From 8c9981cf74c8b7be8fdbaad7138798438227ab98 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Fri, 8 Mar 2024 16:45:57 +0000 Subject: [PATCH 01/20] Miscellaneous fixes --- mlptrain/config.py | 2 +- mlptrain/training/active.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/mlptrain/config.py b/mlptrain/config.py index 9ef1d26f..a65aaffe 100644 --- a/mlptrain/config.py +++ b/mlptrain/config.py @@ -48,7 +48,7 @@ class _ConfigClass: 'forces_weight': 5.0, 'hidden_irreps': '128x0e + 128x1o', 'batch_size': 10, - 'r_max': 5, + 'r_max': 5.0, 'correlation': 3, 'device': mace_device, 'calc_device': 'cpu', diff --git a/mlptrain/training/active.py b/mlptrain/training/active.py index bfafa362..441d7833 100644 --- a/mlptrain/training/active.py +++ b/mlptrain/training/active.py @@ -405,7 +405,7 @@ def _gen_active_config( mlp=mlp, temp=temp if curr_time > 0 else i_temp, dt=0.5, - interval=max(1, 2 * md_time // selector.n_backtrack), + interval=int(max(1, 2 * md_time // selector.n_backtrack)), fs=md_time, n_cores=1, **kwargs, @@ -416,7 +416,7 @@ def _gen_active_config( mlp=mlp, temp=temp if curr_time > 0 else i_temp, dt=0.5, - interval=max(1, 2 * md_time // selector.n_backtrack), + interval=int(max(1, 2 * md_time // selector.n_backtrack)), fs=md_time, n_cores=1, **kwargs, From 1f88323cca4fbe3ee45668fc2e1e3eea65a7a048 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Fri, 8 Mar 2024 16:46:42 +0000 Subject: [PATCH 02/20] Updated environment_mace.yml --- environment_mace.yml | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/environment_mace.yml b/environment_mace.yml index aaac7b78..2ae824b1 100644 --- a/environment_mace.yml +++ b/environment_mace.yml @@ -20,9 +20,11 @@ dependencies: - scipy - xtb - scikit-learn + - openmm + - openmm-torch + - nnpops # MACE dependencies - pytorch=2.0 - - openmm-torch=1.1 - torchvision - torchaudio - torch-ema @@ -32,10 +34,6 @@ dependencies: # - pytorch-cuda=11.8 # - pytorch-cuda=12.1 - pip: - # e3nn is available on conda as well, but it is a dependency of mace - # so needs to be installed together. - - e3nn - - mace@git+https://github.com/ACEsuit/mace.git@v0.2.0 - # The upstream PR to openmm-ml has not been merged yet: https://github.com/openmm/openmm-ml/pull/61) - - openmmml@git+https://github.com/sef43/openmm-ml.git@mace + - mace-torch + - openmmml@git+https://github.com/openmm/openmm-ml.git@main - ase@git+https://gitlab.com/ase/ase.git@f2615a6e9a # For PLUMED From 27f9f72e8b8f62ab42be93cdc3b5e410e0e697fb Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Fri, 8 Mar 2024 16:47:54 +0000 Subject: [PATCH 03/20] Refactored md_openmm.py --- mlptrain/sampling/md_openmm.py | 438 +++++++++++++++++++++++---------- 1 file changed, 309 insertions(+), 129 deletions(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 0213c964..89385383 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -1,7 +1,36 @@ -import copy -from typing import Optional, Sequence, List +import os +from copy import deepcopy +from typing import List, Optional, Sequence, Union + +import ase +import numpy as np import mlptrain as mlt +from mlptrain.log import logger +from mlptrain.sampling.md import ( + _convert_ase_traj, + _get_traj_name, + _initialise_traj, + _n_simulation_steps, + _save_trajectory, + _traj_saving_interval, +) + +try: + import openmm as mm + import openmm.app as app + import openmm.unit as unit + + _HAS_OPENMM = True +except ImportError: + _HAS_OPENMM = False + +try: + from openmmml import MLPotential + + _HAS_OPENMM_ML = True +except ImportError: + _HAS_OPENMM_ML = False def run_mlp_md_openmm( @@ -13,7 +42,7 @@ def run_mlp_md_openmm( init_temp: Optional[float] = None, fbond_energy: Optional[dict] = None, bbond_energy: Optional[dict] = None, - bias: Optional = None, + bias: Optional[Union['mlt.Bias', 'mlt.PlumedBias']] = None, restart_files: Optional[List[str]] = None, copied_substrings: Optional[Sequence[str]] = None, kept_substrings: Optional[Sequence[str]] = None, @@ -80,16 +109,17 @@ def run_mlp_md_openmm( (mlt.Trajectory): """ - - restart = restart_files is not None - - # TODO: Implement this! - if copied_substrings is not None: + if ( + fbond_energy is not None + or bbond_energy is not None + or bias is not None + ): + # TODO: Implement bias and other types of constraints. raise NotImplementedError( - 'copied_substrings argument not supported yet' + 'fbond_energy, bbond_energy and bias arguments not supported yet' ) - if kept_substrings is not None: - raise NotImplementedError('kept_substrings argument not supported yet') + + restart = restart_files is not None if copied_substrings is None: copied_substrings = [] @@ -97,14 +127,15 @@ def run_mlp_md_openmm( kept_substrings = [] copied_substrings_list = list(copied_substrings) - # kept_substrings_list = list(kept_substrings) + kept_substrings_list = list(kept_substrings) - copied_substrings_list.extend(['.xml', '.json', '.pth', '.model']) + copied_substrings_list.extend( + ['.state.xml', '.xml', '.json', '.pth', '.model'] + ) if restart: - msg = 'Restarting MLP MD with OpenMM not supported' - raise NotImplementedError(msg) - """ + logger.info('Restarting MLP OpenMM MD') + if not isinstance(restart_files, list): raise TypeError('Restart files must be a list') @@ -115,24 +146,29 @@ def run_mlp_md_openmm( 'specifying filenames' ) + if not any(file.endswith('.state.xml') for file in restart_files): + raise ValueError( + 'Restaring an OpenMM simulation requires a .state.xml file ' + 'from the previous simulation' + ) + if not any(file.endswith('.traj') for file in restart_files): raise ValueError( - 'Restaring a simulation requires a .traj file ' + 'Restaring an OpenMM simulation requires a .traj file ' 'from the previous