diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml new file mode 100644 index 000000000..becafd6d3 --- /dev/null +++ b/.github/workflows/test.yml @@ -0,0 +1,25 @@ +name: Python package + +on: + - push + - pull_request + +jobs: + build: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: [3.7, 3.8] + PYMATGEN_VERSION: [2019.1.13, 2019.7.30] + + steps: + - uses: actions/checkout@v2 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v2 + with: + python-version: ${{ matrix.python-version }} + - name: Install dependencies + run: pip install coverage codecov pymatgen==${{ matrix.PYMATGEN_VERSION }} . + - name: Test + run: coverage run --source=./dpgen -m unittest -v && coverage report + - run: codecov diff --git a/.gitignore b/.gitignore index 59c551707..0bf470ad4 100644 --- a/.gitignore +++ b/.gitignore @@ -37,4 +37,5 @@ dpgen.egg-info .eggs .coverage dbconfig.json -.vscode/* \ No newline at end of file +.vscode/* +.idea/* diff --git a/.travis.yml b/.travis.yml deleted file mode 100644 index bad74118a..000000000 --- a/.travis.yml +++ /dev/null @@ -1,19 +0,0 @@ -language: python -python: - - "3.6" - - "3.7" -# command to install dependencies -env: - matrix: - - PYMATGEN_VERSION=2019.1.13 - - PYMATGEN_VERSION=2019.7.30 -before_install: - - pip install --upgrade pip coverage codecov - - pip install pymatgen==$PYMATGEN_VERSION -install: - - pip install . -# command to run tests -script: - - coverage run --source=./dpgen -m unittest -v && coverage report -after_success: - - codecov diff --git a/README.md b/README.md index ffce3a901..dbefd954f 100644 --- a/README.md +++ b/README.md @@ -571,7 +571,8 @@ The bold notation of key (such aas **type_map**) means that it's a necessary key |**fp_params["mixingweight"]** | Float| 0.05 | Proportion a of output Density Matrix to be used for the input Density Matrix of next SCF cycle (linear mixing). |**fp_params["NumberPulay"]** | Integer| 5 | Controls the Pulay convergence accelerator. | *fp_style == cp2k* -| **fp_params** | Dict | |Parameters for cp2k calculation. find detail in manual.cp2k.org. only the kind section must be set before use. we assume that you have basic knowledge for cp2k input. +| **user_fp_params** | Dict | |Parameters for cp2k calculation. find detail in manual.cp2k.org. only the kind section must be set before use. we assume that you have basic knowledge for cp2k input. +| **external_input_path** | String | | Conflict with key:user_fp_params, use the template input provided by user, some rules should be followed, read the following text in detail. #### Rules for cp2k input at dictionary form @@ -609,9 +610,54 @@ Here are examples for setting: } } } + ``` + +#### Rules for use cp2k template input provided by user + +See Full example template.inp and dpgen input parameter file in + +`tests/generator/cp2k_make_fp_files/exinput/template.inp` and `tests/generator/param-mgo-cp2k-exinput.json` + +Here is example for provide external input + +```python + { + "_comment": " 02.fp ", + "fp_style": "cp2k", + "shuffle_poscar": false, + "fp_task_max": 100, + "fp_task_min": 10, + "fp_pp_path": ".", + "fp_pp_files": [], + "external_input_path": "./cp2k_make_fp_files/exinput/template.inp", + "_comment": " that's all + } ``` +the following essential section should be provided in user template +``` + + &FORCE_EVAL + # add this line if you need to fit virial + STRESS_TENSOR ANALYTICAL + &PRINT + &FORCES ON + &END FORCES + # add this line if you need to fit virial + &STRESS_TENSOR ON + &END FORCES + &END PRINT + &SUBSYS + &CELL + ABC LEFT FOR DPGEN + &END CELL + &COORD + @include coord.xyz + &END COORD + &END SUBSYS +&END FORCE_EVAL +``` ## Test: Auto-test for Deep Generator ### configure and param.json diff --git a/dpgen/__init__.py b/dpgen/__init__.py index b38875dee..b89688542 100644 --- a/dpgen/__init__.py +++ b/dpgen/__init__.py @@ -8,7 +8,7 @@ SHORT_CMD="dpgen" dlog = logging.getLogger(__name__) dlog.setLevel(logging.INFO) -dlogf = logging.FileHandler(os.getcwd()+os.sep+SHORT_CMD+'.log') +dlogf = logging.FileHandler(os.getcwd()+os.sep+SHORT_CMD+'.log', delay=True) dlogf_formatter=logging.Formatter('%(asctime)s - %(levelname)s : %(message)s') #dlogf_formatter=logging.Formatter('%(asctime)s - %(name)s - [%(filename)s:%(funcName)s - %(lineno)d ] - %(levelname)s \n %(message)s') dlogf.setFormatter(dlogf_formatter) diff --git a/dpgen/auto_test/EOS.py b/dpgen/auto_test/EOS.py new file mode 100644 index 000000000..b69db6e1c --- /dev/null +++ b/dpgen/auto_test/EOS.py @@ -0,0 +1,187 @@ +import glob +import json +import os +import re + +import numpy as np +from monty.serialization import loadfn, dumpfn + +import dpgen.auto_test.lib.vasp as vasp +from dpgen import dlog +from dpgen.auto_test.Property import Property +from dpgen.auto_test.refine import make_refine +from dpgen.auto_test.reproduce import make_repro +from dpgen.auto_test.reproduce import post_repro + + +class EOS(Property): + def __init__(self, + parameter): + parameter['reproduce'] = parameter.get('reproduce', False) + self.reprod = parameter['reproduce'] + if not self.reprod: + if not ('init_from_suffix' in parameter and 'output_suffix' in parameter): + self.vol_start = parameter['vol_start'] + self.vol_end = parameter['vol_end'] + self.vol_step = parameter['vol_step'] + parameter['cal_type'] = parameter.get('cal_type', 'relaxation') + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": True, + "relax_shape": True, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + else: + parameter['cal_type'] = 'static' + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": False, + "relax_shape": False, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + parameter['init_from_suffix'] = parameter.get('init_from_suffix', '00') + self.init_from_suffix = parameter['init_from_suffix'] + self.parameter = parameter + + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + path_to_work = os.path.abspath(path_to_work) + if os.path.exists(path_to_work): + dlog.warning('%s already exists' % path_to_work) + else: + os.makedirs(path_to_work) + path_to_equi = os.path.abspath(path_to_equi) + + if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): + init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) + struct_init_name_list = [] + for ii in init_path_list: + struct_init_name_list.append(ii.split('/')[-1]) + struct_output_name = path_to_work.split('/')[-2] + assert struct_output_name in struct_init_name_list + path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], + struct_output_name, 'relaxation', 'relax_task')) + + cwd = os.getcwd() + task_list = [] + if self.reprod: + print('eos reproduce starts') + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + task_list = make_repro(init_data_path, self.init_from_suffix, + path_to_work, self.parameter.get('reprod_last_frame', True)) + os.chdir(cwd) + + else: + if refine: + print('eos refine starts') + task_list = make_refine(self.parameter['init_from_suffix'], + self.parameter['output_suffix'], + path_to_work) + os.chdir(cwd) + + init_from_path = re.sub(self.parameter['output_suffix'][::-1], + self.parameter['init_from_suffix'][::-1], + path_to_work[::-1], count=1)[::-1] + task_list_basename = list(map(os.path.basename, task_list)) + + for ii in task_list_basename: + init_from_task = os.path.join(init_from_path, ii) + output_task = os.path.join(path_to_work, ii) + os.chdir(output_task) + if os.path.isfile('eos.json'): + os.remove('eos.json') + if os.path.islink('eos.json'): + os.remove('eos.json') + os.symlink(os.path.relpath(os.path.join(init_from_task, 'eos.json')), 'eos.json') + os.chdir(cwd) + + else: + print('gen eos from ' + str(self.vol_start) + ' to ' + str(self.vol_end) + ' by every ' + str(self.vol_step)) + equi_contcar = os.path.join(path_to_equi, 'CONTCAR') + if not os.path.exists(equi_contcar): + raise RuntimeError("please do relaxation first") + vol_to_poscar = vasp.poscar_vol(equi_contcar) / vasp.poscar_natoms(equi_contcar) + self.parameter['scale2equi'] = [] + + task_num = 0 + while self.vol_start + self.vol_step * task_num < self.vol_end: + # for vol in np.arange(int(self.vol_start * 100), int(self.vol_end * 100), int(self.vol_step * 100)): + # vol = vol / 100.0 + vol = self.vol_start + task_num * self.vol_step + #task_num = int((vol - self.vol_start) / self.vol_step) + output_task = os.path.join(path_to_work, 'task.%06d' % task_num) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for ii in ['INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(ii): + os.remove(ii) + task_list.append(output_task) + os.symlink(os.path.relpath(equi_contcar), 'POSCAR.orig') + # scale = (vol / vol_to_poscar) ** (1. / 3.) + scale = vol ** (1. / 3.) + eos_params = {'volume': vol * vol_to_poscar, 'scale': scale} + dumpfn(eos_params, 'eos.json', indent=4) + self.parameter['scale2equi'].append(scale) # 06/22 + vasp.poscar_scale('POSCAR.orig', 'POSCAR', scale) + task_num += 1 + os.chdir(cwd) + return task_list + + def post_process(self, task_list): + pass + + def task_type(self): + return self.parameter['type'] + + def task_param(self): + return self.parameter + + def _compute_lower(self, + output_file, + all_tasks, + all_res): + output_file = os.path.abspath(output_file) + res_data = {} + ptr_data = "conf_dir: " + os.path.dirname(output_file) + "\n" + if not self.reprod: + ptr_data += ' VpA(A^3) EpA(eV)\n' + for ii in range(len(all_tasks)): + # vol = self.vol_start + ii * self.vol_step + vol = loadfn(os.path.join(all_tasks[ii], 'eos.json'))['volume'] + task_result = loadfn(all_res[ii]) + res_data[vol] = task_result['energies'][-1] / task_result['atom_numbs'][0] + ptr_data += '%7.3f %8.4f \n' % (vol, task_result['energies'][-1] / task_result['atom_numbs'][0]) + # res_data[vol] = all_res[ii]['energy'] / len(all_res[ii]['force']) + # ptr_data += '%7.3f %8.4f \n' % (vol, all_res[ii]['energy'] / len(all_res[ii]['force'])) + + else: + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + res_data, ptr_data = post_repro(init_data_path, self.parameter['init_from_suffix'], + all_tasks, ptr_data, self.parameter.get('reprod_last_frame', True)) + + with open(output_file, 'w') as fp: + json.dump(res_data, fp, indent=4) + + return res_data, ptr_data diff --git a/dpgen/auto_test/Elastic.py b/dpgen/auto_test/Elastic.py new file mode 100644 index 000000000..f3e0a64ca --- /dev/null +++ b/dpgen/auto_test/Elastic.py @@ -0,0 +1,224 @@ +import glob +import os +from shutil import copyfile +import re + +from monty.serialization import loadfn, dumpfn +from pymatgen.analysis.elasticity.elastic import ElasticTensor +from pymatgen.analysis.elasticity.strain import DeformedStructureSet, Strain +from pymatgen.analysis.elasticity.stress import Stress +from pymatgen.core.structure import Structure +from pymatgen.io.vasp import Incar, Kpoints + +import dpgen.auto_test.lib.vasp as vasp +from dpgen import dlog +from dpgen.auto_test.Property import Property +from dpgen.auto_test.refine import make_refine +from dpgen.generator.lib.vasp import incar_upper + + +class Elastic(Property): + def __init__(self, + parameter): + if not ('init_from_suffix' in parameter and 'output_suffix' in parameter): + default_norm_def = 2e-3 + default_shear_def = 5e-3 + parameter['norm_deform'] = parameter.get('norm_deform', default_norm_def) + self.norm_deform = parameter['norm_deform'] + parameter['shear_deform'] = parameter.get('shear_deform', default_shear_def) + self.shear_deform = parameter['shear_deform'] + parameter['cal_type'] = parameter.get('cal_type', 'relaxation') + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": True, + "relax_shape": False, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + # parameter['reproduce'] = False + # self.reprod = parameter['reproduce'] + self.parameter = parameter + + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + path_to_work = os.path.abspath(path_to_work) + if os.path.exists(path_to_work): + dlog.warning('%s already exists' % path_to_work) + else: + os.makedirs(path_to_work) + path_to_equi = os.path.abspath(path_to_equi) + + if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): + init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) + struct_init_name_list = [] + for ii in init_path_list: + struct_init_name_list.append(ii.split('/')[-1]) + struct_output_name = path_to_work.split('/')[-2] + assert struct_output_name in struct_init_name_list + path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], + struct_output_name, 'relaxation', 'relax_task')) + + task_list = [] + cwd = os.getcwd() + equi_contcar = os.path.join(path_to_equi, 'CONTCAR') + + os.chdir(path_to_work) + if os.path.isfile('POSCAR'): + os.remove('POSCAR') + if os.path.islink('POSCAR'): + os.remove('POSCAR') + os.symlink(os.path.relpath(equi_contcar), 'POSCAR') + # task_poscar = os.path.join(output, 'POSCAR') + + # stress, deal with unsupported stress in dpdata + #with open(os.path.join(path_to_equi, 'result.json')) as fin: + # equi_result = json.load(fin) + #equi_stress = np.array(equi_result['stress']['data'])[-1] + equi_result = loadfn(os.path.join(path_to_equi, 'result.json')) + equi_stress = equi_result['stress'][-1] + dumpfn(equi_stress, 'equi.stress.json', indent=4) + os.chdir(cwd) + + if refine: + print('elastic refine starts') + task_list = make_refine(self.parameter['init_from_suffix'], + self.parameter['output_suffix'], + path_to_work) + + # record strain + # df = Strain.from_deformation(dfm_ss.deformations[idid]) + # dumpfn(df.as_dict(), 'strain.json', indent=4) + init_from_path = re.sub(self.parameter['output_suffix'][::-1], + self.parameter['init_from_suffix'][::-1], + path_to_work[::-1], count=1)[::-1] + task_list_basename = list(map(os.path.basename, task_list)) + + for ii in task_list_basename: + init_from_task = os.path.join(init_from_path, ii) + output_task = os.path.join(path_to_work, ii) + os.chdir(output_task) + if os.path.isfile('strain.json'): + os.remove('strain.json') + copyfile(os.path.join(init_from_task, 'strain.json'), 'strain.json') + #os.symlink(os.path.relpath( + # os.path.join((re.sub(self.parameter['output_suffix'], self.parameter['init_from_suffix'], ii)), + # 'strain.json')), + # 'strain.json') + os.chdir(cwd) + else: + norm_def = self.norm_deform + shear_def = self.shear_deform + norm_strains = [-norm_def, -0.5 * norm_def, 0.5 * norm_def, norm_def] + shear_strains = [-shear_def, -0.5 * shear_def, 0.5 * shear_def, shear_def] + + if not os.path.exists(equi_contcar): + raise RuntimeError("please do relaxation first") + + ss = Structure.from_file(equi_contcar) + dfm_ss = DeformedStructureSet(ss, + symmetry=False, + norm_strains=norm_strains, + shear_strains=shear_strains) + n_dfm = len(dfm_ss) + + print('gen with norm ' + str(norm_strains)) + print('gen with shear ' + str(shear_strains)) + for ii in range(n_dfm): + output_task = os.path.join(path_to_work, 'task.%06d' % ii) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for jj in ['INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(jj): + os.remove(jj) + task_list.append(output_task) + dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR') + # record strain + df = Strain.from_deformation(dfm_ss.deformations[ii]) + dumpfn(df.as_dict(), 'strain.json', indent=4) + os.chdir(cwd) + return task_list + + def post_process(self, task_list): + cwd = os.getcwd() + poscar_start = os.path.abspath(os.path.join(task_list[0], '..', 'POSCAR')) + os.chdir(os.path.join(task_list[0], '..')) + if os.path.isfile(os.path.join(task_list[0], 'INCAR')): + incar = incar_upper(Incar.from_file(os.path.join(task_list[0], 'INCAR'))) + kspacing = incar.get('KSPACING') + kgamma = incar.get('KGAMMA', False) + ret = vasp.make_kspacing_kpoints(poscar_start, kspacing, kgamma) + kp = Kpoints.from_string(ret) + if os.path.isfile('KPOINTS'): + os.remove('KPOINTS') + kp.write_file("KPOINTS") + os.chdir(cwd) + kpoints_universal = os.path.abspath(os.path.join(task_list[0], '..', 'KPOINTS')) + for ii in task_list: + if os.path.isfile(os.path.join(ii, 'KPOINTS')): + os.remove(os.path.join(ii, 'KPOINTS')) + if os.path.islink(os.path.join(ii, 'KPOINTS')): + os.remove(os.path.join(ii, 'KPOINTS')) + os.chdir(ii) + os.symlink(os.path.relpath(kpoints_universal), 'KPOINTS') + os.chdir(cwd) + + def task_type(self): + return self.parameter['type'] + + def task_param(self): + return self.parameter + + def _compute_lower(self, + output_file, + all_tasks, + all_res): + output_file = os.path.abspath(output_file) + res_data = {} + ptr_data = os.path.dirname(output_file) + '\n' + equi_stress = Stress(loadfn(os.path.join(os.path.dirname(output_file), 'equi.stress.json'))) + lst_strain = [] + lst_stress = [] + for ii in all_tasks: + strain = loadfn(os.path.join(ii, 'strain.json')) + # stress, deal with unsupported stress in dpdata + #with open(os.path.join(ii, 'result_task.json')) as fin: + # task_result = json.load(fin) + #stress = np.array(task_result['stress']['data'])[-1] + stress = loadfn(os.path.join(ii, 'result_task.json'))['stress'][-1] + lst_strain.append(strain) + lst_stress.append(Stress(stress * -1000)) + + et = ElasticTensor.from_independent_strains(lst_strain, lst_stress, eq_stress=equi_stress, vasp=False) + res_data['elastic_tensor'] = [] + for ii in range(6): + for jj in range(6): + res_data['elastic_tensor'].append(et.voigt[ii][jj] / 1e4) + ptr_data += "%7.2f " % (et.voigt[ii][jj] / 1e4) + ptr_data += '\n' + + BV = et.k_voigt / 1e4 + GV = et.g_voigt / 1e4 + EV = 9 * BV * GV / (3 * BV + GV) + uV = 0.5 * (3 * BV - 2 * GV) / (3 * BV + GV) + + res_data['BV'] = BV + res_data['GV'] = GV + res_data['EV'] = EV + res_data['uV'] = uV + ptr_data += "# Bulk Modulus BV = %.2f GPa\n" % BV + ptr_data += "# Shear Modulus GV = %.2f GPa\n" % GV + ptr_data += "# Youngs Modulus EV = %.2f GPa\n" % EV + ptr_data += "# Poission Ratio uV = %.2f\n " % uV + + dumpfn(res_data, output_file, indent=4) + + return res_data, ptr_data diff --git a/dpgen/auto_test/Interstitial.py b/dpgen/auto_test/Interstitial.py new file mode 100644 index 000000000..9f781c88e --- /dev/null +++ b/dpgen/auto_test/Interstitial.py @@ -0,0 +1,251 @@ +import glob +import json +import os +import re + +from monty.serialization import loadfn, dumpfn +from pymatgen.analysis.defects.generators import InterstitialGenerator +from pymatgen.core.structure import Structure + +import dpgen.auto_test.lib.lammps as lammps +from dpgen.auto_test.Property import Property +from dpgen.auto_test.refine import make_refine +from dpgen.auto_test.reproduce import make_repro +from dpgen.auto_test.reproduce import post_repro + + +class Interstitial(Property): + def __init__(self, + parameter): + parameter['reproduce'] = parameter.get('reproduce', False) + self.reprod = parameter['reproduce'] + if not self.reprod: + if not ('init_from_suffix' in parameter and 'output_suffix' in parameter): + default_supercell = [1, 1, 1] + parameter['supercell'] = parameter.get('supercell', default_supercell) + self.supercell = parameter['supercell'] + self.insert_ele = parameter['insert_ele'] + parameter['cal_type'] = parameter.get('cal_type', 'relaxation') + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": True, + "relax_shape": True, + "relax_vol": True} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + else: + parameter['cal_type'] = 'static' + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": False, + "relax_shape": False, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + parameter['init_from_suffix'] = parameter.get('init_from_suffix', '00') + self.init_from_suffix = parameter['init_from_suffix'] + self.parameter = parameter + + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + path_to_work = os.path.abspath(path_to_work) + path_to_equi = os.path.abspath(path_to_equi) + + if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): + init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) + struct_init_name_list = [] + for ii in init_path_list: + struct_init_name_list.append(ii.split('/')[-1]) + struct_output_name = path_to_work.split('/')[-2] + assert struct_output_name in struct_init_name_list + path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], + struct_output_name, 'relaxation', 'relax_task')) + + task_list = [] + cwd = os.getcwd() + + if self.reprod: + print('interstitial reproduce starts') + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + task_list = make_repro(init_data_path, self.init_from_suffix, + path_to_work, self.parameter.get('reprod_last_frame', False)) + os.chdir(cwd) + + else: + if refine: + print('interstitial refine starts') + task_list = make_refine(self.parameter['init_from_suffix'], + self.parameter['output_suffix'], + path_to_work) + + init_from_path = re.sub(self.parameter['output_suffix'][::-1], + self.parameter['init_from_suffix'][::-1], + path_to_work[::-1], count=1)[::-1] + task_list_basename = list(map(os.path.basename, task_list)) + + os.chdir(path_to_work) + if os.path.isfile('element.out'): + os.remove('element.out') + if os.path.islink('element.out'): + os.remove('element.out') + os.symlink(os.path.relpath(os.path.join(init_from_path, 'element.out')), 'element.out') + os.chdir(cwd) + + for ii in task_list_basename: + init_from_task = os.path.join(init_from_path, ii) + output_task = os.path.join(path_to_work, ii) + os.chdir(output_task) + if os.path.isfile('supercell.json'): + os.remove('supercell.json') + if os.path.islink('supercell.json'): + os.remove('supercell.json') + os.symlink(os.path.relpath(os.path.join(init_from_task, 'supercell.json')), 'supercell.json') + os.chdir(cwd) + + else: + equi_contcar = os.path.join(path_to_equi, 'CONTCAR') + if not os.path.exists(equi_contcar): + raise RuntimeError("please do relaxation first") + + ss = Structure.from_file(equi_contcar) + # gen defects + dss = [] + insert_element_task = os.path.join(path_to_work, 'element.out') + if os.path.isfile(insert_element_task): + os.remove(insert_element_task) + + for ii in self.insert_ele: + vds = InterstitialGenerator(ss, ii) + for jj in vds: + temp = jj.generate_defect_structure(self.supercell) + smallest_distance = list(set(temp.distance_matrix.ravel()))[1] + if 'conf_filters' in self.parameter and 'min_dist' in self.parameter['conf_filters']: + min_dist = self.parameter['conf_filters']['min_dist'] + if smallest_distance >= min_dist: + dss.append(temp) + with open(insert_element_task, 'a+') as fout: + print(ii, file=fout) + else: + dss.append(temp) + with open(insert_element_task, 'a+') as fout: + print(ii, file=fout) + # dss.append(jj.generate_defect_structure(self.supercell)) + + print( + 'gen interstitial with supercell ' + str(self.supercell) + ' with element ' + str(self.insert_ele)) + os.chdir(path_to_work) + if os.path.isfile('POSCAR'): + os.remove('POSCAR') + if os.path.islink('POSCAR'): + os.remove('POSCAR') + os.symlink(os.path.relpath(equi_contcar), 'POSCAR') + # task_poscar = os.path.join(output, 'POSCAR') + + for ii in range(len(dss)): + output_task = os.path.join(path_to_work, 'task.%06d' % ii) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for jj in ['INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(jj): + os.remove(jj) + task_list.append(output_task) + dss[ii].to('POSCAR', 'POSCAR') + # np.savetxt('supercell.out', self.supercell, fmt='%d') + dumpfn(self.supercell, 'supercell.json') + os.chdir(cwd) + + return task_list + + def post_process(self, task_list): + if True: + fin1 = open(os.path.join(task_list[0], '..', 'element.out'), 'r') + for ii in task_list: + conf = os.path.join(ii, 'conf.lmp') + inter = os.path.join(ii, 'inter.json') + insert_ele = fin1.readline().split()[0] + if os.path.isfile(conf): + with open(conf, 'r') as fin2: + conf_line = fin2.read().split('\n') + insert_line = conf_line[-2] + type_map = loadfn(inter)['type_map'] + type_map_list = lammps.element_list(type_map) + if int(insert_line.split()[1]) > len(type_map_list): + type_num = type_map[insert_ele] + 1 + conf_line[2] = str(len(type_map_list)) + ' atom types' + conf_line[-2] = '%6.d' % int(insert_line.split()[0]) + '%7.d' % type_num + \ + '%16.10f' % float(insert_line.split()[2]) + \ + '%16.10f' % float(insert_line.split()[3]) + \ + '%16.10f' % float(insert_line.split()[4]) + with open(conf, 'w+') as fout: + for jj in conf_line: + print(jj, file=fout) + fin1.close() + + def task_type(self): + return self.parameter['type'] + + def task_param(self): + return self.parameter + + def _compute_lower(self, + output_file, + all_tasks, + all_res): + output_file = os.path.abspath(output_file) + res_data = {} + ptr_data = os.path.dirname(output_file) + '\n' + + if not self.reprod: + with open(os.path.join(os.path.dirname(output_file), 'element.out'), 'r') as fin: + fc = fin.read().split('\n') + ptr_data += "Insert_ele-Struct: Inter_E(eV) E(eV) equi_E(eV)\n" + idid = -1 + for ii in all_tasks: + idid += 1 + structure_dir = os.path.basename(ii) + task_result = loadfn(all_res[idid]) + natoms = task_result['atom_numbs'][0] + equi_path = os.path.abspath(os.path.join(os.path.dirname(output_file), '../relaxation/relax_task')) + equi_result = loadfn(os.path.join(equi_path, 'result.json')) + equi_epa = equi_result['energies'][-1] / equi_result['atom_numbs'][0] + evac = task_result['energies'][-1] - equi_epa * natoms + + supercell_index = loadfn(os.path.join(ii, 'supercell.json')) + # insert_ele = loadfn(os.path.join(ii, 'task.json'))['insert_ele'][0] + insert_ele = fc[idid] + ptr_data += "%s: %7.3f %7.3f %7.3f \n" % ( + insert_ele + '-' + str(supercell_index) + '-' + structure_dir, evac, + task_result['energies'][-1], equi_epa * natoms) + res_data[insert_ele + '-' + str(supercell_index) + '-' + structure_dir] = [evac, + task_result['energies'][-1], + equi_epa * natoms] + + else: + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + res_data, ptr_data = post_repro(init_data_path, self.parameter['init_from_suffix'], + all_tasks, ptr_data, self.parameter.get('reprod_last_frame', False)) + + with open(output_file, 'w') as fp: + json.dump(res_data, fp, indent=4) + + return res_data, ptr_data diff --git a/dpgen/auto_test/Lammps.py b/dpgen/auto_test/Lammps.py new file mode 100644 index 000000000..fd9e85a81 --- /dev/null +++ b/dpgen/auto_test/Lammps.py @@ -0,0 +1,393 @@ +import os +import warnings +import dpgen.auto_test.lib.lammps as lammps +from dpgen import dlog +from monty.serialization import loadfn, dumpfn +from dpgen.auto_test.Task import Task +from dpgen.auto_test.lib.lammps import inter_deepmd, inter_meam, inter_eam_fs, inter_eam_alloy + +supported_inter = ["deepmd", 'meam', 'eam_fs', 'eam_alloy'] + + +class Lammps(Task): + def __init__(self, + inter_parameter, + path_to_poscar): + self.inter = inter_parameter + self.inter_type = inter_parameter['type'] + self.type_map = inter_parameter['type_map'] + self.in_lammps = inter_parameter.get('in_lammps', 'auto') + if self.type_map == 'meam': + self.model = list(map(os.path.abspath, inter_parameter['model'])) + else: + self.model = os.path.abspath(inter_parameter['model']) + self.path_to_poscar = path_to_poscar + assert self.inter_type in supported_inter + self.set_inter_type_func() + + def set_inter_type_func(self): + + if self.inter_type == "deepmd": + self.inter_func = inter_deepmd + + elif self.inter_type == 'meam': + self.inter_func = inter_meam + + elif self.inter_type == 'eam_fs': + self.inter_func = inter_eam_fs + + else: + self.inter_func = inter_eam_alloy + + def set_model_param(self): + + if self.inter_type == "deepmd": + model_name = os.path.basename(self.model) + deepmd_version = self.inter.get("deepmd_version", "1.2.0") + self.model_param = {'model_name': [model_name], + 'param_type': self.type_map, + 'deepmd_version': deepmd_version} + elif self.inter_type == 'meam': + model_name = list(map(os.path.basename, self.model)) + self.model_param = {'model_name': [model_name], + 'param_type': self.type_map} + else: + model_name = os.path.basename(self.model) + self.model_param = {'model_name': [model_name], + 'param_type': self.type_map} + + def make_potential_files(self, + output_dir): + cwd = os.getcwd() + if self.inter_type == 'meam': + model_lib = os.path.basename(self.model[0]) + model_file = os.path.basename(self.model[1]) + os.chdir(os.path.join(output_dir, '../')) + if os.path.islink(model_lib): + link_lib = os.readlink(model_lib) + if not os.path.abspath(link_lib) == self.model[0]: + os.remove(model_lib) + os.symlink(os.path.relpath(self.model[0]), model_lib) + else: + os.symlink(os.path.relpath(self.model[0]), model_lib) + + if os.path.islink(model_file): + link_file = os.readlink(model_file) + if not os.path.abspath(link_file) == self.model[1]: + os.remove(model_file) + os.symlink(os.path.relpath(self.model[1]), model_file) + else: + os.symlink(os.path.relpath(self.model[1]), model_file) + os.chdir(output_dir) + if not os.path.islink(model_lib): + os.symlink(os.path.join('..', model_lib), model_lib) + elif not os.path.join('..', model_lib) == os.readlink(model_lib): + os.remove(model_lib) + os.symlink(os.path.join('..', model_lib), model_lib) + + if not os.path.islink(model_file): + os.symlink(os.path.join('..', model_file), model_file) + elif not os.path.join('..', model_file) == os.readlink(model_file): + os.remove(model_file) + os.symlink(os.path.join('..', model_file), model_file) + os.chdir(cwd) + + else: + model_file = os.path.basename(self.model) + os.chdir(os.path.join(output_dir, '../')) + if os.path.islink(model_file): + link_file = os.readlink(model_file) + if not os.path.abspath(link_file) == self.model: + os.remove(model_file) + os.symlink(os.path.relpath(self.model), model_file) + else: + os.symlink(os.path.relpath(self.model), model_file) + os.chdir(output_dir) + if not os.path.islink(model_file): + os.symlink(os.path.join('..', model_file), model_file) + elif not os.path.join('..', model_file) == os.readlink(model_file): + os.remove(model_file) + os.symlink(os.path.join('..', model_file), model_file) + os.chdir(cwd) + + dumpfn(self.inter, os.path.join(output_dir, 'inter.json'), indent=4) + + def make_input_file(self, + output_dir, + task_type, + task_param): + lammps.cvt_lammps_conf(os.path.join(output_dir, 'POSCAR'), os.path.join(output_dir, 'conf.lmp'), lammps.element_list(self.type_map)) + + # dumpfn(task_param, os.path.join(output_dir, 'task.json'), indent=4) + + etol = 1e-12 + ftol = 1e-6 + maxiter = 5000 + maxeval = 500000 + B0 = 70 + bp = 0 + ntypes = len(self.type_map) + + cal_type = task_param['cal_type'] + cal_setting = task_param['cal_setting'] + + self.set_model_param() + + # deal with user input in.lammps for relaxation + if os.path.isfile(self.in_lammps) and task_type == 'relaxation': + with open(self.in_lammps, 'r') as fin: + fc = fin.read() + # user input in.lammps for property calculation + if 'input_prop' in cal_setting and os.path.isfile(cal_setting['input_prop']): + with open(os.path.abspath(cal_setting['input_prop']), 'r') as fin: + fc = fin.read() + + else: + if 'etol' in cal_setting: + dlog.info("%s setting etol to %s" % (self.make_input_file.__name__, cal_setting['etol'])) + etol = cal_setting['etol'] + if 'ftol' in cal_setting: + dlog.info("%s setting ftol to %s" % (self.make_input_file.__name__, cal_setting['ftol'])) + ftol = cal_setting['ftol'] + if 'maxiter' in cal_setting: + dlog.info("%s setting maxiter to %s" % (self.make_input_file.__name__, cal_setting['maxiter'])) + maxiter = cal_setting['maxiter'] + if 'maxeval' in cal_setting: + dlog.info("%s setting maxeval to %s" % (self.make_input_file.__name__, cal_setting['maxeval'])) + maxeval = cal_setting['maxeval'] + + if cal_type == 'relaxation': + relax_pos = cal_setting['relax_pos'] + relax_shape = cal_setting['relax_shape'] + relax_vol = cal_setting['relax_vol'] + + if [relax_pos, relax_shape, relax_vol] == [True, False, False]: + fc = lammps.make_lammps_equi('conf.lmp', self.type_map, self.inter_func, self.model_param, + etol, ftol, maxiter, maxeval, False) + elif [relax_pos, relax_shape, relax_vol] == [True, True, True]: + fc = lammps.make_lammps_equi('conf.lmp', self.type_map, self.inter_func, self.model_param, + etol, ftol, maxiter, maxeval, True) + elif [relax_pos, relax_shape, relax_vol] == [True, True, False] and not task_type == 'eos': + if 'scale2equi' in task_param: + scale2equi = task_param['scale2equi'] + fc = lammps.make_lammps_press_relax('conf.lmp', self.type_map, scale2equi[int(output_dir[-6:])], + self.inter_func, + self.model_param, B0, bp, etol, ftol, maxiter, maxeval) + else: + fc = lammps.make_lammps_equi('conf.lmp', self.type_map, self.inter_func, self.model_param, + etol, ftol, maxiter, maxeval, True) + elif [relax_pos, relax_shape, relax_vol] == [True, True, False] and task_type == 'eos': + task_param['cal_setting']['relax_shape'] = False + fc = lammps.make_lammps_equi('conf.lmp', self.type_map, self.inter_func, self.model_param, + etol, ftol, maxiter, maxeval, False) + elif [relax_pos, relax_shape, relax_vol] == [False, False, False]: + fc = lammps.make_lammps_eval('conf.lmp', self.type_map, self.inter_func, self.model_param) + + else: + raise RuntimeError("not supported calculation setting for LAMMPS") + + elif cal_type == 'static': + fc = lammps.make_lammps_eval('conf.lmp', self.type_map, self.inter_func, self.model_param) + + else: + raise RuntimeError("not supported calculation type for LAMMPS") + + dumpfn(task_param, os.path.join(output_dir, 'task.json'), indent=4) + + in_lammps_not_link_list = ['eos'] + if task_type not in in_lammps_not_link_list: + with open(os.path.join(output_dir, '../in.lammps'), 'w') as fp: + fp.write(fc) + cwd = os.getcwd() + os.chdir(output_dir) + if not (os.path.islink('in.lammps') or os.path.isfile('in.lammps')): + os.symlink('../in.lammps', 'in.lammps') + else: + os.remove('in.lammps') + os.symlink('../in.lammps', 'in.lammps') + os.chdir(cwd) + else: + with open(os.path.join(output_dir, 'in.lammps'), 'w') as fp: + fp.write(fc) + + def compute(self, + output_dir): + log_lammps = os.path.join(output_dir, 'log.lammps') + dump_lammps = os.path.join(output_dir, 'dump.relax') + if not os.path.isfile(log_lammps): + warnings.warn("cannot find log.lammps in " + output_dir + " skip") + return None + if not os.path.isfile(dump_lammps): + warnings.warn("cannot find dump.relax in " + output_dir + " skip") + return None + else: + box = [] + coord = [] + vol = [] + energy = [] + force = [] + virial = [] + stress = [] + with open(dump_lammps, 'r') as fin: + dump = fin.read().split('\n') + dumptime = [] + for idx, ii in enumerate(dump): + if ii == 'ITEM: TIMESTEP': + box.append([]) + coord.append([]) + force.append([]) + dumptime.append(int(dump[idx + 1])) + natom = int(dump[idx + 3]) + xlo_bound = float(dump[idx + 5].split()[0]) + xhi_bound = float(dump[idx + 5].split()[1]) + xy = float(dump[idx + 5].split()[2]) + ylo_bound = float(dump[idx + 6].split()[0]) + yhi_bound = float(dump[idx + 6].split()[1]) + xz = float(dump[idx + 6].split()[2]) + zlo = float(dump[idx + 7].split()[0]) + zhi = float(dump[idx + 7].split()[1]) + yz = float(dump[idx + 7].split()[2]) + xx = xhi_bound - max([0, xy, xz, xy + xz]) - (xlo_bound - min([0, xy, xz, xy + xz])) + yy = yhi_bound - max([0, yz]) - (ylo_bound - min([0, yz])) + zz = zhi - zlo + box[-1].append([xx, 0.0, 0.0]) + box[-1].append([xy, yy, 0.0]) + box[-1].append([xz, yz, zz]) + vol.append(xx * yy * zz) + type_list = [] + for jj in range(natom): + type_list.append(int(dump[idx + 9 + jj].split()[1]) - 1) + if 'xs ys zs' in dump[idx + 8]: + a_x = float(dump[idx + 9 + jj].split()[2]) * xx + float( + dump[idx + 9 + jj].split()[3]) * xy \ + + float(dump[idx + 9 + jj].split()[4]) * xz + a_y = float(dump[idx + 9 + jj].split()[3]) * yy + float( + dump[idx + 9 + jj].split()[4]) * yz + a_z = float(dump[idx + 9 + jj].split()[4]) * zz + else: + a_x = float(dump[idx + 9 + jj].split()[2]) + a_y = float(dump[idx + 9 + jj].split()[3]) + a_z = float(dump[idx + 9 + jj].split()[4]) + coord[-1].append([a_x, a_y, a_z]) + fx = float(dump[idx + 9 + jj].split()[5]) + fy = float(dump[idx + 9 + jj].split()[6]) + fz = float(dump[idx + 9 + jj].split()[7]) + force[-1].append([fx, fy, fz]) + + with open(log_lammps, 'r') as fp: + if 'Total wall time:' not in fp.read(): + warnings.warn("lammps not finished " + log_lammps + " skip") + return None + else: + fp.seek(0) + lines = fp.read().split('\n') + idid = -1 + for ii in dumptime: + idid += 1 + for jj in lines: + line = jj.split() + if len(line) and str(ii) == line[0]: + try: + [float(kk) for kk in line] + except: + continue + stress.append([]) + virial.append([]) + energy.append(float(line[1])) + # virials = stress * vol * 1e5 *1e-30 * 1e19/1.6021766208 + stress[-1].append([float(line[2]) / 1000.0, float(line[5]) / 1000.0, float(line[6]) / 1000.0]) + stress[-1].append([float(line[5]) / 1000.0, float(line[3]) / 1000.0, float(line[7]) / 1000.0]) + stress[-1].append([float(line[6]) / 1000.0, float(line[7]) / 1000.0, float(line[4]) / 1000.0]) + stress_to_virial = vol[idid] * 1e5 * 1e-30 * 1e19 / 1.6021766208 + virial[-1].append([float(line[2]) * stress_to_virial, float(line[5]) * stress_to_virial, + float(line[6]) * stress_to_virial]) + virial[-1].append([float(line[5]) * stress_to_virial, float(line[3]) * stress_to_virial, + float(line[7]) * stress_to_virial]) + virial[-1].append([float(line[6]) * stress_to_virial, float(line[7]) * stress_to_virial, + float(line[4]) * stress_to_virial]) + break + + _tmp = self.type_map + dlog.debug(_tmp) + type_map_list = lammps.element_list(self.type_map) + + type_map_idx = list(range(len(type_map_list))) + atom_numbs = [] + for ii in type_map_idx: + count = 0 + for jj in type_list: + if jj == ii: + count += 1 + atom_numbs.append(count) + + # d_dump = dpdata.System(dump_lammps, fmt='lammps/dump', type_map=type_map_list) + # d_dump.to('vasp/poscar', contcar, frame_idx=-1) + + result_dict = {"@module": "dpdata.system", "@class": "LabeledSystem", "data": {"atom_numbs": atom_numbs, + "atom_names": type_map_list, + "atom_types": { + "@module": "numpy", + "@class": "array", + "dtype": "int64", + "data": type_list}, + "orig": {"@module": "numpy", + "@class": "array", + "dtype": "int64", + "data": [0, 0, 0]}, + "cells": {"@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": box}, + "coords": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": coord}, + "energies": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": energy}, + "forces": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": force}, + "virials": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": virial}, + "stress": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": stress}}} + + contcar = os.path.join(output_dir, 'CONTCAR') + dumpfn(result_dict, contcar, indent=4) + d_dump = loadfn(contcar) + d_dump.to('vasp/poscar', contcar, frame_idx=-1) + + return result_dict + + def forward_files(self, property_type='relaxation'): + if self.inter_type == 'meam': + return ['conf.lmp', 'in.lammps'] + list(map(os.path.basename, self.model)) + else: + return ['conf.lmp', 'in.lammps', os.path.basename(self.model)] + + def forward_common_files(self, property_type='relaxation'): + if property_type not in ['eos']: + if self.inter_type == 'meam': + return ['in.lammps'] + list(map(os.path.basename, self.model)) + else: + return ['in.lammps', os.path.basename(self.model)] + else: + if self.inter_type == 'meam': + return list(map(os.path.basename, self.model)) + else: + return [os.path.basename(self.model)] + + def backward_files(self, property_type='relaxation'): + return ['log.lammps', 'outlog', 'dump.relax'] diff --git a/dpgen/auto_test/Property.py b/dpgen/auto_test/Property.py new file mode 100644 index 000000000..3d1de3350 --- /dev/null +++ b/dpgen/auto_test/Property.py @@ -0,0 +1,139 @@ +import glob +import json +import os +from abc import ABC, abstractmethod + +from monty.serialization import dumpfn + +from dpgen.auto_test.calculator import make_calculator + + +class Property(ABC): + @abstractmethod + def __init__(self, + parameter): + """ + Constructor + + Parameters + ---------- + parameters : dict + A dict that defines the property. + """ + pass + + @abstractmethod + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + """ + Make configurations needed to compute the property. + The tasks directory will be named as path_to_work/task.xxxxxx + IMPORTANT: handel the case when the directory exists. + + Parameters + ---------- + path_to_work : str + The path where the tasks for the property are located + path_to_equi : str + -refine == False: The path to the directory that equilibrated the configuration. + -refine == True: The path to the directory that has property confs. + refine: str + To refine existing property confs or generate property confs from a equilibrated conf + + Returns + ------- + task_list: list of str + The list of task directories. + """ + pass + + @abstractmethod + def post_process(self, task_list): + """ + post_process the KPOINTS file in elastic. + """ + pass + + @property + @abstractmethod + def task_type(self): + """ + Return the type of each computational task, for example, 'relaxation', 'static'.... + """ + pass + + @property + @abstractmethod + def task_param(self): + """ + Return the parameter of each computational task, for example, {'ediffg': 1e-4} + """ + pass + + def compute(self, + output_file, + print_file, + path_to_work): + """ + Postprocess the finished tasks to compute the property. + Output the result to a json database + + Parameters + ---------- + output_file: + The file to output the property in json format + print_file: + The file to output the property in txt format + path_to_work: + The working directory where the computational tasks locate. + """ + path_to_work = os.path.abspath(path_to_work) + task_dirs = glob.glob(os.path.join(path_to_work, 'task.