neuromancer package

Subpackages

• neuromancer.dynamics package
  • Submodules
    • neuromancer.dynamics.integrators module
      • BasicSDEIntegrator
      • DiffEqIntegrator
      • Euler
      • Euler_Trap
      • Integrator
      • LatentSDEIntegrator
      • LeapFrog
      • Luther
      • MultiStep_PredictorCorrector
      • RK2
      • RK4
      • RK4_Trap
      • Runge_Kutta_Fehlberg
      • Yoshida4
      • make_norm()
      • rms_norm()
    • neuromancer.dynamics.interpolation module
      • Interpolation
      • LinInterp_Offline
      • LinInterp_Online
    • neuromancer.dynamics.library module
      • FourierLibrary
      • FunctionLibrary
      • PolynomialLibrary
    • neuromancer.dynamics.ode module
      • BrusselatorHybrid
      • BrusselatorParam
      • CSTR_Param
      • DuffingParam
      • GeneralNetworkedODE
      • LorenzControl
      • LorenzParam
      • LotkaVolterraHybrid
      • LotkaVolterraParam
      • ODESystem
      • SINDy
      • SSM
      • TwoTankParam
      • VanDerPolControl
    • neuromancer.dynamics.physics module
      • Agent
      • DeltaTemp
      • DeltaTempSwitch
      • HVACConnection
      • Interaction
      • RCNode
      • SourceSink
      • map_from_agents()
    • neuromancer.dynamics.sde module
      • BaseSDESystem
      • Encoder
      • LatentSDE_Decoder
      • LatentSDE_Encoder
      • LotkaVolterraSDE
      • SDECoxIngersollRand
      • SDEOrnsteinUhlenbeck
      • StochasticLorenzAttractor
  • Module contents
• neuromancer.modules package
  • Submodules
    • neuromancer.modules.activations module
      • APLU
      • BLU
      • PELU
      • PReLU
      • RectifiedSoftExp
      • SmoothedReLU
      • SoftExponential
      • soft_exp()
    • neuromancer.modules.blocks module
      • BasisLinear
      • BilinearTorch
      • Block
      • Dropout
      • InputConvexNN
      • InteractionEmbeddingMLP
      • InterpolateAddMultiply
      • KAN
      • KANBlock
      • KANLinear
      • Linear
      • MLP
      • MLPDropout
      • MLP_bounds
      • Poly2
      • PosDef
      • PytorchRNN
      • RNN
      • ResMLP
      • StackedMLP
      • Transformer
      • set_model_dropout_mode()
    • neuromancer.modules.functions module
      • bounds_clamp()
      • bounds_scaling()
      • window_functions()
    • neuromancer.modules.lopo module
      • ADMMSolver
      • DRSolver
      • ParaMetricDiagonal
      • ProxBoxConstraint
      • ProxObjectivePlusEqualityConstraint
    • neuromancer.modules.rnn module
      • RNN
      • RNNCell
    • neuromancer.modules.solvers module
      • GradientProjection
      • IterativeSolver
      • Solver
  • Module contents
• neuromancer.psl package
  • Submodules
    • neuromancer.psl.autonomous module
      • Autoignition
      • Brusselator1D
      • ChuaCircuit
      • DoublePendulum
      • Duffing
      • LorenzSystem
      • LotkaVolterra
      • Pendulum
      • RosslerAttractor
