完成求解器雅可比矩阵首轮优化，增加更新目录，整理了文档文件夹，增加了服务启动脚本
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@@ -3,6 +3,7 @@ from __future__ import annotations
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from collections.abc import Callable
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from dataclasses import dataclass, replace
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from math import floor, isfinite
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import os
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from typing import Literal
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from app.simulation.core.base import Component, DynamicComponent
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@@ -12,6 +13,10 @@ from app.simulation.performance import performance_span, profile_phase
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from app.simulation.property_cache import with_property_cache
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from app.simulation.solvers.algebraic import PressureFlowSolver
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from app.simulation.solvers.algebraic_blocks import StreamPressureBlockSolver
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from app.simulation.solvers.jacobian import (
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SparseJacobianCompatibilityError,
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SparseSecantJacobian,
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)
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from app.simulation.solvers.mechanical import (
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MechanicalConstraintGroup,
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MechanicalStateReducer,
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@@ -21,15 +26,58 @@ from app.simulation.solvers.pneumatic_storage import (
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ideal_storage_group_is_reducible,
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)
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from app.simulation.solvers.pneumatic_volume import PneumaticVolumeResolver
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from app.simulation.solvers.solver import ODESolution, SolveIVPConfig, integrate_ode
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from app.simulation.solvers.solver import (
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IntegrationCancelled,
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ODESolution,
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SolveIVPConfig,
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integrate_ode,
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)
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from app.simulation.solvers.signal import SignalResolver
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from app.simulation.solvers.stream import StreamResolver
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from app.simulation.solvers.tangent import (
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ThreePistonTangentCompilation,
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ThreePistonTangentProvider,
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compile_three_piston_tangent_provider,
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)
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from app.simulation.systems.network import Endpoint, SimulationNetwork
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SimulationProgressCallback = Callable[[float, str], None]
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SimulationCancellationCheck = Callable[[], bool]
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SimulationRunStatus = Literal["completed", "cancelled", "failed"]
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ODE_JACOBIAN_MODE_ENVIRONMENT_VARIABLE = "SIMULATION_ODE_JACOBIAN_MODE"
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def _requested_ode_jacobian_mode() -> Literal[
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"optimized",
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"hybrid",
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"semi-analytic",
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"scipy",
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]:
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value = os.getenv(
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ODE_JACOBIAN_MODE_ENVIRONMENT_VARIABLE,
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"scipy",
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).strip().lower()
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if value in {"optimized", "colored"}:
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return "optimized"
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if value in {"hybrid", "secant"}:
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return "hybrid"
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if value in {"semi-analytic", "semi_analytic", "analytic"}:
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return "semi-analytic"
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if value in {
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"scipy",
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"native",
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"finite-difference",
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"0",
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"false",
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"no",
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"off",
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}:
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return "scipy"
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raise ValueError(
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f"{ODE_JACOBIAN_MODE_ENVIRONMENT_VARIABLE} must be "
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"'optimized', 'hybrid', 'semi-analytic', or 'scipy'."
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)
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@dataclass(frozen=True)
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@@ -398,6 +446,7 @@ class GenericFluidSystem:
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self.signal_propagation_count = 0
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self.pneumatic_volume_propagation_count = 0
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self._jacobian_sparsity = None
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self._ode_tangent_provider: ThreePistonTangentProvider | None = None
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def _request_causal_residual_audit(self) -> None:
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"""Make topology or mode boundaries verify the next causal closure."""
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@@ -874,6 +923,23 @@ class GenericFluidSystem:
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"colorGroupCount": group_count,
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}
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def _exact_ode_jacobian_rows(self) -> dict[int, dict[int, float]]:
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"""Return mode-independent kinematic rows safe to evaluate exactly."""
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rows: dict[int, dict[int, float]] = {}
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cursor = 0
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for entry in self.mechanical_state_reducer.state_entries:
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if isinstance(entry, MechanicalConstraintGroup):
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# A discrete endstop can replace x' = v with x' = 0 for the
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# active constrained mode. Keep those rows numerical; free
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# mechanical groups always have d(x')/d(v) = 1.