[0-9]*[0-9]')) + task_dirs.sort() + all_res = [] + for ii in task_dirs: + with open(os.path.join(ii, 'inter.json')) as fp: + idata = json.load(fp) + poscar = os.path.join(ii, 'POSCAR') + task = make_calculator(idata, poscar) + res = task.compute(ii) + dumpfn(res, os.path.join(ii, 'result_task.json'), indent=4) + # all_res.append(res) + all_res.append(os.path.join(ii, 'result_task.json')) + + # cwd = os.getcwd() + # os.chdir(path_to_work) + res, ptr = self._compute_lower(output_file, task_dirs, all_res) + # with open(output_file, 'w') as fp: + # json.dump(fp, res, indent=4) + with open(print_file, 'w') as fp: + fp.write(ptr) + # os.chdir(cwd) + + @abstractmethod + def _compute_lower(self, + output_file, + all_tasks, + all_res): + """ + Compute the property. + + Parameters + ---------- + output_file: + The file to output the property + all_tasks : list of str + The list of directories to the tasks + all_res : list of str + The list of results + + Returns: + ------- + res_data: dist + The dict storing the result of the property + ptr_data: str + The result printed in string format + """ + pass diff --git a/dpgen/auto_test/Surface.py b/dpgen/auto_test/Surface.py new file mode 100644 index 000000000..478845d11 --- /dev/null +++ b/dpgen/auto_test/Surface.py @@ -0,0 +1,210 @@ +import glob +import json +import os +import re + +import numpy as np +from monty.serialization import loadfn, dumpfn +from pymatgen.core.structure import Structure +from pymatgen.core.surface import generate_all_slabs + +import dpgen.auto_test.lib.vasp as vasp +from dpgen import dlog +from dpgen.auto_test.Property import Property +from dpgen.auto_test.refine import make_refine +from dpgen.auto_test.reproduce import make_repro +from dpgen.auto_test.reproduce import post_repro + + +class Surface(Property): + def __init__(self, + parameter): + parameter['reproduce'] = parameter.get('reproduce', False) + self.reprod = parameter['reproduce'] + if not self.reprod: + if not ('init_from_suffix' in parameter and 'output_suffix' in parameter): + self.min_slab_size = parameter['min_slab_size'] + self.min_vacuum_size = parameter['min_vacuum_size'] + parameter['pert_xz'] = parameter.get('pert_xz', 0.01) + self.pert_xz = parameter['pert_xz'] + default_max_miller = 2 + parameter['max_miller'] = parameter.get('max_miller', default_max_miller) + self.miller = parameter['max_miller'] + parameter['cal_type'] = parameter.get('cal_type', 'relaxation') + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": True, + "relax_shape": True, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + else: + parameter['cal_type'] = 'static' + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": False, + "relax_shape": False, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + parameter['init_from_suffix'] = parameter.get('init_from_suffix', '00') + self.init_from_suffix = parameter['init_from_suffix'] + self.parameter = parameter + + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + path_to_work = os.path.abspath(path_to_work) + if os.path.exists(path_to_work): + dlog.warning('%s already exists' % path_to_work) + else: + os.makedirs(path_to_work) + path_to_equi = os.path.abspath(path_to_equi) + + if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): + init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) + struct_init_name_list = [] + for ii in init_path_list: + struct_init_name_list.append(ii.split('/')[-1]) + struct_output_name = path_to_work.split('/')[-2] + assert struct_output_name in struct_init_name_list + path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], + struct_output_name, 'relaxation', 'relax_task')) + + task_list = [] + cwd = os.getcwd() + + if self.reprod: + print('surface reproduce starts') + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + task_list = make_repro(init_data_path, self.init_from_suffix, + path_to_work, self.parameter.get('reprod_last_frame', True)) + os.chdir(cwd) + + else: + if refine: + print('surface refine starts') + task_list = make_refine(self.parameter['init_from_suffix'], + self.parameter['output_suffix'], + path_to_work) + os.chdir(cwd) + # record miller + init_from_path = re.sub(self.parameter['output_suffix'][::-1], + self.parameter['init_from_suffix'][::-1], + path_to_work[::-1], count=1)[::-1] + task_list_basename = list(map(os.path.basename, task_list)) + + for ii in task_list_basename: + init_from_task = os.path.join(init_from_path, ii) + output_task = os.path.join(path_to_work, ii) + os.chdir(output_task) + if os.path.isfile('miller.json'): + os.remove('miller.json') + if os.path.islink('miller.json'): + os.remove('miller.json') + os.symlink(os.path.relpath(os.path.join(init_from_task, 'miller.json')), 'miller.json') + os.chdir(cwd) + + else: + equi_contcar = os.path.join(path_to_equi, 'CONTCAR') + if not os.path.exists(equi_contcar): + raise RuntimeError("please do relaxation first") + ptypes = vasp.get_poscar_types(equi_contcar) + # gen structure + ss = Structure.from_file(equi_contcar) + # gen slabs + all_slabs = generate_all_slabs(ss, self.miller, self.min_slab_size, self.min_vacuum_size) + + os.chdir(path_to_work) + if os.path.isfile('POSCAR'): + os.remove('POSCAR') + if os.path.islink('POSCAR'): + os.remove('POSCAR') + os.symlink(os.path.relpath(equi_contcar), 'POSCAR') + # task_poscar = os.path.join(output, 'POSCAR') + for ii in range(len(all_slabs)): + output_task = os.path.join(path_to_work, 'task.%06d' % ii) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for jj in ['INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(jj): + os.remove(jj) + task_list.append(output_task) + print("# %03d generate " % ii, output_task, " \t %d atoms" % len(all_slabs[ii].sites)) + # make confs + all_slabs[ii].to('POSCAR', 'POSCAR.tmp') + vasp.regulate_poscar('POSCAR.tmp', 'POSCAR') + vasp.sort_poscar('POSCAR', 'POSCAR', ptypes) + vasp.perturb_xz('POSCAR', 'POSCAR', self.pert_xz) + # record miller + dumpfn(all_slabs[ii].miller_index, 'miller.json') + os.chdir(cwd) + + return task_list + + def post_process(self, task_list): + pass + + def task_type(self): + return self.parameter['type'] + + def task_param(self): + return self.parameter + + def _compute_lower(self, + output_file, + all_tasks, + all_res): + output_file = os.path.abspath(output_file) + res_data = {} + ptr_data = os.path.dirname(output_file) + '\n' + + if not self.reprod: + ptr_data += "Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n" + for ii in all_tasks: + task_result = loadfn(os.path.join(ii, 'result_task.json')) + natoms = task_result['atom_numbs'][0] + epa = task_result['energies'][-1] / task_result['atom_numbs'][0] + AA = np.linalg.norm(np.cross(task_result['cells'][0][0], task_result['cells'][0][1])) + + equi_path = os.path.abspath(os.path.join(os.path.dirname(output_file), '../relaxation/relax_task')) + equi_result = loadfn(os.path.join(equi_path, 'result.json')) + equi_epa = equi_result['energies'][-1] / equi_result['atom_numbs'][0] + structure_dir = os.path.basename(ii) + + Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001 + evac = (task_result['energies'][-1] - equi_epa * natoms) / AA * Cf + + miller_index = loadfn(os.path.join(ii, 'miller.json')) + ptr_data += "%-25s %7.3f %8.3f %8.3f\n" % ( + str(miller_index) + '-' + structure_dir + ':', evac, epa, equi_epa) + res_data[str(miller_index) + '-' + structure_dir] = [evac, epa, equi_epa] + + else: + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + res_data, ptr_data = post_repro(init_data_path, self.parameter['init_from_suffix'], + all_tasks, ptr_data, self.parameter.get('reprod_last_frame', True)) + + with open(output_file, 'w') as fp: + json.dump(res_data, fp, indent=4) + + return res_data, ptr_data diff --git a/dpgen/auto_test/Task.py b/dpgen/auto_test/Task.py new file mode 100644 index 000000000..c04aac586 --- /dev/null +++ b/dpgen/auto_test/Task.py @@ -0,0 +1,116 @@ +from abc import ABC, abstractmethod + + +class Task(ABC): + @abstractmethod + def __init__(self, + inter_parameter, + path_to_poscar): + """ + Constructor + + Parameters + ---------- + inter_parameter : dict + A dict that specifies the interaction. + path_to_poscar : str + The path to POSCAR. Indicating in which system the task will be initialized. + """ + pass + + @abstractmethod + def make_potential_files(self, + output_dir): + """ + Prepare potential files for a computational task. + For example, the VASP prepares POTCAR. + DeePMD prepares frozen model(s). + IMPORTANT: Interaction should be stored in output_dir/inter.json + + Parameters + ---------- + output_dir : str + The directory storing the potential files. + Outputs + ------- + inter.json: output file + The task information is stored in `output_dir/inter.json` + """ + pass + + @abstractmethod + def make_input_file(self, + output_dir, + task_type, + task_param): + """ + Prepare input files for a computational task + For example, the VASP prepares INCAR. + LAMMPS (including DeePMD, MEAM...) prepares in.lammps. + + Parameters + ---------- + output_dir : str + The directory storing the input files. + task_type : str + Can be + - "relaxation:": structure relaxation + - "static": static computation calculates the energy, force... of a strcture + task_parame: dict + The parameters of the task. + For example the VASP interaction can be provided with + { "ediff": 1e-6, "ediffg": 1e-5 } + """ + pass + + @abstractmethod + def compute(self, + output_dir): + """ + Compute output of the task. + IMPORTANT: The output configuration should be converted and stored in a CONTCAR file. + + Parameters + ---------- + output_dir : str + The directory storing the input and output files. + + Returns + ------- + result_dict: dict + A dict that storing the result. For example: + { "energy": xxx, "force": [xxx] } + + Outputs + ------- + CONTCAR: output file + The output configuration is converted to CONTCAR and stored in the `output_dir` + """ + pass + + @property + @staticmethod + @abstractmethod + def forward_files(self): + """ + Return forward files. + """ + pass + + @property + @staticmethod + @abstractmethod + def forward_common_files(self): + """ + Return forward common files. + """ + pass + + @property + @staticmethod + @abstractmethod + def backward_files(self): + """ + Return backward files. + """ + pass diff --git a/dpgen/auto_test/VASP.py b/dpgen/auto_test/VASP.py new file mode 100644 index 000000000..410bde02c --- /dev/null +++ b/dpgen/auto_test/VASP.py @@ -0,0 +1,215 @@ +import os +from dpgen import dlog +from dpgen.util import sepline +import dpgen.auto_test.lib.vasp as vasp +from dpgen.auto_test.Task import Task +from dpgen.generator.lib.vasp import incar_upper +from dpdata import LabeledSystem +from monty.serialization import dumpfn +from pymatgen.io.vasp import Incar, Kpoints +from pymatgen.core.structure import Structure + + +class VASP(Task): + def __init__(self, + inter_parameter, + path_to_poscar): + self.inter = inter_parameter + self.inter_type = inter_parameter['type'] + self.incar = inter_parameter['incar'] + self.potcar_prefix = inter_parameter.get('potcar_prefix', '') + self.potcars = inter_parameter['potcars'] + self.path_to_poscar = path_to_poscar + + def make_potential_files(self, + output_dir): + potcar_not_link_list = ['vacancy', 'interstitial'] + task_type = output_dir.split('/')[-2].split('_')[0] + + ele_pot_list = [key for key in self.potcars.keys()] + poscar = os.path.abspath(os.path.join(output_dir, 'POSCAR')) + pos_str = Structure.from_file(poscar) + ele_pos_list_tmp = list(ii.as_dict()['element'] for ii in pos_str.species) + + ele_pos_list = [ele_pos_list_tmp[0]] + for ii in range(1, len(ele_pos_list_tmp)): + if not ele_pos_list_tmp[ii] == ele_pos_list_tmp[ii - 1]: + ele_pos_list.append(ele_pos_list_tmp[ii]) + + if task_type in potcar_not_link_list: + with open(os.path.join(output_dir, 'POTCAR'), 'w') as fp: + for ii in ele_pos_list: + for jj in ele_pot_list: + if ii == jj: + with open(os.path.join(self.potcar_prefix, self.potcars[jj]), 'r') as fin: + for line in fin: + print(line.strip('\n'), file=fp) + + else: + if not os.path.isfile(os.path.join(output_dir, '../POTCAR')): + with open(os.path.join(output_dir, '../POTCAR'), 'w') as fp: + for ii in ele_pos_list: + for jj in ele_pot_list: + if ii == jj: + with open(os.path.join(self.potcar_prefix, self.potcars[jj]), 'r') as fin: + for line in fin: + print(line.strip('\n'), file=fp) + cwd = os.getcwd() + os.chdir(output_dir) + if not os.path.islink('POTCAR'): + os.symlink('../POTCAR', 'POTCAR') + elif not '../POTCAR' == os.readlink('POTCAR'): + os.remove('POTCAR') + os.symlink('../POTCAR', 'POTCAR') + os.chdir(cwd) + + dumpfn(self.inter, os.path.join(output_dir, 'inter.json'), indent=4) + + def make_input_file(self, + output_dir, + task_type, + task_param): + sepline(ch=output_dir) + dumpfn(task_param, os.path.join(output_dir, 'task.json'), indent=4) + + assert (os.path.exists(self.incar)), 'no INCAR file for relaxation' + relax_incar_path = os.path.abspath(self.incar) + incar_relax = incar_upper(Incar.from_file(relax_incar_path)) + + # deal with relaxation + + cal_type = task_param['cal_type'] + cal_setting = task_param['cal_setting'] + + # user input INCAR for property calculation + if 'input_prop' in cal_setting and os.path.isfile(cal_setting['input_prop']): + incar_prop = os.path.abspath(cal_setting['input_prop']) + incar = incar_upper(Incar.from_file(incar_prop)) + + # revise INCAR based on the INCAR provided in the "interaction" + else: + incar = incar_relax + if cal_type == 'relaxation': + relax_pos = cal_setting['relax_pos'] + relax_shape = cal_setting['relax_shape'] + relax_vol = cal_setting['relax_vol'] + if [relax_pos, relax_shape, relax_vol] == [True, False, False]: + isif = 2 + elif [relax_pos, relax_shape, relax_vol] == [True, True, True]: + isif = 3 + elif [relax_pos, relax_shape, relax_vol] == [True, True, False]: + isif = 4 + elif [relax_pos, relax_shape, relax_vol] == [False, True, False]: + isif = 5 + elif [relax_pos, relax_shape, relax_vol] == [False, True, True]: + isif = 6 + elif [relax_pos, relax_shape, relax_vol] == [False, False, True]: + isif = 7 + elif [relax_pos, relax_shape, relax_vol] == [False, False, False]: + nsw = 0 + isif = 2 + if not ('NSW' in incar and incar.get('NSW') == nsw): + dlog.info("%s setting NSW to %d" % (self.make_input_file.__name__, nsw)) + incar['NSW'] = nsw + else: + raise RuntimeError("not supported calculation setting for VASP") + + if not ('ISIF' in incar and incar.get('ISIF') == isif): + dlog.info("%s setting ISIF to %d" % (self.make_input_file.__name__, isif)) + incar['ISIF'] = isif + + elif cal_type == 'static': + nsw = 0 + if not ('NSW' in incar and incar.get('NSW') == nsw): + dlog.info("%s setting NSW to %d" % (self.make_input_file.__name__, nsw)) + incar['NSW'] = nsw + + else: + raise RuntimeError("not supported calculation type for VASP") + + if 'ediff' in cal_setting: + dlog.info("%s setting EDIFF to %s" % (self.make_input_file.__name__, cal_setting['ediff'])) + incar['EDIFF'] = cal_setting['ediff'] + + if 'ediffg' in cal_setting: + dlog.info("%s setting EDIFFG to %s" % (self.make_input_file.__name__, cal_setting['ediffg'])) + incar['EDIFFG'] = cal_setting['ediffg'] + + if 'encut' in cal_setting: + dlog.info("%s setting ENCUT to %s" % (self.make_input_file.__name__, cal_setting['encut'])) + incar['ENCUT'] = cal_setting['encut'] + + if 'kspacing' in cal_setting: + dlog.info("%s setting KSAPCING to %s" % (self.make_input_file.__name__, cal_setting['kspacing'])) + incar['KSAPCING'] = cal_setting['kspacing'] + + if 'kgamma' in cal_setting: + dlog.info("%s setting KGAMMA to %s" % (self.make_input_file.__name__, cal_setting['kgamma'])) + incar['KGAMMA'] = cal_setting['kgamma'] + + try: + kspacing = incar.get('KSPACING') + except KeyError: + raise RuntimeError("KSPACING must be given in INCAR") + + if 'KGAMMA' in incar: + kgamma = incar.get('KGAMMA') + else: + kgamma = False + + incar.write_file(os.path.join(output_dir, '../INCAR')) + cwd = os.getcwd() + os.chdir(output_dir) + if not os.path.islink('INCAR'): + os.symlink('../INCAR', 'INCAR') + elif not '../INCAR' == os.readlink('INCAR'): + os.remove('INCAR') + os.symlink('../INCAR', 'INCAR') + os.chdir(cwd) + ret = vasp.make_kspacing_kpoints(self.path_to_poscar, kspacing, kgamma) + kp = Kpoints.from_string(ret) + kp.write_file(os.path.join(output_dir, "KPOINTS")) + + def compute(self, + output_dir): + outcar = os.path.join(output_dir, 'OUTCAR') + if not os.path.isfile(outcar): + dlog.warning("cannot find OUTCAR in " + output_dir + " skip") + return None + else: + ls = LabeledSystem(outcar) + stress = [] + with open(outcar, 'r') as fin: + lines = fin.read().split('\n') + for line in lines: + if 'in kB' in line: + stress_xx = float(line.split()[2]) + stress_yy = float(line.split()[3]) + stress_zz = float(line.split()[4]) + stress_xy = float(line.split()[5]) + stress_yz = float(line.split()[6]) + stress_zx = float(line.split()[7]) + stress.append([]) + stress[-1].append([stress_xx, stress_xy, stress_zx]) + stress[-1].append([stress_xy, stress_yy, stress_yz]) + stress[-1].append([stress_zx, stress_yz, stress_zz]) + + outcar_dict = ls.as_dict() + outcar_dict['data']['stress'] = {"@module": "numpy", "@class": "array", "dtype": "float64", "data": stress} + + return outcar_dict + + def forward_files(self, property_type='relaxation'): + return ['INCAR', 'POSCAR', 'KPOINTS', 'POTCAR'] + + def forward_common_files(self, property_type='relaxation'): + potcar_not_link_list = ['vacancy', 'interstitial'] + if property_type == 'elastic': + return ['INCAR', 'KPOINTS', 'POTCAR'] + elif property_type in potcar_not_link_list: + return ['INCAR'] + else: + return ['INCAR', 'POTCAR'] + + def backward_files(self, property_type='relaxation'): + return ['OUTCAR', 'outlog', 'CONTCAR', 'OSZICAR', 'XDATCAR'] diff --git a/dpgen/auto_test/Vacancy.py b/dpgen/auto_test/Vacancy.py new file mode 100644 index 000000000..c0e8c3893 --- /dev/null +++ b/dpgen/auto_test/Vacancy.py @@ -0,0 +1,197 @@ +import glob +import json +import os +import re + +from monty.serialization import loadfn, dumpfn +from pymatgen.analysis.defects.generators import VacancyGenerator +from pymatgen.core.structure import Structure + +from dpgen import dlog +from dpgen.auto_test.Property import Property +from dpgen.auto_test.refine import make_refine +from dpgen.auto_test.reproduce import make_repro +from dpgen.auto_test.reproduce import post_repro + + +class Vacancy(Property): + def __init__(self, + parameter): + parameter['reproduce'] = parameter.get('reproduce', False) + self.reprod = parameter['reproduce'] + if not self.reprod: + if not ('init_from_suffix' in parameter and 'output_suffix' in parameter): + default_supercell = [1, 1, 1] + parameter['supercell'] = parameter.get('supercell', default_supercell) + self.supercell = parameter['supercell'] + parameter['cal_type'] = parameter.get('cal_type', 'relaxation') + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": True, + "relax_shape": True, + "relax_vol": True} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + else: + parameter['cal_type'] = 'static' + self.cal_type = parameter['cal_type'] + default_cal_setting = {"relax_pos": False, + "relax_shape": False, + "relax_vol": False} + if 'cal_setting' not in parameter: + parameter['cal_setting'] = default_cal_setting + else: + if "relax_pos" not in parameter['cal_setting']: + parameter['cal_setting']['relax_pos'] = default_cal_setting['relax_pos'] + if "relax_shape" not in parameter['cal_setting']: + parameter['cal_setting']['relax_shape'] = default_cal_setting['relax_shape'] + if "relax_vol" not in parameter['cal_setting']: + parameter['cal_setting']['relax_vol'] = default_cal_setting['relax_vol'] + self.cal_setting = parameter['cal_setting'] + parameter['init_from_suffix'] = parameter.get('init_from_suffix', '00') + self.init_from_suffix = parameter['init_from_suffix'] + self.parameter = parameter + + def make_confs(self, + path_to_work, + path_to_equi, + refine=False): + path_to_work = os.path.abspath(path_to_work) + if os.path.exists(path_to_work): + dlog.warning('%s already exists' % path_to_work) + else: + os.makedirs(path_to_work) + path_to_equi = os.path.abspath(path_to_equi) + + if 'start_confs_path' in self.parameter and os.path.exists(self.parameter['start_confs_path']): + init_path_list = glob.glob(os.path.join(self.parameter['start_confs_path'], '*')) + struct_init_name_list = [] + for ii in init_path_list: + struct_init_name_list.append(ii.split('/')[-1]) + struct_output_name = path_to_work.split('/')[-2] + assert struct_output_name in struct_init_name_list + path_to_equi = os.path.abspath(os.path.join(self.parameter['start_confs_path'], + struct_output_name, 'relaxation', 'relax_task')) + + task_list = [] + cwd = os.getcwd() + + if self.reprod: + print('vacancy reproduce starts') + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + task_list = make_repro(init_data_path, self.init_from_suffix, + path_to_work, self.parameter.get('reprod_last_frame', False)) + os.chdir(cwd) + + else: + if refine: + print('vacancy refine starts') + task_list = make_refine(self.parameter['init_from_suffix'], + self.parameter['output_suffix'], + path_to_work) + + init_from_path = re.sub(self.parameter['output_suffix'][::-1], + self.parameter['init_from_suffix'][::-1], + path_to_work[::-1], count=1)[::-1] + task_list_basename = list(map(os.path.basename, task_list)) + + for ii in task_list_basename: + init_from_task = os.path.join(init_from_path, ii) + output_task = os.path.join(path_to_work, ii) + os.chdir(output_task) + if os.path.isfile('supercell.json'): + os.remove('supercell.json') + if os.path.islink('supercell.json'): + os.remove('supercell.json') + os.symlink(os.path.relpath(os.path.join(init_from_task, 'supercell.json')), 'supercell.json') + os.chdir(cwd) + else: + equi_contcar = os.path.join(path_to_equi, 'CONTCAR') + if not os.path.exists(equi_contcar): + raise RuntimeError("please do relaxation first") + + ss = Structure.from_file(equi_contcar) + vds = VacancyGenerator(ss) + dss = [] + for jj in vds: + dss.append(jj.generate_defect_structure(self.supercell)) + + print('gen vacancy with supercell ' + str(self.supercell)) + os.chdir(path_to_work) + if os.path.isfile('POSCAR'): + os.remove('POSCAR') + if os.path.islink('POSCAR'): + os.remove('POSCAR') + os.symlink(os.path.relpath(equi_contcar), 'POSCAR') + # task_poscar = os.path.join(output, 'POSCAR') + + for ii in range(len(dss)): + output_task = os.path.join(path_to_work, 'task.%06d' % ii) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for jj in ['INCAR', 'POTCAR', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(jj): + os.remove(jj) + task_list.append(output_task) + dss[ii].to('POSCAR', 'POSCAR') + # np.savetxt('supercell.out', self.supercell, fmt='%d') + dumpfn(self.supercell, 'supercell.json') + os.chdir(cwd) + return task_list + + def post_process(self, task_list): + pass + + def task_type(self): + return self.parameter['type'] + + def task_param(self): + return self.parameter + + def _compute_lower(self, + output_file, + all_tasks, + all_res): + output_file = os.path.abspath(output_file) + res_data = {} + ptr_data = os.path.dirname(output_file) + '\n' + + if not self.reprod: + ptr_data += "Structure: \tVac_E(eV) E(eV) equi_E(eV)\n" + idid = -1 + for ii in all_tasks: + idid += 1 + structure_dir = os.path.basename(ii) + task_result = loadfn(all_res[idid]) + natoms = task_result['atom_numbs'][0] + equi_path = os.path.abspath(os.path.join(os.path.dirname(output_file), '../relaxation/relax_task')) + equi_result = loadfn(os.path.join(equi_path, 'result.json')) + equi_epa = equi_result['energies'][-1] / equi_result['atom_numbs'][0] + evac = task_result['energies'][-1] - equi_epa * natoms + + supercell_index = loadfn(os.path.join(ii, 'supercell.json')) + ptr_data += "%s: %7.3f %7.3f %7.3f \n" % (str(supercell_index) + '-' + structure_dir, + evac, task_result['energies'][-1], equi_epa * natoms) + res_data[str(supercell_index) + '-' + structure_dir] = [evac, task_result['energies'][-1], + equi_epa * natoms] + + else: + if 'init_data_path' not in self.parameter: + raise RuntimeError("please provide the initial data path to reproduce") + init_data_path = os.path.abspath(self.parameter['init_data_path']) + res_data, ptr_data = post_repro(init_data_path, self.parameter['init_from_suffix'], + all_tasks, ptr_data, self.parameter.get('reprod_last_frame', False)) + + with open(output_file, 'w') as fp: + json.dump(res_data, fp, indent=4) + + return res_data, ptr_data diff --git a/dpgen/auto_test/calculator.py b/dpgen/auto_test/calculator.py new file mode 100644 index 000000000..f2ffff20c --- /dev/null +++ b/dpgen/auto_test/calculator.py @@ -0,0 +1,19 @@ +from dpgen.auto_test.VASP import VASP +from dpgen.auto_test.Lammps import Lammps + + +def make_calculator(inter_parameter, + path_to_poscar): + """ + Make an instance of Task + """ + inter_type = inter_parameter['type'] + if inter_type == 'vasp': + return VASP(inter_parameter, path_to_poscar) + elif inter_type in ['deepmd', 'meam', 'eam_fs', 'eam_alloy']: + return Lammps(inter_parameter, path_to_poscar) + # if inter_type == 'siesta': + # return Siesta(inter_parameter, path_to_poscar) + # pass + else: + raise RuntimeError(f'unsupported interaction {inter_type}') diff --git a/dpgen/auto_test/cmpt_00_equi.py b/dpgen/auto_test/cmpt_00_equi.py deleted file mode 100755 index cffa8faf5..000000000 --- a/dpgen/auto_test/cmpt_00_equi.py +++ /dev/null @@ -1,120 +0,0 @@ -#!/usr/bin/env python3 - -import os, glob, argparse, json, warnings, re -import numpy as np -import dpgen.auto_test.lib.lammps as lammps -import dpgen.auto_test.lib.vasp as vasp - -global_equi_name = '00.equi' - -def comput_e_shift(poscar, task_name) : - a_types = vasp.get_poscar_types(poscar) - a_natoms = vasp.get_poscar_natoms(poscar) - ener_shift = 0 - if len(a_types) > 1 : - if not os.path.isdir('stables') : - raise RuntimeError('no dir "stable". Stable energy and volume of components should be computed before calculating formation energy of an alloy') - for ii in range(len(a_types)) : - ref_e_file = a_types[ii] + '.' + task_name + '.e' - ref_e_file = os.path.join('stables', ref_e_file) - ener = float(open(ref_e_file).read()) - ener_shift += a_natoms[ii] * ener - return ener_shift - -def comput_lmp_nev(conf_dir, task_name,write_shift = False) : - conf_path = re.sub('confs', global_equi_name, conf_dir) - conf_path = os.path.abspath(conf_path) - poscar = os.path.join(conf_path, 'POSCAR') - ele_types = vasp.get_poscar_types(poscar) - - lmp_path = os.path.join(conf_path, task_name) - log_lammps = os.path.join(lmp_path, 'log.lammps') - if os.path.isfile(log_lammps): - natoms, epa, vpa = lammps.get_nev(log_lammps) - if write_shift and len(ele_types)>1: - ener_shift = comput_e_shift(poscar, task_name) - shift = (epa * natoms - ener_shift) / natoms - return natoms,epa,vpa,shift - if len(ele_types)==1: - stable_dir = 'stables' - os.makedirs(stable_dir, exist_ok=True) - name_prefix=os.path.join(stable_dir,'%s.%s' % (ele_types[0], task_name)) - open(name_prefix + '.e', 'w').write('%.16f\n' % (epa)) - open(name_prefix + '.v', 'w').write('%.16f\n' % (vpa)) - return natoms, epa, vpa , None - else : - return None, None, None, None - -def comput_vasp_nev(jdata, conf_dir, write_shift = False) : - - conf_path = re.sub('confs', global_equi_name, conf_dir) - conf_path = os.path.abspath(conf_path) - poscar = os.path.join(conf_path, 'POSCAR') - ele_types = vasp.get_poscar_types(poscar) - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - vasp_path = os.path.join(conf_path, vasp_str) - outcar = os.path.join(vasp_path, 'OUTCAR') - # tag_fin = os.path.join(vasp_path, 'tag_finished') - if not os.path.isfile(outcar) : - warnings.warn("cannot find OUTCAR in "+vasp_path+" skip") - elif not vasp.check_finished(outcar): - warnings.warn("incomplete job "+vasp_path+" use the last frame") - if os.path.isfile(outcar): - natoms, epa, vpa = vasp.get_nev(outcar) - if write_shift and len(ele_types)>1: - ener_shift = comput_e_shift(poscar, vasp_str) - shift = (epa * natoms - ener_shift) / natoms - return natoms,epa,vpa,shift - if len(ele_types)==1: - stable_dir = 'stables' - os.makedirs(stable_dir, exist_ok=True) - name_prefix=os.path.join(stable_dir,'%s.'% (ele_types[0])+vasp_str) - open(name_prefix + '.e', 'w').write('%.16f\n' % (epa)) - open(name_prefix + '.v', 'w').write('%.16f\n' % (vpa)) - return natoms, epa, vpa, None - else : - return None, None, None, None - -def _main(): - parser = argparse.ArgumentParser( - description="cmpt 00.equi") - parser.add_argument('TASK', type=str, - choices = ['all', 'vasp', 'deepmd', 'meam'], - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='the json param') - parser.add_argument('CONF', type=str, - help='the dir of conf') - parser.add_argument('-s','--stable', action = 'store_true', - help='the dir of conf') - args = parser.parse_args() - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - if args.TASK == 'all' : - ln, le, lv = comput_lmp_nev(args.CONF, 'deepmd', args.stable) - mn, me, mv = comput_lmp_nev(args.CONF, 'meam', args.stable) - vn, ve, vv = comput_vasp_nev(jdata, args.CONF, args.stable) - if le == None or ve == None or lv == None or vv == None: - print("%s" % args.CONF) - else : - print("%s\t %8.4f %8.4f %8.4f %7.3f %7.3f %7.3f %8.4f %7.3f" % (args.CONF, ve, le, (me), vv, lv, (mv), (le-ve), (lv-vv))) - elif args.TASK == 'vasp' : - vn, ve, vv = comput_vasp_nev(jdata, args.CONF, args.stable) - print("%s\t %8.4f %7.3f " % (args.CONF, ve, vv)) - elif args.TASK == 'deepmd' : - ln, le, lv = comput_lmp_nev(args.CONF, 'deepmd', args.stable) - print("%s\t %8.4f %7.3f " % (args.CONF, le, lv)) - elif args.TASK == 'meam' : - ln, le, lv = comput_lmp_nev(args.CONF, 'meam', args.stable) - print("%s\t %8.4f %7.3f " % (args.CONF, le, lv)) - - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_01_eos.py b/dpgen/auto_test/cmpt_01_eos.py deleted file mode 100755 index 385475059..000000000 --- a/dpgen/auto_test/cmpt_01_eos.py +++ /dev/null @@ -1,81 +0,0 @@ -#!/usr/bin/env python3 - -import os, glob, argparse, json, re -import dpgen.auto_test.lib.util as util -import dpgen.auto_test.lib.lammps as lammps -import dpgen.auto_test.lib.vasp as vasp - -global_task_name = '01.eos' - -def comput_lmp_eos(jdata,conf_dir, task_name) : - conf_path = re.sub('confs', global_task_name, conf_dir) - conf_path = os.path.abspath(conf_path) - conf_path = os.path.join(conf_path, task_name) - vol_paths = glob.glob(os.path.join(conf_path, 'vol-*')) - vol_paths.sort(key=lambda k : float(k.split('-')[-1])) - result = os.path.join(conf_path,'result') - print('Vpa(A^3)\tEpA(eV)') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n VpA(A^3) EpA(eV)\n'% (conf_dir)) - for ii in vol_paths : - log_lammps = os.path.join(ii, 'log.lammps') - natoms, epa, vpa = lammps.get_nev(log_lammps) - print(vpa, epa) - fp.write('%7.3f %8.4f \n' % (vpa,epa)) - fp.close() - if 'upload_username' in jdata.keys() and task_name =='deepmd': - upload_username=jdata['upload_username'] - util.insert_data('eos','deepmd',upload_username,result) - -def comput_vasp_eos(jdata, conf_dir) : - conf_path = re.sub('confs', global_task_name, conf_dir) - conf_path = os.path.abspath(conf_path) - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - task_path = os.path.join(conf_path, vasp_str) - vol_paths = glob.glob(os.path.join(task_path, 'vol-*')) - vol_paths.sort(key=lambda k : float(k.split('-')[-1])) - result = os.path.join(task_path,'result') - print('Vpa(A^3)\tEpA(eV)') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n VpA(A^3) EpA(eV)\n'% (conf_dir)) - for ii in vol_paths : - outcar = os.path.join(ii, 'OUTCAR') - natoms, epa, vpa = vasp.get_nev(outcar) - print(vpa, epa) - fp.write('%7.3f %8.4f \n' % (vpa,epa)) - fp.close() - if 'upload_username' in jdata.keys(): - upload_username=jdata['upload_username'] - util.insert_data('eos','vasp',upload_username,result) - -def _main(): - parser = argparse.ArgumentParser( - description="cmpt 01.eos") - parser.add_argument('TASK', type=str, - choices = ['vasp', 'deepmd', 'meam'], - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - if args.TASK == 'vasp': - comput_vasp_eos(jdata, args.CONF) - elif args.TASK == 'deepmd' : - comput_lmp_eos(jdata,args.CONF, args.TASK) - elif args.TASK == 'meam' : - comput_lmp_eos(jdata,args.CONF, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_02_elastic.py b/dpgen/auto_test/cmpt_02_elastic.py deleted file mode 100755 index b1a0c9229..000000000 --- a/dpgen/auto_test/cmpt_02_elastic.py +++ /dev/null @@ -1,139 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, sys -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -import dpgen.auto_test.lib.util as util -from pymatgen.analysis.elasticity.elastic import ElasticTensor -from pymatgen.analysis.elasticity.strain import Strain -from pymatgen.analysis.elasticity.stress import Stress - -global_equi_name = '00.equi' -global_task_name = '02.elastic' - -def result_et(et,conf_dir,result): - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - for ii in range(6) : - for jj in range(6) : - fp.write ("%7.2f " % (et.voigt[ii][jj] / 1e4)) - fp.write('\n') - BV = et.k_voigt / 1e4 - GV = et.g_voigt / 1e4 - EV = 9*BV*GV/(3*BV+GV) - uV = 0.5*(3*BV-2*GV)/(3*BV+GV) - fp.write("# Bulk Modulus BV = %.2f GPa\n" % (BV)) - fp.write("# Shear Modulus GV = %.2f GPa\n" % (GV)) - fp.write("# Youngs Modulus EV = %.2f GPa\n" % (EV)) - fp.write("# Poission Ratio uV = %.2f \n" % (uV)) - fp.close() - - -def print_et (et): - for ii in range(6) : - for jj in range(6) : - sys.stdout.write ("%7.2f " % (et.voigt[ii][jj] / 1e4)) - sys.stdout.write('\n') - BV = et.k_voigt / 1e4 - GV = et.g_voigt / 1e4 - EV = 9*BV*GV/(3*BV+GV) - uV = 0.5*(3*BV-2*GV)/(3*BV+GV) - print("# Bulk Modulus BV = %.2f GPa" % (BV)) - print("# Shear Modulus GV = %.2f GPa" % (GV)) - print("# Youngs Modulus EV = %.2f GPa" % (EV)) - print("# Poission Ratio uV = %.2f " % (uV)) - -def cmpt_vasp(jdata, conf_dir) : - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - task_path = re.sub('confs', global_task_name, conf_path) - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - fp_params = jdata['vasp_params'] - kspacing = fp_params['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - task_path = os.path.join(task_path, vasp_str) - - equi_stress = Stress(np.loadtxt(os.path.join(task_path, 'equi.stress.out'))) - - lst_dfm_path = glob.glob(os.path.join(task_path, 'dfm-*')) - lst_strain = [] - lst_stress = [] - for ii in lst_dfm_path : - strain = np.loadtxt(os.path.join(ii, 'strain.out')) - stress = vasp.get_stress(os.path.join(ii, 'OUTCAR')) - # convert from pressure in kB to stress - stress *= -1000 - lst_strain.append(Strain(strain)) - lst_stress.append(Stress(stress)) - et = ElasticTensor.from_independent_strains(lst_strain, lst_stress, eq_stress = equi_stress, vasp = False) - # et = ElasticTensor.from_independent_strains(lst_strain, lst_stress, eq_stress = None) - # bar to GPa - # et = -et / 1e4 - print_et(et) - result = os.path.join(task_path,'result') - result_et(et,conf_dir,result) - if 'upload_username' in jdata.keys(): - upload_username=jdata['upload_username'] - util.insert_data('elastic','vasp',upload_username,result) - - -def cmpt_deepmd_lammps(jdata, conf_dir, task_name) : - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_name) - equi_stress = Stress(np.loadtxt(os.path.join(task_path, 'equi.stress.out'))) - - lst_dfm_path = glob.glob(os.path.join(task_path, 'dfm-*')) - lst_strain = [] - lst_stress = [] - for ii in lst_dfm_path : - strain = np.loadtxt(os.path.join(ii, 'strain.out')) - stress = lammps.get_stress(os.path.join(ii, 'log.lammps')) - # convert from pressure to stress - stress = -stress - lst_strain.append(Strain(strain)) - lst_stress.append(Stress(stress)) - et = ElasticTensor.from_independent_strains(lst_strain, lst_stress, eq_stress = equi_stress, vasp = False) - # et = ElasticTensor.from_independent_strains(lst_strain, lst_stress, eq_stress = None) - # bar to GPa - # et = -et / 1e4 - print_et(et) - result = os.path.join(task_path,'result') - result_et(et,conf_dir,result) - if 'upload_username' in jdata.keys() and task_name=='deepmd': - upload_username=jdata['upload_username'] - util.insert_data('elastic','deepmd',upload_username,result) - - - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 02.elastic") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK) - elif args.TASK == 'meam' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_03_vacancy.py b/dpgen/auto_test/cmpt_03_vacancy.py deleted file mode 100755 index a53602d38..000000000 --- a/dpgen/auto_test/cmpt_03_vacancy.py +++ /dev/null @@ -1,136 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, sys -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.analysis.elasticity.elastic import ElasticTensor -from pymatgen.analysis.elasticity.strain import Strain -from pymatgen.analysis.elasticity.stress import Stress - -global_equi_name = '00.equi' -global_task_name = '03.vacancy' - -def comput_e_shift(poscar, task_name) : - a_types = vasp.get_poscar_types(poscar) - a_natoms = vasp.get_poscar_natoms(poscar) - ener_shift = 0 - if not os.path.isdir('stables') : - raise RuntimeError('no dir "stable". Stable energy and volume of components should be computed before calculating formation energy of an alloy') - for ii in range(len(a_types)) : - ref_e_file = a_types[ii] + '.' + task_name + '.e' - ref_e_file = os.path.join('stables', ref_e_file) - ener = float(open(ref_e_file).read()) - ener_shift += a_natoms[ii] * ener - return ener_shift - -def cmpt_vasp(jdata, conf_dir, supercell) : - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, vasp_str) - equi_path = os.path.abspath(equi_path) - equi_outcar = os.path.join(equi_path, 'OUTCAR') - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.join(task_path, vasp_str) - task_path = os.path.abspath(task_path) - print("# ", task_path) - - equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar) - - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_path_widecard = os.path.join(task_path, 'struct-%s-*' % (copy_str)) - struct_path_list = glob.glob(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s supercell %s" % (conf_dir, supercell)) - sys.stdout.write ("Structure: \tVac_E(eV) E(eV) equi_E(eV)\n") - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write("Structure: \tVac_E(eV) E(eV) equi_E(eV)\n") - for ii in struct_path_list : - struct_poscar = os.path.join(ii, 'POSCAR') - #energy_shift = comput_e_shift(struct_poscar, vasp_str) - structure_dir = os.path.basename(ii) - outcar = os.path.join(ii, 'OUTCAR') - natoms, epa, vpa = vasp.get_nev(outcar) - evac = epa * natoms - equi_epa * natoms - sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa*natoms)) - fp.write("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa*natoms)) - fp.close() - # evac = epa * natoms - energy_shift - # sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, energy_shift)) - # sys.stdout.write ("%s: %7.3f \n" % (structure_dir, evac)) - -def cmpt_deepmd_lammps(jdata, conf_dir, supercell, task_name) : - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, task_name) - equi_path = os.path.abspath(equi_path) - equi_log = os.path.join(equi_path, 'log.lammps') - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.join(task_path, task_name) - task_path = os.path.abspath(task_path) - print("# ", task_path) - - equi_natoms, equi_epa, equi_vpa = lammps.get_nev(equi_log) - - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_path_widecard = os.path.join(task_path, 'struct-%s-*' % (copy_str)) - struct_path_list = glob.glob(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s supercell %s" % (conf_dir, supercell)) - sys.stdout.write ("Structure: \tVac_E(eV) E(eV) equi_E(eV)\n") - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write("Structure: \tVac_E(eV) E(eV) equi_E(eV)\n") - for ii in struct_path_list : - struct_poscar = os.path.join(ii, 'POSCAR') - #energy_shift = comput_e_shift(struct_poscar, task_name) - structure_dir = os.path.basename(ii) - lmp_log = os.path.join(ii, 'log.lammps') - natoms, epa, vpa = lammps.get_nev(lmp_log) - evac = epa * natoms - equi_epa * natoms - sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa * natoms)) - fp.write("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa*natoms)) - fp.close() - # evac = epa * natoms - energy_shift - # sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, energy_shift)) - # sys.stdout.write ("%s: %7.3f\n" % (structure_dir, evac)) - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 03.vacancy") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('COPY', type=int, nargs = 3, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF, args.COPY) - elif args.TASK == 'deepmd' : - cmpt_deepmd_lammps(jdata, args.CONF, args.COPY, args.TASK) - elif args.TASK == 'meam' : - cmpt_deepmd_lammps(jdata, args.CONF, args.COPY, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_04_interstitial.py b/dpgen/auto_test/cmpt_04_interstitial.py deleted file mode 100755 index 6b029909c..000000000 --- a/dpgen/auto_test/cmpt_04_interstitial.py +++ /dev/null @@ -1,177 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, sys -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.analysis.elasticity.elastic import ElasticTensor -from pymatgen.analysis.elasticity.strain import Strain -from pymatgen.analysis.elasticity.stress import Stress - -global_equi_name = '00.equi' -global_task_name = '04.interstitial' - -def cmpt_vasp(jdata, conf_dir, supercell, insert_ele) : - for ii in insert_ele: - _cmpt_vasp(jdata, conf_dir, supercell, ii) - -def _cmpt_vasp(jdata, conf_dir, supercell, insert_ele) : - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, vasp_str) - equi_path = os.path.abspath(equi_path) - equi_outcar = os.path.join(equi_path, 'OUTCAR') - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.join(task_path, vasp_str) - task_path = os.path.abspath(task_path) - - equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar) - - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_path_widecard = os.path.join(task_path, 'struct-%s-%s-*' % (insert_ele, copy_str)) - print(struct_path_widecard) - struct_path_list = glob.glob(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s supercell %s" % (conf_dir, supercell)) - sys.stdout.write ("Insert_ele-Struct: Inter_E(eV) E(eV) equi_E(eV)\n") - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write ("Insert_ele-Struct: Inter_E(eV) E(eV) equi_E(eV)\n") - for ii in struct_path_list : - structure_dir = os.path.basename(ii) - outcar = os.path.join(ii, 'OUTCAR') - natoms, epa, vpa = vasp.get_nev(outcar) - evac = epa * natoms - equi_epa * natoms - sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa * natoms)) - fp.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa * natoms)) - fp.close() - -def cmpt_deepmd_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_name) : - for ii in insert_ele: - _cmpt_deepmd_reprod_traj(jdata, conf_dir, supercell, ii, task_name) - -def _cmpt_deepmd_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_name) : - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - conf_path = os.path.abspath(conf_dir) - task_path = re.sub('confs', global_task_name, conf_path) - vasp_path = os.path.join(task_path, vasp_str) - lmps_path = os.path.join(task_path, task_name + vasp_str.replace('vasp','')) - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_widecard = os.path.join(vasp_path, 'struct-%s-%s-*' % (insert_ele,copy_str)) - vasp_struct = glob.glob(struct_widecard) - vasp_struct.sort() - cwd=os.getcwd() - - for vs in vasp_struct : - # compute vasp - outcar = os.path.join(vs, 'OUTCAR') - vasp_ener = np.array(vasp.get_energies(outcar)) - vasp_ener_file = os.path.join(vs, 'ener.vasp.out') - # compute reprod - struct_basename = os.path.basename(vs) - ls = os.path.join(lmps_path, struct_basename) - frame_widecard = os.path.join(ls, 'frame.*') - frames = glob.glob(frame_widecard) - frames.sort() - lmp_ener = [] - for ii in frames : - log_lmp = os.path.join(ii, 'log.lammps') - natoms, epa, vpa = lammps.get_nev(log_lmp) - lmp_ener.append(epa) - lmp_ener = np.array(lmp_ener) - lmp_ener = np.reshape(lmp_ener, [-1,1]) - lmp_ener_file = os.path.join(ls, 'ener.lmp.out') - vasp_ener = np.reshape(vasp_ener, [-1,1]) / natoms - error_start = 1 - lmp_ener -= lmp_ener[-1] - vasp_ener[-1] - diff = lmp_ener - vasp_ener - diff = diff[error_start:] - error = np.linalg.norm(diff) / np.sqrt(np.size(lmp_ener)) - np.savetxt(vasp_ener_file, vasp_ener[error_start:]) - np.savetxt(lmp_ener_file, lmp_ener[error_start:]) - print(os.path.basename(ls), 'EpA_std_err=',error) - -def cmpt_deepmd_lammps(jdata, conf_dir, supercell, insert_ele, task_name) : - for ii in insert_ele: - _cmpt_deepmd_lammps(jdata, conf_dir, supercell, ii, task_name) - -def _cmpt_deepmd_lammps(jdata, conf_dir, supercell, insert_ele, task_name) : - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, task_name.split('-')[0]) - equi_path = os.path.abspath(equi_path) - equi_log = os.path.join(equi_path, 'log.lammps') - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.join(task_path, task_name) - task_path = os.path.abspath(task_path) - - equi_natoms, equi_epa, equi_vpa = lammps.get_nev(equi_log) - - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_path_widecard = os.path.join(task_path, 'struct-%s-%s-*' % (insert_ele,copy_str)) - struct_path_list = glob.glob(struct_path_widecard) - print(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s supercell %s" % (conf_dir, supercell)) - sys.stdout.write ("Insert_ele-Struct: Inter_E(eV) E(eV) equi_E(eV)\n") - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write ("Insert_ele-Struct: Inter_E(eV) E(eV) equi_E(eV)\n") - for ii in struct_path_list : - structure_dir = os.path.basename(ii) - lmp_log = os.path.join(ii, 'log.lammps') - natoms, epa, vpa = lammps.get_nev(lmp_log) - evac = epa * natoms - equi_epa * natoms - sys.stdout.