Analyzer API

MoltenSaltAnalyzer

Class for analyzing molten salt simulation results.

init

__init__(
    traj_files_npt: (
        list[str] | list[Path] | str | Path | None
    ) = None,
    traj_files_nvt: (
        list[str] | list[Path] | str | Path | None
    ) = None,
    temperatures_npt: list[float] | list[int] | None = None,
    temperatures_nvt: list[float] | list[int] | None = None,
    ids_npt: list[str] | None = None,
    ids_nvt: list[str] | None = None,
    timestep_fs: int | float | None = None,
    calculator: Calculator | None = None,
)

Initialize the analyzer with the trajectories and the always used properties

Parameters:

Name	Type	Description	Default
`traj_files_npt`	`(list, str, Path)`	Path to the NPT trajectory file(s). Defaults to None.	`None`
`traj_files_nvt`	`(list, str, Path)`	Path to the NVT trajectory file(s). Defaults to None.	`None`
`temperatures_npt`	`list`	List of temperatures in K for the NPT trajectories. Defaults to None.	`None`
`temperatures_nvt`	`list`	List of temperatures in K for the NVT trajectories. Defaults to None.	`None`
`ids_npt`	`list`	List of identifiers for the NPT trajectories. Defaults to None.	`None`
`ids_nvt`	`list`	List of identifiers for the NVT trajectories. Defaults to None.	`None`
`timestep_fs`	`(int, float)`	Constant timestep in fs. Only applies if time_fs is not found in the trajectory files. Defaults to None which is treated as 10.0 later but a warning is issued.	`None`
`calculator`	`calculator`	Calculator to use for the energy and forces predictions (needed in case they are not available from the trajectory files, but leads to a slow initialization). Defaults to None.	`None`

Raises:

Type	Description
`ValueError`	If the number of trajectory files is not equal to the number of temperatures.
`ValueError`	If ids are provided but the number of trajectory files is not equal to the number of ids.
`FileNotFoundError`	If the trajectory file(s) does not exist.

Defines

self.trajs_npt (list): List of Trajectory objects for the NPT trajectories. self.trajs_nvt (list): List of Trajectory objects for the NVT trajectories. self.times_fs_npt (list[np.ndarray]): List of arrays of times in fs for each NPT trajectory. self.times_fs_nvt (list[np.ndarray]): List of arrays of times in fs for each NVT trajectory. self.temperatures_npt (list): List of temperatures in K for the NPT trajectories. self.temperatures_nvt (list): List of temperatures in K for the NVT trajectories. self.ids_npt (list): List of identifiers for the NPT trajectories. self.ids_nvt (list): List of identifiers for the NVT trajectories. self.timestep_fs (float): Constant timestep in fs, only applies if time_fs is not found in the trajectory files.

recompute_times

recompute_times(timestep_fs: int | float)

Sets the times corresponding to the atoms in the trajectories according to the provided constant timestep.

Parameters:

Name	Type	Description	Default
`timestep_fs`	`(int, float)`	Newly chosen timestep in fs.	required

compute_density_vs_time

compute_density_vs_time(
    traj_id: str | None = None, T: int | float | None = None
) -> tuple[np.ndarray, np.ndarray]

Compute the density from the trajectory file. If both NPT and NVT trajectories are loaded, the density is computed from the NPT trajectory.

Parameters:

Name	Type	Description	Default
`traj_id`	`str`	Identifier for the trajectory. Defaults to None.	`None`
`T`	`(int, float)`	Temperature in K. The trajectory with the matching temperature is selected if traj_id is None. Defaults to None.	`None`

Returns:

Type	Description
`tuple[ndarray, ndarray]`	Tuple[np.ndarray, np.ndarray]: Densities in g/cm³ and times in fs.

compute_eq_density

compute_eq_density(
    traj_id: str | None = None,
    T: int | float | None = None,
    eq_fraction: float = 0.1,
) -> float

Compute the density after equilibration (last x time% of the trajectory). If both NPT and NVT trajectories are loaded, the density is computed from the NPT trajectory.

Parameters:

Name	Type	Description	Default
`traj_id`	`str`	Identifier for the trajectory. Defaults to None.	`None`
`T`	`(int, float)`	Temperature in K. The trajectory with the matching temperature is selected if traj_id is None. Defaults to None.	`None`
`eq_fraction`	`float`	Final fraction of the simulation time to be considered as equilibrium. Defaults to 0.1.	`0.1`

Returns:

Name	Type	Description
`float`	`float`	Density in g/cm³

compute_thermal_expansion

compute_thermal_expansion(
    eq_fraction: float = 0.1, ids: list[str] | None = None
) -> dict

Compute the thermal expansion coefficient from the initialized trajectory files and NPT temperatures.

Parameters:

Name	Type	Description	Default
`eq_fraction`	`float`	Final fraction of the simulation time to be considered as equilibrium. Defaults to 0.1.	`0.1`
`ids`	`list`	Identifiers for the trajectories to be used. Defaults to None.	`None`

Raises:

Type	Description
`ValueError`	If no trajectory identifiers are provided but were not initialized.
`ValueError`	If at least one of the provided ids is not available in the initialized NPT trajectories.
`ValueError`	If no NPT trajectory files are provided.
`ValueError`	If no NPT temperatures are provided.
`ValueError`	If less than two NPT trajectory files are provided.

