def open(cls, obj, nids=None, **kwargs): """ Flexible constructor. obj can be a :class:`Flow` or a string with the directory containing the Flow. nids is an optional list of :class:`Node` identifiers used to filter the set of :class:`Task` in the Flow. """ has_dirpath = False if is_string(obj): try: obj = Flow.pickle_load(obj) except: has_dirpath = True if not has_dirpath: # We have a Flow. smeth is the name of the Task method used to open the file. items = [] smeth = "open_" + cls.EXT.lower() for task in obj.iflat_tasks(nids=nids): #, status=obj.S_OK): open_method = getattr(task, smeth, None) if open_method is None: continue ncfile = open_method() if ncfile is not None: items.append((task.pos_str, ncfile)) return cls(*items) else: # directory --> search for files with the appropriate extension and open it with abiopen. if nids is not None: raise ValueError("nids cannot be used when obj is a directory.") return cls.from_dir(obj)
def abiopen(filepath): """ Factory function that opens any file supported by abipy. File type is detected from the extension Args: filepath: string with the filename. """ if os.path.basename(filepath) == "__AbinitFlow__.pickle": return Flow.pickle_load(filepath) cls = abifile_subclass_from_filename(filepath) return cls.from_file(filepath)
def test_flow(self): """ Testing flow creation and task registering """ flow = Flow(workdir=test_dir, manager=TaskManager.from_file( os.path.join(test_dir, "taskmanager.yml"))) inp = {} flow.register_task(input=inp) flow.allocate() self.assertTrue(flow.allocated) self.assertIsInstance(flow[0], Work) self.assertIsInstance(flow[0][0], Task) self.assertEqual(flow.check_status(), None)
def test_flow(self): """ Testing flow creation and task registering """ flow = Flow(workdir=test_dir, manager=TaskManager.from_file(os.path.join(test_dir, "taskmanager.yml"))) inp = {} flow.register_task(input=inp) flow.allocate() self.assertTrue(flow.allocated) self.assertIsInstance(flow[0], Work) self.assertIsInstance(flow[0][0], Task) self.assertEqual(flow.check_status(), None)
def abiopen(filepath): """ Factory function that opens any file supported by abipy. File type is detected from the extension Args: filepath: string with the filename. """ if os.path.basename(filepath) == "__AbinitFlow__.pickle": return Flow.pickle_load(filepath) # Handle old output files produced by Abinit. import re outnum = re.compile(".+\.out[\d]+") abonum = re.compile(".+\.abo[\d]+") if outnum.match(filepath) or abonum.match(filepath): return AbinitOutputFile.from_file(filepath) cls = abifile_subclass_from_filename(filepath) return cls.from_file(filepath)
def open(cls, obj, nids=None, **kwargs): """ Flexible constructor. obj can be a :class:`Flow` or a string with the directory containing the Flow. nids is an optional list of :class:`Node` identifiers used to filter the set of :class:`Task` in the Flow. """ has_dirpath = False if is_string(obj): try: obj = Flow.pickle_load(obj) except: has_dirpath = True items = [] if not has_dirpath: # We have a Flow. smeth is the name of the Task method used to open the file. smeth = "open_" + cls.EXT.lower() for task in obj.iflat_tasks(nids=nids): #, status=obj.S_OK): open_method = getattr(task, smeth, None) if open_method is None: continue ncfile = open_method() if ncfile is not None: items.append((task.pos_str, ncfile)) else: # directory --> search for files with the appropriate extension and open it with abiopen. if nids is not None: raise ValueError("nids cannot be used when obj is a directory.") from abipy.abilab import abiopen for dirpath, dirnames, filenames in os.walk(obj): filenames = [f for f in filenames if f.endswith(cls.EXT + ".nc") or f.endswith(cls.EXT)] for f in filenames: ncfile = abiopen(os.path.join(dirpath, f)) if ncfile is not None: items.append((ncfile.filepath, ncfile)) new = cls(*items) # Save a reference to the initial object so that we can reload it if needed #new._initial_object = obj return new
