def from_inputfile(cls, inputfile):
if not (exists_and_isfile(inputfile)):
config = cls.generate_input(inputfile, config=None)
else:
config = cls.generate_input(inputfile, config=inputfile)
quests = cls.generate_questions(config=inputfile)
config = quests.check_only(inputfile)
plot_config = {}
if config['plot_pes'].value == 'yes':
plot_config = {}
plot_config['x_label'] = 'mode'
plot_config['x_label_unit'] = False
plot_config['y_label_unit'] = True
plot_config['y_label'] = 'energy'
plot_config = {'': plot_config}
presets = ''
presets += f"y_label = energy\n"
presets += f"x_label_unit = True\n"
presets += f"[save_plot(yes)]\nplot_file = plot_fit_pes_nm.png\n"
presets += "legend = {}\n"
plot_input = config['plot_pes']['plot_inputfile']
if exists_and_isfile(plot_input):
plot_config = Plot.generate_input(plot_input,
config=plot_input,
presets=presets)
else:
plot_config = Plot.generate_input(plot_input,
config=plot_config,
presets=presets)
return cls(config, plot_config)
def __init__(self, config):
""" Class to create initial conditions due to user input. Initial conditions are saved
in a file for further usage.
"""
logger = get_logger('setup_propagation.log', 'setup_propagation')
SetupBase.__init__(self, logger)
# Open DB of initial conditions once, so that it is available
sampling = Sampling.from_db(config['sampling_db'])
#Make sure that inputfile for the SPP exists and is complete
if exists_and_isfile(config['spp']): lconfig = config['spp']
else: lconfig = None
SurfacePointProvider.generate_input(config['spp'], config=lconfig)
#Make sure that inputfile for RunTrajectory exists and is complete
if exists_and_isfile(config['prop']): lconfig = config['prop']
else: lconfig = None
RunTrajectory.generate_input(config['prop'], config=lconfig)
#
if config['n_traj'] == -1:
ntraj = len(sampling._db)
else:
ntraj = config['n_traj']
if sampling.nconditions < ntraj:
logger.error(f"Too few initial conditions in {config['sampling_db']}")
self.setup_folders(range(ntraj), config, sampling)
def __init__(self, config):
""" Class to create initial conditions due to user input. Initial conditions are saved
in a file for further usage.
"""
logger = get_logger('setup_spectrum.log', 'setup_spectrum')
logger.header('SETUP SPECTRUM', config)
SetupBase.__init__(self, logger)
#
logger.info(f"Opening sampling database {config['sampling_db']}")
sampling = Sampling.from_db(config['sampling_db'], logger=logger)
if not exists_and_isfile(config['spp']):
presets="""
use_db = no
"""
logger.info(f"Setting up SPP inputfile: {config['spp']}")
SurfacePointProvider.generate_input(config['spp'], config=None, presets=presets)
else:
logger.info(f"Using SPP inputfile as it is")
if not exists_and_isfile(config['sp_calc']):
presets=f"""
properties = {config['properties']}
nstates = {config['nstates']}
init_db = init.db
"""
logger.info(f"Setting up inputfile for the single point calculations")
SinglePointCalculation.generate_input(config['sp_calc'], config=None, presets=presets)
else:
logger.info(f"Using inputfile for the single point calculations as it is")
logger.info("Starting to prepare the folders...")
