GPUMD IO#

calorine.gpumd.read_dipole(fname)[source]#

Read a GPUMD dipole.out file written by the dump_dipole keyword.

GPUMD writes one header per run and appends to the same file. The blocks are laid end to end, each contributing its own dt_output, so time runs across the whole file. The step column is the counter GPUMD wrote, which restarts at every run.

Parameters:

fname (str) – Path to the dipole.out file.

Returns:

DataFrame with columns step (int), mu_x, mu_y, mu_z (dipole moment \(\mu\) for molecules, or polarization P for extended systems, in e·Å). If a header is present in the dipole.out file, the time in ps is also included as a column.

Return type:

DataFrame

calorine.gpumd.read_dpdt(fname)[source]#

Read a GPUMD dpdt.out file.

The time column is converted from fs (as written by GPUMD) to ps.

GPUMD writes one header per run and appends to the same file. The blocks are laid end to end, each contributing its own dt_output, so time runs across the whole file.

Parameters:

fname (str) – Path to the dpdt.out file.

Returns:

DataFrame with columns time (ps), dPx, dPy, dPz (time derivatives of the polarization in e·Å/fs), and Px, Py, Pz (polarization components in e·Å).

Return type:

DataFrame

calorine.gpumd.read_hac(filename, exclude_currents=True, exclude_in_out=True)[source]#

Parses a file in hac.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here.

Parameters:

  • filename (str) – Input file name.

  • exclude_currents (bool) – Do not include currents in output to save memory.

  • exclude_in_out (bool) – Do not include in and out parts of conductivity in output to save memory.

Return type:

DataFrame

calorine.gpumd.read_kappa(filename)[source]#

Parses a file in kappa.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here.

Parameters:

filename (str) – Input file name.

Return type:

DataFrame

calorine.gpumd.read_mcmd(filename, accumulate=True)[source]#

Parses a Monte Carlo output file in mcmd.out format and returns the content in the form of a DataFrame.

Parameters:

  • filename (str) – Path to file to be parsed.

  • accumulate (bool) – If True the MD steps between subsequent Monte Carlo runs in the same output file will be accumulated.

Return type:

DataFrame

Returns:

DataFrame containing acceptance ratios and concentrations (if available), as well as key Monte Carlo parameters.

calorine.gpumd.read_msd(filename)[source]#

Parses a file in msd.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here.

GPUMD writes one header per run and appends to the same file. Each block is a separate correlation function, so a file holding more than one is rejected rather than combined.

Parameters:

filename (str) – Input file name.

Return type:

DataFrame

calorine.gpumd.read_polarizability(fname, normalize=None, scale=None)[source]#

Read a GPUMD polarizability.out file written by dump_polarizability.

GPUMD writes one header per run and appends to the same file. The blocks are laid end to end, each contributing its own dt_output and num_atoms, so time runs across the whole file. The step column is the counter GPUMD wrote, which restarts at every run.

Parameters:

  • fname (str) – Path to the polarizability.out file.

  • normalize (bool | None) – Divide the six susceptibility columns by the number of atoms, taken from the num_atoms line of each header block.

  • scale (float) – Divisor applied to the six susceptibility columns in place of the count in the header. Passing it implies normalize, and naming it together with normalize=False raises. GPUMD writes the total supercell susceptibility \(\chi_\mathrm{cell}\), so the divisor should match the normalization constant used as the training target scale of the TNEP model, typically the number of atoms. Dividing by it recovers the intensive, per-atom quantity that get_raman_spectrum() expects. The step column is not affected.

Returns:

DataFrame with columns step (int) and the six independent components xx, yy, zz, xy, yz, xz of the polarizability \(\alpha\) (molecules) or susceptibility \(\chi\) (extended systems), in the same units as the TNEP training data (typically Å^3 or bohr^3 per atom when scale equals the number of atoms). The off-diagonal order follows the GPUMD polarizability.out file (xy, yz, xz). If a header is present in the polarizability.out file, the time in ps is also included as a column.

Return type:

DataFrame

calorine.gpumd.read_runfile(filename)[source]#

Parses a GPUMD input file in run.in format and returns the content in the form a list of keyword-value pairs.

The values of a few keywords are cast to a number, among them the dump interval that opens a dump_xyz line. The remaining fields of such a line, meaning the file name and any flags, are kept as strings, and all other values fall back to strings as well.

Parameters:

filename (str) – Input file name.

Return type:

list[tuple[str, list]]

Returns:

List of keyword-value pairs.

calorine.gpumd.read_sdc(filename)[source]#

Parses a file in sdc.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here.

