IMLCV.base.MdEngine =================== .. py:module:: IMLCV.base.MdEngine .. autoapi-nested-parse:: MD engine class peforms MD simulations in a given NVT/NPT ensemble. Classes ------- .. autoapisummary:: IMLCV.base.MdEngine.StaticMdInfo IMLCV.base.MdEngine.TrajectoryInfo IMLCV.base.MdEngine.MDEngine Module Contents --------------- .. py:class:: StaticMdInfo .. py:attribute:: _attr :value: ['timestep', 'r_cut', 'timecon_thermo', 'T', 'P', 'timecon_baro', 'write_step', 'equilibration',... .. py:attribute:: _arr :value: ['atomic_numbers'] .. py:attribute:: timestep :type: float .. py:attribute:: T :type: float .. py:attribute:: timecon_thermo :type: float .. py:attribute:: atomic_numbers :type: jax.Array .. py:attribute:: r_cut :type: float | None :value: None .. py:attribute:: P :type: float | None :value: None .. py:attribute:: timecon_baro :type: float | None :value: None .. py:attribute:: write_step :type: int :value: 100 .. py:attribute:: equilibration :type: float | None :value: None .. py:attribute:: screen_log :type: int :value: 1000 .. py:attribute:: invalid :type: bool :value: False .. py:attribute:: max_grad :type: float | None :value: 0.04031059429903557 .. py:property:: masses .. py:property:: thermostat .. py:property:: barostat .. py:property:: neighbour_list_info :type: IMLCV.base.CV.NeighbourListInfo .. py:method:: __post_init__() .. py:method:: _save(hf: h5py.File) .. py:method:: save(filename: str | pathlib.Path) .. py:method:: _load(hf: h5py.File) -> StaticMdInfo :staticmethod: .. py:method:: load(filename) -> StaticMdInfo :staticmethod: .. py:class:: TrajectoryInfo(*args, **kwargs) Bases: :py:obj:`IMLCV.base.datastructures.MyPyTreeNode` Base class for dataclasses that should act like a JAX pytree node. .. py:attribute:: _positions :type: jax.Array .. py:attribute:: _cell :type: jax.Array | None :value: None .. py:attribute:: _charges :type: jax.Array | None :value: None .. py:attribute:: _e_pot :type: jax.Array | None :value: None .. py:attribute:: _e_bias :type: jax.Array | None :value: None .. py:attribute:: _w :type: jax.Array | None :value: None .. py:attribute:: _rho :type: jax.Array | None :value: None .. py:attribute:: _cv :type: jax.Array | None :value: None .. py:attribute:: _cv_orig :type: jax.Array | None :value: None .. py:attribute:: _T :type: jax.Array | None :value: None .. py:attribute:: _P :type: jax.Array | None :value: None .. py:attribute:: _err :type: jax.Array | None :value: None .. py:attribute:: _t :type: jax.Array | None :value: None .. py:attribute:: _capacity :type: int .. py:attribute:: _size :type: int .. py:attribute:: _finished :type: int .. py:attribute:: _invalid :type: int .. py:attribute:: _items_scal :value: ['_t', '_e_pot', '_e_bias', '_T', '_P', '_err', '_w', '_rho'] .. py:attribute:: _items_vec :value: ['_positions', '_cell', '_charges', '_cv', '_cv_orig'] .. py:method:: create(positions: jax.Array, cell: jax.Array | None = None, charges: jax.Array | None = None, e_pot: jax.Array | None = None, e_bias: jax.Array | None = None, cv: jax.Array | None = None, cv_orig: jax.Array | None = None, w: jax.Array | None = None, rho: jax.Array | None = None, T: jax.Array | None = None, P: jax.Array | None = None, err: jax.Array | None = None, t: jax.Array | None = None, capacity: int = -1, size: int = -1, finished=False, invalid=False) -> TrajectoryInfo :staticmethod: .. py:method:: __getitem__(slices) gets slice from indices. the output is truncated to the to include only items wihtin _size .. py:method:: _stack(*ti: TrajectoryInfo) .. py:method:: __add__(ti: TrajectoryInfo) -> TrajectoryInfo .. py:method:: _expand_capacity(nc=None) -> TrajectoryInfo .. py:method:: _shrink_capacity() -> TrajectoryInfo .. py:method:: save(filename: str | pathlib.Path) .. py:method:: _save(hf: h5py.File) .. py:method:: load(filename) -> TrajectoryInfo :staticmethod: .. py:method:: _load(hf: h5py.File) :staticmethod: .. py:property:: sp :type: IMLCV.base.CV.SystemParams .. py:property:: positions :type: jax.Array | None .. py:property:: cell :type: jax.Array | None .. py:property:: volume .. py:property:: charges :type: jax.Array | None .. py:property:: e_pot :type: jax.Array | None .. py:property:: w :type: jax.Array | None .. py:property:: rho :type: jax.Array | None .. py:property:: e_bias :type: jax.Array | None .. py:property:: cv :type: jax.Array | None .. py:property:: cv_orig :type: jax.Array | None .. py:property:: T :type: jax.Array | None .. py:property:: P :type: jax.Array | None .. py:property:: err :type: jax.Array | None .. py:property:: t :type: jax.Array | None .. py:property:: shape .. py:property:: CV :type: IMLCV.base.CV.CV | None .. py:property:: CV_orig :type: IMLCV.base.CV.CV | None .. py:class:: MDEngine Bases: :py:obj:`abc.ABC` Base class for MD engine. .. py:attribute:: bias :type: IMLCV.base.bias.Bias .. py:attribute:: energy :type: IMLCV.base.bias.Energy .. py:attribute:: sp :type: IMLCV.base.CV.SystemParams .. py:attribute:: static_trajectory_info :type: StaticMdInfo .. py:attribute:: trajectory_info :type: TrajectoryInfo | None .. py:attribute:: trajectory_file :type: pathlib.Path | None :value: None .. py:attribute:: time0 :type: float .. py:attribute:: step :type: int :value: 1 .. py:attribute:: nl :type: IMLCV.base.CV.NeighbourList | None :value: None .. py:attribute:: r_skin :value: 1.889726133921252 .. py:method:: create(bias: IMLCV.base.bias.Bias, energy: IMLCV.base.bias.Energy, static_trajectory_info: StaticMdInfo, trajectory_info=None, trajectory_file=None, sp: IMLCV.base.CV.SystemParams | None = None, **kwargs) -> typing_extensions.Self :classmethod: .. py:method:: update_nl() .. py:method:: save(file) .. py:method:: load(file, **kwargs) -> MDEngine :staticmethod: .. py:method:: new_bias(bias: IMLCV.base.bias.Bias, **kwargs) -> MDEngine .. py:method:: run(steps) run the integrator for a given number of steps. :param steps: number of MD steps .. py:method:: _run(steps) :abstractmethod: .. py:method:: get_trajectory() -> TrajectoryInfo .. py:method:: save_step(T=None, P=None, t=None, err=None, cv=None, e_bias=None, e_pot=None, gpos_rmsd=None, gpos_bias_rmsd=None, canonicalize=False) .. py:method:: get_energy(sp: IMLCV.base.CV.SystemParams, gpos: bool = False, vtens: bool = False, manual_vir=None) -> IMLCV.base.bias.EnergyResult .. py:method:: get_bias(sp: IMLCV.base.CV.SystemParams, gpos: bool = False, vtens: bool = False, shmap: bool = False, use_jac=False, push_jac=False, rel=False, shmap_kwargs=ShmapKwargs.create()) -> tuple[IMLCV.base.CV.CV, IMLCV.base.bias.EnergyResult] .. py:method:: __getstate__() .. py:method:: __setstate__(statedict: dict)