simulation' ) copied_substrings_list.extend(restart_files) kept_substrings_list.extend(restart_files) - """ - - mlt.log.logger.info('Running MLP MD with OpenMM') + else: + logger.info('Running MLP MD with OpenMM') traj_openmm = _run_mlp_md_openmm( configuration=configuration, mlp=mlp, temp=temp, dt=dt, - interval=interval, + interval=interval, init_temp=init_temp, fbond_energy=fbond_energy, bbond_energy=bbond_energy, @@ -144,41 +180,6 @@ def run_mlp_md_openmm( return traj_openmm -# TODO: This function is already defined in md.py! -def _n_simulation_steps(dt: float, kwargs: dict) -> int: - """ - Calculate the number of simulation steps from a set of keyword - arguments e.g. kwargs = {'fs': 100} - - --------------------------------------------------------------------------- - Arguments: - dt: Timestep in fs - - Returns: - (int): Number of simulation steps to perform - """ - if dt < 0.09 or dt > 5: - mlt.log.logger.warning( - 'Unexpectedly small or large timestep - is it in fs?' - ) - - if 'ps' in kwargs: - time_fs = 1e3 * kwargs['ps'] - - elif 'fs' in kwargs: - time_fs = kwargs['fs'] - - elif 'ns' in kwargs: - time_fs = 1e6 * kwargs['ns'] - - else: - raise ValueError('Simulation time not found') - - n_steps = max(int(time_fs / dt), 1) # Run at least one step - - return n_steps - - def _run_mlp_md_openmm( configuration: 'mlt.Configuration', mlp: 'mlt.potentials._base.MLPotential', @@ -188,7 +189,7 @@ def _run_mlp_md_openmm( init_temp: Optional[float] = None, fbond_energy: Optional[dict] = None, bbond_energy: Optional[dict] = None, - bias: Optional = None, + bias: Optional[Union['mlt.Bias', 'mlt.PlumedBias']] = None, restart_files: Optional[List[str]] = None, **kwargs, ) -> 'mlt.Trajectory': @@ -196,123 +197,302 @@ def _run_mlp_md_openmm( Run molecular dynamics on a system using a MLP to predict energies and forces and OpenMM to drive dynamics """ + restart = restart_files is not None - try: - import openmm as mm - import openmm.app as app - import openmm.unit as unit - except ImportError: + if not _HAS_OPENMM: raise ImportError( - 'Cannot import OpenMM. Please make sure OpenMM is installed.' + 'OpenMM is not installed. Install it with ' + "'conda install -c conda-forge openmm'" ) - try: - from openmmml import MLPotential - except ImportError: - raise ImportError('Cannot import OpenMM-ML') - - from sys import stdout + if not _HAS_OPENMM_ML: + raise ImportError( + 'openmm-ml is not installed. Install it with ' + "'conda install -c conda-forge openmm-ml'" + ) + # Calculate the number of steps to perform. n_steps = _n_simulation_steps(dt=dt, kwargs=kwargs) + # Set the box size if required if mlp.requires_non_zero_box_size and configuration.box is None: - mlt.log.logger.warning( - 'Assuming vaccum simulation. Box size = 1000 nm^3' - ) + logger.warning('Assuming vaccum simulation. Box size = 1000 nm^3') configuration.box = mlt.Box([100, 100, 100]) + # Get the ASE atoms object and positions. ase_atoms = configuration.ase_atoms - # create OpenMM topology - topology = app.Topology() - chain = topology.addChain() + # Get the name of the trajectory and simulation state files. + traj_name = _get_traj_name(restart_files=restart_files, **kwargs) + simulation_name = _get_simulation_name( + restart_files=restart_files, **kwargs + ) - positions = ase_atoms.get_positions() * unit.angstrom - atomic_numbers = ase_atoms.get_atomic_numbers() + # Create the OpenMM topology + topology = _create_openmm_topology(ase_atoms) - for atomic_number in atomic_numbers: - residue = topology.addResidue(name='X', chain=chain) - element = app.Element.getByAtomicNumber(atomic_number) - topology.addAtom(element.name, element, residue) + # Create the OpenMM simulation object + simulation = _create_openmm_simulation( + mlp=mlp, + topology=topology, + temp=temp, + dt=dt, + ) - # use the mace model with openmm-ml - # make sure total energy is used - potential = MLPotential('mace', model_path=mlp.filename) - system = potential.createSystem(topology, interaction_energy=False) + # Set the initial positions and velocities + _set_momenta_and_geometry( + simulation=simulation, + positions=ase_atoms.get_positions() * unit.angstrom, + temp=init_temp if init_temp is not None else temp, + restart_file=simulation_name if restart else None, + ) - # setup OpenMM simulation with Langevin dynamics - integrator = mm.LangevinIntegrator( - 300 * unit.kelvin, 1.0 / unit.picoseconds, dt * unit.femtoseconds + ase_traj = _initialise_traj( + ase_atoms=ase_atoms, restart=restart, traj_name=traj_name ) - simulation = app.Simulation(topology, system, integrator) - simulation.context.setPositions(positions) - simulation.context.setVelocitiesToTemperature(temp * unit.kelvin) - interval = int(interval) + # If MD is restarted, energies of frames from the previous trajectory + # are not loaded. Setting them to None + energies = [None for _ in range(len(ase_traj))] + biased_energies = deepcopy(energies) + bias_energies = deepcopy(energies) + # Calculate the number of steps already performed. + """ + n_previous_steps = interval * len(ase_traj) + + simulation.reporters.append( app.StateDataReporter( stdout, - interval, + int(interval), step=True, potentialEnergy=True, temperature=True, speed=True, ) ) + """ + logger.info( + f'Running using OpenMM for {n_steps} steps with saving interval {interval}' + ) + + # Run the dynamics + _run_dynamics( + simulation=simulation, + simulation_name=simulation_name, + ase_atoms=ase_atoms, + ase_traj=ase_traj, + traj_name=traj_name, + dt=dt, + interval=interval, + n_steps=n_steps, + energies=energies, + biased_energies=biased_energies, + **kwargs, + ) + + # Close the ASE trajectory + ase_traj.close() + + # Duplicate frames removed only if PLUMED bias is initialised not from file + # if restart and