pymatgen.apps.borg package

The borg package contains modules that assimilate large quantities of data into pymatgen objects for analysis.

Submodules

pymatgen.apps.borg.hive module

This module define the various drones used to assimilate data.

class AbstractDrone[source]

Bases: MSONable, ABC

Abstract drone class that defines the various methods that must be implemented by drones. Because of the quirky nature of Python”s multiprocessing, the intermediate data representations has to be in the form of python primitives. So all objects that drones work with must be MSONable. All drones must also implement the standard MSONable as_dict() and from_dict API.

abstract assimilate(path)[source]

Assimilate data in a directory path into a pymatgen object. Because of the quirky nature of Python’s multiprocessing, the object must support pymatgen’s as_dict() for parallel processing.

Parameters:: path – directory path
Returns:: An assimilated object

abstract get_valid_paths(path)[source]

Check if path contains valid data for assimilation, and then returns the valid paths. The paths returned can be a list of directory or file paths, depending on what kind of data you are assimilating. For example, if you are assimilating VASP runs, you are only interested in directories containing vasprun.xml files. On the other hand, if you are interested converting all POSCARs in a directory tree to CIFs for example, you will want the file paths.

Parameters:: path – input path as a tuple generated from os.walk, i.e., (parent, subdirs, files).
Returns:: List of valid dir/file paths for assimilation

class GaussianToComputedEntryDrone(inc_structure: bool = False, parameters: list[str] | None = None, data: list[str] | None = None, file_extensions: Sequence[str] = ('.log',))[source]

Bases: AbstractDrone

GaussianToEntryDrone assimilates directories containing Gaussian output to ComputedEntry/ComputedStructureEntry objects. By default, it is assumed that Gaussian output files have a “.log” extension.

Note

Like the GaussianOutput class, this is still in early beta.

Parameters:

inc_structure (bool) – Set to True if you want ComputedStructureEntries to be returned instead of ComputedEntries.
parameters (list) – Input parameters to include. It has to be one of the properties supported by the GaussianOutput object. See pymatgen.io.gaussian.GaussianOutput. The parameters have to be one of python’s primitive types, i.e., list, dict of strings and integers. If parameters is None, a default set of parameters will be set.
data (list) – Output data to include. Has to be one of the properties supported by the GaussianOutput object. The parameters have to be one of python’s primitive types, i.e. list, dict of strings and integers. If data is None, a default set will be set.
file_extensions (list) – File extensions to be considered as Gaussian output files. Defaults to just the typical “log” extension.

as_dict() → dict[str, Any][source]: Get MSONable dict.

assimilate(path: PathLike) → ComputedStructureEntry | ComputedEntry | None[source]

Assimilate data in a directory path into a ComputedEntry object.

Parameters:: path – directory path
Returns:: ComputedEntry

classmethod from_dict(dct: dict[str, Any]) → Self[source]

Parameters:: dct (dict) – Dict Representation.
Returns:: GaussianToComputedEntryDrone

get_valid_paths(path: tuple[str, str, str]) → list[str][source]

Check if path contains files with define extensions.

Parameters:: path – input path as a tuple generated from os.walk, i.e., (parent, subdirs, files).
Returns:: List of valid dir/file paths for assimilation

class SimpleVaspToComputedEntryDrone(inc_structure: bool = False)[source]

Bases: VaspToComputedEntryDrone

A simpler VaspToComputedEntryDrone. Instead of parsing vasprun.xml, it parses only the INCAR, POTCAR, OSZICAR and KPOINTS files, which are much smaller and faster to parse. However, much fewer properties are available compared to the standard VaspToComputedEntryDrone.

Parameters:: inc_structure (bool) – Return ComputedStructureEntries (True) instead of ComputedEntries (False). Structure will be parsed from the CONTCAR.

as_dict() → dict[str, Any][source]: Get MSONable dict.

assimilate(path: PathLike) → ComputedStructureEntry | ComputedEntry | None[source]

Assimilate data in a directory path into a ComputedEntry object.

Parameters:: path – directory path
Returns:: ComputedEntry

classmethod from_dict(dct: dict[str, Any]) → Self[source]

Parameters:: dct (dict) – Dict Representation.
Returns:: SimpleVaspToComputedEntryDrone

class VaspToComputedEntryDrone(inc_structure: bool = False, parameters: list[str] | None = None, data: list[str] | None = None)[source]

Bases: AbstractDrone

VaspToEntryDrone assimilates directories containing VASP output to ComputedEntry/ComputedStructureEntry objects.

There are some restrictions on the valid directory structures:

There can be only one vasp run in each directory.
Directories designated “relax1”, “relax2” are considered to be 2 parts of an aflow style run, and only “relax2” is parsed.
The drone parses only the vasprun.xml file.

Parameters:

inc_structure (bool) – Set to True if you want ComputedStructureEntries to be returned instead of ComputedEntries.
parameters (list) – Input parameters to include. It has to be one of the properties supported by the Vasprun object. See pymatgen.io.vasp.Vasprun. If parameters is None, a default set of parameters that are necessary for typical post-processing will be set.
data (list) – Output data to include. Has to be one of the properties supported by the Vasprun object.

as_dict() → dict[str, Any][source]: Get MSONable dict.

assimilate(path: PathLike) → ComputedStructureEntry | ComputedEntry | None[source]

Assimilate data in a directory path into a ComputedEntry object.

Parameters:: path – directory path
Returns:: ComputedEntry

classmethod from_dict(dct: dict[str, Any]) → Self[source]

Parameters:: dct (dict) – Dict Representation.
Returns:: VaspToComputedEntryDrone

get_valid_paths(path: tuple[str, str, str]) → list[str][source]

Check if paths contains vasprun.xml or (POSCAR+OSZICAR).

Parameters:: path – input path as a tuple generated from os.walk, i.e., (parent, subdirs, files).
Returns:: List of valid dir/file paths for assimilation

pymatgen.apps.borg.queen module

This module defines the BorgQueen class, which manages drones to assimilate data using Python’s multiprocessing.

class BorgQueen(drone: AbstractDrone, rootpath: PathLike | None = None, number_of_drones: int = 1)[source]

Bases: object

The Borg Queen controls the drones to assimilate data in an entire directory tree. Uses multiprocessing to speed up things considerably. It also contains convenience methods to save and load data between sessions.

Parameters:

drone (AbstractDrone) – An implementation of AbstractDrone to use for assimilation.
rootpath (PathLike) – The root directory to start assimilation. Leave it as None if you want to do assimilation later, or is using the BorgQueen to load previously assimilated data.
number_of_drones (int) – Number of drones to parallelize over. Typical machines today have up to four processors. Note that you won’t see a 100% improvement with two drones over one, but you will definitely see a significant speedup of at least 50% or so. If you are running this over a server with far more processors, the speedup will be even greater.

get_data() → list[source]: Get an list of assimilated objects.

load_data(filename: PathLike) → None[source]: Load assimilated data from a file.

parallel_assimilate(rootpath: PathLike) → None[source]: Assimilate the entire subdirectory structure in rootpath.

save_data(filename: PathLike) → None[source]

Save the assimilated data to a file.

Parameters:: filename (str) – filename to save the assimilated data to. Note that if the filename ends with gz or bz2, the relevant gzip or bz2 compression will be applied.

serial_assimilate(root: PathLike) → None[source]: Assimilate the entire subdirectory structure in rootpath serially.

order_assimilation(args: tuple) → None[source]: Internal helper method for BorgQueen to process assimilation.