def create(self): """ create single abinit G0W0 flow """ # manager = 'slurm' if 'ceci' in self.spec['mode'] else 'shell' # an AbiStructure object has an overwritten version of get_sorted_structure that sorts according to Z # this could also be pulled into the constructor of Abistructure # abi_structure = self.structure.get_sorted_structure() from abipy import abilab item = copy.copy(self.structure.item) self.structure.__class__ = abilab.Structure self.structure = self.structure.get_sorted_structure_z() self.structure.item = item abi_structure = self.structure manager = TaskManager.from_user_config() # Initialize the flow. flow = Flow(self.work_dir, manager, pickle_protocol=0) # flow = Flow(self.work_dir, manager) # kpoint grid defined over density 40 > ~ 3 3 3 if self.spec['converge'] and not self.all_converged: # (2x2x2) gamma centered mesh for the convergence test on nbands and ecuteps # if kp_in is present in the specs a kp_in X kp_in x kp_in mesh is used for the convergence study if 'kp_in' in self.spec.data.keys(): if self.spec['kp_in'] > 9: print('WARNING:\nkp_in should be < 13 to generate an n x n x n mesh\nfor larger values a grid with ' 'density kp_in will be generated') kppa = self.spec['kp_in'] else: kppa = 2 else: # use the specified density for the final calculation with the converged nbands and ecuteps of other # stand alone calculations kppa = self.spec['kp_grid_dens'] gamma = True # 'standard' parameters for stand alone calculation scf_nband = self.get_bands(self.structure) + 20 # additional bands to accommodate for nbdbuf and a bit extra nscf_nband = [10 * self.get_bands(self.structure)] nksmall = None ecuteps = [8] extra_abivars = dict() # read user defined extra abivars from file 'extra_abivars' should be dictionary extra_abivars.update(read_extra_abivars()) # self.bands_fac = 0.5 if 'gwcomp' in extra_abivars.keys() else 1 # self.convs['nscf_nbands']['test_range'] = # tuple([self.bands_fac*x for x in self.convs['nscf_nbands']['test_range']]) ecut = extra_abivars.pop('ecut', 44) ecutsigx = extra_abivars.pop('ecutsigx', 44) if ecutsigx > ecut: raise RuntimeError('ecutsigx can not be largen than ecut') if ecutsigx < max(ecuteps): raise RuntimeError('ecutsigx < ecuteps this is not realistic') response_models = ['godby'] if 'ppmodel' in extra_abivars.keys(): response_models = [extra_abivars.pop('ppmodel')] if self.option is not None: for k in self.option.keys(): if k == 'ecut': ecut = self.option[k] if k in ['ecuteps', 'nscf_nbands']: pass else: extra_abivars.update({k: self.option[k]}) try: grid = read_grid_from_file(s_name(self.structure)+".full_res")['grid'] all_done = read_grid_from_file(s_name(self.structure)+".full_res")['all_done'] workdir = os.path.join(s_name(self.structure), 'w'+str(grid)) except (IOError, OSError): grid = 0 all_done = False workdir = None if not all_done: if (self.spec['test'] or self.spec['converge']) and not self.all_converged: if self.spec['test']: print('| setting test calculation') tests = SingleAbinitGWWork(self.structure, self.spec).tests response_models = [] else: if grid == 0: print('| setting convergence calculations for grid 0') # tests = SingleAbinitGWWorkFlow(self.structure, self.spec).convs tests = self.convs else: print('| extending grid') # tests = expand(SingleAbinitGWWorkFlow(self.structure, self.spec).convs, grid) tests = expand(self.convs, grid) ecuteps = [] nscf_nband = [] for test in tests: if tests[test]['level'] == 'scf': if self.option is None: extra_abivars.update({test + '_s': tests[test]['test_range']}) elif test in self.option: extra_abivars.update({test: self.option[test]}) else: extra_abivars.update({test + '_s': tests[test]['test_range']}) else: for value in tests[test]['test_range']: if test == 'nscf_nbands': nscf_nband.append(value * self.get_bands(self.structure)) # scr_nband takes nscf_nbands if not specified # sigma_nband takes scr_nbands if not specified if test == 