dpgen2.fp package

Submodules

dpgen2.fp.abacus module

Bases: AbacusInputs

Methods

`get_mass`(element_list)	Get the mass of elements.
`read_inputf`(inputf)	Read INPUT and transfer to a dict.
`write_deepks`()	Check if INPUT is a deepks job, if yes, will return the deepks descriptor file name, else will return None.
`write_pporb`(element_list)	Based on element list, write the pp/orb files, and return a list of the filename.

args
get_deepks_descriptor
get_deepks_model
get_input
get_orb
get_pp
set_deepks_descriptor
set_deepks_model
set_input
set_mass
set_orb
set_pp
write_input
write_kpt

static args()[source]

class dpgen2.fp.abacus.PrepFpOpAbacus(*args, **kwargs)[source]

Bases: OP

Attributes:

key
workflow_name

Methods

`execute`(ip)	Run the OP
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

execute(ip: OPIO) → OPIO[source]: Run the OP

classmethod get_input_sign()[source]: Get the signature of the inputs

classmethod get_output_sign()[source]: Get the signature of the outputs

class dpgen2.fp.abacus.RunFpOpAbacus(*args, **kwargs)[source]

Bases: OP

Attributes:

key
workflow_name

Methods

`execute`(ip)	Run the OP
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs

args
convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

static args()[source]

execute(ip: OPIO) → OPIO[source]: Run the OP

classmethod get_input_sign()[source]: Get the signature of the inputs

classmethod get_output_sign()[source]: Get the signature of the outputs

dpgen2.fp.deepmd module

Prep and Run Gaussian tasks.

class dpgen2.fp.deepmd.DeepmdInputs(**kwargs: Any)[source]

Bases: object

Methods

args

static args() → List[Argument][source]

class dpgen2.fp.deepmd.PrepDeepmd(*args, **kwargs)[source]

Bases: PrepFp

Attributes:

key
workflow_name

Methods

`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`prep_task`(conf_frame, inputs)	Define how one Deepmd task is prepared.

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

prep_task(conf_frame: System, inputs)[source]

Define how one Deepmd task is prepared.

Parameters:

conf_framedpdata.System: One frame of configuration in the dpdata format.
inputsstr or dict: This parameter is useless in deepmd.

class dpgen2.fp.deepmd.RunDeepmd(*args, **kwargs)[source]

Bases: RunFp

Attributes:

key
workflow_name

Methods

`args`()	The argument definition of the run_task method.
`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`input_files`()	The mandatory input files to run a Deepmd task.
`normalize_config`([data, strict])	Normalized the argument.
`optional_input_files`()	The optional input files to run a Deepmd task.
`run_task`(teacher_model_path, out, log)	Defines how one FP task runs

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

static args() → List[Argument][source]

The argument definition of the run_task method.

Returns:

arguments: List[dargs.Argument]: List of dargs.Argument defines the arguments of run_task method.

input_files() → List[str][source]

The mandatory input files to run a Deepmd task.

Returns:

files: List[str]: A list of madatory input files names.

optional_input_files() → List[str][source]

The optional input files to run a Deepmd task.

Returns:

files: List[str]: A list of optional input files names.

run_task(teacher_model_path: BinaryFileInput, out: str, log: str) → Tuple[str, str][source]

Defines how one FP task runs

Parameters:

commandstr: The command of running Deepmd task
outstr: The name of the output data file.

Returns:

out_name: str: The file name of the output data in the dpdata.LabeledSystem format.
log_name: str: The file name of the log.

dpgen2.fp.gaussian module

Prep and Run Gaussian tasks.

class dpgen2.fp.gaussian.GaussianInputs(**kwargs: Any)[source]

Bases: object

Methods

args()

The arguments of the GaussianInputs class.

static args() → List[Argument][source]: The arguments of the GaussianInputs class.

class dpgen2.fp.gaussian.PrepGaussian(*args, **kwargs)[source]

Bases: PrepFp

Attributes:

key
workflow_name

Methods

`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`prep_task`(conf_frame, inputs)	Define how one Gaussian task is prepared.

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

prep_task(conf_frame: System, inputs: GaussianInputs)[source]

Define how one Gaussian task is prepared.