      • ThomasAttractor
      • UniversalOscillator
      • VanDerPol
    • neuromancer.psl.base module
      • Backend
      • EmulatorBase
      • EquationWrapper
      • ODE_Autonomous
      • ODE_NonAutonomous
      • cast_backend()
      • download()
      • grad()
    • neuromancer.psl.building_envelope module
      • BuildingEnvelope
      • LinearBuildingEnvelope
    • neuromancer.psl.coupled_systems module
      • Boids
      • Coupled_NonAutonomous
      • Coupled_ODE
      • Gravitational_System
      • RC_Network
      • multidim()
    • neuromancer.psl.file_emulator module
      • FileEmulator
      • read_file()
    • neuromancer.psl.gym module
    • neuromancer.psl.nonautonomous module
      • Actuator
      • CSTR
      • DuffingControl
      • HindmarshRose
      • InvPendulum
      • IverSimple
      • LorenzControl
      • SEIR_population
      • SwingEquation
      • Tank
      • ThomasAttractorControl
      • TwoTank
      • VanDerPolControl
    • neuromancer.psl.norms module
      • StandardScaler
      • denormalize()
      • normalize()
    • neuromancer.psl.perturb module
      • Periodic()
      • RandomWalk()
      • Sawtooth()
      • SplineSignal()
      • Step()
      • Steps()
      • WhiteNoise()
      • random_walk()
      • white_noise()
    • neuromancer.psl.plot module
      • get_colors()
      • pltCL()
      • pltCorrelate()
      • pltOL()
      • pltPhase()
      • pltRecurrence()
    • neuromancer.psl.signals module
      • arma()
      • beta()
      • beta_walk_max_step()
      • beta_walk_mean()
      • nd_walk()
      • noise()
      • np_softmax()
      • periodic()
      • prbs()
      • sines()
      • spline()
      • step()
      • walk()
    • neuromancer.psl.system_emulator module
      • system_to_psl()
  • Module contents
• neuromancer.slim package
  • Subpackages
    • neuromancer.slim.butterfly package
      • Submodules
      • Module contents
  • Submodules
    • neuromancer.slim.bench module
    • neuromancer.slim.linear module
      • BoundedNormLinear
      • ButterflyLinear
      • DampedSkewSymmetricLinear
      • GershgorinLinear
      • Hprod()
      • IdentityGradReLU
      • IdentityInitLinear
      • IdentityLinear
      • L0Linear
      • LassoLinear
      • LassoLinearRELU
      • LeftStochasticLinear
      • Linear
      • LinearBase
      • NonNegativeLinear
      • OrthogonalLinear
      • PSDLinear
      • PerronFrobeniusLinear
      • PowerBoundLinear
      • RightStochasticLinear
      • SVDLinear
      • SVDLinearLearnBounds
      • SchurDecompositionLinear
      • SkewSymmetricLinear
      • SpectralLinear
      • SplitLinear
      • SquareLinear
      • StableSplitLinear
      • SymmetricLinear
      • SymmetricSVDLinear
      • SymmetricSpectralLinear
      • SymplecticLinear
      • TrivialNullSpaceLinear
    • neuromancer.slim.rnn module
      • RNN
      • RNNCell
  • Module contents