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if not entry.discrete_endstop_components:
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rows[cursor + 1] = {cursor: 1.0}
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cursor += 2
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else:
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cursor += entry.state_size
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return rows
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@profile_phase(
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"simulation.closure",
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minimum_mode="audit",
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@@ -1065,7 +1131,11 @@ class GenericFluidSystem:
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def rhs(self, _time: float, state_vector: list[float]) -> list[float]:
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self.apply_state_vector(state_vector)
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connected_h = self._close_current_state(_time)
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return self._state_derivatives(connected_h)
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derivatives = self._state_derivatives(connected_h)
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provider = self._ode_tangent_provider
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if provider is not None:
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provider.record_primal(_time, state_vector, connected_h)
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return derivatives
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def _append_current_state(self, series: dict[str, list[float]]) -> None:
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for component in self.network.components.values():
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@@ -1156,29 +1226,112 @@ class GenericFluidSystem:
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report_solver_time(time)
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return self.rhs(time, state_vector)
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jacobian = None
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jacobian_fallback_reason: str | None = None
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tangent_compilation: ThreePistonTangentCompilation | None = None
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selected_tangent_provider: ThreePistonTangentProvider | None = None
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self._ode_tangent_provider = None
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requested_jacobian_mode = (
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_requested_ode_jacobian_mode()
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if jac_sparsity is not None
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else "scipy"
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)
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if (
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jac_sparsity is not None
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and requested_jacobian_mode
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in {"optimized", "hybrid", "semi-analytic"}
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):
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state_count = int(jac_sparsity.shape[0])
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if (
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requested_jacobian_mode == "hybrid"
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and not self.pressure_flow_solver.causal_fast_path_enabled
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):
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jacobian_fallback_reason = "causalAlgebraicExecutionUnavailable"
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elif int(jac_sparsity.nnz) >= state_count * state_count:
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jacobian_fallback_reason = "denseStateDependencyPattern"
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else:
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exact_columns = None
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if requested_jacobian_mode == "semi-analytic":
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tangent_compilation = (
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compile_three_piston_tangent_provider(self)
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)
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if tangent_compilation.eligible:
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provider = tangent_compilation.provider
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if provider is None:
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raise RuntimeError(
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"An eligible tangent compilation has no provider."
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)
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selected_tangent_provider = provider
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exact_columns = (
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tangent_compilation.columns,
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provider,
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)
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else:
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jacobian_fallback_reason = (
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f"semiAnalytic:{tangent_compilation.reason}"
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)
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if (
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requested_jacobian_mode != "semi-analytic"
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or tangent_compilation is not None
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and tangent_compilation.eligible
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):
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def evaluate_jacobian_rhs(time, state):
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if cancel_check is not None and cancel_check():
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raise IntegrationCancelled
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return monitored_rhs(
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time,
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[float(value) for value in state],
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)
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try:
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jacobian = SparseSecantJacobian(
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evaluate_jacobian_rhs,
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jac_sparsity,
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integration_config.atol,
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exact_rows=self._exact_ode_jacobian_rows(),
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exact_columns=exact_columns,
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max_consecutive_reuses=(
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1
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if requested_jacobian_mode == "hybrid"
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else 0
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),
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)
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self._ode_tangent_provider = (
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selected_tangent_provider
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)
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except SparseJacobianCompatibilityError as exc:
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jacobian_fallback_reason = (
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f"scipyCompatibility:{type(exc).__name__}"
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)
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def handle_state_transition(*args):
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transition = self.mechanical_state_reducer.state_transition(*args)
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if transition is not None:
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self._request_causal_residual_audit()
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return transition
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solution = integrate_ode(
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rhs=monitored_rhs,
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initial_state=initial_state,
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config=integration_config,
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t_eval=t_eval,
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cancel_check=cancel_check,
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accepted_step_callback=(
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report_solver_time if cancel_check is not None else None
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),
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breakpoints=signal_event_times,
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state_transition_handler=(
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handle_state_transition
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if self.mechanical_state_reducer.has_state_events
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else None
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),
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jac_sparsity=jac_sparsity,
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)
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try:
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solution = integrate_ode(
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rhs=monitored_rhs,
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initial_state=initial_state,
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config=integration_config,
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t_eval=t_eval,
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cancel_check=cancel_check,
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accepted_step_callback=(
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report_solver_time if cancel_check is not None else None
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),
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breakpoints=signal_event_times,
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state_transition_handler=(
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handle_state_transition
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if self.mechanical_state_reducer.has_state_events
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else None
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),
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jac_sparsity=jac_sparsity,
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jac=jacobian,
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)
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finally:
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self._ode_tangent_provider = None
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if isinstance(solution, ODESolution):
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run_status: SimulationRunStatus = solution.status
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integration_error = solution.error
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@@ -1212,6 +1365,44 @@ class GenericFluidSystem:
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"recoverableRetryCount": 0,
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}
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]
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if jacobian is not None:
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direct_jacobian = jacobian.diagnostics()
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solver_segment_diagnostics[0].update(
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{
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"jacobianEvaluationCount": int(
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direct_jacobian["jacobianEvaluationCount"]
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),
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"jacobianFullBuildCount": int(
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direct_jacobian["fullBuildCount"]
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),
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"jacobianSecantReuseCount": int(
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direct_jacobian["secantReuseCount"]