Parameters:

conf_framedpdata.System: One frame of configuration in the dpdata format.
inputsGaussianInputs: The GaussianInputs object handels all other input files of the task.

class dpgen2.fp.gaussian.RunGaussian(*args, **kwargs)[source]

Bases: RunFp

Attributes:

key
workflow_name

Methods

`args`()	The argument definition of the run_task method.
`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`input_files`()	The mandatory input files to run a Gaussian task.
`normalize_config`([data, strict])	Normalized the argument.
`optional_input_files`()	The optional input files to run a Gaussian task.
`run_task`(command, out)	Defines how one FP task runs

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

static args() → List[Argument][source]

The argument definition of the run_task method.

Returns:

arguments: List[dargs.Argument]: List of dargs.Argument defines the arguments of run_task method.

input_files() → List[str][source]

The mandatory input files to run a Gaussian task.

Returns:

files: List[str]: A list of madatory input files names.

optional_input_files() → List[str][source]

The optional input files to run a Gaussian task.

Returns:

files: List[str]: A list of optional input files names.

run_task(command: str, out: str) → Tuple[str, str][source]

Defines how one FP task runs

Parameters:

commandstr: The command of running gaussian task
outstr: The name of the output data file.

Returns:

out_name: str: The file name of the output data in the dpdata.LabeledSystem format.
log_name: str: The file name of the log.

dpgen2.fp.prep_fp module

class dpgen2.fp.prep_fp.PrepFp(*args, **kwargs)[source]

Bases: OP, ABC

Prepares the working directories for first-principles (FP) tasks.

A list of (same length as ip[“confs”]) working directories containing all files needed to start FP tasks will be created. The paths of the directories will be returned as op[“task_paths”]. The identities of the tasks are returned as op[“task_names”].

Attributes:

key
workflow_name

Methods

`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`prep_task`(conf_frame, inputs)	Define how one FP task is prepared.

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

execute(ip: OPIO) → OPIO[source]

Execute the OP.

Parameters:

ipdict

Input dict with components:

config : (dict) Should have config[‘inputs’], which defines the input files of the FP task.
confs : (Artifact(List[Path])) Configurations for the FP tasks. Stored in folders as deepmd/npy format. Can be parsed as dpdata.MultiSystems.

Returns:

opdict

Output dict with components:

task_names: (List[str]) The name of tasks. Will be used as the identities of the tasks. The names of different tasks are different.
task_paths: (Artifact(List[Path])) The parepared working paths of the tasks. Contains all input files needed to start the FP. The order fo the Paths should be consistent with op[“task_names”]

classmethod get_input_sign()[source]: Get the signature of the inputs

classmethod get_output_sign()[source]: Get the signature of the outputs

abstract prep_task(conf_frame: System, inputs: Any)[source]

Define how one FP task is prepared.

Parameters:

conf_framedpdata.System: One frame of configuration in the dpdata format.
inputsAny: The class object handels all other input files of the task. For example, pseudopotential file, k-point file and so on.

dpgen2.fp.run_fp module

class dpgen2.fp.run_fp.RunFp(*args, **kwargs)[source]

Bases: OP, ABC

Execute a first-principles (FP) task.

A working directory named task_name is created. All input files are copied or symbol linked to directory task_name. The FP command is exectuted from directory task_name. The op[“labeled_data”] in “deepmd/npy” format (HF5 in the future) provided by dpdata will be created.

Attributes:

key
workflow_name

Methods

`args`()	The argument definition of the run_task method.
`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`input_files`()	The mandatory input files to run a FP task.
`normalize_config`([data, strict])	Normalized the argument.
`optional_input_files`()	The optional input files to run a FP task.
`run_task`(**kwargs)	Defines how one FP task runs

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

abstract static args() → List[Argument][source]

The argument definition of the run_task method.

Returns:

arguments: List[dargs.Argument]: List of dargs.Argument defines the arguments of run_task method.

execute(ip: OPIO) → OPIO[source]

Execute the OP.

Parameters:

ipdict

Input dict with components:

config: (dict) The config of FP task. Should have config[‘run’], which defines the runtime configuration of the FP task.
task_name: (str) The name of task.
task_path: (Artifact(Path)) The path that contains all input files prepareed by PrepFp.