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa * natoms)) - fp.write ("%s: %7.3f %7.3f %7.3f \n" % (structure_dir, evac, epa * natoms, equi_epa * natoms)) - fp.close() - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 04.interstitial") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('COPY', type=int, nargs = 3, - help='define the supercell') - parser.add_argument('ELEMENT', type=str, nargs = '+', - help='the inserted element') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF, args.COPY, args.ELEMENT) - elif args.TASK == 'deepmd' : - cmpt_deepmd_lammps(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - elif args.TASK == 'deepmd-reprod' : - cmpt_deepmd_reprod_traj(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - elif args.TASK == 'meam' : - cmpt_deepmd_lammps(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - elif args.TASK == 'meam-reprod' : - cmpt_deepmd_reprod_traj(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_05_surf.py b/dpgen/auto_test/cmpt_05_surf.py deleted file mode 100755 index fde28911d..000000000 --- a/dpgen/auto_test/cmpt_05_surf.py +++ /dev/null @@ -1,134 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, sys -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.util as util -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps - -global_equi_name = '00.equi' -global_task_name = '05.surf' - -def cmpt_vasp(jdata, conf_dir, static = False) : - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % (kspacing) - - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, vasp_str) - equi_path = os.path.abspath(equi_path) - equi_outcar = os.path.join(equi_path, 'OUTCAR') - task_path = re.sub('confs', global_task_name, conf_dir) - if static : - if 'scf_incar' in jdata.keys(): - vasp_static_str='vasp-static-scf_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_static_str='vasp-static-k%.2f' % (kspacing) - task_path = os.path.join(task_path, vasp_static_str) - else : - task_path = os.path.join(task_path, vasp_str) - task_path = os.path.abspath(task_path) - - equi_natoms, equi_epa, equi_vpa = vasp.get_nev(equi_outcar) - - struct_path_widecard = os.path.join(task_path, 'struct-*-m*m') - struct_path_list = glob.glob(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s" % (conf_dir)) - sys.stdout.write ("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n") - - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n") - for ii in struct_path_list : - structure_dir = os.path.basename(ii) - outcar = os.path.join(ii, 'OUTCAR') - natoms, epa, vpa = vasp.get_nev(outcar) - if static : - e0 = np.array(vasp.get_energies(outcar)) / natoms - epa = e0[0] - boxes = vasp.get_boxes(outcar) - AA = np.linalg.norm(np.cross(boxes[0][0], boxes[0][1])) - Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001 - evac = (epa * natoms - equi_epa * natoms) / AA * Cf - sys.stdout.write ("%s:\t %7.3f %8.3f %8.3f\n" % (structure_dir, evac, epa, equi_epa)) - fp.write("%s:\t %7.3f %8.3f %8.3f\n" % (structure_dir, evac, epa, equi_epa)) - fp.close() - if 'upload_username' in jdata.keys(): - upload_username=jdata['upload_username'] - util.insert_data('surf','vasp',upload_username,result) - -def cmpt_deepmd_lammps(jdata, conf_dir, task_name, static = False) : - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, task_name.split('-')[0]) - equi_path = os.path.abspath(equi_path) - equi_log = os.path.join(equi_path, 'log.lammps') - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.join(task_path, task_name) - task_path = os.path.abspath(task_path) - - equi_natoms, equi_epa, equi_vpa = lammps.get_nev(equi_log) - - struct_path_widecard = os.path.join(task_path, 'struct-*-m*m') - struct_path_list = glob.glob(struct_path_widecard) - struct_path_list.sort() - if len(struct_path_list) == 0: - print("# cannot find results for conf %s" % (conf_dir)) - sys.stdout.write ("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n") - result = os.path.join(task_path,'result') - with open(result,'w') as fp: - fp.write('conf_dir:%s\n'% (conf_dir)) - fp.write("Miller_Indices: \tSurf_E(J/m^2) EpA(eV) equi_EpA(eV)\n") - for ii in struct_path_list : - structure_dir = os.path.basename(ii) - lmp_log = os.path.join(ii, 'log.lammps') - natoms, epa, vpa = lammps.get_nev(lmp_log) - AA = lammps.get_base_area(lmp_log) - Cf = 1.60217657e-16 / (1e-20 * 2) * 0.001 - evac = (epa * natoms - equi_epa * natoms) / AA * Cf - sys.stdout.write ("%s: \t%7.3f %8.3f %8.3f\n" % (structure_dir, evac, epa, equi_epa)) - fp.write("%s:\t %7.3f %8.3f %8.3f\n" % (structure_dir, evac, epa, equi_epa)) - fp.close() - if 'upload_username' in jdata.keys() and task_name=='deepmd': - upload_username=jdata['upload_username'] - util.insert_data('surf','deepmd',upload_username,result) - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 05.surf") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF) - elif args.TASK == 'vasp-static': - cmpt_vasp(jdata, args.CONF, static = True) - elif args.TASK == 'deepmd' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK) - elif args.TASK == 'deepmd-static' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK, static = True) - elif args.TASK == 'meam' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK) - elif args.TASK == 'meam-static' : - cmpt_deepmd_lammps(jdata, args.CONF, args.TASK, static = True) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/cmpt_06_phonon.py b/dpgen/auto_test/cmpt_06_phonon.py deleted file mode 100644 index cefa615fe..000000000 --- a/dpgen/auto_test/cmpt_06_phonon.py +++ /dev/null @@ -1,117 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from phonopy import Phonopy -from phonopy.structure.atoms import PhonopyAtoms - -import yaml -import phonopy - - - - -global_equi_name = '00.equi' -global_task_name = '06.phonon' - -''' -link poscar -link potcar -make incar -''' - -def get_force_from_dump(cell): - na=len(cell) - with open("dump.relax","r") as fp: - lines = fp.readlines() - flag=False - index=[] - forces=[] - for line in lines: - if flag: - data=line.split() - index.append(data[0]) - forces.append(data[5:9]) - if len(forces)==na: - break - if 'fx fy fz' in line: - flag=True - index = np.asarray(index, int) - indexing = np.argsort(index) - if len(forces)==na: - forces=np.asarray(np.reshape(forces,(na,3)),float)[indexing, :] - else: - raise RuntimeError('Incomplete result: dump.relax') - return forces - -def cmpt_vasp(jdata, conf_dir) : - fp_params = jdata['vasp_params'] - kspacing = fp_params['kspacing'] - supercell_matrix=jdata['supercell_matrix'] - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - vasp_str='vasp-k%.2f' % kspacing - - conf_path = os.path.abspath(conf_dir) - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, vasp_str) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('vasprun.xml'): - os.system('phonopy --fc vasprun.xml') - if os.path.isfile('FORCE_CONSTANTS'): - os.system('phonopy --dim="%d %d %d" -c POSCAR-unitcell band.conf'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - os.system('phonopy-bandplot --gnuplot band.yaml > band.dat') - print('band.dat is created') - else: - print('FORCE_CONSTANTS No such file') - else: - print('vasprun.xml No such file') - - - -def cmpt_lammps(jdata, conf_dir, task_type) : - supercell_matrix=jdata['supercell_matrix'] - - conf_path = os.path.abspath(conf_dir) - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - task_poscar = os.path.join(task_path, 'POSCAR') - - os.chdir(task_path) - if os.path.isfile('FORCE_CONSTANTS'): - os.system('phonopy --dim="%d %d %d" -c POSCAR band.conf'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - os.system('phonopy-bandplot --gnuplot band.yaml > band.dat') - else: - print('FORCE_CONSTANTS No such file') - - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 06.phonon") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK =='meam' : - cmpt_lammps(jdata, args.CONF,args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - diff --git a/dpgen/auto_test/cmpt_07_SScurve.py b/dpgen/auto_test/cmpt_07_SScurve.py deleted file mode 100644 index f8e23ddbe..000000000 --- a/dpgen/auto_test/cmpt_07_SScurve.py +++ /dev/null @@ -1,93 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, sys -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps - - -global_equi_name = '00.equi' -global_task_name = '07.SScurve' - -def cmpt_vasp(jdata, conf_dir) : - fp_params = jdata['vasp_params'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - strain_direct=jdata['strain_direct'] - a,b=strain_direct[0],strain_direct[1] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing) - - lst_dfm_path = glob.glob(os.path.join(task_path, 'dfm-*')) - lst_strain = [] - lst_stress = [] - print('conf_dir:',conf_dir) - print('strain\t stress(kB)') - for ii in lst_dfm_path : - strain = np.loadtxt(os.path.join(ii, 'strain.out')) - stress = vasp.get_stress(os.path.join(ii, 'OUTCAR')) - # convert from pressure in kB to stress - stress = -stress - lst_strain.append(strain[a,b]) - lst_stress.append(stress[a,b]) - index=np.argsort(lst_strain) - for ii in range(len(lst_strain)): - print('%7.4f %7.4f'%(lst_strain[index[ii]],lst_stress[index[ii]])) - - -def cmpt_lammps(jdata, conf_dir, task_name) : - strain_direct=jdata['strain_direct'] - a,b=strain_direct[0],strain_direct[1] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_name) - - - lst_dfm_path = glob.glob(os.path.join(task_path, 'dfm-*')) - lst_strain = [] - lst_stress = [] - print('conf_dir:',conf_dir) - print('strain\t stress(kB)') - for ii in lst_dfm_path : - strain = np.loadtxt(os.path.join(ii, 'strain.out')) - stress = lammps.get_stress(os.path.join(ii, 'log.lammps')) - # convert from pressure to stress - stress = -stress/1000 - lst_strain.append(strain[a,b]) - lst_stress.append(stress[a,b]) - index=np.argsort(lst_strain) - for ii in range(len(lst_strain)): - print('%7.4f %7.4f'%(lst_strain[index[ii]],lst_stress[index[ii]])) - -def _main() : - parser = argparse.ArgumentParser( - description="cmpt 07.SScurve") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - cmpt_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' : - cmpt_lammps(jdata, args.CONF, args.TASK) - elif args.TASK == 'meam' : - cmpt_lammps(jdata, args.CONF, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/common_equi.py b/dpgen/auto_test/common_equi.py new file mode 100644 index 000000000..c8fa31431 --- /dev/null +++ b/dpgen/auto_test/common_equi.py @@ -0,0 +1,191 @@ +import glob +import os + +from monty.serialization import dumpfn + +import dpgen.auto_test.lib.crys as crys +import dpgen.auto_test.lib.util as util +from dpgen import dlog +from dpgen.auto_test.calculator import make_calculator +from dpgen.auto_test.mpdb import get_structure +from dpgen.dispatcher.Dispatcher import make_dispatcher +from dpgen.remote.decide_machine import decide_fp_machine, decide_model_devi_machine + +lammps_task_type = ['deepmd', 'meam', 'eam_fs', 'eam_alloy'] + + +def make_equi(confs, + inter_param, + relax_param): + # find all POSCARs and their name like mp-xxx + # ... + dlog.debug('debug info make equi') + if 'type_map' in inter_param: + ele_list = [key for key in inter_param['type_map'].keys()] + else: + ele_list = [key for key in inter_param['potcars'].keys()] + # ele_list = inter_param['type_map'] + dlog.debug("ele_list %s" % ':'.join(ele_list)) + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + + # generate a list of task names like mp-xxx/relaxation/relax_task + # ... + cwd = os.getcwd() + # generate poscar for single element crystal + if len(ele_list) == 1: + for ii in conf_dirs: + os.chdir(ii) + crys_type = ii.split('/')[-1] + dlog.debug('crys_type: %s' % crys_type) + dlog.debug('pwd: %s' % os.getcwd()) + if crys_type == 'std-fcc': + if not os.path.exists('POSCAR'): + crys.fcc1(ele_list[0]).to('POSCAR', 'POSCAR') + elif crys_type == 'std-hcp': + if not os.path.exists('POSCAR'): + crys.hcp(ele_list[0]).to('POSCAR', 'POSCAR') + elif crys_type == 'std-dhcp': + if not os.path.exists('POSCAR'): + crys.dhcp(ele_list[0]).to('POSCAR', 'POSCAR') + elif crys_type == 'std-bcc': + if not os.path.exists('POSCAR'): + crys.bcc(ele_list[0]).to('POSCAR', 'POSCAR') + elif crys_type == 'std-diamond': + if not os.path.exists('POSCAR'): + crys.diamond(ele_list[0]).to('POSCAR', 'POSCAR') + elif crys_type == 'std-sc': + if not os.path.exists('POSCAR'): + crys.sc(ele_list[0]).to('POSCAR', 'POSCAR') + + os.chdir(cwd) + task_dirs = [] + # make task directories like mp-xxx/relaxation/relax_task + # if mp-xxx/exists then print a warning and exit. + # ... + for ii in conf_dirs: + crys_type = ii.split('/')[-1] + dlog.debug('crys_type: %s' % crys_type) + + if 'mp-' in crys_type and not os.path.exists(os.path.join(ii, 'POSCAR')): + get_structure(crys_type).to('POSCAR', os.path.join(ii, 'POSCAR')) + + poscar = os.path.abspath(os.path.join(ii, 'POSCAR')) + if not os.path.exists(poscar): + raise FileNotFoundError('no configuration for autotest') + relax_dirs = os.path.abspath(os.path.join(ii, 'relaxation', 'relax_task')) # to be consistent with property in make dispatcher + if os.path.exists(relax_dirs): + dlog.warning('%s already exists' % relax_dirs) + else: + os.makedirs(relax_dirs) + task_dirs.append(relax_dirs) + os.chdir(relax_dirs) + # copy POSCARs to mp-xxx/relaxation/relax_task + # ... + if os.path.isfile('POSCAR'): + os.remove('POSCAR') + os.symlink(os.path.relpath(poscar), 'POSCAR') + os.chdir(cwd) + task_dirs.sort() + # generate task files + relax_param['cal_type'] = 'relaxation' + if 'cal_setting' not in relax_param: + relax_param['cal_setting'] = {"relax_pos": True, + "relax_shape": True, + "relax_vol": True} + elif "relax_pos" not in relax_param['cal_setting']: + relax_param['cal_setting']['relax_pos'] = True + elif "relax_shape" not in relax_param['cal_setting']: + relax_param['cal_setting']['relax_shape'] = True + elif "relax_vol" not in relax_param['cal_setting']: + relax_param['cal_setting']['relax_vol'] = True + + for ii in task_dirs: + poscar = os.path.join(ii, 'POSCAR') + dlog.debug('task_dir %s' % ii) + inter = make_calculator(inter_param, poscar) + inter.make_potential_files(ii) + inter.make_input_file(ii, 'relaxation', relax_param) + + +def run_equi(confs, + inter_param, + mdata): + # find all POSCARs and their name like mp-xxx + # ... + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + # generate a list of task names like mp-xxx/relaxation/relax_task + # ... + work_path_list = [] + for ii in conf_dirs: + work_path_list.append(os.path.abspath(os.path.join(ii, 'relaxation'))) + all_task = [] + for ii in work_path_list: + all_task.append(os.path.join(ii, 'relax_task')) + + inter_type = inter_param['type'] + # vasp + if inter_type == "vasp": + mdata = decide_fp_machine(mdata) + elif inter_type in lammps_task_type: + mdata = decide_model_devi_machine(mdata) + else: + raise RuntimeError("unknown task %s, something wrong" % inter_type) + + # dispatch the tasks + # POSCAR here is useless + virtual_calculator = make_calculator(inter_param, "POSCAR") + forward_files = virtual_calculator.forward_files() + forward_common_files = virtual_calculator.forward_common_files() + backward_files = virtual_calculator.backward_files() + # backward_files += logs + # ... + run_tasks = util.collect_task(all_task, inter_type) + if len(run_tasks) == 0: + return + else: + run_tasks = [os.path.basename(ii) for ii in all_task] + machine, resources, command, group_size = util.get_machine_info(mdata, inter_type) + print('%d tasks will be submited '%len(run_tasks)) + for ii in range(len(work_path_list)): + work_path = work_path_list[ii] + disp = make_dispatcher(machine, resources, work_path, [run_tasks[ii]], group_size) + print("%s --> Runing... "%(work_path)) + disp.run_jobs(resources, + command, + work_path, + [run_tasks[ii]], + group_size, + forward_common_files, + forward_files, + backward_files, + outlog='outlog', + errlog='errlog') + + +def post_equi(confs, inter_param): + # find all POSCARs and their name like mp-xxx + # ... + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + task_dirs = [] + for ii in conf_dirs: + task_dirs.append(os.path.abspath(os.path.join(ii, 'relaxation', 'relax_task'))) + task_dirs.sort() + + # generate a list of task names like mp-xxx/relaxation + # ... + + # dump the relaxation result. + for ii in task_dirs: + poscar = os.path.join(ii, 'POSCAR') + inter = make_calculator(inter_param, poscar) + res = inter.compute(ii) + dumpfn(res, os.path.join(ii, 'result.json'), indent=4) diff --git a/dpgen/auto_test/common_prop.py b/dpgen/auto_test/common_prop.py new file mode 100644 index 000000000..0ffe1e60d --- /dev/null +++ b/dpgen/auto_test/common_prop.py @@ -0,0 +1,239 @@ +import glob +import os +from multiprocessing import Pool +import dpgen.auto_test.lib.util as util +from dpgen import dlog +from dpgen.util import sepline +from dpgen.auto_test.EOS import EOS +from dpgen.auto_test.Elastic import Elastic +from dpgen.auto_test.Interstitial import Interstitial +from dpgen.auto_test.Surface import Surface +from dpgen.auto_test.Vacancy import Vacancy +from dpgen.auto_test.calculator import make_calculator +from dpgen.dispatcher.Dispatcher import make_dispatcher +from dpgen.remote.decide_machine import decide_fp_machine, decide_model_devi_machine + +lammps_task_type = ['deepmd', 'meam', 'eam_fs', 'eam_alloy'] + + +def make_property_instance(paramters): + """ + Make an instance of Property + """ + prop_type = paramters['type'] + if prop_type == 'eos': + return EOS(paramters) + elif prop_type == 'elastic': + return Elastic(paramters) + elif prop_type == 'vacancy': + return Vacancy(paramters) + elif prop_type == 'interstitial': + return Interstitial(paramters) + elif prop_type == 'surface': + return Surface(paramters) + else: + raise RuntimeError(f'unknown property type {prop_type}') + + +def make_property(confs, + inter_param, + property_list): + # find all POSCARs and their name like mp-xxx + # ... + # conf_dirs = glob.glob(confs) + # conf_dirs.sort() + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + for ii in conf_dirs: + sepline(ch=ii, screen=True) + for jj in property_list: + if jj.get("skip", False): + continue + if 'init_from_suffix' and 'output_suffix' in jj: + do_refine = True + suffix = jj['output_suffix'] + elif 'reproduce' in jj and jj['reproduce']: + do_refine = False + suffix = 'reprod' + else: + do_refine = False + suffix = '00' + # generate working directory like mp-xxx/eos_00 if jj['type'] == 'eos' + # handel the exception that the working directory exists + # ... + + # determine the suffix: from scratch or refine + # ... + + property_type = jj['type'] + path_to_equi = os.path.join(ii, 'relaxation', 'relax_task') + path_to_work = os.path.join(ii, property_type + '_' + suffix) + + if os.path.exists(path_to_work): + dlog.warning('%s already exists' % path_to_work) + else: + os.makedirs(path_to_work) + + prop = make_property_instance(jj) + task_list = prop.make_confs(path_to_work, path_to_equi, do_refine) + + inter_param_prop = inter_param + if 'cal_setting' in jj and 'overwrite_interaction' in jj['cal_setting']: + inter_param_prop = jj['cal_setting']['overwrite_interaction'] + + for kk in task_list: + poscar = os.path.join(kk, 'POSCAR') + inter = make_calculator(inter_param_prop, poscar) + inter.make_potential_files(kk) + dlog.debug(prop.task_type()) ### debug + inter.make_input_file(kk, prop.task_type(), prop.task_param()) + + prop.post_process(task_list) # generate same KPOINTS file for elastic when doing VASP + + +def run_property(confs, + inter_param, + property_list, + mdata): + # find all POSCARs and their name like mp-xxx + # ... + # conf_dirs = glob.glob(confs) + # conf_dirs.sort() + processes = len(property_list) + pool = Pool(processes=processes) + print("Submit job via %d processes" % processes) + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + task_list = [] + work_path_list = [] + for ii in conf_dirs: + sepline(ch=ii, screen=True) + for jj in property_list: + # determine the suffix: from scratch or refine + # ... + if jj.get("skip", False): + continue + if 'init_from_suffix' and 'output_suffix' in jj: + suffix = jj['output_suffix'] + elif 'reproduce' in jj and jj['reproduce']: + suffix = 'reprod' + else: + suffix = '00' + + property_type = jj['type'] + path_to_work = os.path.abspath(os.path.join(ii, property_type + '_' + suffix)) + + work_path_list.append(path_to_work) + tmp_task_list = glob.glob(os.path.join(path_to_work, 'task.[0-9]*[0-9]')) + tmp_task_list.sort() + task_list.append(tmp_task_list) + + inter_param_prop = inter_param + if 'cal_setting' in jj and 'overwrite_interaction' in jj['cal_setting']: + inter_param_prop = jj['cal_setting']['overwrite_interaction'] + + # dispatch the tasks + # POSCAR here is useless + virtual_calculator = make_calculator(inter_param_prop, "POSCAR") + forward_files = virtual_calculator.forward_files(property_type) + forward_common_files = virtual_calculator.forward_common_files(property_type) + backward_files = virtual_calculator.backward_files(property_type) + # backward_files += logs + # ... + inter_type = inter_param_prop['type'] + # vasp + if inter_type == "vasp": + mdata = decide_fp_machine(mdata) + elif inter_type in lammps_task_type: + mdata = decide_model_devi_machine(mdata) + else: + raise RuntimeError("unknown task %s, something wrong" % inter_type) + + work_path = path_to_work + all_task = tmp_task_list + run_tasks = util.collect_task(all_task, inter_type) + if len(run_tasks) == 0: + return + else: + ret = pool.apply_async(worker, (work_path, + all_task, + forward_common_files, + forward_files, + backward_files, + mdata, + inter_type, + )) + # run_tasks = [os.path.basename(ii) for ii in all_task] + # machine, resources, command, group_size = util.get_machine_info(mdata, inter_type) + # disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) + # disp.run_jobs(resources, + # command, + # work_path, + # run_tasks, + # group_size, + # forward_common_files, + # forward_files, + # backward_files, + # outlog='outlog', + # errlog='errlog') + pool.close() + pool.join() + if ret.successful(): + print('finished') + + +def worker(work_path, + all_task, + forward_common_files, + forward_files, + backward_files, + mdata, + inter_type): + run_tasks = [os.path.basename(ii) for ii in all_task] + machine, resources, command, group_size = util.get_machine_info(mdata, inter_type) + disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) + disp.run_jobs(resources, + command, + work_path, + run_tasks, + group_size, + forward_common_files, + forward_files, + backward_files, + outlog='outlog', + errlog='errlog') + + +def post_property(confs, + # inter_param, + property_list): + # find all POSCARs and their name like mp-xxx + # ... + # task_list = [] + # conf_dirs = glob.glob(confs) + # conf_dirs.sort() + conf_dirs = [] + for conf in confs: + conf_dirs.extend(glob.glob(conf)) + conf_dirs.sort() + for ii in conf_dirs: + for jj in property_list: + # determine the suffix: from scratch or refine + # ... + if jj.get("skip", False): + continue + if 'init_from_suffix' and 'output_suffix' in jj: + suffix = jj['output_suffix'] + elif 'reproduce' in jj and jj['reproduce']: + suffix = 'reprod' + else: + suffix = '00' + property_type = jj['type'] + path_to_work = os.path.join(ii, property_type + '_' + suffix) + prop = make_property_instance(jj) + prop.compute(os.path.join(path_to_work, 'result.json'), os.path.join(path_to_work, 'result.out'), + path_to_work) diff --git a/dpgen/auto_test/gen_00_equi.py b/dpgen/auto_test/gen_00_equi.py deleted file mode 100755 index a2b5b00c9..000000000 --- a/dpgen/auto_test/gen_00_equi.py +++ /dev/null @@ -1,193 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps - -from dpgen import dlog -from dpgen.generator.lib.vasp import incar_upper -from dpgen import ROOT_PATH -from pymatgen.io.vasp import Incar -from dpgen.generator.lib.vasp import incar_upper - -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - -global_task_name = '00.equi' - -''' -link poscar -link potcar -make incar -''' -def make_vasp(jdata, conf_dir) : - conf_path = os.path.abspath(conf_dir) - equi_path = re.sub('confs', global_task_name, conf_path) - os.makedirs(equi_path, exist_ok = True) - cwd = os.getcwd() - from_poscar = os.path.join(conf_path, 'POSCAR') - to_poscar = os.path.join(equi_path, 'POSCAR') - if os.path.exists(to_poscar) : - assert(filecmp.cmp(from_poscar, to_poscar)) - else : - os.chdir(equi_path) - os.symlink(os.path.relpath(from_poscar), 'POSCAR') - os.chdir(cwd) - is_alloy = \ - os.path.exists( - os.path.join( - os.path.join(conf_path, '..'), - 'alloy' - ) - ) - # read potcar - with open(to_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - - # gen incar - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - isif = 3 - if incar.get('ISIF') != isif: - dlog.info("%s:%s setting ISIF to %d" % (__file__, make_vasp.__name__, isif)) - incar['ISIF'] = isif - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - vasp_path = os.path.join(equi_path, 'vasp-relax_incar' ) - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, is_alloy, True, True, npar, kpar, kspacing, kgamma) - vasp_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing) - - os.makedirs(vasp_path, exist_ok = True) - os.chdir(vasp_path) - - # write incar - with open('INCAR', 'w') as fp : - fp.write(fc) - - # gen poscar - if os.path.exists('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(to_poscar), 'POSCAR') - - # gen kpoints - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, 'cvasp.py') - - # gen potcar - with open('POTCAR', 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - os.chdir(cwd) - -def make_lammps (jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type =='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - conf_path = os.path.abspath(conf_dir) - equi_path = re.sub('confs', global_task_name, conf_path) - os.makedirs(equi_path, exist_ok = True) - cwd = os.getcwd() - from_poscar = os.path.join(conf_path, 'POSCAR') - to_poscar = os.path.join(equi_path, 'POSCAR') - if os.path.exists(to_poscar) : - assert(filecmp.cmp(from_poscar, to_poscar)) - else : - os.chdir(equi_path) - os.symlink(os.path.relpath(from_poscar), 'POSCAR') - os.chdir(cwd) - # lmp path - lmp_path = os.path.join(equi_path, task_type) - os.makedirs(lmp_path, exist_ok = True) - print(lmp_path) - # lmp conf - conf_file = os.path.join(lmp_path, 'conf.lmp') - lammps.cvt_lammps_conf(to_poscar, os.path.relpath(conf_file)) - ptypes = vasp.get_poscar_types(to_poscar) - lammps.apply_type_map(conf_file, type_map, ptypes) - # lmp input - if task_type=='deepmd': - fc = lammps.make_lammps_equi(os.path.basename(conf_file), - ntypes, - lammps.inter_deepmd, - model_param) - elif task_type=='meam': - fc = lammps.make_lammps_equi(os.path.basename(conf_file), - ntypes, - lammps.inter_meam, - model_param) - with open(os.path.join(lmp_path, 'lammps.in'), 'w') as fp : - fp.write(fc) - # link models - os.chdir(lmp_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - os.chdir(cwd) - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 00.equi") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK =='meam' : - make_lammps(jdata, args.CONF,args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - diff --git a/dpgen/auto_test/gen_01_eos.py b/dpgen/auto_test/gen_01_eos.py deleted file mode 100755 index ba9fae386..000000000 --- a/dpgen/auto_test/gen_01_eos.py +++ /dev/null @@ -1,358 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps - -from dpgen import dlog -from dpgen.generator.lib.vasp import incar_upper -from pymatgen.core.structure import Structure -from pymatgen.io.vasp import Incar -from dpgen import ROOT_PATH - -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - -global_equi_name = '00.equi' -global_task_name = '01.eos' - -''' -link poscar -link potcar -make incar -''' -def make_vasp(jdata, conf_dir) : - vol_start = jdata['vol_start'] - vol_end = jdata['vol_end'] - vol_step = jdata['vol_step'] - eos_relax_cell_shape = jdata.get('eos_relax_cell_shape', True) - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, vasp_str) - os.makedirs(task_path, exist_ok = True) - # link poscar - cwd = os.getcwd() - from_poscar = os.path.join(equi_contcar) - to_poscar = os.path.join(task_path, 'POSCAR') - if os.path.exists(to_poscar) : - assert(filecmp.cmp(from_poscar, to_poscar)) - else : - os.chdir(task_path) - os.symlink(os.path.relpath(from_poscar), 'POSCAR') - os.chdir(cwd) - vol_to_poscar = vasp.poscar_vol(to_poscar) / vasp.poscar_natoms(to_poscar) - # print(to_poscar, vol_to_poscar) - is_alloy = \ - os.path.exists( - os.path.join( - os.path.join(conf_path, '..'), - 'alloy' - ) - ) - # read potcar - with open(to_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - - # gen incar - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - if eos_relax_cell_shape: - isif = 4 - else: - isif = 2 - if incar.get('ISIF') != isif: - dlog.info("%s:%s setting ISIF to %d" % (__file__, make_vasp.__name__, isif)) - incar['ISIF'] = isif - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, is_alloy, True, False, npar, kpar, kspacing, kgamma) - - os.chdir(task_path) - - with open('INCAR', 'w') as fp : - fp.write(fc) - # gen potcar - with open('POTCAR', 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # loop over volumes - for vol in np.arange(vol_start, vol_end, vol_step) : - vol_path = os.path.join(task_path, 'vol-%.2f' % vol) - os.makedirs(vol_path, exist_ok = True) - os.chdir(vol_path) - for ii in ['INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR'] : - if os.path.exists(ii) : - os.remove(ii) - # link incar, potcar - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR') - # gen poscar - os.symlink(os.path.relpath(to_poscar), 'POSCAR.orig') - scale = (vol / vol_to_poscar) ** (1./3.) - # print(scale) - vasp.poscar_scale('POSCAR.orig', 'POSCAR', scale) - # print(vol_path, vasp.poscar_vol('POSCAR') / vasp.poscar_natoms('POSCAR')) - # gen kpoints - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(vol_path,'cvasp.py')) - os.chdir(cwd) - - -def make_lammps (jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type =='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - ntypes = len(type_map) - - vol_start = jdata['vol_start'] - vol_end = jdata['vol_end'] - vol_step = jdata['vol_step'] - - # # get equi props - # equi_path = re.sub('confs', global_equi_name, conf_path) - # equi_path = os.path.join(equi_path, 'lmp') - # equi_log = os.path.join(equi_path, 'log.lammps') - # if not os.path.isfile(equi_log) : - # raise RuntimeError("the system should be equilibriated first") - # natoms, epa, vpa = lammps.get_nev(equi_log) - # task path - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.abspath(task_path) - os.makedirs(task_path, exist_ok = True) - cwd = os.getcwd() - conf_path = os.path.abspath(conf_dir) - from_poscar = os.path.join(conf_path, 'POSCAR') - to_poscar = os.path.join(task_path, 'POSCAR') - if os.path.exists(to_poscar) : - assert(filecmp.cmp(from_poscar, to_poscar)) - else : - os.chdir(task_path) - os.symlink(os.path.relpath(from_poscar), 'POSCAR') - os.chdir(cwd) - volume = vasp.poscar_vol(to_poscar) - natoms = vasp.poscar_natoms(to_poscar) - vpa = volume / natoms - # structrure - ss = Structure.from_file(to_poscar) - - # lmp path - lmp_path = os.path.join(task_path, task_type) - os.makedirs(lmp_path, exist_ok = True) - #Null lammps.in - f_lammps_in = os.path.join(lmp_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - None - # # lmp conf - # conf_file = os.path.join(lmp_path, 'conf.lmp') - # lammps.cvt_lammps_conf(to_poscar, conf_file) - # ptypes = vasp.get_poscar_types(to_poscar) - # lammps.apply_type_map(conf_file, deepmd_type_map, ptypes) - - os.chdir(lmp_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models =[os.path.join(lmp_path,ii) for ii in model_name] - - for vol in np.arange(vol_start, vol_end, vol_step) : - vol_path = os.path.join(lmp_path, 'vol-%.2f' % vol) - print('# generate %s' % (vol_path)) - os.makedirs(vol_path, exist_ok = True) - os.chdir(vol_path) - #print(vol_path) - for ii in ['conf.lmp', 'conf.lmp'] + model_name : - if os.path.exists(ii) : - os.remove(ii) - # # link conf - # os.symlink(os.path.relpath(conf_file), 'conf.lmp') - # make conf - scale_ss = ss.copy() - scale_ss.scale_lattice(vol * natoms) - scale_ss.to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - # make lammps input - scale = (vol / vpa) ** (1./3.) - if task_type=='deepmd': - fc = lammps.make_lammps_press_relax('conf.lmp', ntypes, scale,lammps.inter_deepmd, model_param) - elif task_type =='meam': - fc = lammps.make_lammps_press_relax('conf.lmp', ntypes, scale,lammps.inter_meam, model_param) - with open(os.path.join(vol_path, 'lammps.in'), 'w') as fp : - fp.write(fc) - os.chdir(cwd) - -def make_lammps_fixv (jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type =='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - ntypes = len(type_map) - - - vol_start = jdata['vol_start'] - vol_end = jdata['vol_end'] - vol_step = jdata['vol_step'] - - # get equi props - equi_path = re.sub('confs', global_equi_name, conf_dir) - task_path = re.sub('confs', global_task_name, conf_dir) - equi_path = os.path.join(equi_path, task_type) - task_path = os.path.join(task_path, task_type) - equi_path = os.path.abspath(equi_path) - task_path = os.path.abspath(task_path) - equi_dump = os.path.join(equi_path, 'dump.relax') - os.makedirs(task_path, exist_ok = True) - task_poscar = os.path.join(task_path, 'POSCAR') - lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map) - - cwd = os.getcwd() - volume = vasp.poscar_vol(task_poscar) - natoms = vasp.poscar_natoms(task_poscar) - vpa = volume / natoms - # structrure - ss = Structure.from_file(task_poscar) - # make lammps.in - if task_type=='deepmd': - fc = lammps.make_lammps_equi('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param, - change_box = False) - elif task_type=='meam': - fc = lammps.make_lammps_equi('conf.lmp', - ntypes, - lammps.inter_meam, - model_param, - change_box = False) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(task_path,ii) for ii in model_name] - - # make vols - for vol in np.arange(vol_start, vol_end, vol_step) : - vol_path = os.path.join(task_path, 'vol-%.2f' % vol) - print('# generate %s' % (vol_path)) - os.makedirs(vol_path, exist_ok = True) - os.chdir(vol_path) - for ii in ['conf.lmp', 'conf.lmp', 'lammps.in'] + model_name : - if os.path.exists(ii) : - os.remove(ii) - # make conf - scale_ss = ss.copy() - scale_ss.scale_lattice(vol * natoms) - scale_ss.to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models,model_name) : - os.symlink(os.path.relpath(ii), jj) - # make lammps input - os.chdir(cwd) - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 01.eos") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('-f', '--fix-shape', action = 'store_true', - help='fix shape of box') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - # print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK =='meam': - if args.fix_shape : - make_lammps_fixv(jdata, args.CONF,args.TASK) - else : - make_lammps(jdata, args.CONF,args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - diff --git a/dpgen/auto_test/gen_02_elastic.py b/dpgen/auto_test/gen_02_elastic.py deleted file mode 100755 index 13b20a715..000000000 --- a/dpgen/auto_test/gen_02_elastic.py +++ /dev/null @@ -1,258 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps - -from dpgen import dlog -from dpgen.generator.lib.vasp import incar_upper -from pymatgen.core.structure import Structure -from pymatgen.analysis.elasticity.strain import Deformation, DeformedStructureSet, Strain -from pymatgen.io.vasp import Incar -from dpgen import ROOT_PATH - -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - -global_equi_name = '00.equi' -global_task_name = '02.elastic' - -def make_vasp(jdata, conf_dir) : - default_norm_def = 2e-3 - default_shear_def = 5e-3 - norm_def = jdata.get('norm_deform', default_norm_def) - shear_def = jdata.get('shear_deform', default_shear_def) - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, vasp_str) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - # stress - equi_outcar = os.path.join(equi_path, 'OUTCAR') - stress = vasp.get_stress(equi_outcar) - np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress) - # gen strcture - ss = Structure.from_file(task_poscar) - # gen defomations - norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def] - shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def] - dfm_ss = DeformedStructureSet(ss, - symmetry = False, - norm_strains = norm_strains, - shear_strains = shear_strains) - n_dfm = len(dfm_ss) - # gen incar - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - if incar.get('ISIF') != 2: - dlog.info("%s:%s setting ISIF to 2" % (__file__, make_vasp.__name__)) - incar['ISIF'] = 2 - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, True, False, False, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma) - - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen potcar - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - with open(os.path.join(task_path,'POTCAR'), 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # gen kpoints - fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma) - with open(os.path.join(task_path,'KPOINTS'), 'w') as fp: - fp.write(fc) - # gen tasks - cwd = os.getcwd() - for ii in range(n_dfm) : - # make dir - dfm_path = os.path.join(task_path, 'dfm-%03d' % ii) - os.makedirs(dfm_path, exist_ok=True) - os.chdir(dfm_path) - for jj in ['POSCAR', 'POTCAR', 'INCAR', 'KPOINTS'] : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR') - # record strain - strain = Strain.from_deformation(dfm_ss.deformations[ii]) - np.savetxt('strain.out', strain) - # link incar, potcar, kpoints - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'KPOINTS')), 'KPOINTS') - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(dfm_path,'cvasp.py')) - os.chdir(cwd) - - -def make_lammps(jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type =='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - - norm_def = jdata['norm_deform'] - shear_def = jdata['shear_deform'] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, task_type) - equi_dump = os.path.join(equi_path, 'dump.relax') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - task_poscar = os.path.join(task_path, 'POSCAR') - lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map) - # get equi stress - equi_log = os.path.join(equi_path, 'log.lammps') - stress = lammps.get_stress(equi_log) - np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress) - # gen strcture - # ss = Structure.from_file(conf_poscar) - # print(ss) - # ss = ss.from_file(task_poscar) - # print(ss) - ss = Structure.from_file(task_poscar) - # gen defomations - norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def] - shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def] - print('gen with norm '+str(norm_strains)) - print('gen with shear '+str(shear_strains)) - dfm_ss = DeformedStructureSet(ss, - symmetry = False, - norm_strains = norm_strains, - shear_strains = shear_strains) - n_dfm = len(dfm_ss) - # gen tasks - cwd = os.getcwd() - # make lammps.in - if task_type=='deepmd': - fc = lammps.make_lammps_elastic('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param) - elif task_type=='meam': - fc = lammps.make_lammps_elastic('conf.lmp', - ntypes, - lammps.inter_meam, - model_param) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - cwd = os.getcwd() - - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(task_path,ii) for ii in model_name] - - for ii in range(n_dfm) : - # make dir - dfm_path = os.path.join(task_path, 'dfm-%03d' % ii) - os.makedirs(dfm_path, exist_ok=True) - os.chdir(dfm_path) - for jj in ['conf.lmp', 'lammps.in'] + model_name : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # record strain - strain = Strain.from_deformation(dfm_ss.deformations[ii]) - np.savetxt('strain.out', strain) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - cwd = os.getcwd() - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 02.elastic") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK=='meam': - make_lammps(jdata, args.CONF,args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - - diff --git a/dpgen/auto_test/gen_03_vacancy.py b/dpgen/auto_test/gen_03_vacancy.py deleted file mode 100755 index f50591b45..000000000 --- a/dpgen/auto_test/gen_03_vacancy.py +++ /dev/null @@ -1,245 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.core.structure import Structure -from pymatgen.analysis.defects.core import Vacancy -from pymatgen.analysis.defects.generators import VacancyGenerator - -from dpgen import ROOT_PATH -from pymatgen.io.vasp import Incar -from dpgen.generator.lib.vasp import incar_upper -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - - -global_equi_name = '00.equi' -global_task_name = '03.vacancy' - -def make_vasp(jdata, conf_dir, supercell = [1,1,1]) : - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, vasp_str) - - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - # gen strcture - ss = Structure.from_file(task_poscar) - # gen defects - vds = VacancyGenerator(ss) - dss = [] - for jj in vds : - dss.append(jj.generate_defect_structure(supercell)) - # gen incar - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, True, True, True, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma) - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen potcar - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - with open(os.path.join(task_path,'POTCAR'), 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # gen tasks - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - cwd = os.getcwd() - for ii in range(len(dss)) : - struct_path = os.path.join(task_path, 'struct-%s-%03d' % (copy_str,ii)) - print('# generate %s' % (struct_path)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['POSCAR', 'POTCAR', 'INCAR'] : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dss[ii].to('POSCAR', 'POSCAR') - # link incar, potcar, kpoints - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR') - # save supercell - np.savetxt('supercell.out', supercell, fmt='%d') - - # write kp - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(struct_path,'cvasp.py')) - os.chdir(cwd) - -def make_lammps(jdata, conf_dir, task_type, supercell) : - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type =='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % kspacing - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - # equi_path = re.sub('confs', global_equi_name, conf_path) - # equi_path = os.path.join(equi_path, 'lmp') - # equi_dump = os.path.join(equi_path, 'dump.relax') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - # gen task poscar - task_poscar = os.path.join(task_path, 'POSCAR') - # lammps.poscar_from_last_dump(equi_dump, task_poscar, deepmd_type_map) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - # gen structure from equi poscar - ss = Structure.from_file(task_poscar) - # gen defects - vds = VacancyGenerator(ss) - dss = [] - for jj in vds : - dss.append(jj.generate_defect_structure(supercell)) - # gen tasks - cwd = os.getcwd() - # make lammps.in, relax at 0 bar (scale = 1) - if task_type=='deepmd': - fc = lammps.make_lammps_press_relax('conf.lmp', - ntypes, - 1, - lammps.inter_deepmd, - model_param) - elif task_type =='meam': - fc = lammps.make_lammps_press_relax('conf.lmp', - ntypes, - 1, - lammps.inter_meam, - model_param) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - # gen tasks - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - cwd = os.getcwd() - - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(task_path,ii) for ii in model_name] - - for ii in range(len(dss)) : - struct_path = os.path.join(task_path, 'struct-%s-%03d' % (copy_str,ii)) - print('# generate %s' % (struct_path)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['conf.lmp', 'lammps.in'] + model_name : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dss[ii].to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - # save supercell - np.savetxt('supercell.out', supercell, fmt='%d') - os.chdir(cwd) - -def _main() : - parser = argparse.ArgumentParser( - description="gen 03.vacancy") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('COPY', type=int, nargs = 3, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF, args.COPY) - elif args.TASK == 'deepmd' or args.TASK=='meam' : - make_lammps(jdata, args.CONF, args.TASK, args.COPY) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/gen_04_interstitial.py b/dpgen/auto_test/gen_04_interstitial.py deleted file mode 100755 index f1c10c4c3..000000000 --- a/dpgen/auto_test/gen_04_interstitial.py +++ /dev/null @@ -1,391 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, warnings, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.core.structure import Structure -from pymatgen.analysis.defects.core import Interstitial -from pymatgen.analysis.defects.generators import InterstitialGenerator - -from dpgen import ROOT_PATH -from pymatgen.io.vasp import Incar -from dpgen.generator.lib.vasp import incar_upper -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - - -global_equi_name = '00.equi' -global_task_name = '04.interstitial' - -def make_vasp(json, conf_dir, supercell, insert_ele) : - for ii in insert_ele : - _make_vasp(json, conf_dir, supercell, ii) - -def _make_vasp(jdata, conf_dir, supercell, insert_ele) : - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % (kspacing) - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, vasp_str) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - # gen strcture - print("task poscar: ", task_poscar) - ss = Structure.from_file(task_poscar) - # gen defects - vds = InterstitialGenerator(ss, insert_ele) - dss = [] - for jj in vds : - dss.append(jj.generate_defect_structure(supercell)) - # gen incar - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, True, True, True, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma) - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen tasks - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - cwd = os.getcwd() - for ii in range(len(dss)) : - struct_path = os.path.join(task_path, 'struct-%s-%s-%03d' % (insert_ele,copy_str,ii)) - print('# generate %s' % (struct_path)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['POSCAR', 'POTCAR', 'INCAR'] : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dss[ii].to('POSCAR', 'POSCAR') - # gen potcar - with open('POSCAR','r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - - os.chdir(cwd) - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - os.chdir(struct_path) - - with open('POTCAR', 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - - # link incar - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - # save supercell - np.savetxt('supercell.out', supercell, fmt='%d') - - # write kp - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(struct_path,'cvasp.py')) - os.chdir(cwd) - - -def make_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_type) : - for ii in insert_ele : - _make_reprod_traj(jdata, conf_dir, supercell, ii, task_type) - -def _make_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_type) : - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type=='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - - conf_path = os.path.abspath(conf_dir) - task_path = re.sub('confs', global_task_name, conf_path) - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - lmps_str= task_type + '-reprod-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str = 'vasp-k%.2f' % (kspacing) - lmps_str = task_type + '-reprod-k%.2f' % (kspacing) - - vasp_path = os.path.join(task_path, vasp_str) - lmps_path = os.path.join(task_path, lmps_str) - - os.makedirs(lmps_path, exist_ok = True) - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - struct_widecard = os.path.join(vasp_path, 'struct-%s-%s-*' % (insert_ele,copy_str)) - vasp_struct = glob.glob(struct_widecard) - assert len(vasp_struct)>0 ,"Please compute the interstitial defect using vasp first" - vasp_struct.sort() - cwd=os.getcwd() - - # make lammps.in - if task_type =='deepmd': - fc = lammps.make_lammps_eval('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param) - elif task_type =='meam': - fc = lammps.make_lammps_eval('conf.lmp', - ntypes, - lammps.inter_meam, - model_param) - f_lammps_in = os.path.join(lmps_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - - for vs in vasp_struct : - # get vasp energy - outcar = os.path.join(vs, 'OUTCAR') - energies = vasp.get_energies(outcar) - # get xdat - xdatcar = os.path.join(vs, 'XDATCAR') - struct_basename = os.path.basename(vs) - ls = os.path.join(lmps_path, struct_basename) - print(ls) - os.makedirs(ls, exist_ok = True) - os.chdir(ls) - if os.path.exists('XDATCAR') : - os.remove('XDATCAR') - os.symlink(os.path.relpath(xdatcar), 'XDATCAR') - xdat_lines = open('XDATCAR', 'r').read().split('\n') - natoms = vasp.poscar_natoms('XDATCAR') - xdat_secsize = natoms + 8 - xdat_nframes = len(xdat_lines) // xdat_secsize - if xdat_nframes > len(energies) : - warnings.warn('nframes %d in xdat is larger than energy %d, use the last %d frames' % (xdat_nframes, len(energies), len(energies))) - xdat_nlines = len(energies) * xdat_secsize - xdat_lines = xdat_lines[xdat_nlines:] - xdat_nframes = len(xdat_lines) // xdat_secsize - print(xdat_nframes, len(energies)) - #link lammps.in and model - for jj in ['lammps.in'] + model_name : - if os.path.islink(jj): - os.unlink(jj) - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(ls,ii) for ii in model_name] - - # loop over frames - for ii in range(xdat_nframes) : - frame_path = 'frame.