isinstance(bias, PlumedBias) and not bias.from_file: + # _remove_colvar_duplicate_frames(bias=bias, **kwargs) + + traj = _convert_ase_traj(traj_name=traj_name, bias=bias, **kwargs) + + for energy, biased_energy in zip(energies, biased_energies): + if energy is not None and biased_energy is not None: + bias_energy = biased_energy - energy + bias_energies.append(bias_energy) + + for i, (frame, energy, bias_energy) in enumerate( + zip(traj, energies, bias_energies) + ): + frame.update_attr_from(configuration) + frame.energy.predicted = energy + frame.energy.bias = bias_energy + frame.time = dt * interval * i + + return traj + + +# ============================================================================= # +# Functions for running the OpenMM MD simulation # +# ============================================================================= # +def _create_openmm_topology(ase_atoms: ase.Atoms) -> app.Topology: + """Create an OpenMM topology from an ASE atoms object.""" + logger.info('Creating the OpenMM topology') + topology = app.Topology() + chain = topology.addChain() + + atomic_numbers = ase_atoms.get_atomic_numbers() + + for atomic_number in atomic_numbers: + residue = topology.addResidue(name='X', chain=chain) + element = app.Element.getByAtomicNumber(atomic_number) + topology.addAtom(element.name, element, residue) + + return topology + + +def _create_openmm_simulation( + mlp: 'mlt.potentials._base.MLPotential', + topology: app.Topology, + temp: float, + dt: float, +) -> app.Simulation: + """Create an OpenMM simulation object.""" + logger.info('Creating the OpenMM simulation object') + + # Use the mace model with openmm-ml and make sure the total energy is used. + potential = MLPotential('mace', modelPath=mlp.filename) + system = potential.createSystem(topology, returnEnergyType='energy') + + # Use a Langevin integrator if temp>0 (NVT ensemble). + # Otherwise, use a Verlet integrator (NVE ensemble). + if temp > 0: + logger.info(f'Using Langevin integrator as temperture is {temp} K') + integrator = mm.LangevinMiddleIntegrator( + temp * unit.kelvin, 1.0 / unit.picoseconds, dt * unit.femtoseconds + ) + else: + logger.info(f'Using Verlet integrator as temperture is {temp} K') + integrator = mm.VerletIntegrator(dt * unit.femtoseconds) + + # TODO: Add platform + simulation = app.Simulation(topology, system, integrator) - # create MLP train trajectory to save frames into + return simulation - mlt_traj = mlt.Trajectory() - mlt.log.logger.info( - 'Running using OpenMM for ', - n_steps, - ' steps with saving interval', - interval, +def _set_momenta_and_geometry( + simulation: app.Simulation, + positions: unit.Quantity, + temp: float, + restart_file: Optional[str] = None, +) -> app.Simulation: + """Set the momenta and geometry for the OpenMM simulation.""" + + if restart_file is not None: + if os.path.isfile(restart_file): + logger.info( + f'Restarting the OpenMM simulation state from file {restart_file}' + ) + simulation.loadState(restart_file) + else: + raise FileNotFoundError(f'File {restart_file} not found') + else: + logger.info( + 'Setting the initial momenta and geometry for the OpenMM simulation' + ) + simulation.context.setPositions(positions) + simulation.context.setVelocitiesToTemperature(temp * unit.kelvin) + + return simulation + + +def _get_simulation_name( + restart_files: Optional[List[str]] = None, **kwargs +) -> str: + """Return the name of the OpenMM simulation to be created or restarted.""" + if restart_files is None: + if 'idx' in kwargs: + simulation_name = f'simulation_{kwargs["idx"]}.state.xml' + else: + simulation_name = 'simulation.state.xml' + + return simulation_name + else: + for filename in restart_files: + if filename.endswith('.state.xml'): + return filename + + raise FileNotFoundError( + 'Restart mode detected, but no simulation state files were found in restart_files. ' ) - # add the first config using energies from current MLP - state = simulation.context.getState(getPositions=True, getEnergy=True) - coordinates = state.getPositions(asNumpy=True).value_in_unit(unit.angstrom) - energy = state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) +def _run_dynamics( + simulation: app.Simulation, + simulation_name: str, + ase_atoms: ase.Atoms, + ase_traj: ase.io.trajectory.Trajectory, + traj_name: str, + dt: float, + interval: int, + n_steps: int, + energies: List[Optional[float]], + biased_energies: List[Optional[float]], + **kwargs, +) -> None: + """Run the MD and save frames to the mlt.Trajectory.""" + + def append_unbiased_energy(): + energies.append(energy) - config = mlt.Configuration() - config.atoms = copy.deepcopy(configuration.atoms) - config.box = copy.deepcopy(configuration.box) + def append_biased_energy(): + # TODO: Implement this when bias is implemented + biased_energies.append(biased_energy) - for i, position in enumerate(coordinates): - config.atoms[i].coord = position + def save_trajectory(): + _save_trajectory(ase_traj, traj_name, **kwargs) - config.energy.predicted = energy / 96.48530749925793 # kj/mol -> eV - config.time = 0.0 + def save_simulation_state(): + simulation.saveState(simulation_name) - mlt_traj.append(config) + # Determine saving intervals + if any(key in kwargs for key in ['save_fs', 'save_ps', 'save_ns']): + traj_saving_interval = _traj_saving_interval(kwargs) + else: + traj_saving_interval = 0 - # now run for n_steps saving at every interval + # Run the dynamics n_steps, performing interval steps at a time. for j in range(n_steps // interval): + logger.info(f'Step {j + 1} / {n_steps // interval}') simulation.step(interval) + time = dt * interval * (j + 1) - state = simulation.context.getState(getPositions=True, getEnergy=True) - - coordinates = state.getPositions(asNumpy=True).value_in_unit( - unit.angstrom - ) - energy = state.getPotentialEnergy().value_in_unit( - unit.kilojoules_per_mole + # Add frame to the ASE trajectory, and save energies and trajectory. + coordinates, energy, biased_energy = _get_coordinates_energy( + simulation ) - config = mlt.Configuration() - config.atoms = copy.deepcopy(configuration.atoms) - config.box = copy.deepcopy(configuration.box) + _add_frame_to_ase_traj(coordinates, energy, ase_atoms, ase_traj) + append_unbiased_energy() + append_biased_energy() + save_simulation_state() - for i, position in enumerate(coordinates): - config.atoms[i].coord = position + if traj_saving_interval > 0 and time % traj_saving_interval == 0: + save_trajectory() - config.energy.predicted = energy / 96.48530749925793 # kJ/mol -> eV - config.time = dt * interval * (j + 1) - mlt_traj.append(config) +def _get_coordinates_energy(simulation: app.Simulation) -> tuple: + """Get the coordinates and energy of the system from the OpenMM simulation.""" + state = simulation.context.getState(getPositions=True, getEnergy=True) + coordinates = state.getPositions(asNumpy=True).value_in_unit(unit.angstrom) + energy = state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) + energy *= 0.01036427230133138 # kilojoules_per_mole_to_eV + biased_energy = energy # TODO: Implement this when bias is implemented + + return coordinates, energy, biased_energy + + +def _add_frame_to_ase_traj( + coordinates: 'np.ndarray', + potential_energy: float, + ase_atoms: ase.Atoms, + ase_traj: ase.io.trajectory.Trajectory, +) -> ase.io.trajectory.Trajectory: + """Add a new frame to the ASE train trajectory""" + # Create a new ASE atoms object. + new_ase_atoms = ase.Atoms( + symbols=ase_atoms.get_chemical_symbols(), + positions=coordinates, + cell=ase_atoms.get_cell(), + ) + + # Append the new frame to the trajectory. + ase_traj.write(new_ase_atoms, energy=potential_energy) - return mlt_traj + return ase_traj From c573cc5604a9cf8d0ef5d2cfa5d6886adc1b06f7 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 16:05:45 +0000 Subject: [PATCH 04/20] Added quotes to type hints --- mlptrain/sampling/md_openmm.py | 25 ++++++++++++------------- 1 file changed, 12 insertions(+), 13 deletions(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 89385383..6d4506c3 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -320,7 +320,7 @@ def _run_mlp_md_openmm( # ============================================================================= # # Functions for running the OpenMM MD simulation # # ============================================================================= # -def _create_openmm_topology(ase_atoms: ase.Atoms) -> app.Topology: +def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': """Create an OpenMM topology from an ASE atoms object.""" logger.info('Creating the OpenMM topology') topology = app.Topology() @@ -338,10 +338,10 @@ def _create_openmm_topology(ase_atoms: ase.Atoms) -> app.Topology: def _create_openmm_simulation( mlp: 'mlt.potentials._base.MLPotential', - topology: app.Topology, + topology: 'app.Topology', temp: float, dt: float, -) -> app.Simulation: +) -> 'app.Simulation': """Create an OpenMM simulation object.""" logger.info('Creating the OpenMM simulation object') @@ -367,8 +367,8 @@ def _create_openmm_simulation( def _set_momenta_and_geometry( - simulation: app.Simulation, - positions: unit.Quantity, + simulation: 'app.Simulation', + positions: 'unit.Quantity', temp: float, restart_file: Optional[str] = None, ) -> app.Simulation: @@ -414,10 +414,10 @@ def _get_simulation_name( def _run_dynamics( - simulation: app.Simulation, + simulation: 'app.Simulation', simulation_name: str, - ase_atoms: ase.Atoms, - ase_traj: ase.io.trajectory.Trajectory, + ase_atoms: 'ase.Atoms', + ase_traj: 'ase.io.trajectory.Trajectory', traj_name: str, dt: float, interval: int, @@ -432,7 +432,6 @@ def append_unbiased_energy(): energies.append(energy) def append_biased_energy(): - # TODO: Implement this when bias is implemented biased_energies.append(biased_energy) def save_trajectory(): @@ -467,7 +466,7 @@ def save_simulation_state(): save_trajectory() -def _get_coordinates_energy(simulation: app.Simulation) -> tuple: +def _get_coordinates_energy(simulation: 'app.Simulation') -> tuple: """Get the coordinates and energy of the system from the OpenMM simulation.""" state = simulation.context.getState(getPositions=True, getEnergy=True) coordinates = state.getPositions(asNumpy=True).value_in_unit(unit.angstrom) @@ -481,9 +480,9 @@ def _get_coordinates_energy(simulation: app.Simulation) -> tuple: def _add_frame_to_ase_traj( coordinates: 'np.ndarray', potential_energy: float, - ase_atoms: ase.Atoms, - ase_traj: ase.io.trajectory.Trajectory, -) -> ase.io.trajectory.Trajectory: + ase_atoms: 'ase.Atoms', + ase_traj: 'ase.io.trajectory.Trajectory', +) -> 'ase.io.trajectory.Trajectory': """Add a new frame to the ASE train trajectory""" # Create a new ASE atoms object. new_ase_atoms = ase.Atoms( From 45845edc1c92af98464b2f43935219c6ebf11290 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 16:06:51 +0000 Subject: [PATCH 05/20] Fixed issues with pre-commit hooks --- mlptrain/sampling/md_openmm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 6d4506c3..000d10ba 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -168,7 +168,7 @@ def run_mlp_md_openmm( mlp=mlp, temp=temp, dt=dt, - interval=interval, + interval=interval, init_temp=init_temp, fbond_energy=fbond_energy, bbond_energy=bbond_energy, From 5e532b7d7e587f0808634a40153997a0d876a594 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 17:18:53 +0000 Subject: [PATCH 06/20] Added option to select OpenMM Platform to use --- mlptrain/sampling/md_openmm.py | 129 ++++++++++++++++++++++----------- 