aesp.calculator package

Contents

aesp.calculator package#

Submodules#

aesp.calculator.abacus module#

class aesp.calculator.abacus.AbacusInputs(input_file: str | Path, pp_files: Dict[str, str | Path], element_mass: Dict[str, float] | None = None, kpt_file: str | Path | None = None, orb_files: Dict[str, str | Path] | None = None, deepks_descriptor: str | Path | None = None, deepks_model: str | Path | None = None)#

Bases: object

get_deepks_descriptor()#
get_deepks_model()#
get_input()#
get_mass(element_list: List[str]) → List[float]#

Get the mass of elements. If the element is not specified in self._mass, this funciton will firstly search it in a standard element-mass dictionary. And if the element is also not found in the dictionary, the mass will be set to 1.0.

Parameters#

element_listList[str]

element name

Returns#

List[float]

the mass of each element

get_orb()#
get_pp()#
static read_inputf(inputf: str | Path) → dict#

Read INPUT and transfer to a dict.

Parameters#

inputfstr

INPUT file name

Returns#

dict[str,str]

all input parameters

set_deepks_descriptor(value: str)#
set_deepks_model(value: str)#
set_input(key: str, value: Any)#
set_mass(key: str, value: float)#
set_orb(key: str, value: str)#
set_pp(key: str, value: str)#
write_deepks()#

Check if INPUT is a deepks job, if yes, will return the deepks descriptor file name, else will return None.

Returns#

str

deepks descriptor file name or None.

write_input(inputf: str = 'INPUT')#
write_kpt(kptf='KPT')#
write_pporb(element_list: List[str])#

Based on element list, write the pp/orb files, and return a list of the filename.

Parameters#

element_listList[str]

a list of element name

Returns#

List[List]

a list of the list of pp files, and orbital files

class aesp.calculator.abacus.FpOpAbacusInputs(input_file: str | Path, pp_files: Dict[str, str | Path], element_mass: Dict[str, float] | None = None, kpt_file: str | Path | None = None, orb_files: Dict[str, str | Path] | None = None, deepks_descriptor: str | Path | None = None, deepks_model: str | Path | None = None)#

Bases: AbacusInputs

static args()#
class aesp.calculator.abacus.PrepAbacus(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame, inputs: AbacusInputs, prepare_image_config: Dict | None = None, optional_input: Dict | None = None, optional_artifact: Dict | None = None)#

Define how one Abacus task is prepared.

Parameters#

conf_framedpdata.System

One frame of configuration in the dpdata format.

inputs: AbacusInputs

The AbacusInputs object handels all other input files of the task.

prepare_image_config: Dict

Definition of runtime parameters in the process of preparing tasks.

optional_input:

Other parameters the developers or users may need.

optional_artifact

Other files that users or developers need.

class aesp.calculator.abacus.PrepFpOpAbacus(*args, **kwargs)#

Bases: OP

execute(ip: OPIO) → OPIO#

Run the OP

classmethod get_input_sign()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

class aesp.calculator.abacus.RunAbacus(*args, **kwargs)#

Bases: RunFp

check_run_success(log_name)#
input_files(task_path) → List[str]#

The mandatory input files to run an abacus task. Returns ——- files: List[str]

A list of madatory input files names.

run_task(backward_dir_name, log_name, backward_list: List[str], run_image_config: Dict | None = None, optional_input: Dict | None = None) → str#

Defines how one FP task runs Parameters ———- backward_dir_name:

The name of the directory which contains the backward files.

log_name:

The name of log file.

backward_list:

The output files the users need.

run_image_config:

Keyword args defined by the developer.For example: {

“command”: “source /opt/intel/oneapi/setvars.sh && mpirun -n 16 abacus”

}

optional_input:

The parameters developers need in runtime.