%06d' % ii - os.makedirs(frame_path, exist_ok=True) - os.chdir(frame_path) - # clear dir - for jj in ['conf.lmp'] : - if os.path.isfile(jj): - os.remove(jj) - for jj in ['lammps.in'] + model_name : - if os.path.islink(jj): - os.unlink(jj) - # link lammps in - os.symlink(os.path.relpath('../lammps.in'), 'lammps.in') - # make conf - with open('POSCAR', 'w') as fp : - fp.write('\n'.join(xdat_lines[ii*xdat_secsize:(ii+1)*xdat_secsize])) - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # link models - for (kk,ll) in zip(share_models, model_name) : - os.symlink(os.path.relpath(kk), ll) - os.chdir(ls) - os.chdir(cwd) - - - -def make_lammps(jdata, conf_dir, supercell, insert_ele, task_type) : - for ii in insert_ele: - _make_lammps(jdata, conf_dir, supercell, ii, task_type) - -def _make_lammps(jdata, conf_dir, supercell, insert_ele, task_type) : - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type=='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % (kspacing) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - #equi_path = os.path.join(equi_path, task_type) - #equi_dump = os.path.join(equi_path, 'dump.relax') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - task_poscar = os.path.join(task_path, 'POSCAR') - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - #lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map) - os.chdir(cwd) - # gen structure from equi poscar - print("task poscar: ", task_poscar) - ss = Structure.from_file(task_poscar) - # gen defects - vds = InterstitialGenerator(ss, insert_ele) - dss = [] - for jj in vds : - dss.append(jj.generate_defect_structure(supercell)) - # gen tasks - cwd = os.getcwd() - # make lammps.in, relax at 0 bar (scale = 1) - if task_type=='deepmd': - fc = lammps.make_lammps_press_relax('conf.lmp', - ntypes, - 1, - lammps.inter_deepmd, - model_param) - elif task_type =='meam': - fc = lammps.make_lammps_press_relax('conf.lmp', - ntypes, - 1, - lammps.inter_meam, - model_param) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - # gen tasks - copy_str = "%sx%sx%s" % (supercell[0], supercell[1], supercell[2]) - cwd = os.getcwd() - - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(task_path,ii) for ii in model_name] - - for ii in range(len(dss)) : - struct_path = os.path.join(task_path, 'struct-%s-%s-%03d' % (insert_ele,copy_str,ii)) - print('# generate %s' % (struct_path)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['conf.lmp', 'lammps.in'] + model_name : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dss[ii].to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - # save supercell - np.savetxt('supercell.out', supercell, fmt='%d') - os.chdir(cwd) - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 04.interstitial") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('COPY', type=int, nargs = 3, - help='define the supercell') - parser.add_argument('ELEMENT', type=str, nargs = '+', - help='the inserted element') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF, args.COPY, args.ELEMENT) - elif args.TASK == 'deepmd' or args.TASK=='meam': - make_lammps(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - elif args.TASK == 'deepmd-reprod' or args.TASK == 'meam-reprod': - args.TASK=args.TASK.replace('-reprod','') - make_reprod_traj(jdata, args.CONF, args.COPY, args.ELEMENT, args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/gen_05_surf.py b/dpgen/auto_test/gen_05_surf.py deleted file mode 100755 index ee6cd662d..000000000 --- a/dpgen/auto_test/gen_05_surf.py +++ /dev/null @@ -1,299 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.core.surface import generate_all_slabs, Structure - -from dpgen import ROOT_PATH -from pymatgen.io.vasp import Incar -from dpgen.generator.lib.vasp import incar_upper -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - - -global_equi_name = '00.equi' -global_task_name = '05.surf' - -def make_vasp(jdata, conf_dir, max_miller = 2, relax_box = False, static = False) : - - min_slab_size = jdata['min_slab_size'] - min_vacuum_size = jdata['min_vacuum_size'] - pert_xz = jdata['pert_xz'] - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % (kspacing) - - # get conf poscar - # conf_path = os.path.abspath(conf_dir) - # conf_poscar = os.path.join(conf_path, 'POSCAR') - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, vasp_str) - equi_path = os.path.abspath(equi_path) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.abspath(task_path) - if static: - if 'scf_incar' in jdata.keys(): - vasp_static_str='vasp-static-scf_incar' - else: - vasp_static_str='vasp-static-k%.2f' % (kspacing) - task_path = os.path.join(task_path, vasp_static_str) - else : - task_path = os.path.join(task_path, vasp_str) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - ptypes = vasp.get_poscar_types(task_poscar) - # gen strcture - ss = Structure.from_file(task_poscar) - # gen slabs - all_slabs = generate_all_slabs(ss, max_miller, min_slab_size, min_vacuum_size) - # gen incar - if static : - if 'scf_incar' in jdata.keys(): - scf_incar_path = jdata['scf_incar'] - assert(os.path.exists(scf_incar_path)) - scf_incar_path = os.path.abspath(scf_incar_path) - incar = incar_upper(Incar.from_file(scf_incar_path)) - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_static_incar(ecut, ediff, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma) - else : - if 'relax_incar' in jdata.keys(): - relax_incar_path = jdata['relax_incar'] - assert(os.path.exists(relax_incar_path)) - relax_incar_path = os.path.abspath(relax_incar_path) - incar = incar_upper(Incar.from_file(relax_incar_path)) - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_relax_incar(ecut, ediff, True, relax_box, False, npar=npar,kpar=kpar, kspacing = kspacing, kgamma = kgamma) - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen potcar - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert os.path.exists(os.path.abspath(potcar_map[ii])),"No POTCAR in the potcar_map of %s"%(ii) - potcar_list.append(os.path.abspath(potcar_map[ii])) - with open(os.path.join(task_path,'POTCAR'), 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # gen tasks - cwd = os.getcwd() - for ii in range(len(all_slabs)) : - slab = all_slabs[ii] - miller_str = "m%d.%d.%dm" % (slab.miller_index[0], slab.miller_index[1], slab.miller_index[2]) - # make dir - struct_path = os.path.join(task_path, 'struct-%03d-%s' % (ii, miller_str)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['POSCAR', 'POTCAR', 'INCAR'] : - if os.path.isfile(jj): - os.remove(jj) - print("# %03d generate " % ii, struct_path, " \t %d atoms" % len(slab.sites)) - # make conf - slab.to('POSCAR', 'POSCAR.tmp') - vasp.regulate_poscar('POSCAR.tmp', 'POSCAR') - vasp.sort_poscar('POSCAR', 'POSCAR', ptypes) - vasp.perturb_xz('POSCAR', 'POSCAR', pert_xz) - # record miller - np.savetxt('miller.out', slab.miller_index, fmt='%d') - # link incar, potcar, kpoints - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR') - - # write kp - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(struct_path,'cvasp.py')) - cwd = os.getcwd() - -def make_lammps(jdata, conf_dir, max_miller = 2, static = False, relax_box = False, task_type = 'wrong-task') : - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name and task_type=='deepmd': - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - assert len(model_name)>0,"No deepmd model in the model_dir" - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - ntypes = len(type_map) - - min_slab_size = jdata['min_slab_size'] - min_vacuum_size = jdata['min_vacuum_size'] - - # get equi poscar - # conf_path = os.path.abspath(conf_dir) - # conf_poscar = os.path.join(conf_path, 'POSCAR') - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - kspacing = jdata['vasp_params']['kspacing'] - vasp_str='vasp-k%.2f' % (kspacing) - - equi_path = re.sub('confs', global_equi_name, conf_dir) - equi_path = os.path.join(equi_path, vasp_str) - equi_path = os.path.abspath(equi_path) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - assert os.path.exists(equi_contcar),"Please compute the equilibrium state using vasp first" - task_path = re.sub('confs', global_task_name, conf_dir) - task_path = os.path.abspath(task_path) - if static: - task_path = os.path.join(task_path, task_type+'-static') - else: - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - # gen strcture - ss = Structure.from_file(task_poscar) - # gen slabs - all_slabs = generate_all_slabs(ss, max_miller, min_slab_size, min_vacuum_size) - # make lammps.in - if task_type =='deepmd': - if static : - fc = lammps.make_lammps_eval('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param) - else : - fc = lammps.make_lammps_equi('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param, - change_box = relax_box) - elif task_type =='meam': - if static : - fc = lammps.make_lammps_eval('conf.lmp', - ntypes, - lammps.inter_meam, - model_param) - else : - fc = lammps.make_lammps_equi('conf.lmp', - ntypes, - lammps.inter_meam, - model_param, - change_box = relax_box) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - cwd = os.getcwd() - - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = [os.path.join(task_path,ii) for ii in model_name] - - for ii in range(len(all_slabs)) : - slab = all_slabs[ii] - miller_str = "m%d.%d.%dm" % (slab.miller_index[0], slab.miller_index[1], slab.miller_index[2]) - # make dir - struct_path = os.path.join(task_path, 'struct-%03d-%s' % (ii, miller_str)) - os.makedirs(struct_path, exist_ok=True) - os.chdir(struct_path) - for jj in ['conf.lmp', 'lammps.in'] + model_name : - if os.path.isfile(jj): - os.remove(jj) - print("# %03d generate " % ii, struct_path, " \t %d atoms" % len(slab.sites)) - # make conf - slab.to('POSCAR', 'POSCAR') - vasp.regulate_poscar('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # record miller - np.savetxt('miller.out', slab.miller_index, fmt='%d') - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - cwd = os.getcwd() - -def _main() : - parser = argparse.ArgumentParser( - description="gen 05.surf") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - parser.add_argument('MAX_MILLER', type=int, - help='the maximum miller index') - parser.add_argument('-r', '--relax-box', action = 'store_true', - help='set if the box is relaxed, otherwise only relax atom positions') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('# generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF, args.MAX_MILLER, static = False, relax_box = args.relax_box) - elif args.TASK == 'vasp-static': - make_vasp(jdata, args.CONF, args.MAX_MILLER, static = True, relax_box = args.relax_box) - elif args.TASK == 'deepmd' or args.TASK =='meam': - make_lammps(jdata, args.CONF, args.MAX_MILLER, static = False, relax_box = args.relax_box, task_type = args.TASK) - elif args.TASK == 'deepmd-static' or args.TASK == 'meam-static': - args.TASK=args.TASK.replace('-static','') - make_lammps(jdata, args.CONF, args.MAX_MILLER, static = True, relax_box = args.relax_box, task_type = args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() diff --git a/dpgen/auto_test/gen_06_phonon.py b/dpgen/auto_test/gen_06_phonon.py deleted file mode 100644 index 09e9ef9b3..000000000 --- a/dpgen/auto_test/gen_06_phonon.py +++ /dev/null @@ -1,287 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob, shutil -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from phonopy.structure.atoms import PhonopyAtoms -import yaml - -from dpgen import ROOT_PATH -from pymatgen.io.vasp import Incar -from dpgen.generator.lib.vasp import incar_upper -cvasp_file=os.path.join(ROOT_PATH,'generator/lib/cvasp.py') - - -global_equi_name = '00.equi' -global_task_name = '06.phonon' - -''' -link poscar -link potcar -make incar -''' - -def get_structure_from_poscar(file_name, number_of_dimensions=3): - """ - Read crystal structure from a VASP POSCAR type file - :param file_name: POSCAR filename - :param number_of_dimensions: number of dimensions of the crystal structure - :return: Atoms (phonopy) type object containing the crystal structure - """ - # Check file exists - if not os.path.isfile(file_name): - print('Structure file does not exist!') - exit() - - # Read from VASP POSCAR file - poscar_file = open(file_name, 'r') - data_lines = poscar_file.read().split('\n') - poscar_file.close() - - multiply = float(data_lines[1]) - direct_cell = np.array([data_lines[i].split() - for i in range(2, 2+number_of_dimensions)], dtype=float) - direct_cell *= multiply - scaled_positions = None - positions = None - - try: - number_of_types = np.array(data_lines[3+number_of_dimensions].split(),dtype=int) - - coordinates_type = data_lines[4+number_of_dimensions][0] - if coordinates_type == 'D' or coordinates_type == 'd' : - - scaled_positions = np.array([data_lines[8+k].split()[0:3] - for k in range(np.sum(number_of_types))],dtype=float) - else: - positions = np.array([data_lines[8+k].split()[0:3] - for k in range(np.sum(number_of_types))],dtype=float) - - atomic_types = [] - for i,j in enumerate(data_lines[5].split()): - atomic_types.append([j]*number_of_types[i]) - atomic_types = [item for sublist in atomic_types for item in sublist] - - # Old style POSCAR format - except ValueError: - number_of_types = np.array(data_lines[5].split(), dtype=int) - coordinates_type = data_lines[6][0] - if coordinates_type == 'D' or coordinates_type == 'd': - scaled_positions = np.array([data_lines[7+k].split()[0:3] - for k in range(np.sum(number_of_types))], dtype=float) - else: - positions = np.array([data_lines[7+k].split()[0:3] - for k in range(np.sum(number_of_types))], dtype=float) - - atomic_types = [] - for i,j in enumerate(data_lines[0].split()): - atomic_types.append([j]*number_of_types[i]) - atomic_types = [item for sublist in atomic_types for item in sublist] - - return PhonopyAtoms(symbols=atomic_types, - scaled_positions=scaled_positions, - cell=direct_cell) - -def make_vasp(jdata, conf_dir) : - - supercell_matrix=jdata['supercell_matrix'] - band_path=jdata['band'] - - if 'relax_incar' in jdata.keys(): - vasp_str='vasp-relax_incar' - else: - vasp_str='vasp-k%.2f' % kspacing - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, vasp_str) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - task_path = re.sub('confs', global_task_name, conf_path) - if 'user_incar' in jdata.keys(): - vasp_user_str='vasp-user_incar' - else: - vasp_user_str='vasp-k%.2f' % kspacing - task_path = os.path.join(task_path, vasp_user_str) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - print(task_path) - if os.path.isfile('POSCAR-unitcell') : - os.remove('POSCAR-unitcell') - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR-unitcell') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR-unitcell') - # gen incar - if 'user_incar' in jdata.keys(): - user_incar_path = jdata['user_incar'] - assert(os.path.exists(user_incar_path)) - user_incar_path = os.path.abspath(user_incar_path) - incar = incar_upper(Incar.from_file(user_incar_path)) - fc = incar.get_string() - kspacing = incar['KSPACING'] - kgamma = incar['KGAMMA'] - else : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - fc = vasp.make_vasp_phonon_incar(ecut, ediff, npar, kpar, kspacing = None, kgamma = None) - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen potcar - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert(os.path.exists(potcar_map[ii])) - potcar_list.append(potcar_map[ii]) - with open(os.path.join(task_path,'POTCAR'), 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # gen kpoints -# fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma) -# with open(os.path.join(task_path,'KPOINTS'), 'w') as fp: -# fp.write(fc) - - # write kp - fc = vasp.make_kspacing_kpoints('POSCAR', kspacing, kgamma) - with open('KPOINTS', 'w') as fp: fp.write(fc) - #copy cvasp - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - shutil.copyfile(cvasp_file, os.path.join(task_path,'cvasp.py')) - - # gen band.conf - os.chdir(task_path) - with open('band.conf','w') as fp: - fp.write('ATOM_NAME = ') - for ii in ele_list: - fp.write(ii) - fp.write(' ') - fp.write('\n') - fp.write('DIM = %d %d %d\n'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - fp.write('BAND = %s\n'%band_path) - fp.write('FORCE_CONSTANTS=READ') - # gen POSCAR - os.system('phonopy -d --dim="%d %d %d" -c POSCAR-unitcell'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - os.symlink('SPOSCAR', 'POSCAR') - -def make_lammps(jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - - supercell_matrix=jdata['supercell_matrix'] - band_path=jdata['band'] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, task_type) - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - - task_poscar = os.path.join(task_path, 'POSCAR') - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(conf_poscar), 'POSCAR') - os.chdir(cwd) - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - - print(task_path) - # make conf.lmp - conf_file = os.path.join(task_path, 'conf.lmp') - lammps.cvt_lammps_conf(task_poscar, os.path.relpath(conf_file)) - ptypes = vasp.get_poscar_types(task_poscar) - lammps.apply_type_map(conf_file, type_map, ptypes) - # make lammps.in - ntypes=len(ele_list) - unitcell=get_structure_from_poscar(task_poscar) - if task_type=='deepmd': - fc = lammps.make_lammps_phonon('conf.lmp', - unitcell.masses, - lammps.inter_deepmd, - model_param) - if task_type=='meam': - fc = lammps.make_lammps_phonon('conf.lmp', - unitcell.masses, - lammps.inter_meam, - model_param) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - cwd = os.getcwd() - # link models - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - # gen band.conf - os.chdir(task_path) - with open('band.conf','w') as fp: - fp.write('ATOM_NAME = ') - for ii in ele_list: - fp.write(ii) - fp.write(' ') - fp.write('\n') - fp.write('DIM = %d %d %d\n'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - fp.write('BAND = %s\n'%band_path) - fp.write('FORCE_CONSTANTS=READ\n') - os.system('phonolammps lammps.in --dim %d %d %d -c POSCAR'%(supercell_matrix[0],supercell_matrix[1],supercell_matrix[2])) - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 06.phonon") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - -# print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK =='meam' : - make_lammps(jdata, args.CONF,args.TASK) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - diff --git a/dpgen/auto_test/gen_07_SScurve.py b/dpgen/auto_test/gen_07_SScurve.py deleted file mode 100644 index 557aaccf3..000000000 --- a/dpgen/auto_test/gen_07_SScurve.py +++ /dev/null @@ -1,309 +0,0 @@ -#!/usr/bin/env python3 - -import os, re, argparse, filecmp, json, glob -import subprocess as sp -import numpy as np -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -from pymatgen.core.structure import Structure -from pymatgen.analysis.elasticity.strain import Deformation, DeformedStructureSet, Strain - -global_equi_name = '00.equi' -global_task_name = '07.SScurve' - -def make_vasp(jdata, conf_dir, norm_def = 2e-3, shear_def = 5e-3) : - fp_params = jdata['vasp_params'] - ecut = fp_params['ecut'] - ediff = fp_params['ediff'] - npar = fp_params['npar'] - kpar = fp_params['kpar'] - kspacing = fp_params['kspacing'] - kgamma = fp_params['kgamma'] - strain_start=jdata['strain_start'] - strain_end=jdata['strain_end'] - strain_step=jdata['strain_step'] - strain_direct=jdata['strain_direct'] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing) - equi_contcar = os.path.join(equi_path, 'CONTCAR') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing) - os.makedirs(task_path, exist_ok=True) - cwd = os.getcwd() - os.chdir(task_path) - if os.path.isfile('POSCAR') : - os.remove('POSCAR') - os.symlink(os.path.relpath(equi_contcar), 'POSCAR') - os.chdir(cwd) - task_poscar = os.path.join(task_path, 'POSCAR') - # stress - equi_outcar = os.path.join(equi_path, 'OUTCAR') - stress = vasp.get_stress(equi_outcar) - np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress) - # gen strcture - ss = Structure.from_file(task_poscar) - # gen defomations - norm_strains=np.arange(strain_start,strain_end,strain_step) - print('gen with norm '+str(norm_strains)) - deformations=[] - for ii in norm_strains: - strain = Strain.from_index_amount(strain_direct, ii) - deformations.append(strain.get_deformation_matrix()) - deformed_structures = [defo.apply_to_structure(ss) - for defo in deformations] - n_dfm = len(deformed_structures) - # gen incar - fc = vasp.make_vasp_relax_incar(ecut, ediff, True, False, False, npar=npar, kpar=kpar, kspacing = None, kgamma = None) - with open(os.path.join(task_path, 'INCAR'), 'w') as fp : - fp.write(fc) - # gen potcar - with open(task_poscar,'r') as fp : - lines = fp.read().split('\n') - ele_list = lines[5].split() - potcar_map = jdata['potcar_map'] - potcar_list = [] - for ii in ele_list : - assert(os.path.exists(potcar_map[ii])) - potcar_list.append(potcar_map[ii]) - with open(os.path.join(task_path,'POTCAR'), 'w') as outfile: - for fname in potcar_list: - with open(fname) as infile: - outfile.write(infile.read()) - # gen kpoints - fc = vasp.make_kspacing_kpoints(task_poscar, kspacing, kgamma) - with open(os.path.join(task_path,'KPOINTS'), 'w') as fp: - fp.write(fc) - # gen tasks - cwd = os.getcwd() - for ii in range(n_dfm) : - # make dir - dfm_path = os.path.join(task_path, 'dfm-%03d' % ii) - os.makedirs(dfm_path, exist_ok=True) - os.chdir(dfm_path) - for jj in ['POSCAR', 'POTCAR', 'INCAR', 'KPOINTS'] : - if os.path.isfile(jj): - os.remove(jj) - # make conf - deformed_structures[ii].to('POSCAR', 'POSCAR') - # record strain - strain = Strain.from_deformation(deformations[ii]) - np.savetxt('strain.out', strain) - # link incar, potcar, kpoints - os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')), 'POTCAR') - os.symlink(os.path.relpath(os.path.join(task_path, 'KPOINTS')), 'KPOINTS') - cwd = os.getcwd() - -def make_lammps(jdata, conf_dir,task_type) : - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - type_map = fp_params['type_map'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - deepmd_version = fp_params.get("deepmd_version", "0.12") - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - - model_param = {'model_name' : model_name, - 'param_type': fp_params['model_param_type'], - 'deepmd_version' : deepmd_version} - ntypes = len(type_map) - strain_start=jdata['strain_start'] - strain_end=jdata['strain_end'] - strain_step=jdata['strain_step'] - strain_direct=jdata['strain_direct'] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, task_type) - equi_dump = os.path.join(equi_path, 'dump.relax') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, task_type) - os.makedirs(task_path, exist_ok=True) - task_poscar = os.path.join(task_path, 'POSCAR') - lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map) - # get equi stress - equi_log = os.path.join(equi_path, 'log.lammps') - stress = lammps.get_stress(equi_log) - np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress) - # gen strcture - ss = Structure.from_file(task_poscar) - # gen defomations - norm_strains=np.arange(strain_start,strain_end,strain_step) - print('gen with norm '+str(norm_strains)) - deformations=[] - for ii in norm_strains: - strain = Strain.from_index_amount(strain_direct, ii) - deformations.append(strain.get_deformation_matrix()) - deformed_structures = [defo.apply_to_structure(ss) - for defo in deformations] - n_dfm = len(deformed_structures) - # gen tasks - cwd = os.getcwd() - # make lammps.in - if task_type=='deepmd': - fc = lammps.make_lammps_elastic('conf.lmp', - ntypes, - lammps.inter_deepmd, - model_param) - elif task_type =='meam': - fc = lammps.make_lammps_elastic('conf.lmp', - ntypes, - lammps.inter_meam, - model_param) - - - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - cwd = os.getcwd() - if task_type =='deepmd': - os.chdir(task_path) - for ii in model_name : - if os.path.exists(ii) : - os.remove(ii) - for (ii,jj) in zip(models, model_name) : - os.symlink(os.path.relpath(ii), jj) - share_models = glob.glob(os.path.join(task_path, '*pb')) - else: - share_models = models - - for ii in range(n_dfm) : - # make dir - dfm_path = os.path.join(task_path, 'dfm-%03d' % ii) - os.makedirs(dfm_path, exist_ok=True) - os.chdir(dfm_path) - for jj in ['conf.lmp', 'lammps.in'] + model_name : - if os.path.isfile(jj): - os.remove(jj) - # make conf - deformed_structures[ii].to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # record strain - strain = Strain.from_deformation(deformations[ii]) - np.savetxt('strain.out', strain) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(share_models, model_name) : - os.symlink(os.path.relpath(ii), jj) - cwd = os.getcwd() - -def make_meam_lammps(jdata, conf_dir) : - meam_potfile_dir = jdata['meam_potfile_dir'] - meam_potfile_dir = os.path.abspath(meam_potfile_dir) - meam_potfile = jdata['meam_potfile'] - meam_potfile = [os.path.join(meam_potfile_dir,ii) for ii in meam_potfile] - meam_potfile_name = jdata['meam_potfile'] - type_map = jdata['meam_type_map'] - ntypes = len(type_map) - meam_param = {'meam_potfile' : jdata['meam_potfile'], - 'meam_type': jdata['meam_param_type']} - - norm_def = jdata['norm_deform'] - shear_def = jdata['shear_deform'] - - conf_path = os.path.abspath(conf_dir) - conf_poscar = os.path.join(conf_path, 'POSCAR') - # get equi poscar - equi_path = re.sub('confs', global_equi_name, conf_path) - equi_path = os.path.join(equi_path, 'meam') - equi_dump = os.path.join(equi_path, 'dump.relax') - task_path = re.sub('confs', global_task_name, conf_path) - task_path = os.path.join(task_path, 'meam') - os.makedirs(task_path, exist_ok=True) - task_poscar = os.path.join(task_path, 'POSCAR') - lammps.poscar_from_last_dump(equi_dump, task_poscar, type_map) - # get equi stress - equi_log = os.path.join(equi_path, 'log.lammps') - stress = lammps.get_stress(equi_log) - np.savetxt(os.path.join(task_path, 'equi.stress.out'), stress) - # gen strcture - # ss = Structure.from_file(conf_poscar) - # print(ss) - # ss = ss.from_file(task_poscar) - # print(ss) - ss = Structure.from_file(task_poscar) - # gen defomations - norm_strains = [-norm_def, -0.5*norm_def, 0.5*norm_def, norm_def] - shear_strains = [-shear_def, -0.5*shear_def, 0.5*shear_def, shear_def] - print('gen with norm '+str(norm_strains)) - print('gen with shear '+str(shear_strains)) - dfm_ss = DeformedStructureSet(ss, - symmetry = False, - norm_strains = norm_strains, - shear_strains = shear_strains) - n_dfm = len(dfm_ss) - # gen tasks - cwd = os.getcwd() - # make lammps.in - fc = lammps.make_lammps_elastic('conf.lmp', - ntypes, - lammps.inter_meam, - meam_param) - f_lammps_in = os.path.join(task_path, 'lammps.in') - with open(f_lammps_in, 'w') as fp : - fp.write(fc) - cwd = os.getcwd() - for ii in range(n_dfm) : - # make dir - dfm_path = os.path.join(task_path, 'dfm-%03d' % ii) - os.makedirs(dfm_path, exist_ok=True) - os.chdir(dfm_path) - for jj in ['conf.lmp', 'lammps.in'] + meam_potfile_name : - if os.path.isfile(jj): - os.remove(jj) - # make conf - dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR') - lammps.cvt_lammps_conf('POSCAR', 'conf.lmp') - ptypes = vasp.get_poscar_types('POSCAR') - lammps.apply_type_map('conf.lmp', type_map, ptypes) - # record strain - strain = Strain.from_deformation(dfm_ss.deformations[ii]) - np.savetxt('strain.out', strain) - # link lammps.in - os.symlink(os.path.relpath(f_lammps_in), 'lammps.in') - # link models - for (ii,jj) in zip(meam_potfile, meam_potfile_name) : - os.symlink(os.path.relpath(ii), jj) - cwd = os.getcwd() - - -def _main() : - parser = argparse.ArgumentParser( - description="gen 07.SScurve") - parser.add_argument('TASK', type=str, - help='the task of generation, vasp or lammps') - parser.add_argument('PARAM', type=str, - help='json parameter file') - parser.add_argument('CONF', type=str, - help='the path to conf') - args = parser.parse_args() - - with open (args.PARAM, 'r') as fp : - jdata = json.load (fp) - - print('generate %s task with conf %s' % (args.TASK, args.CONF)) - if args.TASK == 'vasp': - make_vasp(jdata, args.CONF) - elif args.TASK == 'deepmd' or args.TASK == 'meam' : - make_lammps(jdata, args.CONF,args.TASK) - #elif args.TASK == 'meam' : - # make_meam_lammps(jdata, args.CONF) - else : - raise RuntimeError("unknow task ", args.TASK) - -if __name__ == '__main__' : - _main() - diff --git a/dpgen/auto_test/lib/lammps.py b/dpgen/auto_test/lib/lammps.py index aafc35e21..9b2820ffa 100644 --- a/dpgen/auto_test/lib/lammps.py +++ b/dpgen/auto_test/lib/lammps.py @@ -5,8 +5,10 @@ import subprocess as sp import dpgen.auto_test.lib.util as util from distutils.version import LooseVersion +from dpdata.periodic_table import Element -def cvt_lammps_conf(fin, fout, ofmt = 'lammps/data'): + +def cvt_lammps_conf(fin, fout, type_map, ofmt='lammps/data'): """ Format convert from fin to fout, specify the output format by ofmt Imcomplete situation @@ -14,23 +16,24 @@ def cvt_lammps_conf(fin, fout, ofmt = 'lammps/data'): supp_ofmt = ['lammps/dump', 'lammps/data', 'vasp/poscar'] supp_exts = ['dump', 'lmp', 'poscar/POSCAR'] - if 'dump' in fout : + if 'dump' in fout: ofmt = 'lammps/dump' - elif 'lmp' in fout : + elif 'lmp' in fout: ofmt = 'lammps/data' - elif 'poscar' in fout or 'POSCAR' in fout : + elif 'poscar' in fout or 'POSCAR' in fout: ofmt = 'vasp/poscar' - if not ofmt in supp_ofmt : - raise RuntimeError ("output format " + ofmt + " is not supported. use one of " + str(supp_ofmt)) + if not ofmt in supp_ofmt: + raise RuntimeError("output format " + ofmt + " is not supported. use one of " + str(supp_ofmt)) - if 'lmp' in fout : - d_poscar=dpdata.System(fin, fmt = 'vasp/poscar') + if 'lmp' in fout: + d_poscar = dpdata.System(fin, fmt='vasp/poscar', type_map=type_map) d_poscar.to_lammps_lmp(fout, frame_idx=0) elif 'poscar' in fout or 'POSCAR' in fout: - d_dump=dpdata.System(fin, fmt = 'lammps/dump') + d_dump = dpdata.System(fin, fmt='lammps/dump', type_map=type_map) d_dump.to_vasp_poscar(fout, frame_idx=-1) -def apply_type_map(conf_file, deepmd_type_map, ptypes) : + +def apply_type_map(conf_file, deepmd_type_map, ptypes): """ apply type map. conf_file: conf file converted from POSCAR @@ -46,51 +49,54 @@ def apply_type_map(conf_file, deepmd_type_map, ptypes) : new_lines = lines # revise ntypes idx_ntypes = -1 - for idx, ii in enumerate(lines) : - if 'atom types' in ii : + for idx, ii in enumerate(lines): + if 'atom types' in ii: idx_ntypes = idx - if idx_ntypes == -1 : + if idx_ntypes == -1: raise RuntimeError("cannot find the entry 'atom types' in ", conf_file) words = lines[idx_ntypes].split() words[0] = str(ntypes) new_lines[idx_ntypes] = " ".join(words) # find number of atoms idx_atom_entry = -1 - for idx, ii in enumerate(lines) : - if 'Atoms' in ii : + for idx, ii in enumerate(lines): + if 'Atoms' in ii: idx_atom_entry = idx - if idx_atom_entry == -1 : + if idx_atom_entry == -1: raise RuntimeError("cannot find the entry 'Atoms' in ", conf_file) # revise atom type - for idx in range(idx_atom_entry+2, idx_atom_entry+2+natoms) : + for idx in range(idx_atom_entry + 2, idx_atom_entry + 2 + natoms): ii = lines[idx] words = ii.split() - assert(len(words) >= 5) + assert (len(words) >= 5) old_id = int(words[1]) - new_id = deepmd_type_map.index(ptypes[old_id-1])+1 + new_id = deepmd_type_map.index(ptypes[old_id - 1]) + 1 words[1] = str(new_id) ii = " ".join(words) new_lines[idx] = ii with open(conf_file, 'w') as fp: fp.write("\n".join(new_lines)) -def _get_ntype(conf) : + +def _get_ntype(conf): with open(conf, 'r') as fp: lines = fp.read().split('\n') - for ii in lines : - if "atom types" in ii : + for ii in lines: + if "atom types" in ii: return int(ii.split()[0]) raise RuntimeError("cannot find line indicate atom types in ", conf) -def _get_conf_natom(conf) : + +def _get_conf_natom(conf): with open(conf, 'r') as fp: lines = fp.read().split('\n') - for ii in lines : - if "atoms" in ii : + for ii in lines: + if "atoms" in ii: return int(ii.split()[0]) raise RuntimeError("cannot find line indicate atom types in ", conf) -def inter_deepmd(param) : + +def inter_deepmd(param): models = param["model_name"] deepmd_version = param["deepmd_version"] ret = "pair_style deepmd " @@ -99,9 +105,9 @@ def inter_deepmd(param) : model_list += ii + " " if LooseVersion(deepmd_version) < LooseVersion('1'): ## DeePMD-kit version == 0.x - if len(models) > 1 : + if len(models) > 1: ret += '%s 10 model_devi.out\n' % model_list - else : + else: ret += models[0] + '\n' else: ## DeePMD-kit version >= 1 @@ -112,22 +118,58 @@ def inter_deepmd(param) : ret += "pair_coeff\n" return ret -def inter_meam(param) : + +def inter_meam(param): ret = "" line = "pair_style meam \n" - line+= "pair_coeff * * %s " % param['model_name'][0] - for ii in param['param_type'] : + line += "pair_coeff * * %s " % param['model_name'][0] + for ii in param['param_type']: line += ii + ' ' - line+= "%s " % param['model_name'][1] - for ii in param['param_type'] : + line += "%s " % param['model_name'][1] + for ii in param['param_type']: line += ii + ' ' - line+= '\n' + line += '\n' ret += line return ret -def make_lammps_eval(conf, ntypes, interaction, param) : + +def inter_eam_fs(param): # 06/08 eam.fs interaction + ret = "" + line = "pair_style eam/fs \n" + line += "pair_coeff * * %s " % param['model_name'][0] + for ii in param['param_type']: + line += ii + ' ' + line += '\n' + ret += line + return ret + + +def inter_eam_alloy(param): # 06/08 eam.alloy interaction + ret = "" + line = "pair_style eam/alloy \n" + line += "pair_coeff * * %s " % param['model_name'] + for ii in param['param_type']: + line += ii + ' ' + line += '\n' + ret += line + return ret + + +def element_list(type_map): + type_map_reverse = {k: v for v, k in type_map.items()} + type_map_list = [] + tmp_list = list(type_map_reverse.keys()) + tmp_list.sort() + for ii in tmp_list: + type_map_list.append(type_map_reverse[ii]) + return type_map_list + + +def make_lammps_eval(conf, type_map, interaction, param): + type_map_list = element_list(type_map) + """ - make lammps input for equilibritation + make lammps input for static calcualtion """ ret = "" ret += "clear\n" @@ -137,13 +179,14 @@ def make_lammps_eval(conf, ntypes, interaction, param) : ret += "atom_style atomic\n" ret += "box tilt large\n" ret += "read_data %s\n" % conf - for ii in range(ntypes) : - ret += "mass %d 1\n" % (ii+1) + for ii in range(len(type_map)): + ret += "mass %d %.3f\n" % (ii + 1, Element(type_map_list[ii]).mass) ret += "neigh_modify every 1 delay 0 check no\n" ret += interaction(param) ret += "compute mype all pe\n" ret += "thermo 100\n" ret += "thermo_style custom step pe pxx pyy pzz pxy pxz pyz lx ly lz vol c_mype\n" + ret += "dump 1 all custom 100 dump.relax id type xs ys zs fx fy fz\n" # 06/09 give dump.relax ret += "run 0\n" ret += "variable N equal count(all)\n" ret += "variable V equal vol\n" @@ -168,10 +211,12 @@ def make_lammps_eval(conf, ntypes, interaction, param) : return ret -def make_lammps_equi(conf, ntypes, interaction, param, +def make_lammps_equi(conf, type_map, interaction, param, etol=1e-12, ftol=1e-6, maxiter=5000, maxeval=500000, - change_box = True) : + change_box=True): + type_map_list = element_list(type_map) + """ make lammps input for equilibritation """ @@ -183,8 +228,8 @@ def make_lammps_equi(conf, ntypes, interaction, param, ret += "atom_style atomic\n" ret += "box tilt large\n" ret += "read_data %s\n" % conf - for ii in range(ntypes) : - ret += "mass %d 1\n" % (ii+1) + for ii in range(len(type_map)): + ret += "mass %d %.3f\n" % (ii + 1, Element(type_map_list[ii]).mass) ret += "neigh_modify every 1 delay 0 check no\n" ret += interaction(param) ret += "compute mype all pe\n" @@ -192,7 +237,7 @@ def make_lammps_equi(conf, ntypes, interaction, param, ret += "thermo_style custom step pe pxx pyy pzz pxy pxz pyz lx ly lz vol c_mype\n" ret += "dump 1 all custom 100 dump.relax id type xs ys zs fx fy fz\n" ret += "min_style cg\n" - if change_box : + if change_box: ret += "fix 1 all box/relax iso 0.0 \n" ret += "minimize %e %e %d %d\n" % (etol, ftol, maxiter, maxeval) ret += "fix 1 all box/relax aniso 0.0 \n" @@ -219,9 +264,12 @@ def make_lammps_equi(conf, ntypes, interaction, param, ret += "print \"Final Stress (xx yy zz xy xz yz) = ${Pxx} ${Pyy} ${Pzz} ${Pxy} ${Pxz} ${Pyz}\"\n" return ret -def make_lammps_elastic(conf, ntypes, interaction, param, + +def make_lammps_elastic(conf, type_map, interaction, param, etol=1e-12, ftol=1e-6, - maxiter=5000, maxeval=500000) : + maxiter=5000, maxeval=500000): + type_map_list = element_list(type_map) + """ make lammps input for elastic calculation """ @@ -233,8 +281,8 @@ def make_lammps_elastic(conf, ntypes, interaction, param, ret += "atom_style atomic\n" ret += "box tilt large\n" ret += "read_data %s\n" % conf - for ii in range(ntypes) : - ret += "mass %d 1\n" % (ii+1) + for ii in range(len(type_map)): + ret += "mass %d %.3f\n" % (ii + 1, Element(type_map_list[ii]).mass) ret += "neigh_modify every 1 delay 0 check no\n" ret += interaction(param) ret += "compute mype all pe\n" @@ -261,10 +309,13 @@ def make_lammps_elastic(conf, ntypes, interaction, param, ret += "print \"Final Stress (xx yy zz xy xz yz) = ${Pxx} ${Pyy} ${Pzz} ${Pxy} ${Pxz} ${Pyz}\"\n" return ret -def make_lammps_press_relax(conf, ntypes, scale2equi, interaction, param, - B0 = 70, bp = 0, + +def make_lammps_press_relax(conf, type_map, scale2equi, interaction, param, + B0=70, bp=0, etol=1e-12, ftol=1e-6, - maxiter=5000, maxeval=500000) : + maxiter=5000, maxeval=500000): + type_map_list = element_list(type_map) + """ make lammps input for relaxation at a certain volume scale2equi: the volume scale with respect to equilibrium volume @@ -284,8 +335,8 @@ def make_lammps_press_relax(conf, ntypes, scale2equi, interaction, param, ret += "atom_style atomic\n" ret += "box tilt large\n" ret += "read_data %s\n" % conf - for ii in range(ntypes) : - ret += "mass %d 1\n" % (ii+1) + for ii in range(len(type_map)): + ret += "mass %d %.3f\n" % (ii + 1, Element(type_map_list[ii]).mass) ret += "neigh_modify every 1 delay 0 check no\n" ret += interaction(param) ret += "compute mype all pe\n" @@ -316,9 +367,10 @@ def make_lammps_press_relax(conf, ntypes, scale2equi, interaction, param, ret += "print \"Final Stress (xx yy zz xy xz yz) = ${Pxx} ${Pyy} ${Pzz} ${Pxy} ${Pxz} ${Pyz}\"\n" return ret + def make_lammps_phonon(conf, masses, interaction, param, - etol=1e-12, ftol=1e-6, - maxiter=5000, maxeval=500000): + etol=1e-12, ftol=1e-6, + maxiter=5000, maxeval=500000): """ make lammps input for elastic calculation """ @@ -330,32 +382,36 @@ def make_lammps_phonon(conf, masses, interaction, param, ret += "atom_style atomic\n" ret += "box tilt large\n" ret += "read_data %s\n" % conf - ntypes=len(masses) - for ii in range(ntypes) : - ret += "mass %d %f\n" % (ii+1,masses[ii]) + ntypes = len(masses) + for ii in range(ntypes): + ret += "mass %d %f\n" % (ii + 1, masses[ii]) ret += "neigh_modify every 1 delay 0 check no\n" ret += interaction(param) return ret -def _get_epa (lines) : + +def _get_epa(lines): for ii in lines: if ("Final energy per atoms" in ii) and (not 'print' in ii): return float(ii.split('=')[1].split()[0]) raise RuntimeError("cannot find key \"Final energy per atoms\" in lines, something wrong") -def _get_vpa (lines) : - for ii in lines : + +def _get_vpa(lines): + for ii in lines: if ("Final volume per atoms" in ii) and (not 'print' in ii): return float(ii.split('=')[1].split()[0]) raise RuntimeError("cannot find key \"Final volume per atoms\" in lines, something wrong") -def _get_natoms (lines) : + +def _get_natoms(lines): for ii in lines: if ("Total number of atoms" in ii) and (not 'print' in ii): return int(ii.split('=')[1].split()[0]) raise RuntimeError("cannot find key \"Total number of atoms\" in lines, something wrong") -def get_nev (log) : + +def get_nev(log): """ get natoms, energy_per_atom and volume_per_atom from lammps log """ @@ -366,7 +422,8 @@ def get_nev (log) : natoms = _get_natoms(lines) return natoms, epa, vpa -def get_base_area (log) : + +def get_base_area(log): """ get base area """ @@ -376,29 +433,31 @@ def get_base_area (log) : if ("Final Base area" in ii) and (not 'print' in ii): return float(ii.split('=')[1].split()[0]) -def get_stress(log) : + +def get_stress(log): """ get stress from lammps log """ - with open(log, 'r') as fp : + with open(log, 'r') as fp: lines = fp.read().split('\n') - for ii in lines : + for ii in lines: if ('Final Stress' in ii) and (not 'print' in ii): vstress = [float(jj) for jj in ii.split('=')[1].split()] stress = util.voigt_to_stress(vstress) return stress -def poscar_from_last_dump(dump, poscar_out, deepmd_type_map) : + +def poscar_from_last_dump(dump, poscar_out, deepmd_type_map): """ get poscar from the last frame of a lammps MD traj (dump format) """ - with open(dump, 'r') as fp : + with open(dump, 'r') as fp: lines = fp.read().split('\n') step_idx = -1 - for idx,ii in enumerate(lines) : - if 'ITEM: TIMESTEP' in ii : + for idx, ii in enumerate(lines): + if 'ITEM: TIMESTEP' in ii: step_idx = idx - if step_idx == -1 : + if step_idx == -1: raise RuntimeError("cannot find timestep in lammps dump, something wrong") with open('tmp_dump', 'w') as fp: fp.write("\n".join(lines[step_idx:])) @@ -406,21 +465,22 @@ def poscar_from_last_dump(dump, poscar_out, deepmd_type_map) : os.remove('tmp_dump') with open(poscar_out, 'r') as fp: lines = fp.read().split('\n') - types = [ deepmd_type_map[int(ii.split('_')[1])] for ii in lines[5].split()] + types = [deepmd_type_map[int(ii.split('_')[1])] for ii in lines[5].split()] lines[5] = " ".join(types) with open(poscar_out, 'w') as fp: lines = fp.write("\n".join(lines)) -def check_finished_new(fname,keyword): - with open(fname, 'r') as fp : +def check_finished_new(fname, keyword): + with open(fname, 'r') as fp: lines = fp.read().split('\n') - flag=False + flag = False for jj in lines: if (keyword in jj) and (not 'print' in jj): - flag=True + flag = True return flag + def check_finished(fname): with open(fname, 'r') as fp: return 'Total wall time:' in fp.read() diff --git a/dpgen/auto_test/lib/util.py b/dpgen/auto_test/lib/util.py index 06fd27208..0a86287fd 100644 --- a/dpgen/auto_test/lib/util.py +++ b/dpgen/auto_test/lib/util.py @@ -6,7 +6,7 @@ from dpgen.auto_test.lib import lammps from dpgen.auto_test.lib.utils import cmd_append_log -lammps_task_type=['deepmd','meam','eam'] +lammps_task_type=['deepmd','meam','eam_fs','eam_alloy'] # 06/13 revised def voigt_to_stress(inpt) : ret = np.zeros((3,3)) @@ -81,7 +81,7 @@ def get_machine_info(mdata,task_type): group_size = mdata['model_devi_group_size'] resources = mdata['model_devi_resources'] machine=mdata['model_devi_machine'] - command = lmp_exec + " -i lammps.in" + command = lmp_exec + " -i in.lammps" command = cmd_append_log(command, "model_devi.log") return machine, resources, command, group_size diff --git a/dpgen/auto_test/mpdb.py b/dpgen/auto_test/mpdb.py new file mode 100644 index 000000000..4a76c9c8d --- /dev/null +++ b/dpgen/auto_test/mpdb.py @@ -0,0 +1,25 @@ +import os +from dpgen import dlog +from pymatgen import MPRester,Structure +from pymatgen.ext.matproj import MPRestError + +web="materials.org" + +def check_apikey(): + try: + apikey=os.environ['MAPI_KEY'] + except KeyError: + print("You have to get a MAPI_KEY from "+web) + print("and execute following command:") + print('echo "export MAPI_KEY=yourkey">> ~/.bashrc') + print("source ~/.bashrc") + os._exit(0) + try: + return MPRester(apikey) + except MPRestError: + dlog.info("MPRester Error, you need to prepare POSCAR manually") + os._exit(0) + +def get_structure(mp_id): + mpr=check_apikey() + return mpr.get_structure_by_material_id(mp_id) diff --git a/dpgen/auto_test/refine.py b/dpgen/auto_test/refine.py new file mode 100644 index 000000000..dd7146604 --- /dev/null +++ b/dpgen/auto_test/refine.py @@ -0,0 +1,39 @@ +import glob +import os +import re + + +def make_refine(init_from_suffix, output_suffix, path_to_work): + cwd = os.getcwd() + init_from = re.sub(output_suffix[::-1], init_from_suffix[::-1], path_to_work[::-1], count=1)[::-1] + if not os.path.exists(init_from): + raise FileNotFoundError("the initial directory does not exist for refine") + + output = path_to_work + init_from_task_tot = glob.glob(os.path.join(init_from, 'task.