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),
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"jacobianAuditFailureCount": int(
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direct_jacobian["auditFailureCount"]
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),
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"finiteDifferenceRhsEvaluationCount": int(
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direct_jacobian[
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"finiteDifferenceRhsEvaluationCount"
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]
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),
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"jacobianBaseRhsEvaluationCount": int(
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direct_jacobian["baseRhsEvaluationCount"]
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),
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"jacobianJvAuditRhsEvaluationCount": int(
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direct_jacobian["jvAuditEvaluationCount"]
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),
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"exactColumnBuildCount": int(
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direct_jacobian["exactColumnBuildCount"]
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),
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"exactColumnFallbackCount": int(
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direct_jacobian["exactColumnFallbackCount"]
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),
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"jacobianAssemblySeconds": float(
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direct_jacobian["assemblySeconds"]
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),
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}
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)
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solver_total_keys = (
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"nfev",
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"njev",
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@@ -1225,21 +1416,123 @@ class GenericFluidSystem:
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key: sum(int(segment[key]) for segment in solver_segment_diagnostics)
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for key in solver_total_keys
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}
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jacobian_work_keys = (
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"jacobianEvaluationCount",
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"jacobianFullBuildCount",
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"jacobianSecantReuseCount",
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"jacobianAuditFailureCount",
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"finiteDifferenceRhsEvaluationCount",
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"jacobianBaseRhsEvaluationCount",
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"jacobianJvAuditRhsEvaluationCount",
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"exactColumnBuildCount",
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"exactColumnFallbackCount",
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"jacobianAssemblySeconds",
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)
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for key in jacobian_work_keys:
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if any(key in segment for segment in solver_segment_diagnostics):
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solver_totals[key] = sum(
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segment.get(key, 0)
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for segment in solver_segment_diagnostics
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)
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jacobian_diagnostics = (
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self.jacobian_sparsity_diagnostics()
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if integration_config.method in {"BDF", "Radau"}
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else None
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)
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runtime_jacobian_diagnostics: dict[str, object] | None = None
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if jacobian_diagnostics is not None:
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color_group_count = int(jacobian_diagnostics["colorGroupCount"])
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for segment in solver_segment_diagnostics:
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segment["finiteDifferenceRhsEstimate"] = (
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int(segment["njev"]) * color_group_count
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if jacobian is None:
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for segment in solver_segment_diagnostics:
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segment["finiteDifferenceRhsEstimate"] = (
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int(segment["njev"]) * color_group_count
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)
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runtime_jacobian_diagnostics = {
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"mode": "scipySparseFiniteDifference",
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"fallbackReason": jacobian_fallback_reason,
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"jacobianEvaluationCount": int(solver_totals["njev"]),
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"fullBuildCount": int(solver_totals["njev"]),
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"finiteDifferenceRhsEstimateIsExact": False,
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}
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else:
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for segment in solver_segment_diagnostics:
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segment["finiteDifferenceRhsEstimate"] = int(
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segment.get("finiteDifferenceRhsEvaluationCount", 0)
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) + int(
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segment.get("jacobianJvAuditRhsEvaluationCount", 0)
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)
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runtime_jacobian_diagnostics = dict(jacobian.diagnostics())
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runtime_jacobian_diagnostics.update(
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{
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"fallbackReason": jacobian_fallback_reason,
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"finiteDifferenceRhsEstimateIsExact": True,
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}
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)
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if tangent_compilation is not None:
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runtime_jacobian_diagnostics["tangentCompilation"] = (
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tangent_compilation.diagnostics()
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)
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if tangent_compilation.eligible and jacobian is not None:
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runtime_jacobian_diagnostics["mode"] = (
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"semiAnalyticExactColumns"
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)
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exact_builds = int(
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runtime_jacobian_diagnostics[
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"exactColumnBuildCount"
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]
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)
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exact_fallbacks = int(
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runtime_jacobian_diagnostics[
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"exactColumnFallbackCount"
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]
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)
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if exact_builds == 0 and exact_fallbacks == 0:
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effective_mode = "notEvaluated"
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elif exact_builds == 0:
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effective_mode = "numericalFallbackOnly"
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elif exact_fallbacks:
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effective_mode = "mixedExactAndNumericalFallback"
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else:
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effective_mode = "exactColumns"
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runtime_jacobian_diagnostics["effectiveMode"] = (
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effective_mode
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)
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if exact_fallbacks:
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runtime_jacobian_diagnostics[
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"runtimeFallbackReason"
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] = runtime_jacobian_diagnostics[
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"lastExactColumnFallbackReason"
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]
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solver_totals["finiteDifferenceRhsEstimate"] = sum(
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int(segment["finiteDifferenceRhsEstimate"])
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for segment in solver_segment_diagnostics
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)
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if jacobian is None:
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solver_totals["jacobianRhsEvaluationCountEstimate"] = (
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int(solver_totals["finiteDifferenceRhsEstimate"])
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+ int(solver_totals["njev"])
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)
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else:
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solver_totals["jacobianRhsEvaluationCount"] = (
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int(
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solver_totals.get(
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"finiteDifferenceRhsEvaluationCount",
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0,
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)
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)
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+ int(
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solver_totals.get(
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"jacobianBaseRhsEvaluationCount",
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0,
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)
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)
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+ int(
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solver_totals.get(
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"jacobianJvAuditRhsEvaluationCount",
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0,
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)
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)
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)
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with performance_span("simulation.postprocessing"):
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series: dict[str, list[float]] = {"time": []}
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@@ -1286,6 +1579,7 @@ class GenericFluidSystem:
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"integration": {
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"method": integration_config.method,
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"jacobianSparsity": jacobian_diagnostics,
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"jacobian": runtime_jacobian_diagnostics,
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"segmentCount": len(solver_segment_diagnostics),
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"segments": solver_segment_diagnostics,
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"totals": solver_totals,
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