Returns#

backward_dir_name: str

The directory name which containers the files users need.

class aesp.calculator.abacus.RunFpOpAbacus(*args, **kwargs)#

Bases: OP

static args()#
execute(ip: OPIO) → OPIO#

Run the OP

classmethod get_input_sign()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

aesp.calculator.abacus.get_pporbdpks_from_stru(stru: str = 'STRU')#

read the label, pp, orb, cell, coord, deepks-descriptor

aesp.calculator.abacus.get_suffix_calculation(INPUT: List[str]) → Tuple[str, str]#

aesp.calculator.base module#

class aesp.calculator.base.PrepFp(*args, **kwargs)#

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”].

execute(ip: OPIO) → OPIO#

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()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

abstractmethod prep_task(conf_frame: System, inputs: Any)#

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.

class aesp.calculator.base.RunFp(*args, **kwargs)#

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.

abstractmethod static args() → List[Argument]#

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#

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()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

abstractmethod input_files() → List[str]#

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#

Normalized the argument.

Parameters#

dataDict

The input dict of arguments.

strictbool

Strictly check the arguments.

Returns#

data: Dict

The normalized arguments.

abstractmethod optional_input_files() → List[str]#

The optional input files to run a FP task.

Returns#

files: List[str]

A list of optional input files names.

abstractmethod run_task(**kwargs) → Tuple[str, str]#

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.

aesp.calculator.base.run_command(cmd: str | List[str], shell: bool = False) → Tuple[int, str, str]#

aesp.calculator.cp2k module#

class aesp.calculator.cp2k.Cp2kInputs(inp_file: str)#

Bases: object

static args()#

Define the arguments required by the Cp2kInputs class.

inp_file_from_file(fname: str)#

Read the content of the input file and store it.

Parameters#

fnamestr

The path to the input file.

property inp_template#

Return the template content of the input file.

class aesp.calculator.cp2k.FpOpCp2kInputs(inp_file: str)#

Bases: Cp2kInputs

static args()#

Define the arguments required by the Cp2kInputs class.

class aesp.calculator.cp2k.PrepCp2k(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, inputs: Cp2kInputs, prepare_image_config: Dict | None = None, optional_input: Dict | None = None, optional_artifact: Dict | None = None)#

Define how one CP2K task is prepared.

Parameters#

conf_framedpdata.System

One frame of configuration in the dpdata format.

inputs: Cp2kInputs

The Cp2kInputs object handles the input file of the task.

prepare_image_config: Dict, optional

Definition of runtime parameters in the process of preparing tasks.

optional_input: Dict, optional

Other parameters the developers or users may need.

optional_artifact: Dict[str, Path], optional

Other files that users or developers need.

class aesp.calculator.cp2k.PrepFpOpCp2k(*args, **kwargs)#

Bases: OP

execute(ip: OPIO) → OPIO#

Run the OP

classmethod get_input_sign()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

class aesp.calculator.cp2k.RunCp2k(*args, **kwargs)#

Bases: RunFp

check_run_success(log_name)#

Check if the CP2K task ran successfully by examining the output file.

Returns#

successbool

True if the task ran successfully with warnings line, False otherwise.

input_files(task_path) → List[str]#

The mandatory input files to run a CP2K task.

Returns#

files: List[str]

A list of mandatory input file names.

run_task(backward_dir_name, log_name, backward_list: List[str], run_image_config: Dict | None = None, optional_input: Dict | None = None) → str#

Defines how one FP task runs.

Parameters#

backward_dir_namestr

The name of the directory which contains the backward files.

log_namestr

The name of log file.

backward_listList[str]

The output files the users need. For example: [“output.log”, “trajectory.xyz”]

run_image_configDict, optional

Keyword args defined by the developer. For example: {

“command”: “source /opt/intel/oneapi/setvars.sh && mpirun -n 64 /opt/cp2k/bin/cp2k.popt”

}

optional_inputDict, optional

The parameters developers need in runtime. For example: {

“conf_format”: “cp2k/input”

}

Returns#

backward_dir_namestr

The directory name which contains the files users need.

class aesp.calculator.cp2k.RunFpOpCp2k(*args, **kwargs)#

Bases: OP

static args()#
execute(ip: OPIO) → OPIO#

Run the OP

classmethod get_input_sign()#

Get the signature of the inputs

classmethod get_output_sign()#

Get the signature of the outputs

aesp.calculator.cp2k.get_run_type(lines: List[str]) → str | None#

aesp.calculator.dpmd module#

class aesp.calculator.dpmd.DpmdInputs(pstress, relax_cell, step_max, f_max, model: str)#