[0-9]*[0-9]')) + + task_num = len(init_from_task_tot) + + task_list = [] + for ii in range(task_num): + output_task = os.path.join(output, 'task.%06d' % ii) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + for jj in ['INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(jj): + os.remove(jj) + task_list.append(output_task) + init_from_task = os.path.join(init_from, 'task.%06d' % ii) + if not os.path.exists(init_from_task): + raise FileNotFoundError("the initial task directory does not exist for refine") + contcar = os.path.join(init_from_task, 'CONTCAR') + init_poscar = os.path.join(init_from_task, 'POSCAR') + if os.path.exists(contcar): + os.symlink(os.path.relpath(contcar), 'POSCAR') + elif os.path.exists(init_poscar): + os.symlink(os.path.relpath(init_poscar), 'POSCAR') + else: + raise FileNotFoundError("no CONTCAR or POSCAR in the init_from directory") + os.chdir(cwd) + + return task_list diff --git a/dpgen/auto_test/reproduce.py b/dpgen/auto_test/reproduce.py new file mode 100644 index 000000000..bc18c9c01 --- /dev/null +++ b/dpgen/auto_test/reproduce.py @@ -0,0 +1,146 @@ +import glob +import os + +import numpy as np +from monty.serialization import loadfn + + +def make_repro(init_data_path, init_from_suffix, path_to_work, reprod_last_frame=True): + path_to_work = os.path.abspath(path_to_work) + property_type = path_to_work.split('/')[-1].split('_')[0] + init_data_path = os.path.join(init_data_path, '*', property_type + '_' + init_from_suffix) + init_data_path_list = glob.glob(init_data_path) + init_data_path_list.sort() + cwd = os.getcwd() + struct_init_name_list = [] + for ii in init_data_path_list: + struct_init_name_list.append(ii.split('/')[-2]) + struct_output_name = path_to_work.split('/')[-2] + + assert struct_output_name in struct_init_name_list + + for idx, ii in enumerate(struct_init_name_list): + if ii == struct_output_name: + label = idx + + init_data_path_todo = init_data_path_list[label] + + init_data_task_todo = glob.glob(os.path.join(init_data_path_todo, 'task.[0-9]*[0-9]')) + assert len(init_data_task_todo) > 0, "There is no task in previous calculations path" + init_data_task_todo.sort() + + task_list = [] + task_num = 0 + + if property_type == 'interstitial': + if os.path.exists(os.path.join(path_to_work, 'element.out')): + os.remove(os.path.join(path_to_work, 'element.out')) + fout_element = open(os.path.join(path_to_work, 'element.out'), 'a+') + fin_element = open(os.path.join(init_data_path_todo, 'element.out'), 'r') + + for ii in init_data_task_todo: + # get frame number + task_result = loadfn(os.path.join(ii, 'result_task.json')) + if reprod_last_frame: + nframe = 1 + else: + nframe = len(task_result['energies']) + if property_type == 'interstitial': + insert_element = fin_element.readline().split()[0] + for jj in range(nframe): + if property_type == 'interstitial': + print(insert_element, file=fout_element) + output_task = os.path.join(path_to_work, 'task.%06d' % task_num) + task_num += 1 + task_list.append(output_task) + os.makedirs(output_task, exist_ok=True) + os.chdir(output_task) + # clear dir + for kk in ['INCAR', 'POTCAR', 'POSCAR.orig', 'POSCAR', 'conf.lmp', 'in.lammps']: + if os.path.exists(kk): + os.remove(kk) + # make conf + if reprod_last_frame: + task_result.to('vasp/poscar', 'POSCAR', frame_idx=-1) + else: + task_result.to('vasp/poscar', 'POSCAR', frame_idx=jj) + os.chdir(cwd) + + if property_type == 'interstitial': + fout_element.close() + fin_element.close() + + return task_list + + +def post_repro(init_data_path, init_from_suffix, all_tasks, ptr_data, reprod_last_frame=True): + ptr_data += "Reproduce: Initial_path Init_E(eV/atom) Reprod_E(eV/atom) Difference(eV/atom)\n" + struct_output_name = all_tasks[0].split('/')[-3] + property_type = all_tasks[0].split('/')[-2].split('_')[0] + init_data_path = os.path.join(init_data_path, '*', property_type + '_' + init_from_suffix) + init_data_path_list = glob.glob(init_data_path) + init_data_path_list.sort() + # cwd = os.getcwd() + struct_init_name_list = [] + for ii in init_data_path_list: + struct_init_name_list.append(ii.split('/')[-2]) + + assert struct_output_name in struct_init_name_list + + for idx, ii in enumerate(struct_init_name_list): + if ii == struct_output_name: + label = idx + + init_data_path_todo = init_data_path_list[label] + + init_data_task_todo = glob.glob(os.path.join(init_data_path_todo, 'task.[0-9]*[0-9]')) + assert len(init_data_task_todo) > 0, "There is no task in previous calculations path" + init_data_task_todo.sort() + + idid = 0 + init_ener_tot = [] + output_ener_tot = [] + res_data = {} + + for ii in init_data_task_todo: + init_task_result = loadfn(os.path.join(ii, 'result_task.json')) + if reprod_last_frame: + nframe = 1 + else: + nframe = len(init_task_result['energies']) + # idid += nframe + natoms = init_task_result['atom_numbs'][0] + if reprod_last_frame: + init_ener = init_task_result['energies'][-1:] + else: + init_ener = init_task_result['energies'] + init_ener_tot.extend(list(init_ener)) + output_ener = [] + for jj in range(idid, idid + nframe): + output_task_result = loadfn(os.path.join(all_tasks[jj], 'result_task.json')) + output_epa = output_task_result['energies'] / natoms + output_ener.append(output_epa) + output_ener_tot.extend(output_task_result['energies']) + + init_epa = init_ener[jj - idid] / natoms + ptr_data += '%s %7.3f %7.3f %7.3f\n' % (ii, init_epa, output_epa, output_epa - init_epa) + idid += nframe + output_ener = np.array(output_ener) + output_ener = np.reshape(output_ener, [-1, 1]) + init_ener = np.reshape(init_ener, [-1, 1]) / natoms + if reprod_last_frame: + error_start = 0 + else: + error_start = 1 + output_ener -= output_ener[-1] - init_ener[-1] + diff = output_ener - init_ener + diff = diff[error_start:] + error = np.linalg.norm(diff) / np.sqrt(np.size(output_ener) - error_start) + res_data[ii] = {'nframes': len(init_ener), 'error': error} + + if not len(init_ener_tot) == len(output_ener_tot): + raise RuntimeError("reproduce tasks not equal to init") + # for ii in range(len(lmp_ener_tot)): + # ptr_data += '%7.3f %7.3f %7.3f\n' % (vasp_ener_tot[ii], lmp_ener_tot[ii], + # lmp_ener_tot[ii] - vasp_ener_tot[ii]) + return res_data, ptr_data diff --git a/dpgen/auto_test/run.py b/dpgen/auto_test/run.py index df5a8cbfd..e7cb6cde2 100644 --- a/dpgen/auto_test/run.py +++ b/dpgen/auto_test/run.py @@ -1,806 +1,61 @@ #!/usr/bin/env python3 -""" -init: crystal configuration -task: - 00.equi - 01.eos - 02.elastic - 03.vacancy - 04.interstitial - 05.surf - 06.phonon -""" - - -import sys -import os, re, argparse, filecmp, json, glob -import dpgen.auto_test.lib.util as util -import dpgen.auto_test.lib.vasp as vasp -import dpgen.auto_test.lib.lammps as lammps -import random import logging -import warnings -import shutil -import time -import numpy as np -import subprocess as sp -from dpgen.auto_test.lib.utils import make_iter_name -from dpgen.auto_test.lib.utils import create_path -from dpgen.auto_test.lib.utils import copy_file_list -from dpgen.auto_test.lib.utils import replace -from dpgen.dispatcher.Dispatcher import make_dispatcher -from dpgen.auto_test.lib.utils import log_iter -from dpgen.auto_test.lib.utils import record_iter -from dpgen.auto_test.lib.utils import log_iter -from dpgen.auto_test.lib.pwscf import make_pwscf_input -from dpgen.auto_test.lib.siesta import make_siesta_input -from dpgen.auto_test import gen_00_equi,cmpt_00_equi -from dpgen.auto_test import gen_01_eos,cmpt_01_eos -from dpgen.auto_test import gen_02_elastic,cmpt_02_elastic -from dpgen.auto_test import gen_03_vacancy,cmpt_03_vacancy -from dpgen.auto_test import gen_04_interstitial,cmpt_04_interstitial -from dpgen.auto_test import gen_05_surf,cmpt_05_surf -from dpgen.remote.decide_machine import decide_fp_machine, decide_model_devi_machine -#from dpgen.auto_test import gen_06_phonon,cmpt_06_phonon -from dpgen.auto_test import gen_confs -import requests -from hashlib import sha1 -from dpgen import dlog - -lammps_task_type=['deepmd','meam','eam'] - -def gen_equi(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - cwd=os.getcwd() - #vasp - if task_type=="vasp": - gen_00_equi.make_vasp(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type: - gen_00_equi.make_lammps (jdata, conf_dir,task_type) - else : - raise RuntimeError ("unknow task %s, something wrong" % task_type) - os.chdir(cwd) - -def run_equi(task_type,jdata,mdata): - #rmprint("This module has been run !") - - work_path=util.make_work_path(jdata,'00.equi',False,False,False) - all_task = glob.glob(os.path.join(work_path,'.')) - - #vasp - if task_type=="vasp": - mdata=decide_fp_machine(mdata) - - forward_files = ['INCAR', 'POTCAR', 'KPOINTS'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - backward_files = ['OUTCAR', task_type+'.out' , 'CONTCAR','OSZICAR'] - common_files=['POSCAR'] - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - forward_files = ['conf.lmp', 'lammps.in'] - backward_files = ['dump.relax','log.lammps', task_type+'.out'] - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - common_files = model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - - -def cmpt_equi(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - cmpt_shift=jdata['alloy_shift'] - #vasp - if task_type=="vasp": - n, e, v, s = cmpt_00_equi.comput_vasp_nev(jdata, conf_dir,cmpt_shift) - #lammps - elif task_type in lammps_task_type: - n, e, v, s = cmpt_00_equi.comput_lmp_nev(conf_dir, task_type,cmpt_shift) - else : - raise RuntimeError ("unknow task %s, something wrong" % task_type) - if cmpt_shift: - print('conf_dir:\t EpA(eV) VpA(A^3) ener_shift(eV)') - print("%s\t %8.4f %7.3f %8.4f" % (conf_dir, e, v, s)) - else: - print('conf_dir:\t EpA(eV) VpA(A^3)') - print("%s\t %8.4f %7.3f " % (conf_dir, e, v)) - -def gen_eos(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - fix_shape = True - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_01_eos.make_vasp(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type: - if fix_shape : - gen_01_eos.make_lammps_fixv(jdata, conf_dir,task_type) - else : - gen_01_eos.make_lammps(jdata, conf_dir,task_type) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) - -def run_eos(task_type,jdata,mdata): - work_path=util.make_work_path(jdata,'01.eos',False,False,False) - - all_task = glob.glob(os.path.join(work_path, "vol-*")) - all_task.sort() - - #vasp - if task_type=="vasp": - mdata=decide_fp_machine(mdata) - - forward_files = ['INCAR', 'POSCAR','POTCAR','KPOINTS'] - backward_files = ['OUTCAR', task_type+'.out' , 'OSZICAR'] - common_files=['INCAR','POTCAR'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - forward_files = ['conf.lmp', 'lammps.in']+model_name - backward_files = ['log.lammps', task_type+'.out'] - common_files=['lammps.in']+model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - -def cmpt_eos(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - #vasp - if task_type == "vasp": - cmpt_01_eos.comput_vasp_eos(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type: - cmpt_01_eos.comput_lmp_eos(jdata, conf_dir, task_type) - else : - raise RuntimeError("unknow task ", task_type) - -def gen_elastic(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_02_elastic.make_vasp(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type: - gen_02_elastic.make_lammps (jdata, conf_dir,task_type) - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - os.chdir(cwd) - -def run_elastic(task_type,jdata,mdata): - work_path=util.make_work_path(jdata,'02.elastic',False,False,False) - - all_task = glob.glob(os.path.join(work_path, "dfm-*")) - all_task.sort() - - #vasp - if task_type == "vasp": - mdata=decide_fp_machine(mdata) - forward_files = ['INCAR', 'POSCAR','POTCAR','KPOINTS'] - backward_files = ['OUTCAR', task_type+'.out' , 'CONTCAR','OSZICAR'] - common_files=['INCAR','POTCAR','KPOINTS'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - forward_files = ['conf.lmp', 'lammps.in','strain.out']+model_name - backward_files = ['log.lammps', task_type+'.out'] - common_files=['lammps.in']+model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - -def cmpt_elastic(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - if task_type == "vasp": - cmpt_02_elastic.cmpt_vasp(jdata, conf_dir) - elif task_type in lammps_task_type: - cmpt_02_elastic.cmpt_deepmd_lammps(jdata, conf_dir, task_type) - else : - raise RuntimeError ("unknow task %s, something wrong" % task_type) -def gen_vacancy(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - supercell=jdata['supercell'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_03_vacancy.make_vasp(jdata, conf_dir, supercell) - #deepmd - elif task_type in lammps_task_type: - gen_03_vacancy.make_lammps(jdata, conf_dir, task_type, supercell) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) +from monty.serialization import loadfn -def run_vacancy(task_type,jdata,mdata): - - work_path=util.make_work_path(jdata,'03.vacancy',False,False,False) - all_task = glob.glob(os.path.join(work_path,'struct-*')) - - #vasp - if task_type == "vasp": - mdata=decide_fp_machine(mdata) - - forward_files = ['INCAR', 'POSCAR','POTCAR','KPOINTS'] - backward_files = ['OUTCAR', task_type+'.out' , 'OSZICAR'] - common_files=['INCAR','POTCAR'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - common_files = model_name - forward_files = ['conf.lmp', 'lammps.in']+model_name - backward_files = ['log.lammps',task_type+'.out'] - common_files=['lammps.in']+model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - -def cmpt_vacancy(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - supercell=jdata['supercell'] - #vasp - if task_type == "vasp": - cmpt_03_vacancy.cmpt_vasp(jdata, conf_dir, supercell) - #lammps - elif task_type in lammps_task_type: - cmpt_03_vacancy.cmpt_deepmd_lammps(jdata, conf_dir, supercell, task_type) - else : - raise RuntimeError("unknow task ", task_type) - -def gen_interstitial(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - supercell=jdata['supercell'] - insert_ele=jdata['insert_ele'] - reprod_opt=jdata['reprod-opt'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_04_interstitial.make_vasp(jdata, conf_dir, supercell, insert_ele) - #lammps - elif task_type in lammps_task_type: - if not reprod_opt: - gen_04_interstitial.make_lammps(jdata, conf_dir, supercell, insert_ele, task_type) - else : - gen_04_interstitial.make_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_type) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) - -def run_interstitial(task_type,jdata,mdata): - - reprod_opt=jdata['reprod-opt'] - work_path=util.make_work_path(jdata,'04.interstitial',reprod_opt,False,False) - all_task = glob.glob(os.path.join(work_path,'struct-*')) - - #vasp - if task_type == "vasp": - mdata=decide_fp_machine(mdata) - - forward_files = ['INCAR', 'POSCAR','POTCAR',"KPOINTS"] - backward_files = ['OUTCAR', task_type+'.out' , 'XDATCAR','OSZICAR'] - common_files=['INCAR'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - if reprod_opt: - all_frame=[] - for ii in all_task: - all_frame+=(glob.glob(os.path.join(ii,'frame.*'))) - work_path = all_task - all_task = all_frame - - run_tasks_ = [] - for ii in all_task: - # fres = os.path.join(ii, 'log.lammps') - # if os.path.isfile(fres) : - # if not lammps.check_finished(fres): - # run_tasks_.append(ii) - # else : - # run_tasks_.append(ii) - run_tasks_.append(ii) - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - forward_files = ['conf.lmp', 'lammps.in']+model_name - backward_files = ['log.lammps', task_type+'.out'] - common_files=['lammps.in']+model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - if reprod_opt: - for ii in work_path: - run_tasks=[] - for jj in run_tasks_: - if ii in jj: - run_tasks.append(os.path.basename(jj)) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - ii, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - else: - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - -def cmpt_interstitial(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - supercell=jdata['supercell'] - insert_ele=jdata['insert_ele'] - reprod_opt=jdata['reprod-opt'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - cmpt_04_interstitial.cmpt_vasp(jdata, conf_dir, supercell, insert_ele) - #lammps - elif task_type in lammps_task_type: - if not reprod_opt: - cmpt_04_interstitial.cmpt_deepmd_lammps(jdata, conf_dir, supercell, insert_ele, task_type) - else : - task_name=task_type+'-reprod' - cmpt_04_interstitial.cmpt_deepmd_reprod_traj(jdata, conf_dir, supercell, insert_ele, task_name) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) - -def gen_surf(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - max_miller=jdata['max_miller'] - relax_box=jdata['relax_box'] - static=jdata['static-opt'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_05_surf.make_vasp(jdata, conf_dir, max_miller, static = static, relax_box = relax_box) - #lammps - elif task_type in lammps_task_type : - gen_05_surf.make_lammps(jdata, conf_dir, max_miller, static = static, relax_box = relax_box, task_type = task_type) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) - -def run_surf(task_type,jdata,mdata): - static=jdata['static-opt'] - work_path=util.make_work_path(jdata,'05.surf',False,static,False) - - all_task = glob.glob(os.path.join(work_path,'struct-*')) - - #vasp - if task_type == "vasp": - mdata=decide_fp_machine(mdata) - - forward_files = ['INCAR', 'POSCAR','POTCAR','KPOINTS'] - backward_files = ['OUTCAR', task_type+'.out' , 'OSZICAR'] - common_files=['INCAR','POTCAR'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - - #lammps - elif task_type in lammps_task_type: - mdata = decide_model_devi_machine(mdata) - - fp_params = jdata['lammps_params'] - model_dir = fp_params['model_dir'] - model_dir = os.path.abspath(model_dir) - model_name =fp_params['model_name'] - if not model_name : - models = glob.glob(os.path.join(model_dir, '*pb')) - model_name = [os.path.basename(ii) for ii in models] - else: - models = [os.path.join(model_dir,ii) for ii in model_name] - forward_files = ['conf.lmp', 'lammps.in']+model_name - backward_files = ['log.lammps',task_type+'.out'] - common_files=['lammps.in']+model_name - - if len(model_name)>1 and task_type == 'deepmd': - backward_files = backward_files + ['model_devi.out'] - - else: - raise RuntimeError ("unknow task %s, something wrong" % task_type) - - run_tasks = util.collect_task(all_task,task_type) - if len(run_tasks)==0: return - else: - run_tasks = [os.path.basename(ii) for ii in all_task] - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') +from dpgen import dlog +from dpgen.auto_test.common_equi import make_equi, run_equi, post_equi +from dpgen.auto_test.common_prop import make_property, run_property, post_property -def cmpt_surf(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - static_opt=jdata['static-opt'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - cmpt_05_surf.cmpt_vasp(jdata, conf_dir, static = static_opt) - #lammps - elif task_type in lammps_task_type : - if static_opt: - task_name =task_type+'-static' - else: - task_name =task_type - cmpt_05_surf.cmpt_deepmd_lammps(jdata, conf_dir, task_name, static = static_opt) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) -def gen_phonon(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - gen_06_phonon.make_vasp(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type: - gen_06_phonon.make_lammps(jdata, conf_dir, task_type) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) +#lammps_task_type = ['deepmd', 'meam', 'eam_fs', 'eam_alloy'] -def run_phonon(task_type,jdata,mdata): - user= ('user_incar' in jdata.keys()) - work_path=util.make_work_path(jdata,'06.phonon',False,False,user) +def run_task(step, param_file, machine_file=None): + jdata=loadfn(param_file) + confs = jdata['structures'] + inter_parameter = jdata['interaction'] - all_task = glob.glob(os.path.join(work_path,'.')) + if machine_file: + mdata=loadfn(machine_file) - #vasp - if task_type == "vasp": - mdata=decide_fp_machine(mdata) - machine,resources,command,group_size=util.get_machine_info(mdata,task_type) + if step == 'make' and 'relaxation' in jdata: + relax_param = jdata['relaxation'] + make_equi(confs, inter_parameter, relax_param) - run_tasks = util.collect_task(all_task,task_type) - forward_files = ['INCAR', 'POTCAR','KPOINTS','KPOINTS'] - backward_files = ['OUTCAR', task_type+'.out' , 'OSZICAR','vasprun.xml'] - common_files=['POSCAR'] - if ('cvasp' in jdata) and (jdata['cvasp'] == True): - mdata['fp_resources']['cvasp'] = True - forward_files.append('cvasp.py') - if len(run_tasks) == 0: return - else: - run_tasks = all_task - disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size) - disp.run_jobs(resources, - command, - work_path, - run_tasks, - group_size, - common_files, - forward_files, - backward_files, - outlog=task_type+'.out', - errlog=task_type+'.err') - #lammps - elif task_type in lammps_task_type: - None - else: - raise RuntimeError ("unknown task %s, something wrong" % task_type) + elif step == 'make' and 'properties' in jdata: + property_list = jdata['properties'] + make_property(confs, inter_parameter, property_list) -def cmpt_phonon(task_type,jdata,mdata): - conf_dir=jdata['conf_dir'] - cwd=os.getcwd() - #vasp - if task_type == "vasp": - cmpt_06_phonon.cmpt_vasp(jdata, conf_dir) - #lammps - elif task_type in lammps_task_type : - cmpt_06_phonon.cmpt_lammps(jdata,conf_dir, task_type) - else : - raise RuntimeError("unknow task ", task_type) - os.chdir(cwd) + elif step == 'run' and 'relaxation' in jdata: + if machine_file is None: + print('Please supply the machine.json, exit now!') + return + run_equi(confs, inter_parameter, mdata) -def run_task (json_file, machine_file) : - with open (json_file, 'r') as fp : - jdata = json.load (fp) - with open (machine_file, 'r') as fp: - mdata = json.load (fp) + elif step == 'run' and 'properties' in jdata: + if machine_file is None: + print('Please supply the machine.json, exit now!') + return + property_list = jdata['properties'] + run_property(confs, inter_parameter, property_list, mdata) - record = "record.auto_test" + elif step == 'post' and 'relaxation' in jdata: + post_equi(confs, inter_parameter) - confs = jdata['conf_dir'] - ele_list=[key for key in jdata['potcar_map'].keys()] - key_id = jdata['key_id'] + elif step == 'post' and 'properties' in jdata: + property_list = jdata['properties'] + post_property(confs, property_list) - ii = jdata['task_type'] - jj=jdata['task'] - task_list=['equi','eos','elastic','vacancy','interstitial','surf','phonon'] - - if isinstance(jj,str): - if jj=='all': - all_task_list=task_list.copy() - else: - try: - assert jj in task_list - except AssertionError: - raise RuntimeError ("unknow task %s, something wrong" % jj) - all_task_list=[jj] - elif isinstance(jj,list): - try: - assert set(jj).issubset(set(task_list)) - except AssertionError: - raise RuntimeError ("unknow task %s, some tasks may not supported" % ' '.join(jj)) - all_task_list=jj.copy() else: - raise RuntimeError ('unknow format for task, it must be a string or list') - - task_type_list=['vasp']+lammps_task_type - #if jj not in task_list : - # raise RuntimeError ("unknow task %s, something wrong" % jj) - if ii not in task_type_list : - raise RuntimeError ("unknow task type %s, something wrong" % ii) - - #gen_configuration - if 'confs' in confs and (not os.path.exists(confs+'/POSCAR')) : - print('generate %s' % (ele_list)) - if len(ele_list) == 1 : - gen_confs.gen_element(ele_list[0],key_id) - else : - gen_confs.gen_alloy(ele_list,key_id) - #default task - # log_iter ("gen_equi", ii, "equi") - # gen_equi (ii, jdata, mdata) - # log_iter ("run_equi", ii, "equi") - # run_equi (ii, jdata, mdata) - # log_iter ("cmpt_equi", ii,"equi") - # cmpt_equi (ii, jdata, mdata) - for jj in all_task_list: - if jj == "equi": - log_iter ("gen_equi", ii, "equi") - gen_equi (ii, jdata, mdata) - log_iter ("run_equi", ii, "equi") - run_equi (ii, jdata, mdata) - log_iter ("cmpt_equi", ii,"equi") - cmpt_equi (ii, jdata, mdata) - if jj == "eos": - log_iter ("gen_eos", ii, "eos") - gen_eos (ii, jdata, mdata) - log_iter ("run_eos", ii, "eos") - run_eos (ii, jdata, mdata) - log_iter ("cmpt_eos", ii, "eos") - cmpt_eos (ii, jdata, mdata) - if jj=="elastic": - log_iter ("gen_elastic", ii, "elastic") - gen_elastic (ii, jdata, mdata) - log_iter ("run_elastic", ii, "elastic") - run_elastic (ii, jdata, mdata) - log_iter ("cmpt_elastic", ii, "elastic") - cmpt_elastic (ii, jdata, mdata) - if jj=="vacancy": - log_iter ("gen_vacancy", ii, "vacancy") - gen_vacancy (ii, jdata, mdata) - log_iter ("run_vacancy", ii, "vacancy") - run_vacancy (ii, jdata, mdata) - log_iter ("cmpt_vacancy", ii, "vacancy") - cmpt_vacancy (ii, jdata, mdata) - if jj=="interstitial": - log_iter ("gen_interstitial", ii, "interstitial") - gen_interstitial (ii, jdata, mdata) - log_iter ("run_interstitial", ii, "interstitial") - run_interstitial (ii, jdata, mdata) - log_iter ("cmpt_interstitial", ii, "interstitial") - cmpt_interstitial (ii, jdata, mdata) - if jj=="surf": - log_iter ("gen_surf", ii, "surf") - gen_surf (ii, jdata, mdata) - log_iter ("run_surf", ii, "surf") - run_surf (ii, jdata, mdata) - log_iter ("cmpt_surf", ii, "surf") - cmpt_surf (ii, jdata, mdata) - - # if jj=="phonon": - # log_iter ("gen_phonon", ii, "phonon") - # gen_phonon (ii, jdata, mdata) - # log_iter ("run_phonon", ii, "phonon") - # run_phonon (ii, jdata, mdata) - # log_iter ("cmpt_phonon", ii, "phonon") - # cmpt_phonon (ii, jdata, mdata) - - record_iter (record, confs, ii, jj) + raise RuntimeError('unknown tasks') def gen_test(args): - logging.info ("start auto-testing") - run_task (args.PARAM, args.MACHINE) - logging.info ("finished!") - - -def _main () : - parser = argparse.ArgumentParser() - parser.add_argument("PARAM", type=str, - help="The parameters of the generator") - parser.add_argument("MACHINE", type=str, - help="The settings of the machine running the generator") - args = parser.parse_args() + dlog.info("start auto-testing") + if args.debug: + dlog.setLevel(logging.DEBUG) + run_task(args.TASK, args.PARAM, args.MACHINE) + dlog.info("finished!") - logging.basicConfig (level=logging.INFO, format='%(asctime)s %(message)s') - # logging.basicConfig (filename="compute_string.log", filemode="a", level=logging.INFO, format='%(asctime)s %(message)s') - logging.getLogger("paramiko").setLevel(logging.WARNING) - logging.info ("start auto-testing") - run_task (args.PARAM, args.MACHINE) - logging.info ("finished!") -if __name__ == '__main__': - _main() diff --git a/dpgen/auto_test/workspace.py b/dpgen/auto_test/workspace.py deleted file mode 100755 index 2840f47e1..000000000 --- a/dpgen/auto_test/workspace.py +++ /dev/null @@ -1,70 +0,0 @@ -#!/usr/bin/env python3 - -import glob, os, shutil - -def copy(kspacing, static = False) : - test_dir = os.path.abspath(os.path.dirname(__file__)) - if static : - vasp_name = 'vasp-static-k%.2f' % kspacing - else : - vasp_name = 'vasp-k%.2f' % kspacing - meam_name = 'meam' - confs = glob.glob(os.path.join(test_dir, "confs")) - params = glob.glob(os.path.join(test_dir, "param.json")) - cmpts = glob.glob(os.path.join(test_dir, "cmpt_*.py")) - gens = glob.glob(os.path.join(test_dir, "gen_*.py")) - vasp = glob.glob(os.path.join(test_dir, "0*/*/*/" + vasp_name)) - meam = glob.glob(os.path.join(test_dir, "0*/*/*/" + meam_name)) + \ - glob.glob(os.path.join(test_dir, "0*/*/*/" + meam_name + '-static')) + \ - glob.glob(os.path.join(test_dir, "0*/*/*/" + meam_name + '-reprod-k0.08')) - cwd = os.getcwd() - os.chdir(test_dir) - vasp_dirs = glob.glob( "0*/*/*/" + vasp_name) - meam_dirs = glob.glob( "0*/*/*/" + meam_name) + \ - glob.glob( "0*/*/*/" + meam_name + '-static') + \ - glob.glob( "0*/*/*/" + meam_name + '-reprod-k0.16') - os.chdir(cwd) - for res,ii in zip(vasp,vasp_dirs) : - dir_ii = os.path.dirname(ii) - os.makedirs(dir_ii, exist_ok = True) - os.chdir(dir_ii) - if os.path.islink(vasp_name) : - os.remove(vasp_name) - os.symlink(os.path.relpath(res), vasp_name) - os.chdir(cwd) - - for res,ii in zip(meam,meam_dirs) : - dir_ii = os.path.dirname(ii) - os.makedirs(dir_ii, exist_ok = True) - os.chdir(dir_ii) - tmp_name = os.path.basename(res) - if os.path.islink(tmp_name) : - os.remove(tmp_name) - os.symlink(os.path.relpath(res), tmp_name) - os.chdir(cwd) - - os.makedirs('results', exist_ok = True) - for ii in cmpts : - fname_ii = os.path.basename(ii) - if os.path.islink(fname_ii) : - os.remove(fname_ii) - os.symlink(os.path.relpath(ii), fname_ii) - for ii in gens : - fname_ii = os.path.basename(ii) - if os.path.islink(fname_ii) : - os.remove(fname_ii) - os.symlink(os.path.relpath(ii), fname_ii) - for ii in confs : - fname_ii = os.path.basename(ii) - if os.path.islink(fname_ii) : - os.remove(fname_ii) - os.symlink(os.path.relpath(ii), fname_ii) - for ii in params : - fname_ii = os.path.basename(ii) - if os.path.isfile(fname_ii) : - os.remove(fname_ii) - shutil.copy2(os.path.relpath(ii), fname_ii) - -copy(0.08) -copy(0.08, static = True) -copy(0.16) diff --git a/dpgen/collect/collect.py b/dpgen/collect/collect.py index a8d5b4060..25f96c23b 100644 --- a/dpgen/collect/collect.py +++ b/dpgen/collect/collect.py @@ -80,6 +80,7 @@ def collect_data(target_folder, param_file, output, out_dir = 'sys.%s' % kk nframes = coll_data[kk].get_nframes() coll_data[kk].to('deepmd/npy', os.path.join(output, out_dir), set_size = nframes) + # coll_data[kk].to('deepmd/npy', os.path.join(output, out_dir)) def gen_collect(args): collect_data(args.JOB_DIR, args.parameter, args.OUTPUT, diff --git a/dpgen/dispatcher/ALI.py b/dpgen/dispatcher/ALI.py index 566f1ca37..ef68322be 100644 --- a/dpgen/dispatcher/ALI.py +++ b/dpgen/dispatcher/ALI.py @@ -127,10 +127,8 @@ def delete(self, ii): sys.exit() def update(self): - if len(self.server_pool) == 0: - self.server_pool = self.get_server_pool() - self.ip_pool = self.get_ip(self.server_pool) - else: pass + self.server_pool = self.get_server_pool() + self.ip_pool = self.get_ip(self.server_pool) # Derivate def catch_dispatcher_exception(self, ii): @@ -303,6 +301,9 @@ def create_template(self, image_id, sg_id, vpc_id): request.set_ImageId(image_id) request.set_ImageOwnerAlias("self") request.set_PasswordInherit(True) + if "address" in self.cloud_resources and self.cloud_resources['address'] == "public": + request.set_InternetMaxBandwidthIn(100) + request.set_InternetMaxBandwidthOut(100) request.set_InstanceType("ecs.c6.large") request.set_InstanceName(self.cloud_resources["instance_name"]) request.set_SecurityGroupId(sg_id) @@ -344,21 +345,31 @@ def get_image_id(self, img_name): request = DescribeImagesRequest() request.set_accept_format('json') request.set_ImageOwnerAlias("self") - request.set_PageSize(100) - count = 0 - flag = 0 - while count < 10: - try: - response = self.client.do_action_with_exception(request) - response = json.loads(response) - for img in response["Images"]["Image"]: - if img["ImageName"] == img_name: - return img["ImageId"] - flag = 1 - break - except: - count += 1 - time.sleep(10) + request.set_PageSize(20) + response = self.client.do_action_with_exception(request) + response = json.loads(response) + totalcount = response["TotalCount"] + + iteration = totalcount // 20 + if iteration * 20 < totalcount: + iteration += 1 + + for ii in range(1, iteration+1): + count = 0 + flag = 0 + request.set_PageNumber(ii) + while count < 10: + try: + response = self.client.do_action_with_exception(request) + response = json.loads(response) + for img in response["Images"]["Image"]: + if img["ImageName"] == img_name: + return img["ImageId"] + flag = 1 + break + except: + count += 1 + time.sleep(10) if not flag: dlog.info("get image failed, exit") sys.exit() @@ -458,7 +469,10 @@ def get_ip(self, instance_list): request.set_InstanceIds([instance_list[i]]) response = self.client.do_action_with_exception(request) response = json.loads(response) - ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) + if "address" in self.cloud_resources and self.cloud_resources['address'] == "public": + ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) + else: + ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) # ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) else: iteration = len(instance_list) // 10 @@ -467,15 +481,19 @@ def get_ip(self, instance_list): request.set_InstanceIds([instance_list[i*10+j]]) response = self.client.do_action_with_exception(request) response = json.loads(response) - ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) - # ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) + if "address" in self.cloud_resources and self.cloud_resources['address'] == "public": + ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) + else: + ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) if len(instance_list) - iteration * 10 != 0: for j in range(len(instance_list) - iteration * 10): request.set_InstanceIds([instance_list[iteration*10+j]]) response = self.client.do_action_with_exception(request) response = json.loads(response) - ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) - # ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) + if "address" in self.cloud_resources and self.cloud_resources['address'] == "public": + ip_list.append(response["Instances"]["Instance"][0]["PublicIpAddress"]["IpAddress"][0]) + else: + ip_list.append(response["Instances"]["Instance"][0]["VpcAttributes"]["PrivateIpAddress"]['IpAddress'][0]) return ip_list except: return [] diff --git a/dpgen/dispatcher/DispatcherList.py b/dpgen/dispatcher/DispatcherList.py index 347144d1e..ba72b7bd2 100644 --- a/dpgen/dispatcher/DispatcherList.py +++ b/dpgen/dispatcher/DispatcherList.py @@ -16,6 +16,8 @@ def __init__(self, mdata_machine, mdata_resources, work_path, run_tasks, group_s self.task_chunks = _split_tasks(run_tasks, group_size) self.nchunks = len(self.task_chunks) self.nchunks_limit = int(self.mdata_machine.get("machine_upper_bound", self.nchunks)) + if(self.nchunks_limit > self.nchunks): + self.nchunks_limit = self.nchunks self.work_path = work_path self.cloud_resources = cloud_resources self.server_pool = [] @@ -49,6 +51,7 @@ def run_jobs(self, self.clean() break self.exception_handling(ratio_failure) + jj = self.nchunks - 1 for ii in range(self.nchunks): dispatcher_status = self.check_dispatcher_status(ii) if dispatcher_status == "unsubmitted": @@ -72,17 +75,54 @@ def run_jobs(self, entity = self.dispatcher_list[ii]["entity"] status_list = [item["dispatcher_status"] for item in self.dispatcher_list] flag = "unallocated" in status_list - if not flag: self.delete(ii) + if not flag: + self.delete(ii) + self.dispatcher_list[ii]["entity"] = None else: self.dispatcher_list[ii]["entity"] = None self.server_pool.append(entity.instance_id) self.ip_pool.append(entity.ip) + while(jj>=ii): + if(self.dispatcher_list[jj]["dispatcher_status"] == "unallocated"): + self.create(jj) + if(self.dispatcher_list[jj]["dispatcher_status"] == "unsubmitted"): + dlog.info(self.dispatcher_list[jj]["entity"].ip) + self.dispatcher_list[jj]["entity"].job_handler = self.dispatcher_list[jj]["dispatcher"].submit_jobs(resources, + command, + work_path, + self.task_chunks[jj], + group_size, + forward_common_files, + forward_task_files, + backward_task_files, + forward_task_deference, + outlog, + errlog) + self.dispatcher_list[jj]["entity"].job_record = self.dispatcher_list[jj]["entity"].job_handler["job_record"] + self.dispatcher_list[jj]["dispatcher_status"] = "running" + break + jj -=1 elif dispatcher_status == "running": pass elif dispatcher_status == "unallocated": # if len(server_pool) > 0: make_dispatcher # else: pass self.create(ii) + if self.dispatcher_list[ii]["dispatcher_status"] == "unsubmitted": + dlog.info(self.dispatcher_list[ii]["entity"].ip) + self.dispatcher_list[ii]["entity"].job_handler = self.dispatcher_list[ii]["dispatcher"].submit_jobs(resources, + command, + work_path, + self.task_chunks[ii], + group_size, + forward_common_files, + forward_task_files, + backward_task_files, + forward_task_deference, + outlog, + errlog) + self.dispatcher_list[ii]["entity"].job_record = self.dispatcher_list[ii]["entity"].job_handler["job_record"] + self.dispatcher_list[ii]["dispatcher_status"] = "running" elif dispatcher_status == "terminated": pass self.update() diff --git a/dpgen/dispatcher/LSF.py b/dpgen/dispatcher/LSF.py index 97ae8f17e..b28b4eec3 100644 --- a/dpgen/dispatcher/LSF.py +++ b/dpgen/dispatcher/LSF.py @@ -108,7 +108,7 @@ def sub_script_head(self, res): if res['node_cpu']: ret += '#BSUB -R span[ptile=%d]\n' % res['node_cpu'] if res.get('new_lsf_gpu', False): - # supportted in LSF >= 10.1.0 SP6 + # supported in LSF >= 10.1.0 SP6 # ref: https://www.ibm.com/support/knowledgecenter/en/SSWRJV_10.1.0/lsf_resource_sharing/use_gpu_res_reqs.html ret += '#BSUB -n %d\n#BSUB -gpu "num=%d:mode=shared:j_exclusive=yes"\n' % ( res['numb_gpu'], res['task_per_node']) @@ -123,6 +123,13 @@ def sub_script_head(self, res): ret += '#BSUB -J %s\n' % (res['job_name'] if 'job_name' in res else 'dpgen') if len(res['partition']) > 0 : ret += '#BSUB -q %s\n' % res['partition'] + if len(res['exclude_list']) > 0: + ret += '#BSUB -R "select[' + temp_exclude = [] + for ii in res['exclude_list']: + temp_exclude.append('hname != %s' % ii) + ret += ' && '.join(temp_exclude) + ret += ']"\n' ret += "\n" for ii in res['module_unload_list'] : ret += "module unload %s\n" % ii diff --git a/dpgen/dispatcher/LazyLocalContext.py b/dpgen/dispatcher/LazyLocalContext.py index 0f79a8161..b93c58de1 100644 --- a/dpgen/dispatcher/LazyLocalContext.py +++ b/dpgen/dispatcher/LazyLocalContext.py @@ -127,7 +127,7 @@ def get_return(self, proc): o, e = proc.communicate() stdout = SPRetObj(o) stderr = SPRetObj(e) - except: + except ValueError: stdout = None stderr = None return ret, stdout, stderr diff --git a/dpgen/dispatcher/LocalContext.py b/dpgen/dispatcher/LocalContext.py index 373f112c7..4c341f7aa 100644 --- a/dpgen/dispatcher/LocalContext.py +++ b/dpgen/dispatcher/LocalContext.py @@ -196,7 +196,7 @@ def get_return(self, proc): o, e = proc.communicate() stdout = SPRetObj(o) stderr = SPRetObj(e) - except: + except ValueError: stdout = None stderr = None return ret, stdout, stderr diff --git a/dpgen/dispatcher/SSHContext.py b/dpgen/dispatcher/SSHContext.py index a6ac3c1d4..552315358 100644 --- a/dpgen/dispatcher/SSHContext.py +++ b/dpgen/dispatcher/SSHContext.py @@ -13,15 +13,19 @@ def __init__ (self, jdata) : self.remote_host = self.remote_profile['hostname'] self.remote_uname = self.remote_profile['username'] self.remote_port = self.remote_profile.get('port', 22) - self.remote_password = None - if 'password' in self.remote_profile : - self.remote_password = self.remote_profile['password'] + self.remote_password = self.remote_profile.get('password', None) + self.local_key_filename = self.remote_profile.get('key_filename', None) + self.remote_timeout = self.remote_profile.get('timeout', None) + self.local_key_passphrase = self.remote_profile.get('passphrase', None) self.remote_workpath = self.remote_profile['work_path'] self.ssh = None - self._setup_ssh(self.remote_host, - self.remote_port, + self._setup_ssh(hostname=self.remote_host, + port=self.remote_port, username=self.remote_uname, - password=self.remote_password) + password=self.remote_password, + key_filename=self.local_key_filename, + timeout=self.remote_timeout, + passphrase=self.local_key_passphrase) def ensure_alive(self, max_check = 10, @@ -32,12 +36,15 @@ def ensure_alive(self, raise RuntimeError('cannot connect ssh after %d failures at interval %d s' % (max_check, sleep_time)) dlog.info('connection check failed, try to reconnect to ' + self.remote_host) - self._setup_ssh(self.remote_host, - self.remote_port, + self._setup_ssh(hostname=self.remote_host, + port=self.remote_port, username=self.remote_uname, - password=self.remote_password) + password=self.remote_password, + key_filename=self.local_key_filename, + timeout=self.remote_timeout, + passphrase=self.local_key_passphrase) count += 1 - time.sleep(sleep) + time.sleep(sleep_time) def _check_alive(self): if self.ssh == None: @@ -51,13 +58,18 @@ def _check_alive(self): def _setup_ssh(self, hostname, - port, - username = None, - password = None): - self.ssh = paramiko.SSHClient() - # ssh_client.load_system_host_keys() + port=22, + username=None, + password=None, + key_filename=None, + timeout=None, + passphrase=None): + self.ssh = paramiko.SSHClient() + # ssh_client.load_system_host_keys() self.ssh.set_missing_host_key_policy(paramiko.WarningPolicy) - self.ssh.connect(hostname, port=port, username=username, password=password) + self.ssh.connect(hostname=hostname, port=port, + username=username, password=password, + key_filename=key_filename, timeout=timeout, passphrase=passphrase) assert(self.ssh.get_transport().is_active()) transport = self.ssh.get_transport() transport.set_keepalive(60) @@ -148,19 +160,11 @@ def download(self, os.chdir(cwd) def block_checkcall(self, - cmd, - retry=0) : + cmd) : self.ssh_session.ensure_alive() stdin, stdout, stderr = self.ssh.exec_command(('cd %s ;' % self.remote_root) + cmd) exit_status = stdout.channel.recv_exit_status() if exit_status != 0: - if retry<3: - # sleep 60 s - dlog.warning("Get error code %d in calling %s through ssh with job: %s . message: %s" % - (exit_status, cmd, self.job_uuid, stderr.read().decode('utf-8'))) - dlog.warning("Sleep 60 s and retry the command...") - time.sleep(60) - return self.block_checkcall(cmd, retry=retry+1) raise RuntimeError("Get error code %d in calling %s through ssh with job: %s . message: %s" % (exit_status, cmd, self.job_uuid, stderr.read().decode('utf-8'))) return stdin, stdout, stderr diff --git a/dpgen/dispatcher/Slurm.py b/dpgen/dispatcher/Slurm.py index 9d409dbcc..67f29fca8 100644 --- a/dpgen/dispatcher/Slurm.py +++ b/dpgen/dispatcher/Slurm.py @@ -81,6 +81,9 @@ def sub_script_head(self, res): ret += "#SBATCH -t %s\n" % res['time_limit'] if res['mem_limit'] > 0 : ret += "#SBATCH --mem=%dG \n" % res['mem_limit'] + if 'job_name' in res: + if len(res['job_name']) > 0: + ret += '#SBATCH --job-name=%s\n' % res['job_name'] if len(res['account']) > 0 : ret += "#SBATCH --account=%s \n" % res['account'] if len(res['partition']) > 0 : @@ -149,7 +152,7 @@ def _get_job_id(self) : else: return "" - def _check_status_inner(self, job_id, retry=0): + def _check_status_inner(self, job_id): ret, stdin, stdout, stderr\ = self.context.block_call ('squeue -o "%.18i %.2t" -j ' + job_id) if (ret != 0) : @@ -160,11 +163,6 @@ def _check_status_inner(self, job_id, retry=0): else : return JobStatus.terminated else : - # retry 3 times - if retry < 3: - # rest 60s - time.sleep(60) - return self._check_status_inner(job_id, retry=retry+1) raise RuntimeError\ ("status command squeue fails to execute\nerror message:%s\nreturn code %d\n" % (err_str, ret)) status_line = stdout.read().decode('utf-8').split ('\n')[-2] diff --git a/dpgen/generator/lib/cp2k.py b/dpgen/generator/lib/cp2k.py index e3dc0266b..368671a50 100644 --- a/dpgen/generator/lib/cp2k.py +++ b/dpgen/generator/lib/cp2k.py @@ -183,4 +183,35 @@ def make_cp2k_xyz(sys_data): +def make_cp2k_input_from_external(sys_data, exinput_path): + # read the input content as string + with open(exinput_path, 'r') as f: + exinput = f.readlines() + + # find the ABC cell string + for line_idx, line in enumerate(exinput): + if 'ABC' in line: + delete_cell_idx = line_idx + delete_cell_line = line + + # remove the useless CELL line + exinput.remove(delete_cell_line) + + # insert the cell information + # covert cell to cell string + cell = sys_data['cells'][0] + cell = np.reshape(cell, [3,3]) + cell_a = np.array2string(cell[0,:]) + cell_a = cell_a[1:-1] + cell_b = np.array2string(cell[1,:]) + cell_b = cell_b[1:-1] + cell_c = np.array2string(cell[2,:]) + cell_c = cell_c[1:-1] + + exinput.insert(delete_cell_idx, 'A ' + cell_a + '\n') + exinput.insert(delete_cell_idx+1, 'B ' + cell_b + '\n') + exinput.insert(delete_cell_idx+2, 'C ' + cell_c + '\n') + + return ''.join(exinput) + diff --git a/dpgen/generator/lib/lammps.py b/dpgen/generator/lib/lammps.py index 95dcb8568..8221f249d 100644 --- a/dpgen/generator/lib/lammps.py +++ b/dpgen/generator/lib/lammps.py @@ -61,7 +61,7 @@ def make_lammps_input(ensemble, ret+= "neigh_modify delay %d\n" % neidelay ret+= "\n" ret+= "box tilt large\n" - ret+= "read_data %s\n" % conf_file + ret+= "if \"${restart} > 0\" then \"read_restart dpgen.restart.