GPUMD IO
- 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 includein
andout
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
) – IfTrue
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.- Parameters:
filename (
str
) – Input file name.- 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.- Parameters:
filename (
str
) – Input file name.- Return type:
List
[Tuple
[str
,list
]]- Returns:
List of keyword-value pairs.
- calorine.gpumd.read_thermo(filename, natoms=1)[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.- Parameters:
filename (
str
) – Input file name.natoms (
int
) – Number of atoms; used to normalize energies.
- Return type:
DataFrame
- calorine.gpumd.read_thermodynamic_data(directory_name, normalize=False)[source]
Parses the data in a GPUMD output directory and returns the content in the form of a
DataFrame
. This function reads thethermo.out
,run.in
, andmodel.xyz
(optionally) files, and returns the thermodynamic data including the time (in ps), the pressure (in GPa), the side lengths of the simulation cell (in Å), and the volume (in Å:sup:3
or Å:sup:3
/atom).- Parameters:
directory_name (
str
) – Path to directory to be parsed.normalize (
bool
) – Normalize thermodynamic quantities per atom. This requires themodel.xyz
file to be present.
- Return type:
DataFrame
- Returns:
DataFrame
containing (augmented) thermodynamic data.
- 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.- Parameters:
filename (
str
) – Name of file from which to read the structure.- Return type:
- 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 (dict) – Defines all key-value 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
).- Parameters:
filename (
str
) – Name of file to which the structure should be written.structure (
Atoms
) – Input structure.groupings (
Optional
[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.