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@@ -23,10 +23,10 @@ Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, and
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## Download and Install
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DP-GEN only supports Python 3.9 and above. You can use one of the following methods to install DP-GEN:
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DP-GEN only supports Python 3.9 and above. You can [setup a conda/pip environment](https://docs.deepmodeling.com/faq/conda.html), and then use one of the following methods to install DP-GEN:
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- Install via pip: `pip install dpgen`
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- Install via conda: `conda install -c conda-forge dpgen``
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- Install via conda: `conda install -c conda-forge dpgen`
doc_numb_models="Number of models to be trained in 00.train. 4 is recommend."
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doc_training_iter0_model_path="The model used to init the first iter training. Number of element should be equal to numb_models."
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doc_training_init_model="Iteration > 0, the model parameters will be initilized from the model trained at the previous iteration. Iteration == 0, the model parameters will be initialized from training_iter0_model_path."
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doc_default_training_param="Training parameters for deepmd-kit in 00.train. You can find instructions from here: (https://github.com/deepmodeling/deepmd-kit)."
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doc_default_training_param="Training parameters for deepmd-kit in 00.train. You can find instructions from `DeePMD-kit documentation <https://docs.deepmodeling.org/projects/deepmd/>`_."
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doc_dp_train_skip_neighbor_stat="Append --skip-neighbor-stat flag to dp train."
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doc_dp_compress="Use dp compress to compress the model."
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doc_training_reuse_iter="The minimal index of iteration that continues training models from old models of last iteration."
doc_model_devi_f_trust_hi="Upper bound of forces for the selection. If list or dict, should be set for each index in sys_configs, respectively."
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doc_model_devi_v_trust_lo="Lower bound of virial for the selection. If list or dict, should be set for each index in sys_configs, respectively. Should be used with DeePMD-kit v2.x."
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doc_model_devi_v_trust_hi="Upper bound of virial for the selection. If list or dict, should be set for each index in sys_configs, respectively. Should be used with DeePMD-kit v2.x."
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doc_model_devi_adapt_trust_lo="Adaptively determines the lower trust levels of force and virial. This option should be used together with model_devi_numb_candi_f, model_devi_numb_candi_v and optionally with model_devi_perc_candi_f and model_devi_perc_candi_v. dpgen will make two sets:\n\n\
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doc_model_devi_adapt_trust_lo= (
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"Adaptively determines the lower trust levels of force and virial. This option should be used together with model_devi_numb_candi_f, model_devi_numb_candi_v and optionally with model_devi_perc_candi_f and model_devi_perc_candi_v. dpgen will make two sets:\n\n\
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- 1. From the frames with force model deviation lower than model_devi_f_trust_hi, select max(model_devi_numb_candi_f, model_devi_perc_candi_f*n_frames) frames with largest force model deviation. \n\n\
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- 2. From the frames with virial model deviation lower than model_devi_v_trust_hi, select max(model_devi_numb_candi_v, model_devi_perc_candi_v*n_frames) frames with largest virial model deviation. \n\n\
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The union of the two sets is made as candidate dataset."
"""Arguments for FP style pwscf (Quantum Espresso).
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Returns
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-------
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list[dargs.Argument]
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list of pwscf fp style arguments
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"""
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doc_fp_pp_path="Directory of psuedo-potential file to be used for 02.fp exists."
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doc_fp_pp_files="Psuedo-potential file to be used for 02.fp. Note that the order of elements should correspond to the order in type_map."
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doc_user_fp_params="Parameters for pwscf calculation. Find details at https://www.quantum-espresso.org/Doc/INPUT_PW.html. When user_fp_params is set, the settings in fp_params will be ignored. If one wants to use user_fp_params, kspacing must be set in user_fp_params. kspacing is the spacing between kpoints, and helps to determin KPOINTS in pwscf."
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doc_fp_params= (
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"Parameters for pwscf calculation. It has lower priority than user_fp_params."
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)
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doc_ecut="ecutwfc in pwscf."
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doc_ediff="conv_thr and ts_vdw_econv_thr in pwscf."
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doc_kspacing="The spacing between kpoints. Helps to determin KPOINTS in pwscf."
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