'ecuteps': ecuteps.append(value) if test == 'response_model': response_models.append(value) elif self.all_converged: print('| setting up for testing the converged values at the high kp grid ') # add a bandstructure and dos calculation if os.path.isfile('bands'): nksmall = -30 # negative value > only bandstructure else: nksmall = 30 # in this case a convergence study has already been performed. # The resulting parameters are passed as option ecuteps = [self.option['ecuteps'], self.option['ecuteps'] + self.convs['ecuteps']['test_range'][1] - self.convs['ecuteps']['test_range'][0]] nscf_nband = [self.option['nscf_nbands'], self.option['nscf_nbands'] + self.convs['nscf_nbands'][ 'test_range'][1] - self.convs['nscf_nbands']['test_range'][0]] # for option in self.option: # if option not in ['ecuteps', 'nscf_nband']: # extra_abivars.update({option + '_s': self.option[option]}) else: print('| all is done for this material') return logger.info('ecuteps : %s ' % str(ecuteps)) logger.info('extra : %s ' % str(extra_abivars)) logger.info('nscf_nb : %s ' % str(nscf_nband)) inputs = g0w0_convergence_inputs(abi_structure, self.pseudo_table, kppa, nscf_nband, ecuteps, ecutsigx, scf_nband, ecut, accuracy="normal", spin_mode="unpolarized", smearing=None, response_models=response_models, charge=0.0, sigma_nband=None, scr_nband=None, gamma=gamma, nksmall=nksmall, extra_abivars=extra_abivars) work = G0W0Work(scf_inputs=inputs[0], nscf_inputs=inputs[1], scr_inputs=inputs[2], sigma_inputs=inputs[3]) # work = g0w0_extended_work(abi_structure, self.pseudo_table, kppa, nscf_nband, ecuteps, ecutsigx, scf_nband, # accuracy="normal", spin_mode="unpolarized", smearing=None, response_models=response_models, # charge=0.0, sigma_nband=None, scr_nband=None, gamma=gamma, nksmall=nksmall, **extra_abivars) print(workdir) flow.register_work(work, workdir=workdir) return flow.allocate()
def test_fixes(self): flow = Flow(workdir=test_dir, manager=TaskManager.from_file(os.path.join(test_dir, "taskmanager.yml"))) inp = {} flow.register_task(input=inp) flow.allocate()
def create(self): """ create single abinit G0W0 flow """ # manager = 'slurm' if 'ceci' in self.spec['mode'] else 'shell' # an AbiStructure object has an overwritten version of get_sorted_structure that sorts according to Z # this could also be pulled into the constructor of Abistructure # abi_structure = self.structure.get_sorted_structure() from abipy import abilab item = copy.copy(self.structure.item) self.structure.__class__ = abilab.Structure self.structure = self.structure.get_sorted_structure_z() self.structure.item = item abi_structure = self.structure manager = TaskManager.from_user_config() # Initialize the flow. flow = Flow(self.work_dir, manager, pickle_protocol=0) # flow = Flow(self.work_dir, manager) # kpoint grid defined over density 40 > ~ 3 3 3 if self.spec['converge'] and not self.all_converged: # (2x2x2) gamma centered mesh for the convergence test on nbands and ecuteps # if kp_in is present in the specs a kp_in X kp_in x kp_in mesh is used for the convergence study if 'kp_in' in self.spec.data.keys(): if self.spec['kp_in'] > 9: print( 'WARNING:\nkp_in should be < 13 to generate an n x n x n mesh\nfor larger values a grid with ' 'density kp_in will be generated') kppa = self.spec['kp_in'] else: kppa = 2 else: # use the specified density for the final calculation with the converged nbands and ecuteps of other # stand alone calculations kppa = self.spec['kp_grid_dens'] gamma = True # 'standard' parameters for stand alone calculation scf_nband = self.get_bands(self.structure) + 20 # additional bands to accommodate for nbdbuf and a bit extra nscf_nband = [10 * self.get_bands(self.structure)] nksmall = None ecuteps = [8] extra_abivars = dict() # read user defined extra abivars from file 'extra_abivars' should be dictionary extra_abivars.update(read_extra_abivars()) # self.bands_fac = 0.5 if 'gwcomp' in extra_abivars.keys() else 1 # self.convs['nscf_nbands']['test_range'] = # tuple([self.bands_fac*x for x in self.convs['nscf_nbands']['test_range']]) ecut = extra_abivars.pop('ecut', 44) ecutsigx = extra_abivars.pop('ecutsigx', 44) if ecutsigx > ecut: raise RuntimeError('ecutsigx can not be largen than ecut') if ecutsigx < max(ecuteps): raise RuntimeError('ecutsigx < ecuteps this is not realistic') response_models = ['godby'] if 'ppmodel' in extra_abivars.keys(): response_models = [extra_abivars.pop('ppmodel')] if self.option is not None: for k in self.option.keys(): if k == 'ecut': ecut = self.option[k] if k in ['ecuteps', 'nscf_nbands']: pass else: extra_abivars.update({k: self.option[k]}) try: grid = read_grid_from_file(s_name(self.structure) + ".full_res")['grid'] all_done = read_grid_from_file( s_name(self.structure) + ".full_res")['all_done'] workdir = os.path.join(s_name(self.structure), 'w' + str(grid)) except (IOError, OSError): grid = 0 all_done = False workdir = None if not all_done: if (self.spec['test'] or self.spec['converge']) and not self.all_converged: if self.spec['test']: print('| setting test calculation') tests = SingleAbinitGWWork(self.structure, self.spec).tests response_models = [] else: if grid == 0: print('| setting convergence calculations for grid 0') # tests = SingleAbinitGWWorkFlow(self.structure, self.spec).convs tests = self.convs else: print('| extending grid') # tests = expand(SingleAbinitGWWorkFlow(self.structure, self.spec).convs, grid) tests = expand(self.convs, grid) ecuteps = [] nscf_nband = [] for test in tests: if tests[test]['level'] == 'scf': if self.option is None: extra_abivars.update( {test + '_s': tests[test]['test_range']}) elif test in self.option: extra_abivars.update({test: self.option[test]}) else: extra_abivars.update( {test + '_s': tests[test]['test_range']}) else: for value in tests[test]['test_range']: if test == 'nscf_nbands': nscf_nband.append( value * self.get_bands(self.structure)) # scr_nband takes nscf_nbands if not specified # sigma_nband takes scr_nbands if not specified if test == 'ecuteps': ecuteps.append(value) if test == 'response_model': response_models.append(value) elif self.all_converged: print( '| setting up for testing the converged values at the high kp grid ' ) # add a bandstructure and dos calculation if os.path.isfile('bands'): nksmall = -30 # negative value > only bandstructure else: nksmall = 30 # in this case a convergence study has already been performed. # The resulting parameters are passed as option ecuteps = [ self.option['ecuteps'], self.option['ecuteps'] + self.convs['ecuteps']['test_range'][1] - self.convs['ecuteps']['test_range'][0] ] nscf_nband = [ self.option['nscf_nbands'], self.option['nscf_nbands'] + self.convs['nscf_nbands']['test_range'][1] - self.convs['nscf_nbands']['test_range'][0] ] # for option in self.option: # if option not in ['ecuteps', 'nscf_nband']: # extra_abivars.update({option + '_s': self.option[option]}) else: print('| all is done for this material') return logger.info('ecuteps : %s ' % str(ecuteps)) logger.info('extra : %s ' % str(extra_abivars)) logger.info('nscf_nb : %s ' % str(nscf_nband)) inputs = g0w0_convergence_inputs(abi_structure, self.pseudo_table, kppa, nscf_nband, ecuteps, ecutsigx, scf_nband, ecut, accuracy="normal", spin_mode="unpolarized", smearing=None, response_models=response_models, charge=0.0, sigma_nband=None, scr_nband=None, gamma=gamma, nksmall=nksmall, extra_abivars=extra_abivars) work = G0W0Work(scf_inputs=inputs[0], nscf_inputs=inputs[1], scr_inputs=inputs[2], sigma_inputs=inputs[3]) # work = g0w0_extended_work(abi_structure, self.pseudo_table, kppa, nscf_nband, ecuteps, ecutsigx, scf_nband, # accuracy="normal", spin_mode="unpolarized", smearing=None, response_models=response_models, # charge=0.0, sigma_nband=None, scr_nband=None, gamma=gamma, nksmall=nksmall, **extra_abivars) print(workdir) flow.register_work(work, workdir=workdir) return flow.allocate()