1 file changed, 85 insertions(+), 44 deletions(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 000d10ba..69135599 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -3,7 +3,6 @@ from typing import List, Optional, Sequence, Union import ase -import numpy as np import mlptrain as mlt from mlptrain.log import logger @@ -32,6 +31,9 @@ except ImportError: _HAS_OPENMM_ML = False +# Conversion factor from kJ/mol to eV +_KJ_PER_MOL_TO_EV = ase.units.eV / (ase.units.kJ / ase.units.mol) + def run_mlp_md_openmm( configuration: 'mlt.Configuration', @@ -46,6 +48,7 @@ def run_mlp_md_openmm( restart_files: Optional[List[str]] = None, copied_substrings: Optional[Sequence[str]] = None, kept_substrings: Optional[Sequence[str]] = None, + platform: Optional[str] = None, **kwargs, ) -> 'mlt.Trajectory': """ @@ -92,6 +95,9 @@ def run_mlp_md_openmm( copied_substrings: List of substrings with which files are copied to the temporary directory. Files required for MLPs are added to the list automatically + + platform: (str) OpenMM platform to use. If None, the fastest available + platform is used in this order: 'CUDA', 'OpenCL', 'CPU', 'Reference'. --------------- Keyword Arguments: @@ -174,6 +180,7 @@ def run_mlp_md_openmm( bbond_energy=bbond_energy, bias=bias, restart_files=restart_files, + platform=platform, **kwargs, ) @@ -191,6 +198,7 @@ def _run_mlp_md_openmm( bbond_energy: Optional[dict] = None, bias: Optional[Union['mlt.Bias', 'mlt.PlumedBias']] = None, restart_files: Optional[List[str]] = None, + platform: Optional[str] = None, **kwargs, ) -> 'mlt.Trajectory': """ @@ -216,7 +224,7 @@ def _run_mlp_md_openmm( # Set the box size if required if mlp.requires_non_zero_box_size and configuration.box is None: - logger.warning('Assuming vaccum simulation. Box size = 1000 nm^3') + logger.warning('Assuming vacuum simulation. Box size = 1000 nm^3') configuration.box = mlt.Box([100, 100, 100]) # Get the ASE atoms object and positions. @@ -231,12 +239,16 @@ def _run_mlp_md_openmm( # Create the OpenMM topology topology = _create_openmm_topology(ase_atoms) + # Get the OpenMM platform + platform = _get_openmm_platform(platform) + # Create the OpenMM simulation object simulation = _create_openmm_simulation( mlp=mlp, topology=topology, temp=temp, dt=dt, + platform=platform, ) # Set the initial positions and velocities @@ -274,7 +286,7 @@ def _run_mlp_md_openmm( ) """ logger.info( - f'Running using OpenMM for {n_steps} steps with saving interval {interval}' + f'Running OpenMM simulation for {n_steps} steps with saving interval {interval}' ) # Run the dynamics @@ -318,7 +330,7 @@ def _run_mlp_md_openmm( # ============================================================================= # -# Functions for running the OpenMM MD simulation # +# Auxiliary functions to create the OpenMM Simulation # # ============================================================================= # def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': """Create an OpenMM topology from an ASE atoms object.""" @@ -336,11 +348,41 @@ def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': return topology +def _get_openmm_platform(platform: Optional[str]) -> 'mm.Platform': + """Get the OpenMM platform to use.""" + available_platforms = [ + mm.Platform.getPlatform(i).getName() + for i in range(mm.Platform.getNumPlatforms()) + ] + + if platform is not None and platform in available_platforms: + platform = mm.Platform.getPlatformByName(platform) + else: + platform = next( + ( + p + for p in ['CUDA', 'OpenCL', 'CPU', 'Reference'] + if p in available_platforms + ), + None, + ) + if platform is None: + raise ValueError( + f'No suitable platform found. Available platforms are: {available_platforms}' + ) + platform = mm.Platform.getPlatformByName(platform) + + logger.info(f'Using the OpenMM platform: {platform.getName()}') + + return platform + + def _create_openmm_simulation( mlp: 'mlt.potentials._base.MLPotential', topology: 'app.Topology', temp: float, dt: float, + platform: 'mm.Platform', ) -> 'app.Simulation': """Create an OpenMM simulation object.""" logger.info('Creating the OpenMM simulation object') @@ -352,16 +394,17 @@ def _create_openmm_simulation( # Use a Langevin integrator if temp>0 (NVT ensemble). # Otherwise, use a Verlet integrator (NVE ensemble). if temp > 0: - logger.info(f'Using Langevin integrator as temperture is {temp} K') + logger.info( + f'Using Langevin integrator (NVT) with temperture={temp} K' + ) integrator = mm.LangevinMiddleIntegrator( temp * unit.kelvin, 1.0 / unit.picoseconds, dt * unit.femtoseconds ) else: - logger.info(f'Using Verlet integrator as temperture is {temp} K') + logger.info(f'Using Verlet integrator (NVE) as temperture is {temp} K') integrator = mm.VerletIntegrator(dt * unit.femtoseconds) - # TODO: Add platform - simulation = app.Simulation(topology, system, integrator) + simulation = app.Simulation(topology, system, integrator, platform) return simulation @@ -413,6 +456,9 @@ def _get_simulation_name( ) +# ============================================================================= # +# Auxiliary functions to run the OpenMM Simulation # +# ============================================================================= # def _run_dynamics( simulation: 'app.Simulation', simulation_name: str, @@ -429,17 +475,33 @@ def _run_dynamics( """Run the MD and save frames to the mlt.Trajectory.""" def append_unbiased_energy(): - energies.append(energy) + """Append the unbiased potential energy to the energies list.""" + energies.append(potential_energy) def append_biased_energy(): + """Append the biased potential energy to the biased_energies list.""" biased_energies.append(biased_energy) def save_trajectory(): + """Save the ASE trajectory