*\" else \"read_data %s\"\n" % conf_file ret+= "change_box all triclinic\n" for jj in range(len(mass_map)) : ret+= "mass %d %f\n" %(jj+1, mass_map[jj]) @@ -89,9 +89,10 @@ def make_lammps_input(ensemble, ret+= "thermo_style custom step temp pe ke etotal press vol lx ly lz xy xz yz\n" ret+= "thermo ${THERMO_FREQ}\n" ret+= "dump 1 all custom ${DUMP_FREQ} traj/*.lammpstrj id type x y z\n" + ret+= "restart 10000 dpgen.restart\n" ret+= "\n" if pka_e is None : - ret+= "velocity all create ${TEMP} %d" % (random.randrange(max_seed-1)+1) + ret+= "if \"${restart} == 0\" then \"velocity all create ${TEMP} %d\"" % (random.randrange(max_seed-1)+1) else : sys = dpdata.System(conf_file, fmt = 'lammps/lmp') sys_data = sys.data @@ -103,7 +104,7 @@ def make_lammps_input(ensemble, pka_vec = _sample_sphere() pka_vec *= pka_vn ret+= 'group first id 1\n' - ret+= 'velocity first set %f %f %f\n' % (pka_vec[0], pka_vec[1], pka_vec[2]) + ret+= 'if \"${restart} == 0\" then \"velocity first set %f %f %f\"\n' % (pka_vec[0], pka_vec[1], pka_vec[2]) ret+= 'fix 2 all momentum 1 linear 1 1 1\n' ret+= "\n" if ensemble.split('-')[0] == 'npt' : @@ -127,7 +128,7 @@ def make_lammps_input(ensemble, ret+= "fix fm all momentum 1 linear 1 1 1\n" ret+= "\n" ret+= "timestep %f\n" % dt - ret+= "run ${NSTEPS}\n" + ret+= "run ${NSTEPS} upto\n" return ret # ret = make_lammps_input ("npt", "al.lmp", ['graph.000.pb', 'graph.001.pb'], 20000, 20, [27], 1000, pres = 1.0) diff --git a/dpgen/generator/run.py b/dpgen/generator/run.py index 728466440..4af67fdbf 100644 --- a/dpgen/generator/run.py +++ b/dpgen/generator/run.py @@ -50,7 +50,7 @@ from dpgen.generator.lib.pwmat import input_upper from dpgen.generator.lib.siesta import make_siesta_input from dpgen.generator.lib.gaussian import make_gaussian_input, take_cluster -from dpgen.generator.lib.cp2k import make_cp2k_input, make_cp2k_xyz +from dpgen.generator.lib.cp2k import make_cp2k_input, make_cp2k_input_from_external, make_cp2k_xyz from dpgen.generator.lib.ele_temp import NBandsEsti from dpgen.remote.RemoteJob import SSHSession, JobStatus, SlurmJob, PBSJob, LSFJob, CloudMachineJob, awsMachineJob from dpgen.remote.group_jobs import ucloud_submit_jobs, aws_submit_jobs @@ -193,17 +193,25 @@ def make_train (iter_index, init_data_sys_ = jdata['init_data_sys'] fp_task_min = jdata['fp_task_min'] model_devi_jobs = jdata['model_devi_jobs'] - use_ele_temp = jdata.get('use_ele_temp', 0) + use_ele_temp = jdata.get('use_ele_temp', 0) training_iter0_model = jdata.get('training_iter0_model_path', []) training_init_model = jdata.get('training_init_model', False) training_reuse_iter = jdata.get('training_reuse_iter') - training_reuse_old_ratio = jdata.get('training_reuse_old_ratio', 0.2) + training_reuse_old_ratio = jdata.get('training_reuse_old_ratio', None) training_reuse_stop_batch = jdata.get('training_reuse_stop_batch', 400000) training_reuse_start_lr = jdata.get('training_reuse_start_lr', 1e-4) training_reuse_start_pref_e = jdata.get('training_reuse_start_pref_e', 0.1) training_reuse_start_pref_f = jdata.get('training_reuse_start_pref_f', 100) model_devi_activation_func = jdata.get('model_devi_activation_func', None) + if training_reuse_iter is not None and training_reuse_old_ratio is None: + raise RuntimeError("training_reuse_old_ratio not found but is mandatory when using init-model (training_reuse_iter is detected in param).\n" \ + "It defines the ratio of the old-data picking probability to the all-data(old-data plus new-data) picking probability in training after training_reuse_iter.\n" \ + "Denoting the index of the current iter as N (N >= training_reuse_iter ), old-data refers to those existed before the N-1 iter, and new-data refers to that obtained by the N-1 iter.\n" \ + "A recommended strategy is making the new-to-old ratio close to 10 times of the default value, to reasonably increase the sensitivity of the model to the new-data.\n" \ + "By default, the picking probability of data from one system or one iter is proportional to the number of batches (the number of frames divided by batch_size) of that systems or iter.\n" \ + "Detailed discussion about init-model (in Chinese) please see https://mp.weixin.qq.com/s/qsKMZ0j270YhQKvwXUiFvQ") + if iter_index > 0 and _check_empty_iter(iter_index-1, fp_task_min) : log_task('prev data is empty, copy prev model') copy_model(numb_models, iter_index-1, iter_index) @@ -368,7 +376,7 @@ def make_train (iter_index, if type(training_iter0_model) == str: training_iter0_model = [training_iter0_model] iter0_models = [] - for ii in training_iter0_model: + for ii in training_iter0_model: model_is = glob.glob(ii) model_is.sort() iter0_models += [os.path.abspath(ii) for ii in model_is] @@ -381,7 +389,7 @@ def make_train (iter_index, def _link_old_models(work_path, old_model_files, ii): """ - link the `ii`th old model given by `old_model_files` to + link the `ii`th old model given by `old_model_files` to the `ii`th training task in `work_path` """ task_path = os.path.join(work_path, train_task_fmt % ii) @@ -393,7 +401,7 @@ def _link_old_models(work_path, old_model_files, ii): basejj = os.path.basename(jj) os.chdir(task_old_path) os.symlink(os.path.relpath(absjj), basejj) - os.chdir(cwd) + os.chdir(cwd) def detect_batch_size(batch_size, system=None): @@ -448,8 +456,8 @@ def run_train (iter_index, command = os.path.join(deepmd_path, 'bin/dp_train %s' % train_input_file) commands.append(command) command = os.path.join(deepmd_path, 'bin/dp_frz') - commands.append(command) - else: + commands.append(command) + else: # 1.x ## Commands are like `dp train` and `dp freeze` ## train_command should not be None @@ -476,7 +484,7 @@ def run_train (iter_index, forward_files = [train_input_file] if training_init_model: - forward_files += [os.path.join('old', 'model.ckpt.meta'), + forward_files += [os.path.join('old', 'model.ckpt.meta'), os.path.join('old', 'model.ckpt.index'), os.path.join('old', 'model.ckpt.data-00000-of-00001') ] @@ -613,9 +621,33 @@ def parse_cur_job_revmat(cur_job, use_plm = False): revise_keys.append(ii) revise_values.append(cur_job['rev_mat']['plm'][ii]) revise_matrix = expand_matrix_values(revise_values) - return revise_keys, revise_matrix, n_lmp_keys + return revise_keys, revise_matrix, n_lmp_keys +def parse_cur_job_sys_revmat(cur_job, sys_idx, use_plm=False): + templates = [cur_job['template']['lmp']] + if use_plm: + templates.append(cur_job['template']['plm']) + sys_revise_keys = [] + sys_revise_values = [] + if 'sys_rev_mat' not in cur_job.keys(): + cur_job['sys_rev_mat'] = {} + local_rev = cur_job['sys_rev_mat'].get(str(sys_idx), {}) + if 'lmp' not in local_rev.keys(): + local_rev['lmp'] = {} + for ii in local_rev['lmp'].keys(): + sys_revise_keys.append(ii) + sys_revise_values.append(local_rev['lmp'][ii]) + n_sys_lmp_keys = len(sys_revise_keys) + if use_plm: + if 'plm' not in local_rev.keys(): + local_rev['plm'] = {} + for ii in local_rev['plm'].keys(): + sys_revise_keys.append(ii) + sys_revise_values.append(local_rev['plm'][ii]) + sys_revise_matrix = expand_matrix_values(sys_revise_values) + return sys_revise_keys, sys_revise_matrix, n_sys_lmp_keys + def find_only_one_key(lmp_lines, key): found = [] for idx in range(len(lmp_lines)): @@ -633,7 +665,7 @@ def find_only_one_key(lmp_lines, key): def revise_lmp_input_model(lmp_lines, task_model_list, trj_freq, deepmd_version = '1'): idx = find_only_one_key(lmp_lines, ['pair_style', 'deepmd']) graph_list = ' '.join(task_model_list) - if LooseVersion(deepmd_version) < LooseVersion('1'): + if LooseVersion(deepmd_version) < LooseVersion('1'): lmp_lines[idx] = "pair_style deepmd %s %d model_devi.out\n" % (graph_list, trj_freq) else: lmp_lines[idx] = "pair_style deepmd %s out_freq %d out_file model_devi.out\n" % (graph_list, trj_freq) @@ -644,13 +676,13 @@ def revise_lmp_input_dump(lmp_lines, trj_freq): idx = find_only_one_key(lmp_lines, ['dump', 'dpgen_dump']) lmp_lines[idx] = "dump dpgen_dump all custom %d traj/*.lammpstrj id type x y z\n" % trj_freq return lmp_lines - + def revise_lmp_input_plm(lmp_lines, in_plm, out_plm = 'output.plumed'): idx = find_only_one_key(lmp_lines, ['fix', 'dpgen_plm']) lmp_lines[idx] = "fix dpgen_plm all plumed plumedfile %s outfile %s\n" % (in_plm, out_plm) return lmp_lines - + def revise_by_keys(lmp_lines, keys, values): for kk,vv in zip(keys, values): @@ -747,7 +779,7 @@ def _make_model_devi_revmat(iter_index, jdata, mdata, conf_systems): model_devi_jobs = jdata['model_devi_jobs'] if (iter_index >= len(model_devi_jobs)) : return False - cur_job = model_devi_jobs[iter_index] + cur_job = model_devi_jobs[iter_index] sys_idx = expand_idx(cur_job['sys_idx']) if (len(sys_idx) != len(list(set(sys_idx)))) : raise RuntimeError("system index should be uniq") @@ -761,10 +793,10 @@ def _make_model_devi_revmat(iter_index, jdata, mdata, conf_systems): lmp_templ = os.path.abspath(lmp_templ) if use_plm: plm_templ = cur_job['template']['plm'] - plm_templ = os.path.abspath(plm_templ) + plm_templ = os.path.abspath(plm_templ) if use_plm_path: plm_path_templ = cur_job['template']['plm_path'] - plm_path_templ = os.path.abspath(plm_path_templ) + plm_path_templ = os.path.abspath(plm_path_templ) iter_name = make_iter_name(iter_index) train_path = os.path.join(iter_name, train_name) @@ -785,8 +817,30 @@ def _make_model_devi_revmat(iter_index, jdata, mdata, conf_systems): conf_counter = 0 task_counter = 0 for cc in ss : - for ii in range(len(rev_mat)): - rev_item = rev_mat[ii] + sys_rev = cur_job.get('sys_rev_mat', None) + total_rev_keys = rev_keys + total_rev_mat = rev_mat + total_num_lmp = num_lmp + if sys_rev is not None: + total_rev_mat = [] + sys_rev_keys, sys_rev_mat, sys_num_lmp = parse_cur_job_sys_revmat(cur_job, + sys_idx=sys_idx[sys_counter], + use_plm=use_plm) + _lmp_keys = rev_keys[:num_lmp] + sys_rev_keys[:sys_num_lmp] + if use_plm: + _plm_keys = rev_keys[num_lmp:] + sys_rev_keys[sys_num_lmp:] + _lmp_keys += _plm_keys + total_rev_keys = _lmp_keys + total_num_lmp = num_lmp + sys_num_lmp + for pub in rev_mat: + for pri in sys_rev_mat: + _lmp_mat = pub[:num_lmp] + pri[:sys_num_lmp] + if use_plm: + _plm_mat = pub[num_lmp:] + pri[sys_num_lmp:] + _lmp_mat += _plm_mat + total_rev_mat.append(_lmp_mat) + for ii in range(len(total_rev_mat)): + total_rev_item = total_rev_mat[ii] task_name = make_model_devi_task_name(sys_idx[sys_counter], task_counter) conf_name = make_model_devi_conf_name(sys_idx[sys_counter], conf_counter) + '.lmp' task_path = os.path.join(work_path, task_name) @@ -799,21 +853,27 @@ def _make_model_devi_revmat(iter_index, jdata, mdata, conf_systems): os.path.join(task_path, loc_conf_name) ) cwd_ = os.getcwd() # chdir to task path - os.chdir(task_path) + os.chdir(task_path) shutil.copyfile(lmp_templ, 'input.lammps') # revise input of lammps with open('input.lammps') as fp: lmp_lines = fp.readlines() lmp_lines = revise_lmp_input_model(lmp_lines, task_model_list, trj_freq, deepmd_version = deepmd_version) lmp_lines = revise_lmp_input_dump(lmp_lines, trj_freq) - lmp_lines = revise_by_keys(lmp_lines, rev_keys[:num_lmp], rev_item[:num_lmp]) + lmp_lines = revise_by_keys( + lmp_lines, total_rev_keys[:total_num_lmp], total_rev_item[:total_num_lmp] + ) # revise input of plumed if use_plm: lmp_lines = revise_lmp_input_plm(lmp_lines, 'input.plumed') shutil.copyfile(plm_templ, 'input.plumed') with open('input.plumed') as fp: plm_lines = fp.readlines() - plm_lines = revise_by_keys(plm_lines, rev_keys[num_lmp:], rev_item[num_lmp:]) + # allow using the same list as lmp + # user should not use the same key name for plm + plm_lines = revise_by_keys( + plm_lines, total_rev_keys, total_rev_item + ) with open('input.plumed', 'w') as fp: fp.write(''.join(plm_lines)) if use_plm_path: @@ -823,12 +883,12 @@ def _make_model_devi_revmat(iter_index, jdata, mdata, conf_systems): fp.write(''.join(lmp_lines)) with open('job.json', 'w') as fp: job = {} - for ii,jj in zip(rev_keys, rev_item) : job[ii] = jj + for ii,jj in zip(total_rev_keys, total_rev_item) : job[ii] = jj json.dump(job, fp, indent = 4) os.chdir(cwd_) task_counter += 1 conf_counter += 1 - sys_counter += 1 + sys_counter += 1 def _make_model_devi_native(iter_index, jdata, mdata, conf_systems): @@ -838,7 +898,7 @@ def _make_model_devi_native(iter_index, jdata, mdata, conf_systems): cur_job = model_devi_jobs[iter_index] ensemble, nsteps, trj_freq, temps, press, pka_e, dt = parse_cur_job(cur_job) if dt is not None : - model_devi_dt = dt + model_devi_dt = dt sys_idx = expand_idx(cur_job['sys_idx']) if (len(sys_idx) != len(list(set(sys_idx)))) : raise RuntimeError("system index should be uniq") @@ -964,12 +1024,12 @@ def run_model_devi (iter_index, all_task = glob.glob(os.path.join(work_path, "task.*")) all_task.sort() - command = lmp_exec + " -i input.lammps" + command = "{ if [ ! -f dpgen.restart.10000 ]; then %s -i input.lammps -v restart 0; else %s -i input.lammps -v restart 1; fi }" % (lmp_exec, lmp_exec) commands = [command] fp = open (os.path.join(work_path, 'cur_job.json'), 'r') cur_job = json.load (fp) - + run_tasks_ = all_task # for ii in all_task: # fres = os.path.join(ii, 'model_devi.out') @@ -1021,10 +1081,10 @@ def _to_face_dist(box_): for [ii,jj] in [[0, 1], [1, 2], [2, 0]]: vv = np.cross(box[ii], box[jj]) dists.append(vol / np.linalg.norm(vv)) - return np.array(dists) + return np.array(dists) -def check_cluster(conf_name, - fp_cluster_vacuum, +def check_cluster(conf_name, + fp_cluster_vacuum, fmt='lammps/dump'): sys = dpdata.System(conf_name, fmt) assert(sys.get_nframes() == 1) @@ -1036,16 +1096,16 @@ def check_cluster(conf_name, a,b,c=map(norm,[cell[0,:],cell[1,:],cell[2,:]]) min_vac=min([a-xlim,b-ylim,c-zlim]) #print([a-xlim,b-ylim,c-zlim]) - #_,r3d=miniball.get_bounding_ball(coord) - + #_,r3d=miniball.get_bounding_ball(coord) + if min_vac < fp_cluster_vacuum: is_bad = True else: is_bad = False return is_bad -def check_bad_box(conf_name, - criteria, +def check_bad_box(conf_name, + criteria, fmt = 'lammps/dump'): all_c = criteria.split(';') sys = dpdata.System(conf_name, fmt) @@ -1063,9 +1123,9 @@ def check_bad_box(conf_name, dists = _to_face_dist(sys['cells'][0]) ratio = np.max(lengths) / np.min(dists) if ratio > float(value): - is_bad = True + is_bad = True else: - raise RuntimeError('unknow key', key) + raise RuntimeError('unknow key', key) return is_bad def _make_fp_vasp_inner (modd_path, @@ -1103,7 +1163,7 @@ def _make_fp_vasp_inner (modd_path, detailed_report_make_fp = jdata.get("detailed_report_make_fp", True) # skip bad box criteria skip_bad_box = jdata.get('fp_skip_bad_box') - # skip discrete structure in cluster + # skip discrete structure in cluster fp_cluster_vacuum = jdata.get('fp_cluster_vacuum',None) for ss in system_index : fp_candidate = [] @@ -1210,7 +1270,7 @@ def _make_fp_vasp_inner (modd_path, if skip_cluster: count_bad_cluster +=1 continue - + # link job.json job_name = os.path.join(tt, "job.json") job_name = os.path.abspath(job_name) @@ -1247,7 +1307,7 @@ def _make_fp_vasp_inner (modd_path, dump_to_poscar('conf.dump', 'POSCAR', type_map) os.chdir(cwd) return fp_tasks - + def make_vasp_incar(jdata, filename): if 'fp_incar' in jdata.keys() : fp_incar_path = jdata['fp_incar'] @@ -1262,7 +1322,7 @@ def make_vasp_incar(jdata, filename): incar = make_vasp_incar_user_dict(jdata['fp_params']) with open(filename, 'w') as fp: fp.write(incar) - return incar + return incar def make_pwmat_input(jdata, filename): if 'fp_incar' in jdata.keys() : @@ -1294,7 +1354,7 @@ def make_pwmat_input(jdata, filename): os.system('rm -rf tmp.config') input_dict = make_pwmat_input_dict(node1, node2, atom_config, ecut, e_error, rho_error, icmix = None, smearing = None, - sigma = None, kspacing = kspacing, + sigma = None, kspacing = kspacing, flag_symm = flag_symm ) @@ -1315,7 +1375,7 @@ def make_pwmat_input(jdata, filename): fp.write(input) fp.write('job=scf\n') fp_pp_files = jdata['fp_pp_files'] - for idx, ii in enumerate(fp_pp_files) : + for idx, ii in enumerate(fp_pp_files) : fp.write('IN.PSP%d = %s\n' %(idx+1, ii)) if 'OUT.MLMD' in input or 'out.mlmd' in input: return input @@ -1354,7 +1414,7 @@ def make_fp_vasp_incar (iter_index, with open('job.json') as fp: job_data = json.load(fp) if 'ele_temp' in job_data: - make_vasp_incar_ele_temp(jdata, 'INCAR', + make_vasp_incar_ele_temp(jdata, 'INCAR', job_data['ele_temp'], nbands_esti = nbands_esti) os.chdir(cwd) @@ -1487,7 +1547,7 @@ def sys_link_fp_vasp_pp (iter_index, sys = dpdata.System(sys_poscar, fmt = 'vasp/poscar') for ele_name in sys['atom_names']: ele_idx = jdata['type_map'].index(ele_name) - potcars.append(fp_pp_files[ele_idx]) + potcars.append(fp_pp_files[ele_idx]) with open(os.path.join(work_path,'POTCAR.%s' % ii), 'w') as fp_pot: for jj in potcars: with open(os.path.join(fp_pp_path, jj)) as fp: @@ -1610,7 +1670,7 @@ def make_fp_siesta(iter_index, os.chdir(cwd) # link pp files _link_fp_vasp_pp(iter_index, jdata) - + def make_fp_gaussian(iter_index, jdata): # make config @@ -1646,6 +1706,11 @@ def make_fp_cp2k (iter_index, work_path = os.path.join(iter_name, fp_name) if 'user_fp_params' in jdata.keys() : fp_params = jdata['user_fp_params'] + # some users might use own inputs + # specify the input path string + elif 'external_input_path' in jdata.keys() : + fp_params = None + exinput_path = os.path.abspath(jdata['external_input_path']) else: fp_params = jdata['fp_params'] cwd = os.getcwd() @@ -1653,7 +1718,12 @@ def make_fp_cp2k (iter_index, os.chdir(ii) sys_data = dpdata.System('POSCAR').data # make input for every task - cp2k_input = make_cp2k_input(sys_data, fp_params) + # if fp_params exits, make keys + if fp_params: + cp2k_input = make_cp2k_input(sys_data, fp_params) + else: + # else read from user input + cp2k_input = make_cp2k_input_from_external(sys_data, exinput_path) with open('input.inp', 'w') as fp: fp.write(cp2k_input) fp.close() @@ -1854,8 +1924,8 @@ def run_fp (iter_index, raise RuntimeError ("unsupported fp style") -def post_fp_check_fail(iter_index, - jdata, +def post_fp_check_fail(iter_index, + jdata, rfailed = None) : ratio_failed = rfailed if rfailed else jdata.get('ratio_failed',0.05) iter_name = make_iter_name(iter_index) @@ -1868,14 +1938,14 @@ def post_fp_check_fail(iter_index, fp_failed_tags = glob.glob(os.path.join(work_path, 'task.*', 'tag_failure*')) fp_failed_tasks = [os.path.dirname(ii) for ii in fp_failed_tags] fp_failed_tasks = list(set(fp_failed_tasks)) - + ntask = len(fp_tasks) nfail = len(fp_failed_tasks) rfail = float(nfail) / float(ntask) dlog.info("failed tasks: %6d in %6d %6.2f %% " % (nfail, ntask, rfail * 100.)) if rfail > ratio_failed: raise RuntimeError("find too many unsuccessfully terminated jobs") - + def post_fp_vasp (iter_index, jdata, @@ -2081,7 +2151,7 @@ def post_fp_gaussian (iter_index, sys_output = glob.glob(os.path.join(work_path, "task.%s.*/output"%ss)) sys_output.sort() for idx,oo in enumerate(sys_output) : - sys = dpdata.LabeledSystem(oo, fmt = 'gaussian/log') + sys = dpdata.LabeledSystem(oo, fmt = 'gaussian/log') if len(sys) > 0: sys.check_type_map(type_map = jdata['type_map']) if jdata.get('use_atom_pref', False): @@ -2242,7 +2312,7 @@ def set_version(mdata): - + def run_iter (param_file, machine_file) : try: @@ -2313,7 +2383,7 @@ def run_iter (param_file, machine_file) : log_iter ("run_model_devi", ii, jj) mdata = decide_model_devi_machine(mdata) run_model_devi (ii, jdata, mdata) - + elif jj == 5 : log_iter ("post_model_devi", ii, jj) post_model_devi (ii, jdata, mdata) diff --git a/dpgen/main.py b/dpgen/main.py index 7d180b596..6dcdc4ccd 100644 --- a/dpgen/main.py +++ b/dpgen/main.py @@ -65,19 +65,8 @@ def main(): parser_auto_gen_param.add_argument('PARAM', type=str, help="parameter file, json/yaml format") parser_auto_gen_param.set_defaults(func=auto_gen_param) - # parser_init.add_argument("-p",'--parameter', type=str, dest='param', - # help="parameter file, json/yaml format") - # parser_init.add_argument("-s","--stage", type=int, dest='stage', - # help="the stage of init, can be 1, 2, 3 or 4. " - # "1: Setup vasp jobs for relaxation. " - # "2: Collect vasp relaxed confs (if relax is not skiped). Perturb system. " - # "3: Setup vasp jobs for MD of perturbed system. " - # "4: Collect vasp md confs, make deepmd data. ") - # parser_init.add_argument("directories", metavar="dir", default=".", - # type=str, nargs="*", - # help="directory to process (default to .)") - # parser_init.set_defaults(func=gen_data) + # parser_init_reaction parser_init_reaction = subparsers.add_parser( "init_reaction", help="Generating initial data for reactive systems.") parser_init_reaction.add_argument('PARAM', type=str, @@ -147,11 +136,15 @@ def main(): parser_run.set_defaults(func=gen_simplify) # test - parser_test = subparsers.add_parser("test", help="Auto-test for Deep Potential.") + parser_test = subparsers.add_parser("autotest", help="Auto-test for Deep Potential.") + parser_test.add_argument('TASK', type=str, + help="task can be make, run or post") parser_test.add_argument('PARAM', type=str, help="parameter file, json/yaml format") - parser_test.add_argument('MACHINE', type=str, + parser_test.add_argument('MACHINE', type=str,default=None,nargs="?", help="machine file, json/yaml format") + parser_test.add_argument('-d','--debug', action='store_true', + help="log debug info") parser_test.set_defaults(func=gen_test) # db diff --git a/dpgen/remote/RemoteJob.py b/dpgen/remote/RemoteJob.py index 2450b59f5..057eb3d3e 100644 --- a/dpgen/remote/RemoteJob.py +++ b/dpgen/remote/RemoteJob.py @@ -108,18 +108,38 @@ def __init__ (self, jdata) : self.remote_password = None if 'password' in self.remote_profile : self.remote_password = self.remote_profile['password'] + self.local_key_filename = None + if 'key_filename' in self.remote_profile: + self.local_key_filename = self.remote_profile['key_filename'] + self.remote_timeout = None + if 'timeout' in self.remote_profile: + self.remote_timeout = self.remote_profile['timeout'] + self.local_key_passphrase = None + if 'passphrase' in self.remote_profile: + self.local_key_passphrase = self.remote_profile['passphrase'] self.remote_workpath = self.remote_profile['work_path'] - self.ssh = self._setup_ssh(self.remote_host, self.remote_port, username = self.remote_uname,password=self.remote_password) + self.ssh = self._setup_ssh(hostname=self.remote_host, + port=self.remote_port, + username=self.remote_uname, + password=self.remote_password, + key_filename=self.local_key_filename, + timeout=self.remote_timeout, + passphrase=self.local_key_passphrase) def _setup_ssh(self, hostname, - port, - username = None, - password = None): - ssh_client = paramiko.SSHClient() + port=22, + username=None, + password=None, + key_filename=None, + timeout=None, + passphrase=None + ): + ssh_client = paramiko.SSHClient() ssh_client.load_system_host_keys() ssh_client.set_missing_host_key_policy(paramiko.WarningPolicy) - ssh_client.connect(hostname, port=port, username=username, password=password) + ssh_client.connect(hostname, port, username, password, + key_filename, timeout, passphrase) assert(ssh_client.get_transport().is_active()) return ssh_client diff --git a/dpgen/util.py b/dpgen/util.py index efff97398..aa805e7e5 100644 --- a/dpgen/util.py +++ b/dpgen/util.py @@ -10,12 +10,14 @@ # constants define MaxLength=70 - -def sepline(ch='-',sp='-'): +def sepline(ch='-',sp='-',screen=False): r''' seperate the output by '-' ''' - dlog.info(ch.center(MaxLength,sp)) + if screen: + print(ch.center(MaxLength,sp)) + else: + dlog.info(ch.center(MaxLength,sp)) def box_center(ch='',fill=' ',sp="|"): r''' diff --git a/examples/machine/DeePMD-kit-1.0/machine-local.json b/examples/machine/DeePMD-kit-1.0/machine-local.json index d418a783e..6281b5bc5 100644 --- a/examples/machine/DeePMD-kit-1.0/machine-local.json +++ b/examples/machine/DeePMD-kit-1.0/machine-local.json @@ -27,7 +27,7 @@ "fp_command": "/home/wanghan/local/bin/vasp_std", "fp_group_size": 2, "fp_machine": { - "batch": "local", + "batch": "shell", "work_path" : "/home/wanghan/tmp/subs/", "_comment" : "that's all" }, diff --git a/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/CONTCAR b/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/CONTCAR deleted file mode 100644 index 4fe904343..000000000 --- a/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/CONTCAR +++ /dev/null @@ -1,25 +0,0 @@ -Si8 - 1.00000000000000 - 5.4687279999999996 0.0000000000000000 0.0000000000000000 - 0.0000000000000000 5.4687279999999996 0.0000000000000000 - 0.0000000000000000 0.0000000000000000 5.4687279999999996 - Si - 8 -Direct - 0.2500000000000000 0.2500000000000000 0.2500000000000000 - 0.5000000000000000 0.5000000000000000 0.0000000000000000 - 0.2500000000000000 0.7500000000000000 0.7500000000000000 - 0.5000000000000000 0.0000000000000000 0.5000000000000000 - 0.7500000000000000 0.2500000000000000 0.7500000000000000 - 0.0000000000000000 0.5000000000000000 0.5000000000000000 - 0.7500000000000000 0.7500000000000000 0.2500000000000000 - 0.0000000000000000 0.0000000000000000 0.0000000000000000 - - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 diff --git a/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/OUTCAR b/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/OUTCAR deleted file mode 100644 index 0bbd2d456..000000000 --- a/tests/auto_test/00.equi/si/mp-149/vasp-relax_incar/OUTCAR +++ /dev/null @@ -1,204 +0,0 @@ - - - INCAR: - POTCAR: PAW_PBE Si 05Jan2001 - - POTCAR: PAW_PBE Si 05Jan2001 - VRHFIN =Si: s2p2 - LEXCH = PE - EATOM = 103.0669 eV, 7.5752 Ry - - TITEL = PAW_PBE Si 05Jan2001 - LULTRA = F use ultrasoft PP ? - IUNSCR = 1 unscreen: 0-lin 1-nonlin 2-no - RPACOR = 1.500 partial core radius - POMASS = 28.085; ZVAL = 4.000 mass and valenz - RCORE = 1.900 outmost cutoff radius - RWIGS = 2.480; RWIGS = 1.312 wigner-seitz radius (au A) - ENMAX = 245.345; ENMIN = 184.009 eV - ICORE = 2 local potential - LCOR = T correct aug charges - LPAW = T paw PP - EAUG = 322.069 - DEXC = 0.000 - RMAX = 1.950 core radius for proj-oper - RAUG = 1.300 factor for augmentation sphere - RDEP = 1.993 radius for radial grids - RDEPT = 1.837 core radius for aug-charge - - Atomic configuration - 6 entries - n l j E occ. - 1 0 0.50 -1785.8828 2.0000 - 2 0 0.50 -139.4969 2.0000 - 2 1 1.50 -95.5546 6.0000 - 3 0 0.50 -10.8127 2.0000 - 3 1 0.50 -4.0811 2.0000 - 3 2 1.50 -4.0817 0.0000 - Description - l E TYP RCUT TYP RCUT - 0 -10.8127223 23 1.900 - 0 -7.6451159 23 1.900 - 1 -4.0811372 23 1.900 - 1 2.4879257 23 1.900 - 2 -4.0817478 7 1.900 - local pseudopotential read in - partial core-charges read in - partial kinetic energy density read in - atomic valenz-charges read in - non local Contribution for L= 0 read in - real space projection operators read in - non local Contribution for L= 0 read in - real space projection operators read in - non local Contribution for L= 1 read in - real space projection operators read in - non local Contribution for L= 1 read in - real space projection operators read in - PAW grid and wavefunctions read in - - number of l-projection operators is LMAX = 4 - number of lm-projection operators is LMMAX = 8 - - PAW_PBE Si 05Jan2001 : - energy of atom 1 EATOM= -103.0669 - kinetic energy error for atom= 0.0003 (will be added to EATOM!!) - - - POSCAR: Si8 - positions in direct lattice - velocities in cartesian coordinates - exchange correlation table for LEXCH = 8 - RHO(1)= 0.500 N(1) = 2000 - RHO(2)= 100.500 N(2) = 4000 - - - ------------------------- aborting loop because EDIFF is reached ---------------------------------------- - - - CHARGE: cpu time 0.2963: real time 0.2963 - FORLOC: cpu time 0.0049: real time 0.0049 - FORNL : cpu time 0.9680: real time 0.9681 - STRESS: cpu time 3.5438: real time 3.5442 - FORCOR: cpu time 0.0514: real time 0.0514 - FORHAR: cpu time 0.0141: real time 0.0141 - MIXING: cpu time 0.0020: real time 0.0020 - OFIELD: cpu time 0.0000: real time 0.0000 - - FORCE on cell =-STRESS in cart. coord. units (eV): - Direction XX YY ZZ XY YZ ZX - -------------------------------------------------------------------------------------- - Alpha Z 13.17272 13.17272 13.17272 - Ewald -302.59373 -302.59373 -302.59373 0.00000 0.00000 -0.00000 - Hartree 20.22818 20.22818 20.22818 -0.00000 0.00000 -0.00001 - E(xc) -100.98430 -100.98430 -100.98430 0.00000 -0.00000 0.00000 - Local -118.00021 -118.00021 -118.00020 0.00001 -0.00000 0.00002 - n-local 309.78388 309.78388 309.78388 -0.00000 0.00000 -0.00000 - augment -46.59684 -46.59684 -46.59684 -0.00000 -0.00000 -0.00000 - Kinetic 224.99250 224.99250 224.99250 0.00000 0.00000 0.00001 - Fock 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 - ------------------------------------------------------------------------------------- - Total 0.00220 0.00220 0.00220 0.00001 0.00000 0.00002 - in kB 0.02151 0.02155 0.02156 0.00008 0.00001 0.00019 - external pressure = 0.02 kB Pullay stress = 0.00 kB - - - VOLUME and BASIS-vectors are now : - ----------------------------------------------------------------------------- - energy-cutoff : 650.00 - volume of cell : 163.55 - direct lattice vectors reciprocal lattice vectors - 5.468728000 0.000000000 0.000000000 0.182857878 0.000000000 0.000000000 - 0.000000000 5.468728000 0.000000000 0.000000000 0.182857878 0.000000000 - 0.000000000 0.000000000 5.468728000 0.000000000 0.000000000 0.182857878 - - length of vectors - 5.468728000 5.468728000 5.468728000 0.182857878 0.182857878 0.182857878 - - - FORCES acting on ions - electron-ion (+dipol) ewald-force non-local-force convergence-correction - ----------------------------------------------------------------------------------------------- - -.236E-04 -.111E-04 -.458E-04 0.249E-13 0.107E-13 -.355E-14 -.871E-05 -.478E-05 0.920E-05 0.337E-04 0.158E-04 0.387E-04 - -.255E-04 -.104E-04 -.182E-04 0.180E-13 0.384E-14 -.710E-14 0.241E-05 0.915E-05 -.846E-06 0.256E-04 0.474E-05 0.222E-04 - -.805E-04 0.107E-05 0.374E-04 0.107E-13 0.355E-14 0.000E+00 0.146E-04 0.648E-05 -.650E-05 0.733E-04 -.793E-05 -.346E-04 - -.760E-05 -.183E-04 -.565E-05 0.341E-14 -.357E-14 -.362E-14 -.135E-05 0.548E-05 0.133E-04 0.888E-05 0.154E-04 -.541E-05 - 0.555E-04 0.406E-05 0.204E-04 0.355E-14 0.355E-14 0.355E-14 -.750E-05 -.781E-05 0.356E-05 -.512E-04 0.202E-05 -.277E-04 - -.321E-05 0.309E-04 0.493E-04 -.178E-13 -.350E-14 -.718E-16 0.836E-05 -.964E-05 -.109E-04 -.534E-05 -.228E-04 -.407E-04 - 0.481E-04 0.281E-04 -.852E-05 -.107E-13 -.355E-14 0.711E-14 -.257E-05 -.775E-05 -.798E-05 -.479E-04 -.223E-04 0.139E-04 - 0.234E-04 -.320E-04 -.298E-04 -.320E-13 -.106E-13 0.356E-14 -.448E-05 0.995E-05 0.233E-05 -.207E-04 0.245E-04 0.287E-04 - ----------------------------------------------------------------------------------------------- - -.134E-04 -.763E-05 -.867E-06 0.124E-15 0.361E-15 -.131E-15 0.759E-06 0.107E-05 0.221E-05 0.165E-04 0.934E-05 -.503E-05 - - - POSITION TOTAL-FORCE (eV/Angst) - ----------------------------------------------------------------------------------- - 1.36718 1.36718 1.36718 0.000001 -0.000000 0.000003 - 2.73436 2.73436 0.00000 0.000002 0.000003 0.000004 - 1.36718 4.10155 4.10155 0.000007 -0.000001 -0.000003 - 2.73436 0.00000 2.73436 -0.000001 0.000002 0.000003 - 4.10155 1.36718 4.10155 -0.000004 -0.000002 -0.000003 - 0.00000 2.73436 2.73436 -0.000001 -0.000002 -0.000002 - 4.10155 4.10155 1.36718 -0.000003 -0.000002 -0.000002 - 0.00000 0.00000 0.00000 -0.000002 0.000002 0.000002 - ----------------------------------------------------------------------------------- - total drift: 0.000004 0.000003 -0.000004 - - --------------------------------------------------------------------------------------------------------- - - - - FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV) - --------------------------------------------------- - free energy TOTEN = -43.40017315 eV - - energy without entropy= -43.40017315 energy(sigma->0) = -43.40017315 - - - --------------------------------------------------------------------------------------------------------- - - - POTLOK: cpu time 0.0496: real time 0.0496 - - --------------------------------------------------------------------------------------------------------- - - - - --------------------------------------------------------------------------------------------------------- - - - - reached required accuracy - stopping structural energy minimisation - LOOP+: cpu time 73.7767: real time 73.8176 - 4ORBIT: cpu time 0.0000: real time 0.0000 - - total amount of memory used by VASP MPI-rank0 119933. kBytes -======================================================================= - - base : 30000. kBytes - nonl-proj : 43479. kBytes - fftplans : 4240. kBytes - grid : 9842. kBytes - one-center: 24. kBytes - wavefun : 32348. kBytes - - - - General timing and accounting informations for this job: - ======================================================== - - Total CPU time used (sec): 75.718 - User time (sec): 75.184 - System time (sec): 0.534 - Elapsed time (sec): 75.841 - - Maximum memory used (kb): 186724. - Average memory used (kb): 0. - - Minor page faults: 71438 - Major page faults: 0 - Voluntary context switches: 409 diff --git a/tests/auto_test/confs/hp-Li/POSCAR b/tests/auto_test/confs/hp-Li/POSCAR new file mode 100644 index 000000000..bba6ab187 --- /dev/null +++ b/tests/auto_test/confs/hp-Li/POSCAR @@ -0,0 +1,48 @@ +Li40 +1.0 + 6.7885999680 0.0000000000 0.0000000000 + 0.0000000000 8.0621995926 0.0000000000 + 0.0000000000 0.0000000000 5.0141000748 + Li + 40 +Direct + 0.093139998 0.116310003 0.000000000 + 0.906859976 0.883689982 0.000000000 + 0.593140024 0.383690012 0.000000000 + 0.406860011 0.616310018 0.000000000 + 0.093139998 0.616310018 0.500000000 + 0.906859976 0.383690012 0.500000000 + 0.593140024 0.883689982 0.500000000 + 0.406860011 0.116310003 0.500000000 + 0.862999962 0.903139985 0.313789986 + 0.137000020 0.096860000 0.313789986 + 0.362999927 0.596860015 0.313789986 + 0.637000038 0.403140015 0.313789986 + 0.862999962 0.403140015 0.813789962 + 0.137000020 0.596860015 0.813789962 + 0.362999927 0.096860000 0.813789962 + 0.637000038 0.903139985 0.813789962 + 0.967830033 0.116910005 0.594070039 + 0.032169997 0.883090018 0.594070039 + 0.467829928 0.383089988 0.594070039 + 0.532170002 0.616909982 0.594070039 + 0.967830033 0.616909982 0.094069955 + 0.032169997 0.383089988 0.094069955 + 0.467829928 0.883090018 0.094069955 + 0.532170002 0.116910005 0.094069955 + 0.351290002 0.268080003 0.175870004 + 0.648710033 0.731919997 0.175870004 + 0.851289967 0.231919997 0.175870004 + 0.148710016 0.768080003 0.175870004 + 0.351290002 0.768080003 0.675869992 + 0.648710033 0.231919997 0.675869992 + 0.851289967 0.731919997 0.675869992 + 0.148710016 0.268080003 0.675869992 + 0.290069992 0.911850003 0.377050007 + 0.709930008 0.088150004 0.377050007 + 0.790069992 0.588149997 0.377050007 + 0.209930008 0.411850003 0.377050007 + 0.290069992 0.411850003 0.877050078 + 0.709930008 0.588149997 0.877050078 + 0.790069992 0.088150004 0.877050078 + 0.209930008 0.911850003 0.877050078 diff --git a/tests/auto_test/confs/mp-141/mp-141.cif b/tests/auto_test/confs/mp-141/mp-141.cif new file mode 100644 index 000000000..cd581a501 --- /dev/null +++ b/tests/auto_test/confs/mp-141/mp-141.cif @@ -0,0 +1,28 @@ +# generated using pymatgen +data_Yb +_symmetry_space_group_name_H-M 'P 1' +_cell_length_a 3.85287197 +_cell_length_b 3.85287197 +_cell_length_c 6.37704700 +_cell_angle_alpha 90.00000000 +_cell_angle_beta 90.00000000 +_cell_angle_gamma 119.99999956 +_symmetry_Int_Tables_number 1 +_chemical_formula_structural Yb +_chemical_formula_sum Yb2 +_cell_volume 81.98216970 +_cell_formula_units_Z 2 +loop_ + _symmetry_equiv_pos_site_id + _symmetry_equiv_pos_as_xyz + 1 'x, y, z' +loop_ + _atom_site_type_symbol + _atom_site_label + _atom_site_symmetry_multiplicity + _atom_site_fract_x + _atom_site_fract_y + _atom_site_fract_z + _atom_site_occupancy + Yb Yb0 1 0.33333300 0.66666700 0.25000000 1 + Yb Yb1 1 0.66666700 0.33333300 0.75000000 1 diff --git a/tests/auto_test/confs/si/mp-149/POSCAR b/tests/auto_test/confs/si/mp-149/POSCAR deleted file mode 100644 index 4fe904343..000000000 --- a/tests/auto_test/confs/si/mp-149/POSCAR +++ /dev/null @@ -1,25 +0,0 @@ -Si8 - 1.00000000000000 - 5.4687279999999996 0.0000000000000000 0.0000000000000000 - 0.0000000000000000 5.4687279999999996 0.0000000000000000 - 0.0000000000000000 0.0000000000000000 5.4687279999999996 - Si - 8 -Direct - 0.2500000000000000 0.2500000000000000 0.2500000000000000 - 0.5000000000000000 0.5000000000000000 0.0000000000000000 - 0.2500000000000000 0.7500000000000000 0.7500000000000000 - 0.5000000000000000 0.0000000000000000 0.5000000000000000 - 0.7500000000000000 0.2500000000000000 0.7500000000000000 - 0.0000000000000000 0.5000000000000000 0.5000000000000000 - 0.7500000000000000 0.7500000000000000 0.2500000000000000 - 0.0000000000000000 0.0000000000000000 0.0000000000000000 - - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 - 0.00000000E+00 0.00000000E+00 0.00000000E+00 diff --git a/tests/auto_test/equi/lammps/Al-fcc.vasp b/tests/auto_test/equi/lammps/Al-fcc.vasp new file mode 100644 index 000000000..5eb349b25 --- /dev/null +++ b/tests/auto_test/equi/lammps/Al-fcc.vasp @@ -0,0 +1,9 @@ +Al1 +1.0 +0.000000 2.025000 2.025000 +2.025000 0.000000 2.025000 +2.025000 2.025000 0.000000 +Al +1 +direct +0.000000 0.000000 0.000000 Al diff --git a/tests/auto_test/equi/vasp/Al-fcc.json b/tests/auto_test/equi/vasp/Al-fcc.json new file mode 100644 index 000000000..ad921e693 --- /dev/null +++ b/tests/auto_test/equi/vasp/Al-fcc.json @@ -0,0 +1,270 @@ +{ + "@module": "dpdata.system", + "@class": "LabeledSystem", + "data": { + "atom_numbs": [ + 1 + ], + "atom_names": [ + "Al" + ], + "atom_types": { + "@module": "numpy", + "@class": "array", + "dtype": "int64", + "data": [ + 0 + ] + }, + "orig": { + "@module": "numpy", + "@class": "array", + "dtype": "int64", + "data": [ + 0, + 0, + 0 + ] + }, + "cells": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": [ + [ + [ + 8.5913473914, + 0.0, + 0.0 + ], + [ + 1.4318912319, + 4.133513941, + 0.0 + ], + [ + 1.4318912319, + 0.8267027882, + 2.3382685902 + ] + ], + [ + [ + 8.564762399405534, + 0.0, + 0.0 + ], + [ + 1.4274603999009239, + 4.120723230762804, + 0.0 + ], + [ + 1.4274603999009212, + 0.8241446461525599, + 2.331033071844216 + ] + ], + [ + [ + 8.56476236490165, + 0.0, + 0.0 + ], + [ + 1.427460394144466, + 4.120723214157234, + 0.0 + ], + [ + 1.427460394154763, + 0.8241446428350139, + 2.331033062460779 + ] + ] + ] + }, + "coords": { + "@module": "numpy", + "@class": "array", + "dtype": "float64", + "data": [ + [ + [ + 0.0, + 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5.3351969e-10, + -9.711598e-06 + ] + ], + [ + [ + 1.4673689e-09, + 1.0859151999999998e-09, + -8.0157309e-10 + ], + [ + 1.0859151999999998e-09, + -6.3465143999999996e-09, + -6.170661800000001e-10 + ], + [ + -8.0157309e-10, + -6.170661800000001e-10, + 4.8698191e-09 + ] + ] + ] + } + } +} \ No newline at end of file diff --git a/tests/auto_test/equi/vasp/CONTCAR b/tests/auto_test/equi/vasp/CONTCAR new file mode 100644 index 000000000..199479402 --- /dev/null +++ b/tests/auto_test/equi/vasp/CONTCAR @@ -0,0 +1,89 @@ +Li40 + 1.00000000000000 + 6.9018805596324686 0.0000000000000000 0.0000000000000000 + 0.0000000000000000 8.1592726359368051 0.0000000000000000 + 0.0000000000000000 0.0000000000000000 5.0741491137471364 + Li + 40 +Direct + 0.0929926939123510 0.1164121140843607 -0.0005830561014952 + 0.9070072800876469 0.8835878709156418 -0.0005830561014952 + 0.5929927199123531 0.3835879009156440 -0.0005830561014952 + 0.4070073150876461 0.6164121290843582 -0.0005830561014952 + 0.0929926939123510 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0.00000000E+00 diff --git a/tests/auto_test/equi/vasp/CONTCAR_Al_fcc b/tests/auto_test/equi/vasp/CONTCAR_Al_fcc new file mode 100644 index 000000000..f8284d0e1 --- /dev/null +++ b/tests/auto_test/equi/vasp/CONTCAR_Al_fcc @@ -0,0 +1,10 @@ +Al1 +1.0 +0.000000 2.025000 2.025000 +2.025000 0.000000 2.025000 +2.025000 2.025000 0.000000 +Al +1 +direct +0.000000 0.000000 0.000000 Al +~ diff --git a/tests/auto_test/equi/vasp/OUTCAR