Submodules

• neuromancer.arg module
  • ArgParser
    • ArgParser.check_for_group()
    • ArgParser.group()
    • ArgParser.parse_arg_groups()
  • add()
  • ctrl_loss()
  • data()
  • freeze()
  • lin()
  • log()
  • loss()
  • opt()
  • policy()
  • ssm()
• neuromancer.callbacks module
  • Callback
    • Callback.begin_epoch()
    • Callback.begin_eval()
    • Callback.begin_test()
    • Callback.begin_train()
    • Callback.end_batch()
    • Callback.end_epoch()
    • Callback.end_eval()
    • Callback.end_test()
    • Callback.end_train()
• neuromancer.constraint module
  • Constraint
    • Constraint.forward()
    • Constraint.grad()
    • Constraint.update_name()
    • Constraint.variable_names
  • Eq
    • Eq.forward()
  • GT
    • GT.forward()
  • LT
    • LT.forward()
  • Loss
    • Loss.forward()
    • Loss.grad()
  • Objective
    • Objective.forward()
    • Objective.grad()
    • Objective.variable_names
  • Variable
    • Variable.T
    • Variable.check_keys()
    • Variable.display_name
    • Variable.forward()
    • Variable.get_value()
    • Variable.grad()
    • Variable.key
    • Variable.keys
    • Variable.mT
    • Variable.make_graph()
    • Variable.minimize()
    • Variable.show()
    • Variable.unpack
    • Variable.value
  • variable()
• neuromancer.dataset module
  • DictDataset
    • DictDataset.collate_fn()
  • GraphDataset
    • GraphDataset.build_graphs()
    • GraphDataset.collate_fn()
    • GraphDataset.make_map()
    • GraphDataset.shuffle()
  • LitDataModule
    • LitDataModule.setup()
    • LitDataModule.test_dataloader()
    • LitDataModule.train_dataloader()
    • LitDataModule.val_dataloader()
  • SequenceDataset
    • SequenceDataset.collate_fn()
    • SequenceDataset.get_full_batch()
    • SequenceDataset.get_full_sequence()
  • StaticDataset
    • StaticDataset.collate_fn()
    • StaticDataset.get_full_batch()
  • batch_tensor()
  • denormalize_01()
  • denormalize_11()
  • destandardize()
  • get_sequence_dataloaders()
  • get_static_dataloaders()
  • normalize_01()
  • normalize_11()
  • normalize_data()
  • read_file()
  • split_sequence_data()
  • split_static_data()
  • standardize()
  • unbatch_tensor()
• neuromancer.gradients module
  • gradient()
  • jacobian()
• neuromancer.loggers module
  • BasicLogger
    • BasicLogger.clean_up()
    • BasicLogger.log_artifacts()
    • BasicLogger.log_metrics()
    • BasicLogger.log_parameters()
    • BasicLogger.log_weights()
  • LossLogger
    • LossLogger.get_losses()
    • LossLogger.log_metrics()
  • MLFlowLogger
    • MLFlowLogger.clean_up()
    • MLFlowLogger.log_artifacts()
    • MLFlowLogger.log_metrics()
    • MLFlowLogger.log_parameters()
    • MLFlowLogger.log_weights()
• neuromancer.loss module
  • AggregateLoss
    • AggregateLoss.calculate_constraints()
    • AggregateLoss.calculate_objectives()
    • AggregateLoss.forward()
  • AugmentedLagrangeLoss
    • AugmentedLagrangeLoss.forward()
  • BarrierLoss
    • BarrierLoss.calculate_constraints()
  • PenaltyLoss
    • PenaltyLoss.forward()
  • get_loss()
• neuromancer.plot module
  • Animator
    • Animator.find_mat()
    • Animator.make_and_save()
  • Visualizer
    • Visualizer.eval()
    • Visualizer.train_output()
    • Visualizer.train_plot()
  • VisualizerClosedLoop
    • VisualizerClosedLoop.eval()
    • VisualizerClosedLoop.plot_matrix()
  • VisualizerDobleIntegrator
    • VisualizerDobleIntegrator.eval()
    • VisualizerDobleIntegrator.train_output()
  • VisualizerOpen
    • VisualizerOpen.eval()
    • VisualizerOpen.plot_matrix()
    • VisualizerOpen.plot_traj()
    • VisualizerOpen.train_output()
    • VisualizerOpen.train_plot()
  • VisualizerTrajectories
    • VisualizerTrajectories.eval()
  • VisualizerUncertaintyOpen
    • VisualizerUncertaintyOpen.eval()
    • VisualizerUncertaintyOpen.plot_traj()
  • cl_simulate()
  • get_colors()
  • plot_cl()
  • plot_cl_train()
  • plot_loss_DPC()
  • plot_loss_mpp()
  • plot_matrices()
  • plot_model_graph()
  • plot_policy()
  • plot_policy_train()
  • plot_solution_mpp()
  • plot_traj()
  • plot_trajectories()
  • pltCL()
  • pltCorrelate()
  • pltOL()
  • pltPhase()
  • pltRecurrence()
  • trajectory_movie()
• neuromancer.problem module
  • LitProblem
    • LitProblem.configure_optimizers()
    • LitProblem.expected_signatures
    • LitProblem.get_problem()
    • LitProblem.on_train_epoch_end()
    • LitProblem.training_step()
    • LitProblem.validation_step()
  • Problem
    • Problem.forward()
    • Problem.freeze()
    • Problem.graph()
    • Problem.show()
    • Problem.step()
    • Problem.unfreeze()
• neuromancer.system module
  • MovingHorizon
    • MovingHorizon.forward()
  • Node
    • Node.forward()
    • Node.freeze()
    • Node.unfreeze()
  • System
    • System.cat()
    • System.forward()
    • System.freeze()
    • System.graph()
    • System.init()
    • System.show()
    • System.unfreeze()
• neuromancer.trainer module
  • CustomEarlyStopping
  • LitTrainer
    • LitTrainer.apply_custom_hooks()
    • LitTrainer.fit()
    • LitTrainer.get_weights()
  • Trainer
    • Trainer.evaluate()
    • Trainer.test()
    • Trainer.train()
  • move_batch_to_device()
• neuromancer.utils module
  • handle_device_placement()
  • load_state_dict_lightning()

Module contents