to a file.""" _save_trajectory(ase_traj, traj_name, **kwargs) def save_simulation_state(): + """Save the state of the OpenMM simulation.""" simulation.saveState(simulation_name) + def _add_frame_to_ase_traj(): + """Add a new frame to the ASE train trajectory""" + # Create a new ASE atoms object. + new_ase_atoms = ase.Atoms( + symbols=ase_atoms.get_chemical_symbols(), + positions=coordinates, + cell=ase_atoms.get_cell(), + ) + + # Append the new frame to the trajectory. + ase_traj.write(new_ase_atoms, energy=potential_energy) + # Determine saving intervals if any(key in kwargs for key in ['save_fs', 'save_ps', 'save_ns']): traj_saving_interval = _traj_saving_interval(kwargs) @@ -452,46 +514,25 @@ def save_simulation_state(): simulation.step(interval) time = dt * interval * (j + 1) - # Add frame to the ASE trajectory, and save energies and trajectory. - coordinates, energy, biased_energy = _get_coordinates_energy( - simulation + # Get the coordinates and energy of the system from the OpenMM simulation. + state = simulation.context.getState(getPositions=True, getEnergy=True) + coordinates = state.getPositions(asNumpy=True).value_in_unit( + unit.angstrom + ) + potential_energy = ( + state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) + * _KJ_PER_MOL_TO_EV ) + # TODO: Implement biased_energy when bias is implemented + biased_energy = potential_energy - _add_frame_to_ase_traj(coordinates, energy, ase_atoms, ase_traj) + # Add the frame to the ASE trajectory. + _add_frame_to_ase_traj() + + # Store the energies append_unbiased_energy() append_biased_energy() save_simulation_state() if traj_saving_interval > 0 and time % traj_saving_interval == 0: save_trajectory() - - -def _get_coordinates_energy(simulation: 'app.Simulation') -> tuple: - """Get the coordinates and energy of the system from the OpenMM simulation.""" - state = simulation.context.getState(getPositions=True, getEnergy=True) - coordinates = state.getPositions(asNumpy=True).value_in_unit(unit.angstrom) - energy = state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) - energy *= 0.01036427230133138 # kilojoules_per_mole_to_eV - biased_energy = energy # TODO: Implement this when bias is implemented - - return coordinates, energy, biased_energy - - -def _add_frame_to_ase_traj( - coordinates: 'np.ndarray', - potential_energy: float, - ase_atoms: 'ase.Atoms', - ase_traj: 'ase.io.trajectory.Trajectory', -) -> 'ase.io.trajectory.Trajectory': - """Add a new frame to the ASE train trajectory""" - # Create a new ASE atoms object. - new_ase_atoms = ase.Atoms( - symbols=ase_atoms.get_chemical_symbols(), - positions=coordinates, - cell=ase_atoms.get_cell(), - ) - - # Append the new frame to the trajectory. - ase_traj.write(new_ase_atoms, energy=potential_energy) - - return ase_traj From 75d04e97133cdc60a779207f3e8153faba16c57f Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 17:38:55 +0000 Subject: [PATCH 07/20] Decorated _run_mlp_md_openmm so that it runs in a temp dir --- mlptrain/sampling/md_openmm.py | 20 +++++++++++++------- 1 file changed, 13 insertions(+), 7 deletions(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 69135599..38461996 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -6,6 +6,7 @@ import mlptrain as mlt from mlptrain.log import logger +from mlptrain.utils import work_in_tmp_dir from mlptrain.sampling.md import ( _convert_ase_traj, _get_traj_name, @@ -32,7 +33,7 @@ _HAS_OPENMM_ML = False # Conversion factor from kJ/mol to eV -_KJ_PER_MOL_TO_EV = ase.units.eV / (ase.units.kJ / ase.units.mol) +_KJ_PER_MOL_TO_EV = (ase.units.kJ / ase.units.mol) / ase.units.eV def run_mlp_md_openmm( @@ -135,9 +136,7 @@ def run_mlp_md_openmm( copied_substrings_list = list(copied_substrings) kept_substrings_list = list(kept_substrings) - copied_substrings_list.extend( - ['.state.xml', '.xml', '.json', '.pth', '.model'] - ) + copied_substrings_list.extend(['.xml', '.json', '.pth', '.model']) if restart: logger.info('Restarting MLP OpenMM MD') @@ -169,7 +168,14 @@ def run_mlp_md_openmm( else: logger.info('Running MLP MD with OpenMM') - traj_openmm = _run_mlp_md_openmm( + decorator = work_in_tmp_dir( + copied_substrings=copied_substrings_list, + kept_substrings=kept_substrings_list, + ) + + _run_mlp_md_decorated = decorator(_run_mlp_md_openmm) + + traj = _run_mlp_md_decorated( configuration=configuration, mlp=mlp, temp=temp, @@ -183,8 +189,7 @@ def run_mlp_md_openmm( platform=platform, **kwargs, ) - - return traj_openmm + return traj def _run_mlp_md_openmm( @@ -523,6 +528,7 @@ def _add_frame_to_ase_traj(): state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) * _KJ_PER_MOL_TO_EV ) + # TODO: Implement biased_energy when bias is implemented biased_energy = potential_energy From 5c8912d4e4175ac63a59d1be41f945d0c5b4bd4a Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 18:49:22 +0000 Subject: [PATCH 08/20] Added restart of OpenMM simulation --- mlptrain/sampling/md.py | 13 ++++++++++--- mlptrain/sampling/md_openmm.py | 26 ++++++++++---------------- 2 files changed, 20 insertions(+), 19 deletions(-) diff --git a/mlptrain/sampling/md.py b/mlptrain/sampling/md.py index 2e8115bb..980435f9 100644 --- a/mlptrain/sampling/md.py +++ b/mlptrain/sampling/md.py @@ -557,7 +557,10 @@ def add_momenta(idx, vector, energy): def _initialise_traj( - ase_atoms: 'ase.atoms.Atoms', restart: bool, traj_name: str + ase_atoms: 'ase.atoms.Atoms', + restart: bool, + traj_name: str, + remove_last: bool = True, ) -> 'ase.io.trajectory.Trajectory': """Initialise ASE trajectory object""" @@ -565,9 +568,13 @@ def _initialise_traj( traj = ASETrajectory(traj_name, 'w', ase_atoms) else: - # Remove the last frame to avoid duplicate frames previous_traj = ASETrajectory(traj_name, 'r', ase_atoms) - previous_atoms = previous_traj[:-1] + + if remove_last: + # Remove the last frame to avoid duplicate frames + previous_atoms = previous_traj[:-1] + else: + previous_atoms = previous_traj os.remove(traj_name) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 38461996..9a67d5ec 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -87,7 +87,7 @@ def run_mlp_md_openmm( to use in the dynamics restart_files: List of files which are needed for restarting the - simulation + simulation, e.g. 