Returns:

Output dict with components:

log: (Artifact(Path)) The log file of FP.
labeled_data: (Artifact(Path)) The path to the labeled data in “deepmd/npy” format provided by dpdata.

Raises:

TransientError: On the failure of FP execution.
FatalError: When mandatory files are not found.

classmethod get_input_sign()[source]: Get the signature of the inputs

classmethod get_output_sign()[source]: Get the signature of the outputs

abstract input_files() → List[str][source]

The mandatory input files to run a FP task.

Returns:

files: List[str]: A list of madatory input files names.

classmethod normalize_config(data: Dict = {}, strict: bool = True) → Dict[source]

Normalized the argument.

Parameters:

dataDict: The input dict of arguments.
strictbool: Strictly check the arguments.

Returns:

data: Dict: The normalized arguments.

abstract optional_input_files() → List[str][source]

The optional input files to run a FP task.

Returns:

files: List[str]: A list of optional input files names.

abstract run_task(**kwargs) → Tuple[str, str][source]

Defines how one FP task runs

Parameters:

**kwargs: Keyword args defined by the developer. The fp/run_config session of the input file will be passed to this function.

Returns:

out_name: str: The file name of the output data. Should be in dpdata.LabeledSystem format.
log_name: str: The file name of the log.

dpgen2.fp.vasp module

class dpgen2.fp.vasp.PrepVasp(*args, **kwargs)[source]

Bases: PrepFp

Attributes:

key
workflow_name

Methods

`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`prep_task`(conf_frame, vasp_inputs)	Define how one Vasp task is prepared.

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

prep_task(conf_frame: System, vasp_inputs: VaspInputs)[source]

Define how one Vasp task is prepared.

Parameters:

conf_framedpdata.System: One frame of configuration in the dpdata format.
vasp_inputsVaspInputs: The VaspInputs object handels all other input files of the task.

class dpgen2.fp.vasp.RunVasp(*args, **kwargs)[source]

Bases: RunFp

Attributes:

key
workflow_name

Methods

`args`()	The argument definition of the run_task method.
`execute`(ip)	Execute the OP.
`get_input_sign`()	Get the signature of the inputs
`get_output_sign`()	Get the signature of the outputs
`input_files`()	The mandatory input files to run a vasp task.
`normalize_config`([data, strict])	Normalized the argument.
`optional_input_files`()	The optional input files to run a vasp task.
`run_task`(command, out, log)	Defines how one FP task runs

convert_to_graph
exec_sign_check
from_graph
function
get_info
get_input_artifact_link
get_input_artifact_storage_key
get_opio_info
get_output_artifact_link
get_output_artifact_storage_key
register_output_artifact
superfunction

static args()[source]

The argument definition of the run_task method.

Returns:

arguments: List[dargs.Argument]: List of dargs.Argument defines the arguments of run_task method.

input_files() → List[str][source]

The mandatory input files to run a vasp task.

Returns:

files: List[str]: A list of madatory input files names.

optional_input_files() → List[str][source]

The optional input files to run a vasp task.

Returns:

files: List[str]: A list of optional input files names.

run_task(command: str, out: str, log: str) → Tuple[str, str][source]

Defines how one FP task runs

Parameters:

commandstr: The command of running vasp task
outstr: The name of the output data file.
logstr: The name of the log file

Returns:

out_name: str: The file name of the output data in the dpdata.LabeledSystem format.
log_name: str: The file name of the log.

dpgen2.fp.vasp_input module

class dpgen2.fp.vasp_input.VaspInputs(kspacing: float | List[float], incar: str, pp_files: Dict[str, str], kgamma: bool = True)[source]

Bases: object

Attributes:

incar_template
potcars

Methods

args
incar_from_file
make_kpoints
make_potcar
normalize_config
potcars_from_file

static args()[source]

incar_from_file(fname: str)[source]

property incar_template

make_kpoints(box: ndarray) → str[source]

make_potcar(atom_names) → str[source]

static normalize_config(data={}, strict=True)[source]

property potcars

potcars_from_file(dict_fnames: Dict[str, str])[source]

dpgen2.fp.vasp_input.make_kspacing_kpoints(box, kspacing, kgamma)[source]