b/tests/auto_test/equi/vasp/OUTCAR new file mode 100644 index 000000000..91da997fa --- /dev/null +++ b/tests/auto_test/equi/vasp/OUTCAR @@ -0,0 +1,33383 @@ + vasp.5.4.1 24Jun15 (build Dec 14 2019 20:21:40) complex + + executed on IFC91_ompi date 2020.01.05 15:53:38 + running on 40 total cores + distrk: each k-point on 40 cores, 1 groups + distr: one band on NCORES_PER_BAND= 10 cores, 4 groups + + +-------------------------------------------------------------------------------------------------------- + TITEL = PAW_PBE Li 04Oct2007 + + INCAR: + POTCAR: PAW_PBE Li 17Jan2003 + POTCAR: PAW_PBE Li 17Jan2003 + local pseudopotential read in + partial core-charges read in + partial kinetic energy density read in + atomic valenz-charges read in + non local Contribution for L= 0 read in + real space projection operators read in + non local Contribution for L= 0 read in + real space projection operators read in + non local Contribution for L= 1 read in + real space projection operators read in + PAW grid and wavefunctions read in + + number of l-projection operators is LMAX = 3 + number of lm-projection operators is LMMAX = 5 + + + ----------------------------------------------------------------------------- +| | +| ADVICE TO THIS USER RUNNING 'VASP/VAMP' (HEAR YOUR MASTER'S VOICE ...): | +| | +| You have a (more or less) 'large supercell' and for larger cells | +| it might be more efficient to use real space projection opertators | +| So try LREAL= Auto in the INCAR file. | +| Mind: At the moment your POTCAR file does not contain real space | +| projectors, and has to be modified, BUT if you | +| want to do an extremely accurate calculation you might also keep the | +| reciprocal projection scheme (i.e. LREAL=.FALSE.) | +| | + ----------------------------------------------------------------------------- + + PAW_PBE Li 17Jan2003 : + energy of atom 1 EATOM= -5.3001 + kinetic energy error for atom= 0.0000 (will be added to EATOM!!) + + + POSCAR: Li40 + positions in direct lattice + No initial velocities read in + exchange correlation table for LEXCH = 8 + RHO(1)= 0.500 N(1) = 2000 + RHO(2)= 100.500 N(2) = 4000 + + + +-------------------------------------------------------------------------------------------------------- + + + ion position nearest neighbor table + 1 0.093 0.116 0.000- 10 1.61 40 1.93 15 2.06 32 2.07 27 2.08 39 2.16 17 2.21 22 2.24 + 2 2.26 25 2.31 37 2.80 18 2.80 9 2.81 33 2.84 13 2.94 28 2.97 + 2 0.907 0.884 0.000- 9 1.61 39 1.93 16 2.06 31 2.07 28 2.08 40 2.16 18 2.21 21 2.24 + 1 2.26 26 2.31 38 2.80 17 2.80 10 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31 2.28 28 2.33 17 2.33 + 10 2.43 35 2.61 21 2.65 39 2.70 27 2.74 1 2.81 23 2.90 33 2.92 + 10 0.137 0.097 0.314- 1 1.61 17 1.82 33 1.85 8 2.06 25 2.12 32 2.28 27 2.33 18 2.33 + 9 2.43 36 2.61 22 2.65 40 2.70 28 2.74 2 2.81 24 2.90 34 2.92 + 11 0.363 0.597 0.314- 4 1.61 20 1.82 36 1.85 5 2.06 28 2.12 29 2.28 26 2.33 19 2.33 + 12 2.43 33 2.61 23 2.65 37 2.70 25 2.74 3 2.81 21 2.90 35 2.92 + 12 0.637 0.403 0.314- 3 1.61 19 1.82 35 1.85 6 2.06 27 2.12 30 2.28 25 2.33 20 2.33 + 11 2.43 34 2.61 24 2.65 38 2.70 26 2.74 4 2.81 22 2.90 36 2.92 + 13 0.863 0.403 0.814- 6 1.61 22 1.82 38 1.85 3 2.06 30 2.12 27 2.28 32 2.33 21 2.33 + 14 2.43 39 2.61 17 2.65 35 2.70 31 2.74 5 2.81 19 2.90 37 2.92 + 14 0.137 0.597 0.814- 5 1.61 21 1.82 37 1.85 4 2.06 29 2.12 28 2.28 31 2.33 22 2.33 + 13 2.43 40 2.61 18 2.65 36 2.70 32 2.74 6 2.81 20 2.90 38 2.92 + 15 0.363 0.097 0.814- 8 1.61 24 1.82 40 1.85 1 2.06 32 2.12 25 2.28 30 2.33 23 2.33 + 16 2.43 37 2.61 19 2.65 33 2.70 29 2.74 7 2.81 17 2.90 39 2.92 + 16 0.637 0.903 0.814- 7 1.61 23 1.82 39 1.85 2 2.06 31 2.12 26 2.28 29 2.33 24 2.33 + 15 2.43 38 2.61 20 2.65 34 2.70 30 2.74 8 2.81 18 2.90 40 2.92 + 17 0.968 0.117 0.594- 32 1.78 10 1.82 39 1.88 18 1.94 34 2.07 1 2.21 6 2.24 9 2.33 + 30 2.39 27 2.43 13 2.65 40 2.73 2 2.80 15 2.90 33 2.95 8 3.02 + 18 0.032 0.883 0.594- 31 1.78 9 1.82 40 1.88 17 1.94 33 2.07 2 2.21 5 2.24 10 2.33 + 29 2.39 28 2.43 14 2.65 39 2.73 1 2.80 16 2.90 34 2.95 7 3.02 + 19 0.468 0.383 0.594- 30 1.78 12 1.82 37 1.88 20 1.94 36 2.07 3 2.21 8 2.24 11 2.33 + 32 2.39 25 2.43 15 2.65 38 2.73 4 2.80 13 2.90 35 2.95 6 3.02 + 20 0.532 0.617 0.594- 29 1.78 11 1.82 38 1.88 19 1.94 35 2.07 4 2.21 7 2.24 12 2.33 + 31 2.39 26 2.43 16 2.65 37 2.73 3 2.80 14 2.90 36 2.95 5 3.02 + 21 0.968 0.617 0.094- 28 1.78 14 1.82 35 1.88 22 1.94 38 2.07 5 2.21 2 2.24 13 2.33 + 26 2.39 31 2.43 9 2.65 36 2.73 6 2.80 11 2.90 37 2.95 4 3.02 + 22 0.032 0.383 0.094- 27 1.78 13 1.82 36 1.88 21 1.94 37 2.07 6 2.21 1 2.24 14 2.33 + 25 2.39 32 2.43 10 2.65 35 2.73 5 2.80 12 2.90 38 2.95 3 3.02 + 23 0.468 0.883 0.094- 26 1.78 16 1.82 33 1.88 24 1.94 40 2.07 7 2.21 4 2.24 15 2.33 + 28 2.39 29 2.43 11 2.65 34 2.73 8 2.80 9 2.90 39 2.95 2 3.02 + 24 0.532 0.117 0.094- 25 1.78 15 1.82 34 1.88 23 1.94 39 2.07 8 2.21 3 2.24 16 2.33 + 27 2.39 30 2.43 12 2.65 33 2.73 7 2.80 10 2.90 40 2.95 1 3.02 + 25 0.351 0.268 0.176- 24 1.78 36 1.81 37 1.94 8 2.07 3 2.08 10 2.12 15 2.28 1 2.31 + 12 2.33 22 2.39 19 2.43 11 2.74 32 2.86 32 2.86 4 2.97 34 3.01 + 26 0.649 0.732 0.176- 23 1.78 35 1.81 38 1.94 7 2.07 4 2.08 9 2.12 16 2.28 2 2.31 + 11 2.33 21 2.39 20 2.43 12 2.74 31 2.86 31 2.86 3 2.97 33 3.01 + 27 0.851 0.232 0.176- 22 1.78 34 1.81 39 1.94 6 2.07 1 2.08 12 2.12 13 2.28 3 2.31 + 10 2.33 24 2.39 17 2.43 9 2.74 30 2.86 30 2.86 2 2.97 36 3.01 + 28 0.149 0.768 0.176- 21 1.78 33 1.81 40 1.94 5 2.07 2 2.08 11 2.12 14 2.28 4 2.31 + 9 2.33 23 2.39 18 2.43 10 2.74 29 2.86 29 2.86 1 2.97 35 3.01 + 29 0.351 0.768 0.676- 20 1.78 40 1.81 33 1.94 4 2.07 7 2.08 14 2.12 11 2.28 5 2.31 + 16 2.33 18 2.39 23 2.43 15 2.74 28 2.86 28 2.86 8 2.97 38 3.01 + 30 0.649 0.232 0.676- 19 1.78 39 1.81 34 1.94 3 2.07 8 2.08 13 2.12 12 2.28 6 2.31 + 15 2.33 17 2.39 24 2.43 16 2.74 27 2.86 27 2.86 7 2.97 37 3.01 + 31 0.851 0.732 0.676- 18 1.78 38 1.81 35 1.94 2 2.07 5 2.08 16 2.12 9 2.28 7 2.31 + 14 2.33 20 2.39 21 2.43 13 2.74 26 2.86 26 2.86 6 2.97 40 3.01 + 32 0.149 0.268 0.676- 17 1.78 37 1.81 36 1.94 1 2.07 6 2.08 15 2.12 10 2.28 8 2.31 + 13 2.33 19 2.39 22 2.43 14 2.74 25 2.86 25 2.86 5 2.97 39 3.01 + 33 0.290 0.912 0.377- 28 1.81 10 1.85 23 1.88 8 1.93 29 1.94 18 2.07 7 2.16 40 2.57 + 40 2.57 11 2.61 15 2.70 24 2.73 5 2.80 1 2.84 9 2.92 17 2.95 + 34 0.710 0.088 0.377- 27 1.81 9 1.85 24 1.88 7 1.93 30 1.94 17 2.07 8 2.16 39 2.57 + 39 2.57 12 2.61 16 2.70 23 2.73 6 2.80 2 2.84 10 2.92 18 2.95 + 35 0.790 0.588 0.377- 26 1.81 12 1.85 21 1.88 6 1.93 31 1.94 20 2.07 5 2.16 38 2.57 + 38 2.57 9 2.61 13 2.70 22 2.73 7 2.80 3 2.84 11 2.92 19 2.95 + 36 0.210 0.412 0.377- 25 1.81 11 1.85 22 1.88 5 1.93 32 1.94 19 2.07 6 2.16 37 2.57 + 37 2.57 10 2.61 14 2.70 21 2.73 8 2.80 4 2.84 12 2.92 20 2.95 + 37 0.290 0.412 0.877- 32 1.81 14 1.85 19 1.88 4 1.93 25 1.94 22 2.07 3 2.16 36 2.57 + 36 2.57 15 2.61 11 2.70 20 2.73 1 2.80 5 2.84 13 2.92 21 2.95 + 38 0.710 0.588 0.877- 31 1.81 13 1.85 20 1.88 3 1.93 26 1.94 21 2.07 4 2.16 35 2.57 + 35 2.57 16 2.61 12 2.70 19 2.73 2 2.80 6 2.84 14 2.92 22 2.95 + 39 0.790 0.088 0.877- 30 1.81 16 1.85 17 1.88 2 1.93 27 1.94 24 2.07 1 2.16 34 2.57 + 34 2.57 13 2.61 9 2.70 18 2.73 3 2.80 7 2.84 15 2.92 23 2.95 + 40 0.210 0.912 0.877- 29 1.81 15 1.85 18 1.88 1 1.93 28 1.94 23 2.07 2 2.16 33 2.57 + 33 2.57 14 2.61 10 2.70 17 2.73 4 2.80 8 2.84 16 2.92 24 2.95 + + + ----------------------------------------------------------------------------- +| | +| W W AA RRRRR N N II N N GGGG !!! | +| W W A A R R NN N II NN N G G !!! | +| W W A A R R N N N II N N N G !!! | +| W WW W AAAAAA RRRRR N N N II N N N G GGG ! | +| WW WW A A R R N NN II N NN G G | +| W W A A R R N N II N N GGGG !!! | +| | +| The distance between some ions is very small | +| please check the nearest neigbor list in the OUTCAR file | +| I HOPE YOU KNOW, WHAT YOU ARE DOING | +| | + ----------------------------------------------------------------------------- + + LATTYP: Found a simple orthorhombic cell. + ALAT = 5.0141000748 + B/A-ratio = 1.3539019698 + C/A-ratio = 1.6079056007 + + Lattice vectors: + + A1 = ( 0.0000000000, 0.0000000000, 5.0141000748) + A2 = ( -6.7885999680, 0.0000000000, 0.0000000000) + A3 = ( 0.0000000000, -8.0621995926, 0.0000000000) + + +Analysis of symmetry for initial positions (statically): +===================================================================== + Subroutine PRICEL returns following result: + + LATTYP: Found a base centered orthorhombic cell. + ALAT = 5.0141000748 + B/A-ratio = 1.6079056746 + C/A-ratio = 1.3539019698 + + Lattice vectors: + + A1 = ( 0.0000000000, 4.0310999817, -2.5070504586) + A2 = ( 0.0000000000, -4.0310999817, -2.5070496162) + A3 = ( -6.7885999680, 0.0000000000, 0.0000000000) + + 2 primitive cells build up your supercell. + + + Routine SETGRP: Setting up the symmetry group for a + simple orthorhombic supercell. + + + Subroutine GETGRP returns: Found 4 space group operations + (whereof 2 operations were pure point group operations) + out of a pool of 8 trial point group operations. + + +The static configuration has the point symmetry C_2 . + The point group associated with its full space group is C_2v. + + +Analysis of symmetry for dynamics (positions and initial velocities): +===================================================================== + Subroutine PRICEL returns following result: + + LATTYP: Found a base centered orthorhombic cell. + ALAT = 5.0141000748 + B/A-ratio = 1.6079056746 + C/A-ratio = 1.3539019698 + + Lattice vectors: + + A1 = ( 0.0000000000, 4.0310999817, -2.5070504586) + A2 = ( 0.0000000000, -4.0310999817, -2.5070496162) + A3 = ( -6.7885999680, 0.0000000000, 0.0000000000) + + 2 primitive cells build up your supercell. + + + Routine SETGRP: Setting up the symmetry group for a + simple orthorhombic supercell. + + + Subroutine GETGRP returns: Found 4 space group operations + (whereof 2 operations were pure point group operations) + out of a pool of 8 trial point group operations. + + +The dynamic configuration has the point symmetry C_2 . + The point group associated with its full space group is C_2v. + + + Subroutine INISYM returns: Found 4 space group operations + (whereof 2 operations are pure point group operations), + and found 2 'primitive' translations + + + + KPOINTS: K-Mesh Generated with KP-Resolved Value + +Automatic generation of k-mesh. +Space group operators: + irot det(A) alpha n_x n_y n_z tau_x tau_y tau_z + 1 1.000000 0.000000 1.000000 0.000000 0.000000 -0.000000 0.000000 -0.000000 + 2 1.000000 180.000000 0.000000 0.000000 1.000000 -0.000000 0.000000 -0.000000 + 3 -1.000000 180.000000 0.000000 1.000000 0.000000 -0.500000 0.000000 -0.500000 + 4 -1.000000 180.000000 1.000000 0.000000 0.000000 -0.500000 0.000000 -0.500000 + + Subroutine IBZKPT returns following result: + =========================================== + + Found 60 irreducible k-points: + + Following reciprocal coordinates: + Coordinates Weight + 0.000000 0.083333 0.050000 4.000000 + 0.142857 0.083333 0.050000 8.000000 + 0.285714 0.083333 0.050000 8.000000 + 0.428571 0.083333 0.050000 8.000000 + 0.000000 0.250000 0.050000 4.000000 + 0.142857 0.250000 0.050000 8.000000 + 0.285714 0.250000 0.050000 8.000000 + 0.428571 0.250000 0.050000 8.000000 + 0.000000 0.416667 0.050000 4.000000 + 0.142857 0.416667 0.050000 8.000000 + 0.285714 0.416667 0.050000 8.000000 + 0.428571 0.416667 0.050000 8.000000 + 0.000000 0.083333 0.150000 4.000000 + 0.142857 0.083333 0.150000 8.000000 + 0.285714 0.083333 0.150000 8.000000 + 0.428571 0.083333 0.150000 8.000000 + 0.000000 0.250000 0.150000 4.000000 + 0.142857 0.250000 0.150000 8.000000 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0.416667 0.350000 4.000000 + 0.142857 0.416667 0.350000 8.000000 + 0.285714 0.416667 0.350000 8.000000 + 0.428571 0.416667 0.350000 8.000000 + 0.000000 0.083333 0.450000 4.000000 + 0.142857 0.083333 0.450000 8.000000 + 0.285714 0.083333 0.450000 8.000000 + 0.428571 0.083333 0.450000 8.000000 + 0.000000 0.250000 0.450000 4.000000 + 0.142857 0.250000 0.450000 8.000000 + 0.285714 0.250000 0.450000 8.000000 + 0.428571 0.250000 0.450000 8.000000 + 0.000000 0.416667 0.450000 4.000000 + 0.142857 0.416667 0.450000 8.000000 + 0.285714 0.416667 0.450000 8.000000 + 0.428571 0.416667 0.450000 8.000000 + + Following cartesian coordinates: + Coordinates Weight + 0.000000 0.010336 0.009972 4.000000 + 0.021044 0.010336 0.009972 8.000000 + 0.042087 0.010336 0.009972 8.000000 + 0.063131 0.010336 0.009972 8.000000 + 0.000000 0.031009 0.009972 4.000000 + 0.021044 0.031009 0.009972 8.000000 + 0.042087 0.031009 0.009972 8.000000 + 0.063131 0.031009 0.009972 8.000000 + 0.000000 0.051682 0.009972 4.000000 + 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+-------------------------------------------------------------------------------------------------------- + + + + + Dimension of arrays: + k-points NKPTS = 60 k-points in BZ NKDIM = 60 number of bands NBANDS= 44 + number of dos NEDOS = 301 number of ions NIONS = 40 + non local maximal LDIM = 3 non local SUM 2l+1 LMDIM = 5 + total plane-waves NPLWV = 67200 + max r-space proj IRMAX = 1 max aug-charges IRDMAX= 8034 + dimension x,y,z NGX = 42 NGY = 50 NGZ = 32 + dimension x,y,z NGXF= 84 NGYF= 100 NGZF= 64 + support grid NGXF= 84 NGYF= 100 NGZF= 64 + ions per type = 40 + NGX,Y,Z is equivalent to a cutoff of 10.29, 10.31, 10.61 a.u. + NGXF,Y,Z is equivalent to a cutoff of 20.57, 20.62, 21.22 a.u. + + + I would recommend the setting: + dimension x,y,z NGX = 42 NGY = 50 NGZ = 31 + SYSTEM = unknown system + POSCAR = Li40 + + Startparameter for this run: + NWRITE = 1 write-flag & timer + PREC = normal normal or accurate (medium, high low for compatibility) + ISTART = 0 job : 0-new 1-cont 2-samecut + ICHARG = 2 charge: 1-file 2-atom 10-const + ISPIN = 1 spin polarized calculation? + LNONCOLLINEAR = F non collinear calculations + LSORBIT = F spin-orbit coupling + INIWAV = 1 electr: 0-lowe 1-rand 2-diag + LASPH = F aspherical Exc in radial PAW + METAGGA= F non-selfconsistent MetaGGA calc. + + Electronic Relaxation 1 + ENCUT = 650.0 eV 47.77 Ry 6.91 a.u. 14.11 16.76 10.42*2*pi/ulx,y,z + ENINI = 650.0 initial cutoff + ENAUG = 331.6 eV augmentation charge cutoff + NELM = 200; NELMIN= 6; NELMDL= -5 # of ELM steps + EDIFF = 0.1E-05 stopping-criterion for ELM + LREAL = F real-space projection + NLSPLINE = F spline interpolate recip. space projectors + LCOMPAT= F compatible to vasp.4.4 + GGA_COMPAT = T GGA compatible to vasp.4.4-vasp.4.6 + LMAXPAW = -100 max onsite density + LMAXMIX = 2 max onsite mixed and CHGCAR + VOSKOWN= 0 Vosko Wilk Nusair interpolation + ROPT = 0.00000 + Ionic relaxation + EDIFFG = -.1E-01 stopping-criterion for IOM + NSW = 200 number of steps for IOM + NBLOCK = 1; KBLOCK = 200 inner block; outer block + IBRION = 2 ionic relax: 0-MD 1-quasi-New 2-CG + NFREE = 1 steps in history (QN), initial steepest desc. (CG) + ISIF = 3 stress and relaxation + IWAVPR = 11 prediction: 0-non 1-charg 2-wave 3-comb + ISYM = 2 0-nonsym 1-usesym 2-fastsym + LCORR = T Harris-Foulkes like correction to forces + + POTIM = 0.6000 time-step for ionic-motion + TEIN = 0.0 initial temperature + TEBEG = 0.0; TEEND = 0.0 temperature during run + SMASS = -3.00 Nose mass-parameter (am) + estimated Nose-frequenzy (Omega) = 0.10E-29 period in steps =****** mass= -0.105E-26a.u. + SCALEE = 1.0000 scale energy and forces + NPACO = 256; APACO = 16.0 distance and # of slots for P.C. + PSTRESS= 700.0 pullay stress + + Mass of Ions in am + POMASS = 7.01 + Ionic Valenz + ZVAL = 1.00 + Atomic Wigner-Seitz radii + RWIGS = -1.00 + virtual crystal weights + VCA = 1.00 + NELECT = 40.0000 total number of electrons + NUPDOWN= -1.0000 fix difference up-down + + DOS related values: + EMIN = 10.00; EMAX =-10.00 energy-range for DOS + EFERMI = 0.00 + ISMEAR = 1; SIGMA = 0.20 broadening in eV -4-tet -1-fermi 0-gaus + + Electronic relaxation 2 (details) + IALGO = 38 algorithm + LDIAG = T sub-space diagonalisation (order eigenvalues) + LSUBROT= F optimize rotation matrix (better conditioning) + TURBO = 0 0=normal 1=particle mesh + IRESTART = 0 0=no restart 2=restart with 2 vectors + NREBOOT = 0 no. of reboots + NMIN = 0 reboot dimension + EREF = 0.00 reference energy to select bands + IMIX = 4 mixing-type and parameters + AMIX = 0.40; BMIX = 1.00 + AMIX_MAG = 1.60; BMIX_MAG = 1.00 + AMIN = 0.10 + WC = 100.; INIMIX= 1; MIXPRE= 1; MAXMIX= -45 + + Intra band minimization: + WEIMIN = 0.0010 energy-eigenvalue tresh-hold + EBREAK = 0.57E-08 absolut break condition + DEPER = 0.30 relativ break condition + + TIME = 0.40 timestep for ELM + + volume/ion in A,a.u. = 6.86 46.30 + Fermi-wavevector in a.u.,A,eV,Ry = 0.861561 1.628114 10.099427 0.742287 + Thomas-Fermi vector in A = 1.979233 + + Write flags + LWAVE = F write WAVECAR + LCHARG = F write CHGCAR + LVTOT = F write LOCPOT, total local potential + LVHAR = F write LOCPOT, Hartree potential only + LELF = F write electronic localiz. function (ELF) + LORBIT = 0 0 simple, 1 ext, 2 COOP (PROOUT) + + + Dipole corrections + LMONO = F monopole corrections only (constant potential shift) + LDIPOL = F correct potential (dipole corrections) + IDIPOL = 0 1-x, 2-y, 3-z, 4-all directions + EPSILON= 1.0000000 bulk dielectric constant + + Exchange correlation treatment: + GGA = -- GGA type + LEXCH = 8 internal setting for exchange type + VOSKOWN= 0 Vosko Wilk Nusair interpolation + LHFCALC = F Hartree Fock is set to + LHFONE = F Hartree Fock one center treatment + AEXX = 0.0000 exact exchange contribution + + Linear response parameters + LEPSILON= F determine dielectric tensor + LRPA = F only Hartree local field effects (RPA) + LNABLA = F use nabla operator in PAW spheres + LVEL = F velocity operator in full k-point grid + LINTERFAST= F fast interpolation + KINTER = 0 interpolate to denser k-point grid + CSHIFT =0.1000 complex shift for real part using Kramers Kronig + OMEGAMAX= -1.0 maximum frequency + DEG_THRESHOLD= 0.2000000E-02 threshold for treating states as degnerate + RTIME = 0.100 relaxation time in fs + + Orbital magnetization related: + ORBITALMAG= F switch on orbital magnetization + LCHIMAG = F perturbation theory with respect to B field + DQ = 0.001000 dq finite difference perturbation B field + + + +-------------------------------------------------------------------------------------------------------- + + + conjugate gradient relaxation of ions + charge density and potential will be updated during run + non-spin polarized calculation + Variant of blocked Davidson + Davidson routine will perform the subspace rotation + perform sub-space diagonalisation + after iterative eigenvector-optimisation + modified Broyden-mixing scheme, WC = 100.0 + initial mixing is a Kerker type mixing with AMIX = 0.4000 and BMIX = 1.0000 + Hartree-type preconditioning will be used + using additional bands 24 + reciprocal scheme for non local part + use partial core corrections + calculate Harris-corrections to forces + (improved forces if not selfconsistent) + use gradient corrections + use of overlap-Matrix (Vanderbilt PP) + Methfessel and Paxton Order N= 1 SIGMA = 0.20 + + +-------------------------------------------------------------------------------------------------------- + + + energy-cutoff : 650.00 + volume of cell : 274.43 + direct lattice vectors reciprocal lattice vectors + 6.788599968 0.000000000 0.000000000 0.147305778 0.000000000 0.000000000 + 0.000000000 8.062199593 0.000000000 0.000000000 0.124035629 0.000000000 + 0.000000000 0.000000000 5.014100075 0.000000000 0.000000000 0.199437583 + + length of vectors + 6.788599968 8.062199593 5.014100075 0.147305778 0.124035629 0.199437583 + + + + k-points in units of 2pi/SCALE and weight: K-Mesh Generated with KP-Resolved Value + 0.00000000 0.01033630 0.00997188 0.010 + 0.02104368 0.01033630 0.00997188 0.019 + 0.04208737 0.01033630 0.00997188 0.019 + 0.06313105 0.01033630 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0.73192000 0.67586999 + 0.14871002 0.26808000 0.67586999 + 0.29006999 0.91185000 0.37705001 + 0.70993001 0.08815000 0.37705001 + 0.79006999 0.58815000 0.37705001 + 0.20993001 0.41185000 0.37705001 + 0.29006999 0.41185000 0.87705008 + 0.70993001 0.58815000 0.87705008 + 0.79006999 0.08815000 0.87705008 + 0.20993001 0.91185000 0.87705008 + + position of ions in cartesian coordinates (Angst): + 0.63229019 0.93771446 0.00000000 + 6.15630960 7.12448501 0.00000000 + 4.02659035 3.09338546 0.00000000 + 2.76200986 4.96881438 0.00000000 + 0.63229019 4.96881438 2.50705004 + 6.15630960 3.09338546 2.50705004 + 4.02659035 7.12448501 2.50705004 + 2.76200986 0.93771446 2.50705004 + 5.85856151 7.28129482 1.57337439 + 0.93003833 0.78090465 1.57337439 + 2.46426129 4.81200457 1.57337439 + 4.32433844 3.25019526 1.57337439 + 5.85856151 3.25019526 4.08042431 + 0.93003833 4.81200457 4.08042431 + 2.46426129 0.78090465 4.08042431 + 4.32433844 7.28129482 4.08042431 + 6.57021093 0.94255179 2.97872663 + 0.21838924 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plane waves: 10329 + k-point 3 : 0.2857 0.0833 0.0500 plane waves: 10343 + k-point 4 : 0.4286 0.0833 0.0500 plane waves: 10347 + k-point 5 : 0.0000 0.2500 0.0500 plane waves: 10357 + k-point 6 : 0.1429 0.2500 0.0500 plane waves: 10339 + k-point 7 : 0.2857 0.2500 0.0500 plane waves: 10331 + k-point 8 : 0.4286 0.2500 0.0500 plane waves: 10326 + k-point 9 : 0.0000 0.4167 0.0500 plane waves: 10328 + k-point 10 : 0.1429 0.4167 0.0500 plane waves: 10344 + k-point 11 : 0.2857 0.4167 0.0500 plane waves: 10341 + k-point 12 : 0.4286 0.4167 0.0500 plane waves: 10333 + k-point 13 : 0.0000 0.0833 0.1500 plane waves: 10336 + k-point 14 : 0.1429 0.0833 0.1500 plane waves: 10331 + k-point 15 : 0.2857 0.0833 0.1500 plane waves: 10328 + k-point 16 : 0.4286 0.0833 0.1500 plane waves: 10334 + k-point 17 : 0.0000 0.2500 0.1500 plane waves: 10343 + k-point 18 : 0.1429 0.2500 0.1500 plane waves: 10327 + k-point 19 : 0.2857 0.2500 0.1500 plane waves: 10330 + k-point 20 : 0.4286 0.2500 0.1500 plane waves: 10341 + k-point 21 : 0.0000 0.4167 0.1500 plane waves: 10336 + k-point 22 : 0.1429 0.4167 0.1500 plane waves: 10337 + k-point 23 : 0.2857 0.4167 0.1500 plane waves: 10343 + k-point 24 : 0.4286 0.4167 0.1500 plane waves: 10333 + k-point 25 : 0.0000 0.0833 0.2500 plane waves: 10319 + k-point 26 : 0.1429 0.0833 0.2500 plane waves: 10325 + k-point 27 : 0.2857 0.0833 0.2500 plane waves: 10329 + k-point 28 : 0.4286 0.0833 0.2500 plane waves: 10334 + k-point 29 : 0.0000 0.2500 0.2500 plane waves: 10325 + k-point 30 : 0.1429 0.2500 0.2500 plane waves: 10322 + k-point 31 : 0.2857 0.2500 0.2500 plane waves: 10331 + k-point 32 : 0.4286 0.2500 0.2500 plane waves: 10331 + k-point 33 : 0.0000 0.4167 0.2500 plane waves: 10340 + k-point 34 : 0.1429 0.4167 0.2500 plane waves: 10329 + k-point 35 : 0.2857 0.4167 0.2500 plane waves: 10325 + k-point 36 : 0.4286 0.4167 0.2500 plane waves: 10327 + k-point 37 : 0.0000 0.0833 0.3500 plane waves: 10306 + k-point 38 : 0.1429 0.0833 0.3500 plane waves: 10306 + k-point 39 : 0.2857 0.0833 0.3500 plane waves: 10328 + k-point 40 : 0.4286 0.0833 0.3500 plane waves: 10328 + k-point 41 : 0.0000 0.2500 0.3500 plane waves: 10311 + k-point 42 : 0.1429 0.2500 0.3500 plane waves: 10316 + k-point 43 : 0.2857 0.2500 0.3500 plane waves: 10314 + k-point 44 : 0.4286 0.2500 0.3500 plane waves: 10330 + k-point 45 : 0.0000 0.4167 0.3500 plane waves: 10307 + k-point 46 : 0.1429 0.4167 0.3500 plane waves: 10316 + k-point 47 : 0.2857 0.4167 0.3500 plane waves: 10318 + k-point 48 : 0.4286 0.4167 0.3500 plane waves: 10334 + k-point 49 : 0.0000 0.0833 0.4500 plane waves: 10285 + k-point 50 : 0.1429 0.0833 0.4500 plane waves: 10305 + k-point 51 : 0.2857 0.0833 0.4500 plane waves: 10314 + k-point 52 : 0.4286 0.0833 0.4500 plane waves: 10328 + k-point 53 : 0.0000 0.2500 0.4500 plane waves: 10279 + k-point 54 : 0.1429 0.2500 0.4500 plane waves: 10282 + k-point 55 : 0.2857 0.2500 0.4500 plane waves: 10317 + k-point 56 : 0.4286 0.2500 0.4500 plane waves: 10316 + k-point 57 : 0.0000 0.4167 0.4500 plane waves: 10306 + k-point 58 : 0.1429 0.4167 0.4500 plane waves: 10314 + k-point 59 : 0.2857 0.4167 0.4500 plane waves: 10301 + k-point 60 : 0.4286 0.4167 0.4500 plane waves: 10336 + + maximum and minimum number of plane-waves per node : 1056 1007 + + maximum number of plane-waves: 10357 + maximum index in each direction: + IXMAX= 14 IYMAX= 16 IZMAX= 10 + IXMIN= -14 IYMIN= -17 IZMIN= -10 + + WARNING: aliasing errors must be expected set NGX to 58 to avoid them + WARNING: aliasing errors must be expected set NGY to 68 to avoid them + WARNING: aliasing errors must be expected set NGZ to 42 to avoid them + aliasing errors are usually negligible using standard VASP settings + and one can safely disregard these warnings + + parallel 3D FFT for wavefunctions: + minimum data exchange during FFTs selected (reduces bandwidth) + parallel 3D FFT for charge: + minimum data exchange during FFTs selected (reduces bandwidth) + + + total amount of memory used by VASP on root node 46714. kBytes +======================================================================== + + base : 30000. kBytes + nonl-proj : 3210. kBytes + fftplans : 874. kBytes + grid : 1264. kBytes + one-center: 4. kBytes + wavefun : 11362. kBytes + + INWAV: cpu time 0.0000: real time 0.0000 + Broyden mixing: mesh for mixing (old mesh) + NGX = 29 NGY = 33 NGZ = 21 + (NGX = 84 NGY =100 NGZ = 64) + gives a total of 20097 points + + initial charge density was supplied: + charge density of overlapping atoms calculated + number of electron 40.0000000 magnetization + keeping initial charge density in first step + + +-------------------------------------------------------------------------------------------------------- + + + Maximum index for augmentation-charges 920 (set IRDMAX) + + +-------------------------------------------------------------------------------------------------------- + + + First call to EWALD: gamma= 0.273 + Maximum number of real-space cells 3x 2x 3 + Maximum number of reciprocal cells 3x 3x 2 + + FEWALD executed in parallel + FEWALD: cpu time 0.0040: real time 0.0051 + + +----------------------------------------- Iteration 1( 1) --------------------------------------- + + + POTLOK: cpu time 0.0238: real time 0.0251 + SETDIJ: cpu time 0.0072: real time 0.0080 + EDDAV: cpu time 5.1757: real time 5.2048 + DOS: cpu time 0.0060: real time 0.0060 + -------------------------------------------- + LOOP: cpu time 5.2164: real time 5.2487 + + eigenvalue-minimisations : 5280 + total energy-change (2. order) : 0.9421387E+02 (-0.1528001E+04) + number of electron 40.0000000 magnetization + augmentation part 40.0000000 magnetization + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.11721019 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -155.09374907 + PAW double counting = 306.50462356 -84.16909176 + entropy T*S EENTRO = 0.00691706 + eigenvalues EBANDS = 228.36218860 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = 94.21386994 eV + + energy without entropy = 94.20695288 energy(sigma->0) = 94.21156425 + + +-------------------------------------------------------------------------------------------------------- + + + + +----------------------------------------- Iteration 1( 2) --------------------------------------- + + + EDDAV: cpu time 5.2739: real time 5.2744 + DOS: cpu time 0.0070: real time 0.0070 + -------------------------------------------- + LOOP: cpu time 5.2828: real time 5.2834 + + eigenvalue-minimisations : 6068 + total energy-change (2. order) :-0.1046978E+03 (-0.9729384E+02) + number of electron 40.0000000 magnetization + augmentation part 40.0000000 magnetization + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.11721019 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -155.09374907 + PAW double counting = 306.50462356 -84.16909176 + entropy T*S EENTRO = 0.00517401 + eigenvalues EBANDS = 123.66612000 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = -10.48394170 eV + + energy without entropy = -10.48911571 energy(sigma->0) = -10.48566637 + + +-------------------------------------------------------------------------------------------------------- + + + + +----------------------------------------- Iteration 1( 3) --------------------------------------- + + + EDDAV: cpu time 5.6954: real time 5.6976 + DOS: cpu time 0.0068: real time 0.0068 + -------------------------------------------- + LOOP: cpu time 5.7043: real time 5.7065 + + eigenvalue-minimisations : 6764 + total energy-change (2. order) :-0.4539957E+01 (-0.4406030E+01) + number of electron 40.0000000 magnetization + augmentation part 40.0000000 magnetization + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.11721019 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -155.09374907 + PAW double counting = 306.50462356 -84.16909176 + entropy T*S EENTRO = 0.00929062 + eigenvalues EBANDS = 119.12204603 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = -15.02389907 eV + + energy without entropy = -15.03318968 energy(sigma->0) = -15.02699594 + + +-------------------------------------------------------------------------------------------------------- + + + + +----------------------------------------- Iteration 1( 4) --------------------------------------- + + + EDDAV: cpu time 5.3601: real time 5.3606 + DOS: cpu time 0.0069: real time 0.0069 + -------------------------------------------- + LOOP: cpu time 5.3689: real time 5.3701 + + eigenvalue-minimisations : 6368 + total energy-change (2. order) :-0.6621817E-01 (-0.6605004E-01) + number of electron 40.0000000 magnetization + augmentation part 40.0000000 magnetization + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.11721019 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -155.09374907 + PAW double counting = 306.50462356 -84.16909176 + entropy T*S EENTRO = 0.00939682 + eigenvalues EBANDS = 119.05572167 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = -15.09011724 eV + + energy without entropy = -15.09951405 energy(sigma->0) = -15.09324951 + + +-------------------------------------------------------------------------------------------------------- + + + + +----------------------------------------- Iteration 1( 5) --------------------------------------- + + + EDDAV: cpu time 5.2311: real time 5.2323 + DOS: cpu time 0.0070: real time 0.0070 + CHARGE: cpu time 0.1900: real time 0.1917 + MIXING: cpu time 0.0040: real time 0.0040 + -------------------------------------------- + LOOP: cpu time 5.4349: real time 5.4386 + + eigenvalue-minimisations : 6288 + total energy-change (2. order) :-0.9307248E-03 (-0.9306247E-03) + number of electron 39.9999999 magnetization + augmentation part 0.9754056 magnetization + + Broyden mixing: + rms(total) = 0.49525E+00 rms(broyden)= 0.49525E+00 + rms(prec ) = 0.71737E+00 + weight for this iteration 100.00 + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.11721019 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -155.09374907 + PAW double counting = 306.50462356 -84.16909176 + entropy T*S EENTRO = 0.00939720 + eigenvalues EBANDS = 119.05479055 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = -15.09104796 eV + + energy without entropy = -15.10044516 energy(sigma->0) = -15.09418036 + + +-------------------------------------------------------------------------------------------------------- + + + + +----------------------------------------- Iteration 1( 6) --------------------------------------- + + + POTLOK: cpu time 0.0237: real time 0.0248 + SETDIJ: cpu time 0.0070: real time 0.0079 + EDDAV: cpu time 5.3933: real time 5.3947 + DOS: cpu time 0.0071: real time 0.0071 + CHARGE: cpu time 0.1759: real time 0.1759 + MIXING: cpu time 0.0040: real time 0.0040 + -------------------------------------------- + LOOP: cpu time 5.6125: real time 5.6167 + + eigenvalue-minimisations : 6092 + total energy-change (2. order) : 0.2211266E+01 (-0.1259117E-01) + number of electron 39.9999999 magnetization + augmentation part 0.9870235 magnetization + + Broyden mixing: + rms(total) = 0.31558E+00 rms(broyden)= 0.31558E+00 + rms(prec ) = 0.45466E+00 + weight for this iteration 100.00 + + eigenvalues of (default mixing * dielectric matrix) + average eigenvalue GAMMA= 2.7248 + 2.7248 + + Free energy of the ion-electron system (eV) + --------------------------------------------------- + alpha Z PSCENC = 15.27370333 + Ewald energy TEWEN = -428.55742867 + -Hartree energ DENC = -0.71849548 + -exchange EXHF = 0.00000000 + -V(xc)+E(xc) XCENC = -153.71901439 + PAW double counting = 560.76212176 -339.60306216 + entropy T*S EENTRO = 0.00996571 + eigenvalues EBANDS = 121.66851084 + atomic energy EATOM = 212.00391708 + Solvation Ediel_sol = 0.00000000 + --------------------------------------------------- + free energy TOTEN = -12.87978199 eV + + 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+atom_style atomic +box tilt large +read_data conf.lmp +mass 1 1 +neigh_modify every 1 delay 0 check no +pair_style deepmd frozen_model.pb +pair_coeff +compute mype all pe +thermo 100 +thermo_style custom step pe pxx pyy pzz pxy pxz pyz lx ly lz vol c_mype +dump 1 all custom 100 dump.relax id type xs ys zs fx fy fz +min_style cg +fix 1 all box/relax iso 0.0 +minimize 1.000000e-16 1.000000e-10 5000 500000 +fix 1 all box/relax aniso 0.0 +minimize 1.000000e-16 1.000000e-10 5000 500000 +variable N equal count(all) +variable V equal vol +variable E equal "c_mype" +variable tmplx equal lx +variable tmply equal ly +variable Pxx equal pxx +variable Pyy equal pyy +variable Pzz equal pzz +variable Pxy equal pxy +variable Pxz equal pxz +variable Pyz equal pyz +variable Epa equal ${E}/${N} +variable Vpa equal ${V}/${N} +variable AA equal (${tmplx}*${tmply}) +print "All done" +print "Total number of atoms = ${N}" +print "Final energy per atoms = ${Epa}" +print "Final volume per atoms = ${Vpa}" +print "Final Base area = ${AA}" +print "Final Stress (xx yy zz xy xz yz) = ${Pxx} ${Pyy} ${Pzz} ${Pxy} ${Pxz} ${Pyz}" diff --git a/tests/auto_test/test_elastic.py b/tests/auto_test/test_elastic.py index 53a8d57a2..b8f464571 100644 --- a/tests/auto_test/test_elastic.py +++ b/tests/auto_test/test_elastic.py @@ -1,52 +1,88 @@ -import os,sys,json,glob,shutil +import os, sys, json, glob, shutil import dpdata import numpy as np import unittest +import dpdata +from monty.serialization import loadfn, dumpfn +from pymatgen.analysis.elasticity.strain import Strain, Deformation +from pymatgen import Structure +from pymatgen.io.vasp import Incar sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) __package__ = 'auto_test' + from .context import make_kspacing_kpoints from .context import setUpModule -from pymatgen.io.vasp import Incar -from dpgen.auto_test.gen_02_elastic import make_vasp +from dpgen.auto_test.Elastic import Elastic -class Test02(unittest.TestCase): - def tearDown(self): - if os.path.exists('02.elastic'): - shutil.rmtree('02.elastic') - def test_make_vasp (self): - jdata = { - 'relax_incar' : 'vasp_input/INCAR.rlx', - 'potcar_map': {'Si': 'vasp_input/POTCAR' }, +class TestElastic(unittest.TestCase): + + def setUp(self): + _jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Al": "vasp_input/POT_Al"} + }, + "properties": [ + { + "skip":False, + "type": "elastic", + "norm_deform": 2e-2, + "shear_deform": 5e-2 + } + ] } - make_vasp(jdata, 'confs/si/mp-149') - - target_path = '02.elastic/si/mp-149/vasp-relax_incar' - equi_path = '00.equi/si/mp-149/vasp-relax_incar' - dfm_dirs = glob.glob(os.path.join(target_path, 'dfm*')) - - # check root INCAR + + self.equi_path = 'confs/std-fcc/relaxation/task_relax' + self.source_path = 'equi/vasp' + self.target_path = 'confs/std-fcc/elastic_00' + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + self.confs = _jdata["structures"] + self.inter_param = _jdata["interaction"] + self.prop_param = _jdata['properties'] + + self.elastic = Elastic(_jdata['properties'][0]) + + def tearDown(self): + if os.path.exists(os.path.join(self.equi_path,'..')): + shutil.rmtree(self.equi_path) + if os.path.exists(self.equi_path): + shutil.rmtree(self.equi_path) + if os.path.exists(self.target_path): + shutil.rmtree(self.target_path) + + def test_task_type(self): + self.assertEqual('elastic', self.elastic.task_type()) + + def test_task_param(self): + self.assertEqual(self.prop_param[0], self.elastic.task_param()) + + def test_make_confs(self): + + shutil.copy(os.path.join(self.source_path, 'Al-fcc.json'), os.path.join(self.equi_path, 'result.json')) + if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')): + with self.assertRaises(RuntimeError): + self.elastic.make_confs(self.target_path, self.equi_path) + shutil.copy(os.path.join(self.source_path, 'CONTCAR_Al_fcc'), os.path.join(self.equi_path, 'CONTCAR')) + task_list = self.elastic.make_confs(self.target_path, self.equi_path) + dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*')) + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) - incar1 = Incar.from_file(os.path.join(target_path, 'INCAR')) - self.assertFalse(incar0 == incar1) - incar0['ISIF'] = 2 - self.assertTrue(incar0 == incar1) - # check root POTCAR - with open(os.path.join('vasp_input', 'POTCAR')) as fp: - pot0 = fp.read() - with open(os.path.join(target_path, 'POTCAR')) as fp: - pot1 = fp.read() - self.assertEqual(pot0, pot1) - # check root POSCAR - self.assertEqual(os.path.realpath(os.path.join(target_path, 'POSCAR')), - os.path.realpath(os.path.join(equi_path, 'CONTCAR'))) - # check subdir + incar0['ISIF'] = 4 + + self.assertEqual(os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')), + os.path.realpath(os.path.join(self.target_path, 'POSCAR'))) + ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR')) + dfm_dirs.sort() for ii in dfm_dirs: - self.assertEqual(os.path.realpath(os.path.join(ii, 'INCAR')), - os.path.realpath(os.path.join(target_path, 'INCAR'))) - self.assertEqual(os.path.realpath(os.path.join(ii, 'KPOINTS')), - os.path.realpath(os.path.join(target_path, 'KPOINTS'))) - self.assertEqual(os.path.realpath(os.path.join(ii, 'POTCAR')), - os.path.realpath(os.path.join(target_path, 'POTCAR'))) + st_file = os.path.join(ii, 'POSCAR') + self.assertTrue(os.path.isfile(st_file)) + strain_json_file = os.path.join(ii, 'strain.json') + self.assertTrue(os.path.isfile(strain_json_file)) diff --git a/tests/auto_test/test_eos.py b/tests/auto_test/test_eos.py index 1cddb92c7..6dfb31f6e 100644 --- a/tests/auto_test/test_eos.py +++ b/tests/auto_test/test_eos.py @@ -1,81 +1,101 @@ -import os,sys,json,glob,shutil +import os, sys, json, glob, shutil import dpdata import numpy as np import unittest +import dpdata +from monty.serialization import loadfn, dumpfn +from pymatgen.io.vasp import Incar sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) __package__ = 'auto_test' + from .context import make_kspacing_kpoints from .context import setUpModule -from pymatgen.io.vasp import Incar -from dpgen.auto_test.gen_01_eos import make_vasp +from dpgen.auto_test.EOS import EOS -class Test01(unittest.TestCase): - def tearDown(self): - if os.path.exists('01.eos'): - shutil.rmtree('01.eos') - - def test_make_vasp_rlx_cell_shape (self): - jdata = { - 'relax_incar' : 'vasp_input/INCAR.rlx', - 'potcar_map': {'Si': 'vasp_input/POTCAR' }, - 'vol_start': 15, - 'vol_end': 25, - 'vol_step': 1.0, - 'eos_relax_cell_shape': True, + +class TestEOS(unittest.TestCase): + + def setUp(self): + _jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Li": "vasp_input/POTCAR"} + }, + "properties": [ + { + "type": "eos", + "skip": False, + "vol_start": 0.8, + "vol_end": 1.2, + "vol_step": 0.01, + "cal_setting": { + "relax_pos": True, + "relax_shape": True, + "relax_vol": False, + "overwrite_interaction":{ + "type": "deepmd", + "model": "lammps_input/frozen_model.pb", + "type_map":{"Al": 0} + } + } + } + ] } - make_vasp(jdata, 'confs/si/mp-149') - - target_path = '01.eos/si/mp-149/vasp-relax_incar' - equi_path = '00.equi/si/mp-149/vasp-relax_incar' - dfm_dirs = glob.glob(os.path.join(target_path, 'vol*')) - - # check root INCAR + + self.equi_path = 'confs/std-fcc/relaxation/relax_task' + self.source_path = 'equi/vasp' + self.target_path = 'confs/std-fcc/eos_00' + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + self.confs = _jdata["structures"] + self.inter_param = _jdata["interaction"] + self.prop_param = _jdata['properties'] + + self.eos = EOS(_jdata['properties'][0]) + + def tearDown(self): + if os.path.exists(self.equi_path): + shutil.rmtree(self.equi_path) + if os.path.exists(self.target_path): + shutil.rmtree(self.target_path) + + def test_task_type(self): + self.assertEqual('eos', self.eos.task_type()) + + def test_task_param(self): + self.assertEqual(self.prop_param[0], self.eos.task_param()) + + def test_make_confs_0(self): + + if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')): + with self.assertRaises(RuntimeError): + self.eos.make_confs(self.target_path, self.equi_path) + shutil.copy(os.path.join(self.source_path, 'CONTCAR'), os.path.join(self.equi_path, 'CONTCAR')) + task_list = self.eos.make_confs(self.target_path, self.equi_path) + dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*')) + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) - incar1 = Incar.from_file(os.path.join(target_path, 'INCAR')) - self.assertFalse(incar0 == incar1) incar0['ISIF'] = 4 - self.assertTrue(incar0 == incar1) - # check root POTCAR - with open(os.path.join('vasp_input', 'POTCAR')) as fp: - pot0 = fp.read() - with open(os.path.join(target_path, 'POTCAR')) as fp: - pot1 = fp.read() - self.assertEqual(pot0, pot1) - # check subdir + for ii in dfm_dirs: - self.assertTrue(os.path.isfile(os.path.join(ii, 'KPOINTS'))) + self.assertTrue(os.path.isfile(os.path.join(ii, 'POSCAR'))) + eos_json_file = os.path.join(ii, 'eos.json') + self.assertTrue(os.path.isfile(eos_json_file)) + eos_json = loadfn(eos_json_file) self.assertEqual(os.path.realpath(os.path.join(ii, 'POSCAR.orig')), - os.path.realpath(os.path.join(equi_path, 'CONTCAR'))) - self.assertEqual(os.path.realpath(os.path.join(ii, 'INCAR')), - os.path.realpath(os.path.join(target_path, 'INCAR'))) - self.assertEqual(os.path.realpath(os.path.join(ii, 'POTCAR')), - os.path.realpath(os.path.join(target_path, 'POTCAR'))) + os.path.realpath(os.path.join(self.equi_path, 'CONTCAR'))) sys = dpdata.System(os.path.join(ii, 'POSCAR')) - vol = float(ii.split('/')[-1].split('-')[1]) natoms = sys.get_natoms() - self.assertAlmostEqual(vol, np.linalg.det(sys['cells'][0]) / natoms) - + self.assertAlmostEqual(eos_json['volume'], np.linalg.det(sys['cells'][0]) / natoms) - def test_make_vasp_norlx_cell_shape (self): - jdata = { - 'relax_incar' : 'vasp_input/INCAR.rlx', - 'potcar_map': {'Si': 'vasp_input/POTCAR' }, - 'vol_start': 15, - 'vol_end': 25, - 'vol_step': 1.0, - 'eos_relax_cell_shape': False, - } - make_vasp(jdata, 'confs/si/mp-149') - - target_path = '01.eos/si/mp-149/vasp-relax_incar' - equi_path = '00.equi/si/mp-149/vasp-relax_incar' - dfm_dirs = glob.glob(os.path.join(target_path, 'vol*')) - - # check root INCAR - incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) - incar1 = Incar.from_file(os.path.join(target_path, 'INCAR')) - self.assertFalse(incar0 == incar1) - incar0['ISIF'] = 2 - self.assertTrue(incar0 == incar1) + def test_make_confs_1(self): + self.eos.reprod = True + shutil.copy(os.path.join(self.source_path, 'CONTCAR'), os.path.join(self.equi_path, 'CONTCAR')) + with self.assertRaises(RuntimeError): + self.eos.make_confs(self.target_path, self.equi_path) diff --git a/tests/auto_test/test_lammps.py b/tests/auto_test/test_lammps.py new file mode 100644 index 000000000..517757e13 --- /dev/null +++ b/tests/auto_test/test_lammps.py @@ -0,0 +1,91 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +from monty.serialization import loadfn, dumpfn + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.lib.lammps import inter_deepmd +from dpgen.auto_test.Lammps import Lammps + + +class TestLammps(unittest.TestCase): + + def setUp(self): + self.jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "deepmd", + "model": "lammps_input/frozen_model.pb", + "deepmd_version": "1.1.0", + "type_map": {"Al": 0} + }, + "relaxation": { + "cal_type": "relaxation", + "cal_setting": {"relax_pos": True, + "relax_shape": True, + "relax_vol": True} + } + } + + self.equi_path = 'confs/std-fcc/relaxation/relax_task' + self.source_path = 'equi/lammps' + + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + if not os.path.isfile(os.path.join(self.equi_path,'POSCAR')): + shutil.copy(os.path.join(self.source_path, 'Al-fcc.vasp'), os.path.join('confs/std-fcc','POSCAR')) + + + self.confs = self.jdata["structures"] + self.inter_param = self.jdata["interaction"] + self.relax_param = self.jdata["relaxation"] + self.Lammps = Lammps(self.inter_param, os.path.join(self.source_path, 'Al-fcc.vasp')) + + def tearDown(self): + if os.path.exists('confs/std-fcc/relaxation'): + shutil.rmtree('confs/std-fcc/relaxation') + + def test_set_inter_type_func(self): + self.Lammps.set_inter_type_func() + self.assertEqual(inter_deepmd, self.Lammps.inter_func) + + def test_set_model_param(self): + self.Lammps.set_model_param() + model_param = {'model_name': ['frozen_model.pb'], + 'param_type': {"Al": 0}, + 'deepmd_version': '1.1.0'} + self.assertEqual(model_param, self.Lammps.model_param) + + def test_make_potential_files(self): + cwd=os.getcwd() + abs_equi_path=os.path.abspath(self.equi_path) + self.Lammps.make_potential_files(abs_equi_path) + self.assertTrue(os.path.islink(os.path.join(self.equi_path, "frozen_model.pb"))) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, 'inter.json'))) + ret=loadfn(os.path.join(self.equi_path, 'inter.json')) + self.assertTrue(self.inter_param,ret) + os.chdir(cwd) + + def test_make_input_file(self): + cwd=os.getcwd() + abs_equi_path=os.path.abspath('confs/std-fcc/relaxation/relax_task') + shutil.copy(os.path.join('confs/std-fcc','POSCAR'), os.path.join(self.equi_path, 'POSCAR')) + self.Lammps.make_input_file(abs_equi_path,'relaxation', self.relax_param) + self.assertTrue(os.path.isfile(os.path.join(abs_equi_path, "conf.lmp"))) + self.assertTrue(os.path.islink(os.path.join(abs_equi_path, "in.lammps"))) + self.assertTrue(os.path.isfile(os.path.join(abs_equi_path, "task.json"))) + + def test_forward_common_files(self): + fc_files = ['in.lammps', 'frozen_model.pb'] + self.assertEqual(self.Lammps.forward_common_files(), fc_files) + + def test_backward_files(self): + backward_files = ['log.lammps', 'outlog', 'dump.relax'] + self.assertEqual(self.Lammps.backward_files(), backward_files) diff --git a/tests/auto_test/test_make_prop.py b/tests/auto_test/test_make_prop.py new file mode 100644 index 000000000..ed733236d --- /dev/null +++ b/tests/auto_test/test_make_prop.py @@ -0,0 +1,92 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +from monty.serialization import loadfn, dumpfn + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from pymatgen.io.vasp import Incar +from dpgen.auto_test.common_prop import make_property + + +class TestMakeProperty(unittest.TestCase): + jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": "vasp_input", + "potcars": {"Al": "POT_Al"} + }, + "properties": [ + { + "type": "eos", + "skip": False, + "vol_start": 0.8, + "vol_end": 1.2, + "vol_step": 0.01, + "cal_setting": { + "relax_pos": True, + "relax_shape": True, + "relax_vol": False, + "overwrite_interaction":{ + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix":"vasp_input", + "potcars": {"Al": "POT_Al"} + } + } + } + ] + } + + def tearDown(self): + if os.path.exists('confs/std-fcc/eos_00'): + shutil.rmtree('confs/std-fcc/eos_00') + if os.path.exists('confs/std-fcc/relaxation'): + shutil.rmtree('confs/std-fcc/relaxation') + + def test_make_eos(self): + confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + property_list = self.jdata["properties"] + + target_path = 'confs/std-fcc/eos_00' + equi_path = 'confs/std-fcc/relaxation/relax_task' + source_path = 'equi/vasp' + + if not os.path.exists(equi_path): + os.makedirs(equi_path) + shutil.copy(os.path.join(source_path, 'CONTCAR_Al_fcc'), os.path.join(equi_path, 'CONTCAR')) + + make_property(confs, inter_param, property_list) + + dfm_dirs = glob.glob(os.path.join(target_path, 'task.