dpgen.simplify package#

Submodules#

dpgen.simplify.arginfo module#

dpgen.simplify.arginfo.fp_args() list[Argument][source]#

Generate arginfo for fp.

Returns:
List[Argument]

arginfo

dpgen.simplify.arginfo.fp_style_variant_type_args() Variant[source]#

Generate variant for fp style variant type.

Returns:
Variant

variant for fp style

dpgen.simplify.arginfo.general_simplify_arginfo() Argument[source]#

General simplify arginfo.

Returns:
Argument

arginfo

dpgen.simplify.arginfo.simplify_jdata_arginfo() Argument[source]#

Generate arginfo for dpgen simplify jdata.

Returns:
Argument

arginfo

dpgen.simplify.arginfo.simplify_mdata_arginfo() Argument[source]#

Generate arginfo for dpgen simplify mdata.

Returns:
Argument

arginfo

dpgen.simplify.simplify module#

Simplify dataset (minimize the dataset size).

Init: pick up init data from dataset randomly

Iter: 00: train models (same as generator) 01: calculate model deviations of the rest dataset, pick up data with proper model deviaiton 02: fp (optional, if the original dataset do not have fp data, same as generator)

dpgen.simplify.simplify.gen_simplify(args)[source]#
dpgen.simplify.simplify.get_multi_system(path: str | list[str], jdata: dict) MultiSystems[source]#

Get MultiSystems from a path or list of paths.

Both NumPy and HDF5 formats are supported. For details of two formats, refer to DeePMD-kit documentation.

If labeled in jdata is True, returns MultiSystems with LabeledSystem. Otherwise, returns MultiSystems with System.

Parameters:
pathstr or list of str

path or list of paths to the dataset

jdatadict

parameters which may contain labeled key

Returns:
dpdata.MultiSystems

MultiSystems with LabeledSystem or System

dpgen.simplify.simplify.get_system_cls(jdata)[source]#
dpgen.simplify.simplify.init_model(iter_index, jdata, mdata)[source]#
dpgen.simplify.simplify.init_model_dp(iter_index, jdata, mdata)[source]#
dpgen.simplify.simplify.init_pick(iter_index, jdata, mdata)[source]#

Pick up init data from dataset randomly.

dpgen.simplify.simplify.make_fp(iter_index, jdata, mdata)[source]#
dpgen.simplify.simplify.make_fp_configs(iter_index, jdata)[source]#
dpgen.simplify.simplify.make_fp_labeled(iter_index, jdata)[source]#
dpgen.simplify.simplify.make_model_devi(iter_index, jdata, mdata)[source]#

Calculate the model deviation of the rest idx.

dpgen.simplify.simplify.post_model_devi(iter_index, jdata, mdata)[source]#

Calculate the model deviation.

dpgen.simplify.simplify.run_iter(param_file, machine_file)[source]#

Init (iter 0): init_pick.

tasks (iter > 0): 00 make_train (same as generator) 01 run_train (same as generator) 02 post_train (same as generator) 03 make_model_devi 04 run_model_devi 05 post_model_devi 06 make_fp 07 run_fp (same as generator) 08 post_fp (same as generator)

dpgen.simplify.simplify.run_model_devi(iter_index, jdata, mdata)[source]#

Submit dp test tasks.