Bases: object

static args()#
incar_from_file(pstress, relax_cell, step_max, f_max, model: str)#
property incar_template#
static normalize_config(data={}, strict=True)#
class aesp.calculator.dpmd.PrepDpmd(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, dpmd_inputs: DpmdInputs)#

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 aesp.calculator.dpmd.RunDpmd(*args, **kwargs)#

Bases: RunFp

static args()#

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]#

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]#

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]#

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.

aesp.calculator.emt module#

class aesp.calculator.emt.EmtInputs(pstress, relax_cell, step_max, f_max)#

Bases: object

static args()#
incar_from_file(pstress, relax_cell, step_max, f_max)#
property incar_template#
static normalize_config(data={}, strict=True)#
class aesp.calculator.emt.PrepEmt(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, emt_inputs: EmtInputs)#

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 aesp.calculator.emt.RunEmt(*args, **kwargs)#

Bases: RunFp

static args()#

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]#

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]#

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]#

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.

aesp.calculator.gaussian module#

Prep and Run Gaussian tasks.

class aesp.calculator.gaussian.GaussianInputs(**kwargs: Any)#

Bases: object

static args() → List[Argument]#

The arguments of the GaussianInputs class.

class aesp.calculator.gaussian.PrepGaussian(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, inputs: GaussianInputs)#

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 aesp.calculator.gaussian.RunGaussian(*args, **kwargs)#

Bases: RunFp

static args() → List[Argument]#

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]#

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]#

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]#

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.

aesp.calculator.gulp module#

class aesp.calculator.gulp.GulpInputs(kw_file: str, pp_file: str)#

Bases: object

static args()#
from_file(fname: str)#
static normalize_config(data={}, strict=True)#
class aesp.calculator.gulp.PrepGulp(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, gulp_inputs: GulpInputs)#

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 aesp.calculator.gulp.RunGulp(*args, **kwargs)#

Bases: RunFp

static args()#

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]#

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]#

The optional input files to run a vasp task.

Returns#

files: List[str]

A list of optional input files names.

static process_data(out_name, log_name)#
run_task(command: str, out: str, log: str) → Tuple[str, str]#

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.

aesp.calculator.matgl module#

class aesp.calculator.matgl.MatglInputs(pstress, relax_cell, step_max, f_max, model: str)#

Bases: object

static args()#
incar_from_file(pstress, relax_cell, step_max, f_max, model: str)#
property incar_template#
static normalize_config(data={}, strict=True)#
class aesp.calculator.matgl.PrepMatgl(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, matgl_inputs: MatglInputs)#

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 aesp.calculator.matgl.RunMatgl(*args, **kwargs)#

Bases: RunFp

static args()#

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]#

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]#

The optional input files to run a vasp task.

Returns#

files: List[str]

A list of optional input files names.

static process_data(out_name)#
run_task(command: str, out: str, log: str) → Tuple[str, str]#

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.

aesp.calculator.vasp module#

class aesp.calculator.vasp.PrepVasp(*args, **kwargs)#

Bases: PrepFp

prep_task(conf_frame: System, vasp_inputs: VaspInputs)#

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 aesp.calculator.vasp.RunVasp(*args, **kwargs)#

Bases: RunFp

static args()#

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]#

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]#

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]#

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.

class aesp.calculator.vasp.VaspInputs(kspacing: float | List[float], incar: str, pp_files: Dict[str, str], kgamma: bool = True)#

Bases: object

static args()#
incar_from_file(fname: str)#
property incar_template#
make_kpoints(box: ndarray) → str#
make_potcar(atom_names) → str#
static normalize_config(data={}, strict=True)#
property potcars#
potcars_from_file(dict_fnames: Dict[str, str])#
aesp.calculator.vasp.make_kspacing_kpoints(box, kspacing, kgamma)#
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