GPUMD writes one header per run and appends to the same file. Each block is a separate correlation function, so a file holding more than one is rejected rather than combined.

Parameters:

filename (str) – Input file name.

Return type:

DataFrame

calorine.gpumd.read_shc(filename)[source]#

Parses a file in shc.out format from GPUMD (written by the compute_shc keyword) and returns the correlation and spectral blocks as two data frames.

When the calculation covers more than one output group, the ki/ko/shc_i/shc_o columns are suffixed with the group index GPUMD assigns, which runs from 1 (ki_1, ko_1, ki_2, …); the shared time/omega grid is not suffixed.

GPUMD writes one header per run and appends to the same file. Each block is a separate correlation function, so a file holding more than one is rejected rather than combined.

This reader requires the header, which alone says how the correlation and spectral blocks are laid out. Its siblings fall back to reading a header-less file by column count.

Parameters:

filename (str) – Input file name.

Return type:

tuple[DataFrame, DataFrame]

Returns:

  • correlation (DataFrame) – DataFrame with columns time, ki, ko (suffixed with the group index, e.g. ki_1, when the calculation covers multiple output groups).

  • shc (DataFrame) – DataFrame with columns omega, shc_i, shc_o (suffixed with the group index when the calculation covers multiple output groups).

calorine.gpumd.read_thermo(filename, normalize=None, natoms=None)[source]#

Parses a file in thermo.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here. Additionally, the time (in ps), the pressure (in GPa), the volume (in Å:sup:3), the lengths of the three cell vectors (cell_length_1 to cell_length_3, in Å) and the angles between them (cell_angle_12, cell_angle_13 and cell_angle_23, in degrees) are included. A header that names one of those derived columns itself, or names any column twice, raises.

GPUMD writes one header per run and appends to the same file. The blocks are laid end to end, each contributing its own dt_output and num_atoms, so time runs across the whole file and each block is normalized by its own atom count.

Parameters:

  • filename (str) – Input file name.

  • normalize (bool | None) – Divide the energies by the number of atoms, taken from the num_atoms line of each header block.

  • natoms (int) – Number of atoms to divide the energies by, in place of the count in the header. Passing it implies normalize, and naming it together with normalize=False raises.

Returns:

DataFrame with columns determined by the thermo.out format.

Return type:

DataFrame

calorine.gpumd.read_viscosity(filename)[source]#

Parses a file in viscosity.out format from GPUMD and returns the content as a data frame. More information concerning file format, content and units can be found here.

GPUMD writes one header per run and appends to the same file. Each block is a separate correlation function, so a file holding more than one is rejected rather than combined.

Parameters:

filename (str) – Input file name.

Return type:

DataFrame

calorine.gpumd.read_xyz(filename)[source]#

Reads the structure input file (model.xyz) for GPUMD and returns the structure.

This is a wrapper function around ase.io.read_xyz() since the ASE implementation does not read velocities properly. Specifically, the velocity unit is converted from GPUMD units (Å/fs) to ASE units (1/sqrt(u/eV)).

Parameters:

filename (str) – Name of file from which to read the structure.

Return type:

Atoms

Returns:

Structure as ASE Atoms object with additional per-atom arrays representing atomic masses, velocities etc.

calorine.gpumd.write_runfile(file, parameters)[source]#

Write a file in run.in format to define input parameters for MD simulation.

Parameters:

  • file (Path) – Path to file to be written.

  • parameters (list[tuple[str, int | float | tuple[str, float]]]) – Defines all command-parameter(s) pairs used in run.in file (see GPUMD documentation for a complete list). Values can be either floats, integers, or lists/tuples.

calorine.gpumd.write_xyz(filename, structure, groupings=None)[source]#

Writes a structure into GPUMD input format (model.xyz).

This is a wrapper function around ase.io.write_xyz() since the ASE implementation does not write velocities properly. Specifically, the velocity unit is converted from ASE units (1/sqrt(u/eV)) to GPUMD units (Å/fs).

Parameters:

  • filename (str) – Name of file to which the structure should be written.

  • structure (Atoms) – Input structure.

  • groupings (list[list[list[int]]]) – Groups into which the individual atoms should be divided in the form of a list of list of lists. Specifically, the outer list corresponds to the grouping methods, of which there can be three at the most, which contains a list of groups in the form of lists of site indices. The sum of the lengths of the latter must be the same as the total number of atoms.

Raises:

ValueError – Raised if parameters are incompatible.