments(arguments: argparse.Namespace) -> Pnl0002ReplayPaths:
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values: Mapping[str, str] = {
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field: getattr(arguments, field)
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for field in PNL83_REPLAY_PATHS.__dataclass_fields__
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}
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return Pnl0002ReplayPaths(**values)
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def main() -> None:
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parser = argparse.ArgumentParser(
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description="Replay saved AMESim p/T/m_flow through a PNL0002 model without integration."
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)
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parser.add_argument("project", type=Path)
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parser.add_argument("amesim_archive", type=Path)
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parser.add_argument("output", type=Path)
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parser.add_argument("--component", default="pneumatic_83")
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parser.add_argument("--mass-flow-scale", type=float, default=-1.0e-3)
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for field in PNL83_REPLAY_PATHS.__dataclass_fields__:
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parser.add_argument(
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"--" + field.replace("_", "-"),
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dest=field,
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default=getattr(PNL83_REPLAY_PATHS, field),
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)
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arguments = parser.parse_args()
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pipe = _compile_project_pipe(arguments.project, arguments.component)
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results = load_test_mql_amesim_results(arguments.amesim_archive)
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report = replay_pnl0002_amesim_states(
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pipe,
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results,
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_paths_from_arguments(arguments),
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amesim_mass_flow_scale=arguments.mass_flow_scale,
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)
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arguments.output.parent.mkdir(parents=True, exist_ok=True)
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arguments.output.write_text(
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json.dumps(report, ensure_ascii=False, indent=2) + "\n",
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encoding="utf-8",
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)
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print(json.dumps({key: report[key] for key in (
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"mode",
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"component",
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"pointCount",
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"parameters",
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"summary",
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)}, ensure_ascii=False, indent=2))
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if __name__ == "__main__":
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main()
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