load_files
An introduction to the functions in /Preprocessing/load_files.py
Please note that all methods in load_files.py inherit BatchStructuresBase.py.
POSCARs2Feat
(
path: <class 'str'> = ./
verbose: <class 'int'> = 0
args: <class 'inspect._empty'>
kwargs: <class 'inspect._empty'>
)
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Read and convert a folder of POSCAR files from given path into arrays of atoms, coordinates, cell vectors, etc.
read
(
file_list: Optional[List] = None
output_coord_type: <class 'str'> = cartesian
)
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Args:
file_list: list (or other Sequences), the list of selected files to be read. 'None' means read all files in the input path.
output_coord_type: str, 'cartesian' or 'direct'. The coordination type of output atom coordination.
Returns:
OUTCAR2Feat
(
path: <class 'str'>
verbose: <class 'int'> = 1
)
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Read atoms, coordinates, atom numbers, energies and force in OUTCARs from given path.
Notes: Because OUTCAR does not store any information of fixed atom (selective dynamics), all atoms would be set to FREE!!
Parameters:
path: str, the path of batched OUTCAR-like files. The Sample ids would be labeled as its file names.
read
(
file_list: Optional[List[str]] = None
n_core: <class 'int'> = -1
backend: <class 'str'> = loky
)
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Parameters:
file_list: List[str], the list of files to read. Default for all files under given path.
n_core: int, the number of CPU cores used in reading files.
backend: backend for parallelization in joblib. Options: 'loky', 'threading', 'multiprocessing'.
Return: None
Update the attribute self.data.
ASETraj2Feat
(
path: <class 'str'>
verbose: <class 'int'> = 1
)
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read ASE files to BatchStructures.
read
(
file_list: <class 'inspect._empty'> = None
n_core: <class 'int'> = -1
backend: Union[Literal['loky', 'threading', 'multiprocessing'], str] = loky
)
ExtXyz2Feat
(
path: <class 'str'>
verbose: <class 'int'> = 1
)
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Read extxyz file with multiple structures.
read
(
file_list: <class 'inspect._empty'> = None
n_core: <class 'int'> = -1
backend: Union[Literal['loky', 'threading', 'multiprocessing'], str] = loky
lattice_tag: <class 'str'> = lattice
energy_tag: <class 'str'> = energy
column_info_tag: <class 'str'> = properties
element_tag: <class 'str'> = species
coordinates_tag: <class 'str'> = pos
forces_tag: str | None = forces
fixed_atom_tag: str | None = move_mask
)
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Read *.extxyz files to BatchStructures.
Args:
file_list: List[str], the list of files to read. Default for all files under given path.
n_core: int, the number of CPU cores used in reading files. -1 for all cores.
backend: backend of parallel reading in `joblib`.
lattice_tag: key-words of lattice information in *.extxyz file, at each structure's 2nd line.
energy_tag: key-words of structure's energy in *.extxyz file.
column_info_tag: key-words of column content information in *.extxyz file. The column content has such format:
`content 1`:`data type 1`:`column occupied number 1`:`content 2`:`data type 2`:`column occupied number 2`: ...
detailed see https://wiki.fysik.dtu.dk/ase/dev/_modules/ase/io/extxyz.html.
element_tag: As a content in `column_info_tag`, name of element column.
coordinates_tag: As a content in `column_info_tag`, name of atom coordinates column.
forces_tag: As a content in `column_info_tag`, name of forces column. If the file does not contain forces, set it to None.
fixed_atom_tag: As a content in `column_info_tag`, name of the mask column specified which atom was fixed.
Returns: None
All data would update as class attributes.
load_from_csv
(
file_name: <class 'str'>
label_type: <class 'type'> = <class 'float'>
ignore_None_label_samp: <class 'bool'> = True
read_column: Tuple[int, int] = (0, 1)
has_title_line: <class 'bool'> = False
)
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load information of a csv file into a dict of {samp_1:label_1, ...}.
Parameters:
file_name: str, csv file of 2 columns (sample name, sample label)
label_type: type, type of sample label
ignore_None_label_samp: bool, whether ignore None label samples i.e., not put them into output dict
read_column: Tuple[int,int], the 2 columns to read, where the 1st column as keys and the 2nd as values.
has_title_line: bool, whether ignore the 1st line which is the title or descriptions.
Return:
dict of {samp_1:label_1, ...} | dict, id_list of [samp_names]
Cif2Feat
(
path: <class 'str'>
verbose: <class 'int'> = 1
)
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Read CIF file with multiple structures.
Notes: CIF file could not contain the fixation information, so all atoms would be free.
read
(
file_list: <class 'inspect._empty'> = None
n_core: <class 'int'> = -1
backend: Union[Literal['loky', 'threading', 'multiprocessing'], str] = loky
)
load_from_structures
(
path: <class 'str'>
)
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Load BatchStructure memory-mapping files from `path` and return this BatchStructures.
Args:
path: the path of BatchStructure memory-mapping files.
Returns: BatchStructures with read data.
Output2Feat
(
path: <class 'str'>
verbose: <class 'int'> = 1
)
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A class of post-processing to reading output files of BatchOptimization and BatchMD
read
(
file_list: List[str]
n_core: <class 'int'> = -1
backend: <class 'inspect._empty'> = loky
)