'simulation.state.xml', 'trajectory.traj' kept_substrings: List of substrings with which files are copied back from the temporary directory @@ -264,8 +264,12 @@ def _run_mlp_md_openmm( restart_file=simulation_name if restart else None, ) + # Initialise the ASE trajectory with the last frame of the previous trajectory ase_traj = _initialise_traj( - ase_atoms=ase_atoms, restart=restart, traj_name=traj_name + ase_atoms=ase_atoms, + restart=restart, + traj_name=traj_name, + remove_last=False, ) # If MD is restarted, energies of frames from the previous trajectory @@ -275,21 +279,8 @@ def _run_mlp_md_openmm( bias_energies = deepcopy(energies) # Calculate the number of steps already performed. - """ n_previous_steps = interval * len(ase_traj) - - simulation.reporters.append( - app.StateDataReporter( - stdout, - int(interval), - step=True, - potentialEnergy=True, - temperature=True, - speed=True, - ) - ) - """ logger.info( f'Running OpenMM simulation for {n_steps} steps with saving interval {interval}' ) @@ -304,6 +295,7 @@ def _run_mlp_md_openmm( dt=dt, interval=interval, n_steps=n_steps, + n_previous_steps=n_previous_steps, energies=energies, biased_energies=biased_energies, **kwargs, @@ -473,6 +465,7 @@ def _run_dynamics( dt: float, interval: int, n_steps: int, + n_previous_steps: int, energies: List[Optional[float]], biased_energies: List[Optional[float]], **kwargs, @@ -514,7 +507,8 @@ def _add_frame_to_ase_traj(): traj_saving_interval = 0 # Run the dynamics n_steps, performing interval steps at a time. - for j in range(n_steps // interval): + + for j in range(n_previous_steps // interval, n_steps // interval): logger.info(f'Step {j + 1} / {n_steps // interval}') simulation.step(interval) time = dt * interval * (j + 1) From 36823cac6ac9d78a8df10dd01d22b5092e32bb2b Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Mon, 25 Mar 2024 18:58:14 +0000 Subject: [PATCH 09/20] Added quotes to type hints --- mlptrain/sampling/md_openmm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index 9a67d5ec..a90a58c0 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -411,7 +411,7 @@ def _set_momenta_and_geometry( positions: 'unit.Quantity', temp: float, restart_file: Optional[str] = None, -) -> app.Simulation: +) -> 'app.Simulation': """Set the momenta and geometry for the OpenMM simulation.""" if restart_file is not None: From ff4a503078794eb402ed9c7d921769fa58e45cea Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Tue, 2 Apr 2024 20:48:33 +0100 Subject: [PATCH 10/20] Removed packages from the dependencies to avoid conflicting builds --- environment_mace.yml | 12 +----------- 1 file changed, 1 insertion(+), 11 deletions(-) diff --git a/environment_mace.yml b/environment_mace.yml index 2ae824b1..d39c0dd2 100644 --- a/environment_mace.yml +++ b/environment_mace.yml @@ -23,17 +23,7 @@ dependencies: - openmm - openmm-torch - nnpops - # MACE dependencies - - pytorch=2.0 - - torchvision - - torchaudio - - torch-ema - # TODO: You might also need CUDA-specific libraries, - # but that depends on CUDA version - # https://pytorch.org/get-started/locally/ - # - pytorch-cuda=11.8 - # - pytorch-cuda=12.1 - pip: - - mace-torch - openmmml@git+https://github.com/openmm/openmm-ml.git@main - ase@git+https://gitlab.com/ase/ase.git@f2615a6e9a # For PLUMED + - mace-torch From a308887abe7e10181fba1d8b90fc5ac42b958436 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Tue, 2 Apr 2024 20:51:24 +0100 Subject: [PATCH 11/20] Remove CUDA from available_platform is a GPU is not available --- mlptrain/sampling/md_openmm.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index a90a58c0..eae769cb 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -347,11 +347,17 @@ def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': def _get_openmm_platform(platform: Optional[str]) -> 'mm.Platform': """Get the OpenMM platform to use.""" + import torch available_platforms = [ mm.Platform.getPlatform(i).getName() for i in range(mm.Platform.getNumPlatforms()) ] + # OpenMM might have been built with CUDA support + # but the current system might not have a GPU available (typical in clusters) + if 'CUDA' in available_platforms and not torch.cuda.is_available(): + available_platforms.remove('CUDA') + if platform is not None and platform in available_platforms: platform = mm.Platform.getPlatformByName(platform) else: From 236c21c5197ea852d3adf2530ed14678698b8192 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Tue, 2 Apr 2024 21:15:33 +0100 Subject: [PATCH 12/20] Fixed foreach argument (pytorch/pytorch#110940) --- mlptrain/potentials/mace/mace.py | 1 + 1 file changed, 1 insertion(+) diff --git a/mlptrain/potentials/mace/mace.py b/mlptrain/potentials/mace/mace.py index 56a0a938..a229acfe 100644 --- a/mlptrain/potentials/mace/mace.py +++ b/mlptrain/potentials/mace/mace.py @@ -690,6 +690,7 @@ def opt_param_options(self) -> Dict: ], lr=self.args.lr, amsgrad=Config.mace_params['amsgrad'], + foreach=False if torch.get_default_dtype() == torch.float64 else True, ) return param_options From 93fabdc9d1484d3cd41d38d1f3ece45da65712c4 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Tue, 2 Apr 2024 21:17:06 +0100 Subject: [PATCH 13/20] Ruff fixes --- mlptrain/potentials/mace/mace.py | 4 +++- mlptrain/sampling/md_openmm.py | 3 ++- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/mlptrain/potentials/mace/mace.py b/mlptrain/potentials/mace/mace.py index a229acfe..018690a3 100644 --- a/mlptrain/potentials/mace/mace.py +++ b/mlptrain/potentials/mace/mace.py @@ -690,7 +690,9 @@ def opt_param_options(self) -> Dict: ], lr=self.args.lr, amsgrad=Config.mace_params['amsgrad'], - foreach=False if torch.get_default_dtype() == torch.float64 else True, + foreach=False + if torch.get_default_dtype() == torch.float64 + else True, ) return param_options diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index eae769cb..f82001dc 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -348,12 +348,13 @@ def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': def _get_openmm_platform(platform: Optional[str]) -> 'mm.Platform': """Get the OpenMM platform to use.""" import torch + available_platforms = [ mm.Platform.getPlatform(i).getName() for i in range(mm.Platform.getNumPlatforms()) ] - # OpenMM might have been built with CUDA support + # OpenMM might have been built with CUDA support # but the current system might not have a GPU available (typical in clusters) if 'CUDA' in available_platforms and not torch.cuda.is_available(): available_platforms.remove('CUDA') From 801bdafabceab060037720fe05614d3976411aed Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Wed, 3 Apr 2024 10:06:21 +0100 Subject: [PATCH 14/20] Updated README.md --- README.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 31b2aca7..10bf131c 100644 --- a/README.md +++ b/README.md @@ -33,14 +33,19 @@ Each model is installed into individual conda environment: - Units are: distance (Å), energy (eV), force (eV Å$`^{-1}`$), time (fs) -## Using with OpenMM (Experimental!) +## Using with OpenMM The OpenMM backend only works with MACE at the moment. The necessary dependencies are installed automatically via conda: -```console +``` ./install_mace.sh ``` +Depending on your machine, you might need to prefix the command above with something like `CONDA_OVERRIDE_CUDA="11.2"` in two scenarios: + +- To ensure an environment that is compatible with your CUDA driver. +- To force CUDA builds to be installed, even if the installation is being done from a CPU-only machine. This is typical in a situation where you are installing from a head node without GPUs but intend to run on GPUs and want to install the CUDA builds. + You should now be able to run `water_openmm.py` in `./examples` or run the jupyter notebook on Google Colab [`water_openmm_colab.ipynb`](./examples/water_openmm_colab.ipynb). You can use OpenMM during active learning by passing the keyword argument `md_program="OpenMM"` to the `al_train` method. From cca9c12f636de795055d56ba9fb212f3e433bcf6 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Wed, 3 Apr 2024 13:20:54 +0100 Subject: [PATCH 15/20] Updated md_openmm --- mlptrain/sampling/md_openmm.py | 25 ++++++++++++++++++------- 1 file changed, 18 insertions(+), 7 deletions(-) diff --git a/mlptrain/sampling/md_openmm.py b/mlptrain/sampling/md_openmm.py index f82001dc..905c1627 100644 --- a/mlptrain/sampling/md_openmm.py +++ b/mlptrain/sampling/md_openmm.py @@ -269,7 +269,6 @@ def _run_mlp_md_openmm( ase_atoms=ase_atoms, restart=restart, traj_name=traj_name, - remove_last=False, ) # If MD is restarted, energies of frames from the previous trajectory @@ -342,10 +341,14 @@ def _create_openmm_topology(ase_atoms: 'ase.Atoms') -> 'app.Topology': element = app.Element.getByAtomicNumber(atomic_number) topology.addAtom(element.name, element, residue) + topology.setPeriodicBoxVectors( + ase_atoms.get_cell().array * 0.1 * unit.nanometer + ) + return topology -def _get_openmm_platform(platform: Optional[str]) -> 'mm.Platform': +def _get_openmm_platform(platform: Optional[str] = None) -> 'mm.Platform': """Get the OpenMM platform to use.""" import torch @@ -495,7 +498,7 @@ def save_simulation_state(): """Save the state of the OpenMM simulation.""" simulation.saveState(simulation_name) - def _add_frame_to_ase_traj(): + def add_frame_to_ase_traj(): """Add a new frame to the ASE train trajectory""" # Create a new ASE atoms object. new_ase_atoms = ase.Atoms( @@ -509,13 +512,21 @@ def _add_frame_to_ase_traj(): # Determine saving intervals if any(key in kwargs for key in ['save_fs', 'save_ps', 'save_ns']): - traj_saving_interval = _traj_saving_interval(kwargs) + traj_saving_interval = _traj_saving_interval(dt, kwargs) else: traj_saving_interval = 0 - # Run the dynamics n_steps, performing interval steps at a time. + # Add the initial frame to the ASE trajectory. + state = simulation.context.getState(getPositions=True, getEnergy=True) + coordinates = state.getPositions(asNumpy=True).value_in_unit(unit.angstrom) + potential_energy = ( + state.getPotentialEnergy().value_in_unit(unit.kilojoules_per_mole) + * _KJ_PER_MOL_TO_EV + ) + add_frame_to_ase_traj() - for j in range(n_previous_steps // interval, n_steps // interval): + # Run the dynamics n_steps, performing interval steps at a time. + for j in range(n_steps // interval): logger.info(f'Step {j + 1} / {n_steps // interval}') simulation.step(interval) time = dt * interval * (j + 1) @@ -534,7 +545,7 @@ def _add_frame_to_ase_traj(): biased_energy = potential_energy # Add the frame to the ASE trajectory. - _add_frame_to_ase_traj() + add_frame_to_ase_traj() # Store the energies append_unbiased_energy() From 854ac3fb467d92bf32d64e9a7ea9d07689ff6308 Mon Sep 17 00:00:00 2001 From: Joao Morado Date: Wed, 3 Apr 2024 13:21:13 +0100 Subject: [PATCH 16/20] Added OpenMM tests --- mlptrain/sampling/tests/data.zip | Bin 1599167 -> 4237778 bytes mlptrain/sampling/tests/test_openmm_md.py | 199 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