Returns:

Name	Type	Description
`dict`	`dict`	Thermal expansion results: - "temperatures": List of temperatures used - "eq_vols": Equilibrium volumes in Å³ for each temperature - "eq_vols_norm": Equilibrium volumes normalized to the mean volume - "fit": Fit parameters - "fit_line": Fit line - "thermal_expansion": Thermal expansion coefficient in 1/K

compute_heat_capacity

compute_heat_capacity(
    T: int | float,
    traj_id: str | None = None,
    eq_fraction: float = 0.1,
) -> float

Compute heat capacity from total energy fluctuations. If both NPT and NVT trajectories are loaded, the heat capacity is computed from the NVT trajectory.

Parameters:

Name	Type	Description	Default
`T`	`(int, float)`	Temperature in K. The trajectory with the matching temperature is selected.	required
`traj_id`	`str`	Identifier for the trajectory, overrides T. Defaults to None.	`None`
`eq_fraction`	`float`	Final fraction of the simulation time to be considered as equilibrium. Defaults to 0.1.	`0.1`

Returns:

Name	Type	Description
`float`	`float`	Heat capacity in J/g/K

compute_diffusion_coefficient

compute_diffusion_coefficient(
    T: int | float, traj_id: str | None = None
) -> dict

Compute diffusion coefficients of each atom species present in the trajectory from the mean squared displacement. If both NPT and NVT trajectories are loaded, the diffusion coefficient is computed from the NVT trajectory, unless selected otherwise with traj_id.

Parameters:

Name	Type	Description	Default
`T`	`(int, float)`	Temperature in K. The trajectory with the matching temperature is selected.	required
`traj_id`	`str`	Identifier for the trajectory, overrides T to select the trajectory. Defaults to None.	`None`

Returns:

Name	Type	Description
`dict`	`dict`	Diffusion coefficients in Å²/fs for each element, in the form {element: diffusion coefficient}

fit_arrhenius

fit_arrhenius(
    temperatures: list[int] | list[float],
    diffusion_coeffs: list[float],
) -> dict

Fit Arrhenius law to diffusion coefficients and temperatures.

Parameters:

Name	Type	Description	Default
`temperatures`	`list`	Temperatures in K.	required
`diffusion_coeffs`	`list`	Diffusion coefficients corresponding to the temperatures in Å²/fs.	required

Returns:

Name	Type	Description
`dict`	`dict`	Arrhenius parameters: - "Ea": Activation energy in J/mol - "D0": Exponential pre-factor of the Arrhenius law in Å²/fs - "slope": Slope of the Arrhenius law - "intercept": Intercept of the Arrhenius law

compute_rdf

compute_rdf(
    T: float,
    traj_id: str | None = None,
    max_num_frames: int | None = None,
    rmax: float = 6.0,
    nbins: int = 100,
    pairs: (
        list[tuple[int, int]] | list[tuple[str, str]] | None
    ) = None,
    cell_constraints: (
        list[tuple[float, float]] | None
    ) = None,
    n_workers: int = 1,
) -> dict

Compute radial distribution functions. If both NPT and NVT trajectories are loaded, the RDF is computed from the NVT trajectory.

Parameters:

Name	Type	Description	Default
`T`	`float`	Temperature in K. The trajectory with the matching temperature is selected.	required
`traj_id`	`str`	Identifier for the trajectory, overrides T. Defaults to None.	`None`
`max_num_frames`	`int`	Maximum number of trajectory frames to compute the RDF for and average over. The frames are selected from the end of the simulation. Defaults to None which means all frames are considered.	`None`
`rmax`	`float`	Maximum distance (Å) to consider. Defaults to 6.0.	`6.0`
`nbins`	`int`	Number of bins for the RDF. Defaults to 100.	`100`
`pairs`	`list[tuple] \| None`	Atom pairs in terms of atomic numbers or symbols to compute the RDF for. Defaults to None which means all unique pairs in the system are analyzed.	`None`
`cell_constraints`	`list[tuple] \| None`	Whether to compute the RDF only for a subpart of the cell, given by the list of cell constraints. Each constraint is a tuple of the form (min, max) for the x, y, and z coordinates. The boundaries are inclusive. Defaults to None which means all atoms are included.	`None`
`n_workers`	`int`	Number of workers to use for parallel RDF computation. Defaults to 1.	`1`

Raises:

Type	Description
`ValueError`	If no pairs are specified.

Returns:

Name	Type	Description
`dict`	`dict`	Dictionary with RDF results: - "(atomic number, atomic number)": (distances, avg_rdf) for each pair. Distances are in Å and avg_rdf is unitless (normalized).

compute_viscosity

compute_viscosity(
    T: float,
    traj_id: str | None = None,
    tmax_fs: int = 20000,
) -> tuple[float, tuple[np.ndarray, np.ndarray]]

Compute shear viscosity using Green-Kubo relation. The timestep between frames has to be constant.

Parameters:

Name	Type	Description	Default
`T`	`float`	Temperature in K. The trajectory with the matching temperature is selected.	required
`traj_id`	`str`	Identifier for the trajectory, overrides T. Defaults to None.	`None`
`tmax_fs`	`int`	Maximum correlation time in femtoseconds. Defaults to 20000.	`20000`

Raises:

Type	Description
`ValueError`	If the timestep between the frames is not constant.

Returns:

Type	Description
`tuple[float, tuple[ndarray, ndarray]]`	Tuple[float, Tuple[np.ndarray, np.ndarray]]: Viscosity in Pa s and the autocorrelation function and times: - "eta": Viscosity in Pa s - "(autocorrelation, times)": (autocorrelation function, times) in eV²/Å⁶ fs and fs