*')) + + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) + incar0['ISIF'] = 4 + + with open(os.path.join('vasp_input', 'POT_Al')) as fp: + pot0 = fp.read() + for ii in dfm_dirs: + self.assertTrue(os.path.isfile(os.path.join(ii, 'KPOINTS'))) + incar1 = Incar.from_file(os.path.join(ii, 'INCAR')) + self.assertTrue(incar0 == incar1) + self.assertTrue(os.path.isfile(os.path.join(ii, 'INCAR'))) + self.assertTrue(os.path.isfile(os.path.join(ii, 'POSCAR'))) + self.assertTrue(os.path.isfile(os.path.join(ii, 'POTCAR'))) + self.assertTrue(os.path.isfile(os.path.join(ii, 'task.json'))) + inter_json_file = os.path.join(ii, 'inter.json') + self.assertTrue(os.path.isfile(inter_json_file)) + inter_json = loadfn(inter_json_file) + self.assertEqual(inter_json, inter_param) + self.assertEqual(os.path.realpath(os.path.join(ii, 'POSCAR.orig')), + os.path.realpath(os.path.join(equi_path, 'CONTCAR'))) + with open(os.path.join(ii, 'POTCAR')) as fp: + poti = fp.read() + self.assertEqual(pot0, poti) diff --git a/tests/auto_test/test_mpdb.py b/tests/auto_test/test_mpdb.py new file mode 100644 index 000000000..8323d77b0 --- /dev/null +++ b/tests/auto_test/test_mpdb.py @@ -0,0 +1,47 @@ +import os +import sys +import unittest +from pymatgen import Structure +from pymatgen.analysis.structure_matcher import StructureMatcher +from monty.serialization import loadfn,dumpfn + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.mpdb import get_structure +try: + os.environ['MAPI_KEY'] + exist_key=True +except: + exist_key=False + + +def fit(struct0,struct1) : + m = StructureMatcher() + if m.fit(struct0, struct1) : + return True + return False + +@unittest.skipIf(not exist_key,"skip mpdb") +class TestMpdb(unittest.TestCase): + + def setUp(self): + if 'MAPI_KEY' in os.environ: + self.key=os.environ['MAPI_KEY'] + else: + self.key=None + self.mpid='mp-141' + self.st_file=self.mpid+'.vasp' + self.st0_file=os.path.join('confs/',self.mpid,self.mpid+'.cif') + + + def tearDown(self): + if os.path.exists(self.st_file): + os.remove(self.st_file) + + def test_get_structure (self): + st1=get_structure(self.mpid) + st0=Structure.from_file(self.st0_file) + self.assertTrue(fit(st0,st1)) diff --git a/tests/auto_test/test_refine.py b/tests/auto_test/test_refine.py new file mode 100644 index 000000000..e758ca7ba --- /dev/null +++ b/tests/auto_test/test_refine.py @@ -0,0 +1,100 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +from monty.serialization import loadfn, dumpfn +from pymatgen.io.vasp import Incar + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.common_prop import make_property +from dpgen.auto_test.refine import make_refine + + +class TestMakeProperty(unittest.TestCase): + jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": "vasp_input", + "potcars": {"Al": "POT_Al"} + }, + "properties": [ + { + "type": "eos", + "skip": False, + "vol_start": 0.8, + "vol_end": 1.2, + "vol_step": 0.01, + "cal_setting": { + "relax_pos": True, + "relax_shape": True, + "relax_vol": False, + "overwrite_interaction":{ + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix":"vasp_input", + "potcars": {"Al": "POT_Al"} + } + } + } + ] + } + + def tearDown(self): + if os.path.exists('confs/std-fcc/eos_00'): + shutil.rmtree('confs/std-fcc/eos_00') + if os.path.exists('confs/std-fcc/eos_02'): + shutil.rmtree('confs/std-fcc/eos_02') + if os.path.exists('confs/std-fcc/relaxation'): + shutil.rmtree('confs/std-fcc/relaxation') + + def test_make_eos(self): + + pwd=os.getcwd() + confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + property_list = self.jdata["properties"] + + target_path_0 = 'confs/std-fcc/eos_00' + target_path_2 = 'confs/std-fcc/eos_02' + equi_path = 'confs/std-fcc/relaxation/relax_task' + source_path = 'equi/vasp' + + if not os.path.exists(equi_path): + os.makedirs(equi_path) + shutil.copy(os.path.join(source_path, 'CONTCAR_Al_fcc'), os.path.join(equi_path, 'CONTCAR')) + + make_property(confs, inter_param, property_list) + + dfm_dirs_0 = glob.glob(os.path.join(target_path_0, 'task.*')) + + for ii in dfm_dirs_0: + self.assertTrue(os.path.isfile(os.path.join(ii, 'POSCAR'))) + shutil.copy(os.path.join(ii, 'POSCAR'),os.path.join(ii, 'CONTCAR')) + + path_to_work = os.path.abspath(target_path_0) + new_prop_list=[ + { + "type": "eos", + "init_from_suffix": "00", + "output_suffix": "02", + "cal_setting": { + "relax_pos": True, + "relax_shape": True, + "relax_vol": False, + "input_prop": "lammps_input/lammps_high"} + } + ] + #ret=make_refine('00', '02', path_to_work) + #self.assertEqual(len(ret),len(dfm_dirs_0)) + make_property(confs, inter_param, new_prop_list) + self.assertTrue(os.path.isdir(path_to_work.replace('00','02'))) + os.chdir(pwd) + dfm_dirs_2 = glob.glob(os.path.join(target_path_2, 'task.*')) + self.assertEqual(len(dfm_dirs_2),len(dfm_dirs_0)) diff --git a/tests/auto_test/test_surface.py b/tests/auto_test/test_surface.py new file mode 100644 index 000000000..7e02bc880 --- /dev/null +++ b/tests/auto_test/test_surface.py @@ -0,0 +1,101 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +import dpdata +from monty.serialization import loadfn, dumpfn +from pymatgen import Structure +from pymatgen.io.vasp import Incar +from pymatgen.core.surface import SlabGenerator + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.Surface import Surface + + +class TestSurface(unittest.TestCase): + + def setUp(self): + _jdata = { + "structures": ["confs/mp-141"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Yb": "vasp_input/POTCAR"} + }, + "properties": [ + { + "type": "surface", + "min_slab_size": 10, + "min_vacuum_size": 11, + "pert_xz": 0.01, + "max_miller": 1, + "cal_type": "relaxation" + } + ] + } + + self.equi_path = 'confs/mp-141/relaxation/relax_task' + self.source_path = 'equi/vasp' + self.target_path = 'confs/mp-141/surface_00' + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + self.confs = _jdata["structures"] + self.inter_param = _jdata["interaction"] + self.prop_param = _jdata['properties'] + + self.surface = Surface(_jdata['properties'][0]) + + def tearDown(self): + if os.path.exists(os.path.abspath(os.path.join(self.equi_path,'..'))): + shutil.rmtree(os.path.abspath(os.path.join(self.equi_path,'..'))) + if os.path.exists(self.equi_path): + shutil.rmtree(self.equi_path) + if os.path.exists(self.target_path): + shutil.rmtree(self.target_path) + + def test_task_type(self): + self.assertEqual('surface', self.surface.task_type()) + + def test_task_param(self): + self.assertEqual(self.prop_param[0], self.surface.task_param()) + + def test_make_confs_0(self): + if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')): + with self.assertRaises(RuntimeError): + self.surface.make_confs(self.target_path, self.equi_path) + shutil.copy(os.path.join(self.source_path, 'mp-141.vasp'), os.path.join(self.equi_path, 'CONTCAR')) + task_list = self.surface.make_confs(self.target_path, self.equi_path) + self.assertEqual(len(task_list), 7) + dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*')) + + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) + incar0['ISIF'] = 4 + + self.assertEqual(os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')), + os.path.realpath(os.path.join(self.target_path, 'POSCAR'))) + ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR')) + dfm_dirs.sort() + for ii in dfm_dirs: + st_file = os.path.join(ii, 'POSCAR') + self.assertTrue(os.path.isfile(st_file)) + st0 = Structure.from_file(st_file) + st1_file = os.path.join(ii, 'POSCAR.tmp') + self.assertTrue(os.path.isfile(st1_file)) + st1 = Structure.from_file(st1_file) + miller_json_file = os.path.join(ii, 'miller.json') + self.assertTrue(os.path.isfile(miller_json_file)) + miller_json = loadfn(miller_json_file) + sl = SlabGenerator(ref_st, + miller_json, + self.prop_param[0]["min_slab_size"], + self.prop_param[0]["min_vacuum_size"]) + slb = sl.get_slab() + st2 = Structure(slb.lattice, slb.species, slb.frac_coords) + self.assertEqual(len(st1), len(st2)) diff --git a/tests/auto_test/test_vacancy.py b/tests/auto_test/test_vacancy.py new file mode 100644 index 000000000..cb27bccd0 --- /dev/null +++ b/tests/auto_test/test_vacancy.py @@ -0,0 +1,90 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +import dpdata +from monty.serialization import loadfn, dumpfn +from pymatgen import Structure +from pymatgen.io.vasp import Incar +from pymatgen.symmetry.analyzer import SpacegroupAnalyzer +from pymatgen.analysis.defects.core import Vacancy as pmg_Vacancy + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.Vacancy import Vacancy + + +class TestVacancy(unittest.TestCase): + + def setUp(self): + _jdata = { + "structures": ["confs/hp-Li"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Yb": "vasp_input/POTCAR"} + }, + "properties": [ + { + "type": "vacancy", + "supercell": [1, 1, 1] + } + ] + } + + self.equi_path = 'confs/hp-Li/relaxation/relax_task' + self.source_path = 'equi/vasp' + self.target_path = 'confs/hp-Li/vacancy_00' + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + self.confs = _jdata["structures"] + self.inter_param = _jdata["interaction"] + self.prop_param = _jdata['properties'] + + self.vacancy = Vacancy(_jdata['properties'][0]) + + def tearDown(self): + if os.path.exists(self.equi_path): + shutil.rmtree(self.equi_path) + if os.path.exists(self.target_path): + shutil.rmtree(self.target_path) + + def test_task_type(self): + self.assertEqual('vacancy', self.vacancy.task_type()) + + def test_task_param(self): + self.assertEqual(self.prop_param[0], self.vacancy.task_param()) + + def test_make_confs_0(self): + if not os.path.exists(os.path.join(self.equi_path, 'CONTCAR')): + with self.assertRaises(RuntimeError): + self.vacancy.make_confs(self.target_path, self.equi_path) + shutil.copy(os.path.join(self.source_path, 'CONTCAR'), os.path.join(self.equi_path, 'CONTCAR')) + task_list = self.vacancy.make_confs(self.target_path, self.equi_path) + dfm_dirs = glob.glob(os.path.join(self.target_path, 'task.*')) + self.assertEqual(len(dfm_dirs), 5) + + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR.rlx')) + incar0['ISIF'] = 4 + + self.assertEqual(os.path.realpath(os.path.join(self.equi_path, 'CONTCAR')), + os.path.realpath(os.path.join(self.target_path, 'POSCAR'))) + ref_st = Structure.from_file(os.path.join(self.target_path, 'POSCAR')) + sga = SpacegroupAnalyzer(ref_st) + sym_st = sga.get_symmetrized_structure() + equiv_site_seq = list(sym_st.equivalent_sites) + dfm_dirs.sort() + for ii in dfm_dirs: + st_file = os.path.join(ii, 'POSCAR') + self.assertTrue(os.path.isfile(st_file)) + st0 = Structure.from_file(st_file) + vac_site = equiv_site_seq.pop(0) + vac = pmg_Vacancy(ref_st, vac_site[0], charge=0.0) + st1 = vac.generate_defect_structure(self.prop_param[0]['supercell']) + self.assertEqual(st0, st1) diff --git a/tests/auto_test/test_vasp.py b/tests/auto_test/test_vasp.py new file mode 100644 index 000000000..ccaa5fc6c --- /dev/null +++ b/tests/auto_test/test_vasp.py @@ -0,0 +1,131 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +import unittest +from dpdata import LabeledSystem +from pymatgen.io.vasp import Incar +from monty.serialization import loadfn, dumpfn + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from dpgen.auto_test.VASP import VASP +from dpgen.generator.lib.vasp import incar_upper + + +class TestVASP(unittest.TestCase): + + def setUp(self): + self.jdata = { + "structures": ["confs/hp-*"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR", + "potcar_prefix": ".", + "potcars": {"Li": "vasp_input/POTCAR"} + }, + "relaxation": { + "cal_type": "relaxation", + "cal_setting": {"relax_pos":True, + "relax_shape":True, + "relax_vol":True} + } + } + + self.conf_path = 'confs/hp-Li' + self.equi_path = 'confs/hp-Li/relaxation/relax_task' + self.source_path = 'equi/vasp' + if not os.path.exists(self.equi_path): + os.makedirs(self.equi_path) + + self.confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + self.task_param = self.jdata["relaxation"] + self.VASP = VASP(inter_param, os.path.join(self.conf_path, 'POSCAR')) + + def tearDown(self): + if os.path.exists('confs/hp-Li/relaxation'): + shutil.rmtree('confs/hp-Li/relaxation') + if os.path.exists('inter.json'): + os.remove('inter.json') + if os.path.exists('POTCAR'): + os.remove('POTCAR') + + def test_make_potential_files(self): + if not os.path.exists(os.path.join(self.equi_path, 'POSCAR')): + with self.assertRaises(FileNotFoundError): + self.VASP.make_potential_files(self.equi_path) + shutil.copy(os.path.join(self.conf_path, 'POSCAR'), os.path.join(self.equi_path, 'POSCAR')) + self.VASP.make_potential_files(self.equi_path) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, "POTCAR"))) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, 'inter.json'))) + + def test_make_input_file_1(self): + param=self.task_param.copy() + param["cal_setting"]= {"relax_pos":True, + "relax_shape":True, + "relax_vol":False} + self.VASP.make_input_file(self.equi_path,'relaxation',param) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],4) + + def test_make_input_file_2(self): + self.VASP.make_input_file(self.equi_path,'relaxation',self.task_param) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, "task.json"))) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, "KPOINTS"))) + self.assertTrue(os.path.isfile(os.path.join(self.equi_path, "INCAR"))) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],3) + + def test_make_input_file_3(self): + param=self.task_param.copy() + param["cal_setting"]= {"relax_pos":True, + "relax_shape":False, + "relax_vol":False} + self.VASP.make_input_file(self.equi_path,'relaxation',param) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],2) + + def test_make_input_file_4(self): + param=self.task_param.copy() + param["cal_setting"]= {"relax_pos":False, + "relax_shape":True, + "relax_vol":False} + self.VASP.make_input_file(self.equi_path,'relaxation',param) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],5) + + def test_make_input_file_5(self): + param=self.task_param.copy() + param["cal_setting"]= {"relax_pos":False, + "relax_shape":True, + "relax_vol":True} + self.VASP.make_input_file(self.equi_path,'relaxation',param) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],6) + + def test_make_input_file_5(self): + param=self.task_param.copy() + param["cal_setting"]= {"relax_pos":False, + "relax_shape":True, + "relax_vol":True, + "kspacing":0.01} + self.VASP.make_input_file(self.equi_path,'relaxation',param) + incar=incar_upper(Incar.from_file(os.path.join(self.equi_path, "INCAR"))) + self.assertTrue(incar['ISIF'],6) + self.assertTrue(incar['KSPACING'],0.01) + + def test_compuate(self): + ret=self.VASP.compute(os.path.join(self.conf_path,'relaxation')) + self.assertIsNone(ret) + shutil.copy(os.path.join(self.source_path, 'OUTCAR'), os.path.join(self.equi_path, 'OUTCAR')) + ret=self.VASP.compute(self.equi_path) + ret_ref=loadfn(os.path.join(self.source_path, 'outcar.json')) + self.assertTrue(ret,ret_ref.as_dict()) + + def test_backward_files(self): + backward_files = ['OUTCAR', 'outlog', 'CONTCAR', 'OSZICAR', 'XDATCAR'] + self.assertEqual(self.VASP.backward_files(), backward_files) diff --git a/tests/auto_test/test_vasp_equi.py b/tests/auto_test/test_vasp_equi.py new file mode 100644 index 000000000..59b78c2f1 --- /dev/null +++ b/tests/auto_test/test_vasp_equi.py @@ -0,0 +1,85 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +from monty.serialization import loadfn, dumpfn +import unittest + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from pymatgen.io.vasp import Incar +from dpgen.auto_test.common_equi import make_equi, post_equi +from dpgen.auto_test.calculator import make_calculator + + +class TestEqui(unittest.TestCase): + jdata = { + "structures": ["confs/hp-Li"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Li": "vasp_input/POTCAR"} + }, + "relaxation": { + "cal_type": "relaxation", + "cal_setting":{"input_prop": "vasp_input/INCAR"} + } + } + + def tearDown(self): + if os.path.exists('confs/hp-Li/relaxation'): + shutil.rmtree('confs/hp-Li/relaxation') + + def test_make_equi(self): + confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + relax_param = self.jdata["relaxation"] + make_equi(confs, inter_param, relax_param) + + target_path = 'confs/hp-Li/relaxation/relax_task' + source_path = 'vasp_input' + + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR')) + incar1 = Incar.from_file(os.path.join(target_path, 'INCAR')) + self.assertTrue(incar0 == incar1) + + with open(os.path.join('vasp_input', 'POTCAR')) as fp: + pot0 = fp.read() + with open(os.path.join(target_path, 'POTCAR')) as fp: + pot1 = fp.read() + self.assertEqual(pot0, pot1) + + self.assertTrue(os.path.isfile(os.path.join(target_path, 'KPOINTS'))) + + task_json_file = os.path.join(target_path, 'task.json') + self.assertTrue(os.path.isfile(task_json_file)) + task_json = loadfn(task_json_file) + self.assertEqual(task_json, relax_param) + + inter_json_file = os.path.join(target_path, 'inter.json') + self.assertTrue(os.path.isfile(inter_json_file)) + inter_json = loadfn(inter_json_file) + self.assertEqual(inter_json, inter_param) + + self.assertTrue(os.path.islink(os.path.join(target_path, 'POSCAR'))) + + def test_post_equi(self): + confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + relax_param = self.jdata["relaxation"] + target_path = 'confs/hp-Li/relaxation/relax_task' + source_path = 'equi/vasp' + + poscar = os.path.join(source_path, 'POSCAR') + make_equi(confs, inter_param, relax_param) + shutil.copy(os.path.join(source_path, 'OUTCAR'), os.path.join(target_path, 'OUTCAR')) + shutil.copy(os.path.join(source_path, 'CONTCAR'), os.path.join(target_path, 'CONTCAR')) + post_equi(confs, inter_param) + + result_json_file = os.path.join(target_path, 'result.json') + result_json = loadfn(result_json_file) + self.assertTrue(os.path.isfile(result_json_file)) diff --git a/tests/auto_test/test_vasp_equi_std.py b/tests/auto_test/test_vasp_equi_std.py new file mode 100644 index 000000000..34f44a9b0 --- /dev/null +++ b/tests/auto_test/test_vasp_equi_std.py @@ -0,0 +1,73 @@ +import os, sys, json, glob, shutil +import dpdata +import numpy as np +from monty.serialization import loadfn, dumpfn +import unittest + +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) +__package__ = 'auto_test' + +from .context import make_kspacing_kpoints +from .context import setUpModule + +from pymatgen.io.vasp import Incar +from dpgen.auto_test.common_equi import make_equi, post_equi +from dpgen.auto_test.calculator import make_calculator + + +class TestEqui(unittest.TestCase): + jdata = { + "structures": ["confs/std-fcc"], + "interaction": { + "type": "vasp", + "incar": "vasp_input/INCAR.rlx", + "potcar_prefix": ".", + "potcars": {"Al": "vasp_input/POT_Al"} + }, + "relaxation": { + "cal_type": "relaxation", + "cal_setting":{"input_prop": "vasp_input/INCAR"} + } + } + + def tearDown(self): + if os.path.isfile('confs/std-fcc/POSCAR'): + os.remove('confs/std-fcc/POSCAR') + if os.path.exists('confs/std-fcc/relaxation'): + shutil.rmtree('confs/std-fcc/relaxation') + + def test_make_equi(self): + confs = self.jdata["structures"] + inter_param = self.jdata["interaction"] + relax_param = self.jdata["relaxation"] + make_equi(confs, inter_param, relax_param) + + self.assertTrue(os.path.isfile("confs/std-fcc/POSCAR")) + + target_path = 'confs/std-fcc/relaxation/relax_task' + source_path = 'vasp_input' + + incar0 = Incar.from_file(os.path.join('vasp_input', 'INCAR')) + incar1 = Incar.from_file(os.path.join(target_path, 'INCAR')) + self.assertTrue(incar0 == incar1) + + with open(os.path.join('vasp_input', 'POT_Al')) as fp: + pot0 = fp.read() + with open(os.path.join(target_path, 'POTCAR')) as fp: + pot1 = fp.read() + self.assertEqual(pot0, pot1) + + self.assertTrue(os.path.isfile(os.path.join(target_path, 'KPOINTS'))) + + task_json_file = os.path.join(target_path, 'task.json') + self.assertTrue(os.path.isfile(task_json_file)) + task_json = loadfn(task_json_file) + self.assertEqual(task_json, relax_param) + + inter_json_file = os.path.join(target_path, 'inter.json') + self.assertTrue(os.path.isfile(inter_json_file)) + inter_json = loadfn(inter_json_file) + self.assertEqual(inter_json, inter_param) + + self.assertTrue(os.path.islink(os.path.join(target_path, 'POSCAR'))) + diff --git a/tests/auto_test/vasp_input/POT_Al b/tests/auto_test/vasp_input/POT_Al new file mode 100644 index 000000000..b6ee454ab --- /dev/null +++ b/tests/auto_test/vasp_input/POT_Al @@ -0,0 +1 @@ +Al POTCAR PBE diff --git a/tests/dispatcher/test_lazy_local_context.py b/tests/dispatcher/test_lazy_local_context.py index 8de1875d8..87270d836 100644 --- a/tests/dispatcher/test_lazy_local_context.py +++ b/tests/dispatcher/test_lazy_local_context.py @@ -157,7 +157,7 @@ def test_file(self) : def test_call(self) : self.job = LazyLocalContext('loc', None) - proc = self.job.call('sleep 3') + proc = self.job.call('sleep 1.5') self.assertFalse(self.job.check_finish(proc)) time.sleep(1) self.assertFalse(self.job.check_finish(proc)) @@ -167,8 +167,8 @@ def test_call(self) : self.assertEqual(r, 0) self.assertEqual(o.read(), b'') self.assertEqual(e.read(), b'') - r,o,e=self.job.get_return(proc) - self.assertEqual(r, 0) - self.assertEqual(o, None) - self.assertEqual(e, None) + # r,o,e=self.job.get_return(proc) + # self.assertEqual(r, 0) + # self.assertEqual(o, None) + # self.assertEqual(e, None) diff --git a/tests/dispatcher/test_local_context.py b/tests/dispatcher/test_local_context.py index 694d48fa2..1b050250d 100644 --- a/tests/dispatcher/test_local_context.py +++ b/tests/dispatcher/test_local_context.py @@ -346,7 +346,7 @@ def test_file(self) : def test_call(self) : work_profile = LocalSession({'work_path':'rmt'}) self.job = LocalContext('loc', work_profile) - proc = self.job.call('sleep 3') + proc = self.job.call('sleep 1.5') self.assertFalse(self.job.check_finish(proc)) time.sleep(1) self.assertFalse(self.job.check_finish(proc)) @@ -356,8 +356,8 @@ def test_call(self) : self.assertEqual(r, 0) self.assertEqual(o.read(), b'') self.assertEqual(e.read(), b'') - r,o,e=self.job.get_return(proc) - self.assertEqual(r, 0) - self.assertEqual(o, None) - self.assertEqual(e, None) + # r,o,e=self.job.get_return(proc) + # self.assertEqual(r, 0) + # self.assertEqual(o, None) + # self.assertEqual(e, None) diff --git a/tests/generator/context.py b/tests/generator/context.py index d79bbfeb4..3183e9440 100644 --- a/tests/generator/context.py +++ b/tests/generator/context.py @@ -14,7 +14,9 @@ param_gaussian_file = 'param-pyridine-gaussian.json' param_siesta_file = 'param-pyridine-siesta.json' param_cp2k_file = 'param-pyridine-cp2k.json' -param_cp2k_file_v1 = 'param-pyridine-cp2k-choose-vdw.json' +param_cp2k_file_exinput = 'param-mgo-cp2k-exinput.json' +ref_cp2k_file_input = 'cp2k_test_ref.inp' +ref_cp2k_file_exinput = 'cp2k_test_exref.inp' machine_file = 'machine-local.json' machine_file_v1 = 'machine-local-v1.json' param_diy_file = 'param-mg-vasp-diy.json' diff --git a/tests/generator/cp2k_make_fp_files/exinput/template.inp b/tests/generator/cp2k_make_fp_files/exinput/template.inp new file mode 100644 index 000000000..2ac3a4f04 --- /dev/null +++ b/tests/generator/cp2k_make_fp_files/exinput/template.inp @@ -0,0 +1,60 @@ +&FORCE_EVAL + METHOD QS + STRESS_TENSOR ANALYTICAL + &PRINT + &FORCES ON + &END FORCES + &STRESS_TENSOR ON + &END FORCES + &END PRINT + &DFT + BASIS_SET_FILE_NAME BASIS_MOLOPT + POTENTIAL_FILE_NAME GTH_POTENTIALS + BASIS_SET_FILE_NAME BASIS_ADMM_MOLOPT + BASIS_SET_FILE_NAME BASIS_ADMM + &MGRID + CUTOFF 400 + REL_CUTOFF 60 + &END MGRID + &QS + EPS_DEFAULT 1.0E-13 + &END QS + &SCF + EPS_SCF 3.0E-7 + MAX_SCF 50 + &OUTER_SCF + EPS_SCF 3.0E-7 + MAX_SCF 10 + &END OUTER_SCF + &OT + MINIMIZER DIIS + PRECONDITIONER FULL_SINGLE_INVERSE + &END OT + &END SCF + &XC + + &XC_FUNCTIONAL PBE + &END XC_FUNCTIONAL + &END XC + &END DFT + &SUBSYS + &CELL + ABC LEFT FOR DPGEN + &END CELL + &COORD + @include coord.xyz + &END COORD + &KIND O + BASIS_SET DZVP-MOLOPT-SR-GTH + POTENTIAL GTH-PBE-q6 + &END KIND + &KIND Mg + BASIS_SET DZVP-MOLOPT-SR-GTH + POTENTIAL GTH-PBE-q10 + &END KIND + &END SUBSYS +&END FORCE_EVAL + +&GLOBAL + PROJECT DPGEN +&END GLOBAL diff --git a/tests/generator/cp2k_test_exref.inp b/tests/generator/cp2k_test_exref.inp new file mode 100644 index 000000000..11eea2abe --- /dev/null +++ b/tests/generator/cp2k_test_exref.inp @@ -0,0 +1,59 @@ +&FORCE_EVAL + METHOD QS + STRESS_TENSOR ANALYTICAL + &PRINT + &FORCES ON + &END FORCES + &STRESS_TENSOR ON + &END FORCES + &END PRINT + &DFT + BASIS_SET_FILE_NAME BASIS_MOLOPT + POTENTIAL_FILE_NAME GTH_POTENTIALS + BASIS_SET_FILE_NAME BASIS_ADMM_MOLOPT + BASIS_SET_FILE_NAME BASIS_ADMM + &MGRID + CUTOFF 400 + REL_CUTOFF 60 + &END MGRID + &QS + EPS_DEFAULT 1.0E-13 + &END QS + &SCF + EPS_SCF 3.0E-7 + MAX_SCF 50 + &OUTER_SCF + EPS_SCF 3.0E-7 + MAX_SCF 10 + &END OUTER_SCF + &OT + MINIMIZER DIIS + PRECONDITIONER FULL_SINGLE_INVERSE + &END OT + &END SCF + &XC + + &XC_FUNCTIONAL PBE + &END XC_FUNCTIONAL + &END XC + &END DFT + &SUBSYS + &CELL + &END CELL + &COORD + @include coord.xyz + &END COORD + &KIND O + BASIS_SET DZVP-MOLOPT-SR-GTH + POTENTIAL GTH-PBE-q6 + &END KIND + &KIND Mg + BASIS_SET DZVP-MOLOPT-SR-GTH + POTENTIAL GTH-PBE-q10 + &END KIND + &END SUBSYS +&END FORCE_EVAL + +&GLOBAL + PROJECT DPGEN +&END GLOBAL diff --git a/tests/generator/cp2k_test_ref.inp b/tests/generator/cp2k_test_ref.inp new file mode 100644 index 000000000..6197bbb97 --- /dev/null +++ b/tests/generator/cp2k_test_ref.inp @@ -0,0 +1,60 @@ +&GLOBAL +PROJECT DPGEN +&END GLOBAL +&FORCE_EVAL +METHOD QS +STRESS_TENSOR ANALYTICAL +&DFT +BASIS_SET_FILE_NAME ./cp2k_basis_pp_file/BASIS_MOLOPT +POTENTIAL_FILE_NAME ./cp2k_basis_pp_file/GTH_POTENTIALS +CHARGE 0 +UKS F +MULTIPLICITY 1 +&MGRID +CUTOFF 400 +REL_CUTOFF 50 +NGRIDS 4 +&END MGRID +&QS +EPS_DEFAULT 1.0E-12 +&END QS +&SCF +SCF_GUESS ATOMIC +EPS_SCF 1.0E-6 +MAX_SCF 50 +&OT +MINIMIZER DIIS +PRECONDITIONER FULL_SINGLE_INVERSE +&END OT +&END SCF +&XC +&XC_FUNCTIONAL PBE +&END XC_FUNCTIONAL +&END XC +&END DFT +&SUBSYS +&CELL +&END CELL +&COORD +@include coord.xyz +&END COORD +&KIND H +BASIS_SET DZVP-MOLOPT-GTH +POTENTIAL GTH-PBE-q1 +&END KIND +&KIND C +BASIS_SET DZVP-MOLOPT-GTH +POTENTIAL GTH-PBE-q4 +&END KIND +&KIND N +BASIS_SET DZVP-MOLOPT-GTH +POTENTIAL GTH-PBE-q5 +&END KIND +&END SUBSYS +&PRINT +&FORCES ON +&END FORCES +&STRESS_TENSOR ON +&END STRESS_TENSOR +&END PRINT +&END FORCE_EVAL diff --git a/tests/generator/param-mgo-cp2k-exinput.json b/tests/generator/param-mgo-cp2k-exinput.json new file mode 100644 index 000000000..85a286f4d --- /dev/null +++ b/tests/generator/param-mgo-cp2k-exinput.json @@ -0,0 +1,105 @@ +{ + "type_map": ["C", "H", "N"], + "mass_map": [16, 2, 14], + + "init_data_prefix": "/home/linfengz/SCR/wanghan/deepgen.pyridine/init", + "init_data_sys": ["Pyridine-I", + "Pyridine-II" + ], + "init_batch_size": [1, 1], + "sys_configs": [ + ["/home/linfengz/SCR/wanghan/data/pyridine/pyI.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/00009?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyI.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[7-8]?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyI.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[5-6]?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyI.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[0-4]?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyII.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/00009?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyII.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[7-8]?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyII.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[5-6]?/POSCAR"], + ["/home/linfengz/SCR/wanghan/data/pyridine/pyII.POSCAR.01x01x01/01.scale_pert/sys-0080-0080-0016/scale-1.000/0000[0-4]?/POSCAR"] + ], + "_comment": "0 1 2 3", + "_comment": "4 5 6 7", + "sys_batch_size": [1, 1, 1, 1, + 1, 1, 1, 1 + ], + + "_comment": " 00.train ", + "numb_models": 4, + "train_param": "input.json", + "default_training_param" : { + "_comment": " model parameters", + "use_smooth": true, + "sel_a": [81, 81, 20], + "rcut_smth": 0.50, + "rcut": 6.50, + "filter_neuron": [25, 50, 100], + "filter_resnet_dt": false, + "n_axis_neuron": 12, + "n_neuron": [240, 240, 240], + "resnet_dt": true, + "coord_norm": true, + "type_fitting_net": false, + + "_comment": " traing controls", + "systems": [], + "set_prefix": "set", + "stop_batch": 400000, + "batch_size": 1, + "start_lr": 0.002, + "decay_steps": 2000, + "decay_rate": 0.95, + "seed": 0, + + "start_pref_e": 0.02, + "limit_pref_e": 2, + "start_pref_f": 1000, + "limit_pref_f": 1, + "start_pref_v": 0.0, + "limit_pref_v": 0.0, + + "_comment": " display and restart", + "_comment": " frequencies counted in batch", + "disp_file": "lcurve.out", + "disp_freq": 2000, + "numb_test": 10, + "save_freq": 20000, + "save_ckpt": "model.ckpt", + "load_ckpt": "model.ckpt", + "disp_training": true, + "time_training": true, + "profiling": false, + "profiling_file": "timeline.json", + + "_comment": "that's all" + }, + + "_comment": " 01.model_devi ", + "_comment": "model_devi_skip: the first x of the recorded frames", + "model_devi_dt": 0.001, + "model_devi_skip": 0, + "model_devi_f_trust_lo": 0.050, + "model_devi_f_trust_hi": 0.150, + "model_devi_e_trust_lo": 1e10, + "model_devi_e_trust_hi": 1e10, + "model_devi_clean_traj": false, + "model_devi_jobs": [ + {"sys_idx": [0,4], "temps": [ 50], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "00"}, + {"sys_idx": [1,5], "temps": [ 50], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "01"}, + {"sys_idx": [0,4], "temps": [ 50], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "02"}, + {"sys_idx": [1,5], "temps": [ 50], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "03"}, + {"sys_idx": [0,4], "temps": [ 100], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "04"}, + {"sys_idx": [1,5], "temps": [ 100], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "05"}, + {"sys_idx": [0,4], "temps": [ 100], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "06"}, + {"sys_idx": [1,5], "temps": [ 100], "press": [1e0,1e1,1e2,1e3,1e4,2e4,4e4], "trj_freq": 10, "nsteps": 1000, "ensemble": "npt", "_idx": "07"} + ], + + "_comment": " 02.fp ", + "fp_style": "cp2k", + "shuffle_poscar": false, + "fp_task_max": 100, + "fp_task_min": 10, + "fp_pp_path": ".", + "fp_pp_files": [], + "external_input_path": "./cp2k_make_fp_files/exinput/template.inp", + "_comment": " that's all " +} diff --git a/tests/generator/test_make_fp.py b/tests/generator/test_make_fp.py index 18cf6ccd6..0607c8132 100644 --- a/tests/generator/test_make_fp.py +++ b/tests/generator/test_make_fp.py @@ -16,7 +16,9 @@ from .context import param_siesta_file from .context import param_gaussian_file from .context import param_cp2k_file -from .context import param_cp2k_file_v1 +from .context import param_cp2k_file_exinput +from .context import ref_cp2k_file_input +from .context import ref_cp2k_file_exinput from .context import machine_file from .context import param_diy_file from .context import make_kspacing_kpoints @@ -129,67 +131,6 @@ DPGEN """ -cp2k_input_ref="\ -&GLOBAL\n\ -PROJECT DPGEN\n\ -&END GLOBAL\n\ -&FORCE_EVAL\n\ -METHOD QS\n\ -STRESS_TENSOR ANALYTICAL\n\ -&DFT\n\ -BASIS_SET_FILE_NAME ./cp2k_basis_pp_file/BASIS_MOLOPT\n\ -POTENTIAL_FILE_NAME ./cp2k_basis_pp_file/GTH_POTENTIALS\n\ -CHARGE 0\n\ -UKS F\n\ -MULTIPLICITY 1\n\ -&MGRID\n\ -CUTOFF 400\n\ -REL_CUTOFF 50\n\ -NGRIDS 4\n\ -&END MGRID\n\ -&QS\n\ -EPS_DEFAULT 1.0E-12\n\ -&END QS\n\ -&SCF\n\ -SCF_GUESS ATOMIC\n\ -EPS_SCF 1.0E-6\n\ -MAX_SCF 50\n\ -&OT\n\ -MINIMIZER DIIS\n\ -PRECONDITIONER FULL_SINGLE_INVERSE\n\ -&END OT\n\ -&END SCF\n\ -&XC\n\ -&XC_FUNCTIONAL PBE\n\ -&END XC_FUNCTIONAL\n\ -&END XC\n\ -&END DFT\n\ -&SUBSYS\n\ -&CELL\n\ -&END CELL\n\ -&COORD\n\ -@include coord.xyz\n\ -&END COORD\n\ -&KIND H\n\ -BASIS_SET DZVP-MOLOPT-GTH\n\ -POTENTIAL GTH-PBE-q1\n\ -&END KIND\n\ -&KIND C\n\ -BASIS_SET DZVP-MOLOPT-GTH\n\ -POTENTIAL GTH-PBE-q4\n\ -&END KIND\n\ -&KIND N\n\ -BASIS_SET DZVP-MOLOPT-GTH\n\ -POTENTIAL GTH-PBE-q5\n\ -&END KIND\n\ -&END SUBSYS\n\ -&PRINT\n\ -&FORCES ON\n\ -&END FORCES\n\ -&STRESS_TENSOR ON\n\ -&END STRESS_TENSOR\n\ -&END PRINT\n\ -&END FORCE_EVAL\n"; pwmat_input_ref = "4 1\n\ in.atom=atom.config\n\ @@ -471,7 +412,7 @@ def _check_gaussian_input_head(testCase, idx) : testCase.assertEqual(('\n'.join(lines)).strip(), gaussian_input_ref.strip()) -def _check_cp2k_input_head(testCase, idx) : +def _check_cp2k_input_head(testCase, idx, ref_out) : fp_path = os.path.join('iter.%06d' % idx, '02.fp') tasks = glob.glob(os.path.join(fp_path, 'task.*')) for ii in tasks : @@ -485,7 +426,7 @@ def _check_cp2k_input_head(testCase, idx) : if '&END CELL' in jj : cell_end_idx = idx lines_check = lines[:cell_start_idx+1] + lines[cell_end_idx:] - testCase.assertEqual(('\n'.join(lines_check)).strip(), cp2k_input_ref.strip()) + testCase.assertEqual(('\n'.join(lines_check)).strip(), ref_out.strip()) @@ -814,9 +755,39 @@ def test_make_fp_cp2k(self): make_fp(0, jdata, {}) _check_sel(self, 0, jdata['fp_task_max'], jdata['model_devi_f_trust_lo'], jdata['model_devi_f_trust_hi']) _check_poscars(self, 0, jdata['fp_task_max'], jdata['type_map']) - _check_cp2k_input_head(self, 0) + with open(ref_cp2k_file_input, 'r') as f: + cp2k_input_ref = ''.join(f.readlines()) + _check_cp2k_input_head(self, 0, cp2k_input_ref) _check_potcar(self, 0, jdata['fp_pp_path'], jdata['fp_pp_files']) shutil.rmtree('iter.000000') + def test_make_fp_cp2k_exinput(self): + if os.path.isdir('iter.000000') : + shutil.rmtree('iter.000000') + with open (param_cp2k_file_exinput, 'r') as fp : + jdata = json.load (fp) + with open (machine_file, 'r') as fp: + mdata = json.load (fp) + md_descript = [] + nsys = 2 + nmd = 3 + n_frame = 10 + for ii in range(nsys) : + tmp = [] + for jj in range(nmd) : + tmp.append(np.arange(0, 0.29, 0.29/10)) + md_descript.append(tmp) + atom_types = [0, 1, 2, 2, 0, 1] + type_map = jdata['type_map'] + _make_fake_md(0, md_descript, atom_types, type_map) + make_fp(0, jdata, {}) + _check_sel(self, 0, jdata['fp_task_max'], jdata['model_devi_f_trust_lo'], jdata['model_devi_f_trust_hi']) + _check_poscars(self, 0, jdata['fp_task_max'], jdata['type_map']) + with open(ref_cp2k_file_exinput, 'r') as f: + cp2k_exinput_ref = ''.join(f.readlines()) + _check_cp2k_input_head(self, 0, cp2k_exinput_ref) + _check_potcar(self, 0, jdata['fp_pp_path'], jdata['fp_pp_files']) + shutil.rmtree('iter.000000') + class TestMakeFPPWmat(unittest.TestCase): diff --git a/tests/generator/test_make_md.py b/tests/generator/test_make_md.py index 4f67b1fbe..02678e30b 100644 --- a/tests/generator/test_make_md.py +++ b/tests/generator/test_make_md.py @@ -3,6 +3,8 @@ import numpy as np import unittest +from dpgen.generator.run import parse_cur_job_sys_revmat + sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) __package__ = 'generator' from .context import make_model_devi @@ -207,10 +209,19 @@ def test_make_model_devi (self) : "model_devi_e_trust_hi": 1e10, "model_devi_plumed": True, "model_devi_jobs": [ - {"sys_idx": [0, 1], 'traj_freq': 10, "template":{"lmp": "lmp/input.lammps", "plm": "lmp/input.plumed"}, - "rev_mat":{ - "lmp": {"V_NSTEPS": [1000], "V_TEMP": [50, 100], "V_PRES": [1, 10]}, "plm": {"V_DIST0": [3,4], "V_DIST1": [5, 6]} - }} + {"sys_idx": [0, 1], 'traj_freq': 10, "template": {"lmp": "lmp/input.lammps", "plm": "lmp/input.plumed"}, + "rev_mat": { + "lmp": {"V_NSTEPS": [1000], "V_TEMP": [50, 100]}, "plm": {"V_DIST0": [3, 4]} + }, + "sys_rev_mat": { + "0": { + "lmp": {"V_PRES": [1, 10]}, "plm": {"V_DIST1": [5, 6]} + }, + "1": { + "lmp": {"V_PRES": [1, 5, 10]}, "plm": {"V_DIST1": [5, 6, 7]} + } + } + } ] } mdata = {'deepmd_version': '1'} @@ -223,23 +234,44 @@ def test_make_model_devi (self) : md_dir = os.path.join('iter.%06d' % 0, '01.model_devi') tasks = glob.glob(os.path.join(md_dir, 'task.*')) tasks.sort() - # 4 accounts for 2 systems each with 2 frames - self.assertEqual(len(tasks), (len(jdata['model_devi_jobs'][0]['rev_mat']['lmp']['V_NSTEPS']) * - len(jdata['model_devi_jobs'][0]['rev_mat']['lmp']['V_TEMP']) * - len(jdata['model_devi_jobs'][0]['rev_mat']['lmp']['V_PRES']) * - len(jdata['model_devi_jobs'][0]['rev_mat']['plm']['V_DIST0']) * - len(jdata['model_devi_jobs'][0]['rev_mat']['plm']['V_DIST1']) * - 4)) + # each system contains 2 frames + self.assertEqual(len(tasks), (len(jdata['model_devi_jobs'][0]['rev_mat']['lmp']['V_NSTEPS']) * + len(jdata['model_devi_jobs'][0]['rev_mat']['lmp']['V_TEMP']) * + len(jdata['model_devi_jobs'][0]['rev_mat']['plm']['V_DIST0']) * + (len(jdata['model_devi_jobs'][0]['sys_rev_mat']['0']['lmp']['V_PRES']) * + len(jdata['model_devi_jobs'][0]['sys_rev_mat']['0']['plm']['V_DIST1']) + + len(jdata['model_devi_jobs'][0]['sys_rev_mat']['1']['lmp']['V_PRES']) * + len(jdata['model_devi_jobs'][0]['sys_rev_mat']['1']['plm']['V_DIST1'])) * + 2)) cur_job = jdata['model_devi_jobs'][0] rev_keys = ['V_NSTEPS', 'V_TEMP', 'V_PRES', 'V_DIST0', 'V_DIST1'] rev_matrix = [] + # 2 systems with each 2 frames for i0 in cur_job['rev_mat']['lmp']['V_NSTEPS']: for i1 in cur_job['rev_mat']['lmp']['V_TEMP']: - for i2 in cur_job['rev_mat']['lmp']['V_PRES']: - for i3 in cur_job['rev_mat']['plm']['V_DIST0']: - for i4 in cur_job['rev_mat']['plm']['V_DIST1']: - rev_matrix.append([i0, i1, i2, i3, i4]) + for i3 in cur_job['rev_mat']['plm']['V_DIST0']: + for i2 in cur_job['sys_rev_mat']['0']['lmp']['V_PRES']: + for i4 in cur_job['sys_rev_mat']['0']['plm']['V_DIST1']: + rev_matrix.append([i0, i1, i2, i3, i4]) + for i0 in cur_job['rev_mat']['lmp']['V_NSTEPS']: + for i1 in cur_job['rev_mat']['lmp']['V_TEMP']: + for i3 in cur_job['rev_mat']['plm']['V_DIST0']: + for i2 in cur_job['sys_rev_mat']['0']['lmp']['V_PRES']: + for i4 in cur_job['sys_rev_mat']['0']['plm']['V_DIST1']: + rev_matrix.append([i0, i1, i2, i3, i4]) + for i0 in cur_job['rev_mat']['lmp']['V_NSTEPS']: + for i1 in cur_job['rev_mat']['lmp']['V_TEMP']: + for i3 in cur_job['rev_mat']['plm']['V_DIST0']: + for i2 in cur_job['sys_rev_mat']['1']['lmp']['V_PRES']: + for i4 in cur_job['sys_rev_mat']['1']['plm']['V_DIST1']: + rev_matrix.append([i0, i1, i2, i3, i4]) + for i0 in cur_job['rev_mat']['lmp']['V_NSTEPS']: + for i1 in cur_job['rev_mat']['lmp']['V_TEMP']: + for i3 in cur_job['rev_mat']['plm']['V_DIST0']: + for i2 in cur_job['sys_rev_mat']['1']['lmp']['V_PRES']: + for i4 in cur_job['sys_rev_mat']['1']['plm']['V_DIST1']: + rev_matrix.append([i0, i1, i2, i3, i4]) numb_rev = len(rev_matrix) for ii in range(len(tasks)): with open(os.path.join(tasks[ii], 'job.json')) as fp: @@ -247,7 +279,7 @@ def test_make_model_devi (self) : job_recd = json.load(fp) for kk in job_recd.keys(): kidx = rev_keys.index(kk) - self.assertEqual(rev_values[kidx], job_recd[kk]) + self.assertEqual(rev_values[kidx], job_recd[kk]) cwd_ = os.getcwd() os.chdir(tasks[0]) @@ -359,6 +391,47 @@ def test_parse_cur_job(self): self.assertEqual(rk, self.ref_keys) self.assertEqual(nl, self.ref_nlmp) self.assertEqual(rm, self.ref_matrix) + + +class TestParseCurJobSysRevMat(unittest.TestCase): + def setUp(self): + self.cur_job = { + "sys_idx": [0, 1], + "template":{"lmp": "lmp/input.lammps", "plm": "lmp/input.plumed"}, + "rev_mat":{ + "lmp": {"V_NSTEPS": [1000], "V_TEMP": [50, 100]}, "plm": {"V_DIST0": [3, 4]} + }, + "sys_rev_mat": { + "0": { + "lmp": {"V_PRES": [1, 10]}, + "plm": {"V_DIST1": [5, 6]} + }, + "1": { + "lmp": {"V_PRES": [1, 10, 20]}, + "plm": {"V_DIST1": [5, 6, 7]} + } + } + } + self.sys_ref_matrix = [[], []] + for i0 in self.cur_job['sys_rev_mat']['0']['lmp']['V_PRES']: + for i1 in self.cur_job['sys_rev_mat']['0']['plm']['V_DIST1']: + self.sys_ref_matrix[0].append([i0, i1]) + for i0 in self.cur_job['sys_rev_mat']['1']['lmp']['V_PRES']: + for i1 in self.cur_job['sys_rev_mat']['1']['plm']['V_DIST1']: + self.sys_ref_matrix[1].append([i0, i1]) + self.sys_ref_keys = ['V_PRES', 'V_DIST1'] + self.sys_ref_nlmp_0 = 1 + self.sys_ref_nlmp_1 = 1 + + def test_parse_cur_job(self): + rk0, rm0, nl0 = parse_cur_job_sys_revmat(self.cur_job, 0, use_plm=True) + rk1, rm1, nl1 = parse_cur_job_sys_revmat(self.cur_job, 1, use_plm=True) + self.assertEqual(rk0, self.sys_ref_keys) + self.assertEqual(nl0, self.sys_ref_nlmp_0) + self.assertEqual(rm0, self.sys_ref_matrix[0]) + self.assertEqual(rk1, self.sys_ref_keys) + self.assertEqual(nl1, self.sys_ref_nlmp_1) + self.assertEqual(rm1, self.sys_ref_matrix[1]) class MakeModelDeviByReviseMatrix(unittest.TestCase):