self.setup_folders(range(config['n_cond']), config, sampling)
def _check_res_db(self, config, sampling):
if exists_and_isfile(config['init_db']):
info = sampling.info
check1 = all(item in info['variables']
for item in config['properties'])
if 'nstates' in info['dimensions']:
if (info['dimensions']['nstates'] >= config['nstates']):
if 'natoms' in info['dimensions']:
if (info['dimensions']['natoms'] ==
sampling._db.info['dimensions']['natoms']):
check2 = True
else:
check2 = False
if 'nmodes' in info['dimensions']:
if (info['dimensions']['nmodes'] ==
sampling._db.info['dimensions']['nmodes']):
check2 = True
else:
check2 = False
else:
check2 = False
else:
check2 = False
if check1 and check2:
return
else:
self.logger.error(
f"Given database is not appropriate for the results: {config['init_db']}"
)
def fill_db(filename, npoints):
if exists_and_isfile(filename) is True:
os.remove(filename)
ho = HarmonicOscillator()
model = PyrazineSala({'n_states': 3})
nmodes = len(model.crd)
nstates = 3
db = PySurfDB.generate_database(filename,
data=['crd', 'energy'],
dimensions={
'nmodes': nmodes,
'nstates': nstates
},
model=True)
x = (np.random.random((npoints, nmodes)) - 0.5) * 20
y = []
for r in x:
db.append('crd', r)
y += [
model.get(Request(r, ['energy'],
[i for i in range(nstates)]))['energy']
]
db.append(
'energy',
model.get(Request(r, ['energy'],
[i for i in range(nstates)]))['energy'])
db.increase
return db
def __init__(self, config):
setup = SubfolderHandle(config['folder'], config['subfolder'])
counter = 0
for file in setup.fileiter(config['dbfiles']):
if counter == 0:
copied = False
if not exists_and_isfile(config['mother_db']):
copy(file, config['mother_db'])
copied = True
info = PySurfDB.info_database(config['mother_db'])
if 'natoms' not in info['dimensions']:
model = True
else:
model = False
mother_db = PySurfDB.load_database(
config['mother_db'],
data=info['variables'],
dimensions=info['dimensions'],
model=model,
sp=False)
counter += 1
if copied is True:
continue
CombineDBs(mother_db, file, start=config['start_value'])
print(f"Added file {file} to DB")
def __init__(self, config, logger=None):
"""
Args:
config, ColtObj:
The config contains the information from the colt
questions of the class
logger, Logger:
Logger for the class. If not provided a new logger is created.
"""
if logger is None:
self.logger = get_logger('sp_calc.log', 'sp_calc')
self.logger.header('Single Point Calculation', config)
else:
self.logger = logger
#
self.logger.info(f"Taking information from {config['init_db']}")
sampling = Sampling.from_db(config['init_db'], logger=self.logger)
if not (exists_and_isfile(config['spp'])):
spp_config = SurfacePointProvider.generate_input(config['spp'])
else:
spp_config = SurfacePointProvider.generate_input(
config['spp'], config=config['spp'])
self.logger.debug(f"Setting up SPP with {config['spp']}")
if sampling.molecule is not None:
spp = SurfacePointProvider.from_config(
spp_config,
config['properties'],
config['nstates'],
sampling.natoms,
nghost_states=config['nghost_states'],
atomids=sampling.atomids)
else: #model calculation
spp = SurfacePointProvider, from_config(spp_config,
config['properties'],
config['nstates'],
sampling.nmodes)
crd = sampling.get_condition(0).crd
#check that DB can take the results
self.logger.debug(
f"Checking whether {config['init_db']} can take the results")
self._check_res_db(config, sampling)
with self.logger.info_block("SPP calculation"):
res = spp.request(crd,
config['properties'],
states=[st for st in range(config['nstates'])])
self.logger.info(f"Writing results to: {config['init_db']}")
for prop, value in res.iter_data():
sampling.set(prop, value)
def from_inputfile(cls, inputfile):
if not(exists_and_isfile(inputfile)):
config = cls.generate_input(inputfile, config=None)
else:
config = cls.generate_input(inputfile, config=inputfile)
quests = cls.generate_questions(config=inputfile)
config = quests.check_only(inputfile)
if config['plot_spectrum'].value == 'yes':
plot_config = {}
if config['broadening'].value == 'yes':
plot_config['x_start'] = config['broadening']['energy_start']
plot_config['x_end'] = config['broadening']['energy_end']
plot_config['x_label'] = 'energy'
plot_config['y_label_unit'] = True
plot_config['y_label'] = 'intensity'
plot_config['x_units'] = config['energy_units']
plot_config['x_label_unit'] = True
plot_config = {'': plot_config}
presets = ''
if config['broadening'].value == 'yes':
presets += f"x_start = {config['broadening']['energy_start']}\n"
presets += f"x_end = {config['broadening']['energy_end']}\n"
presets += f"x_label = energy\n"
presets += f"y_label_unit = True\n"
presets += f"y_label = intensity\n"
presets += f"y_units = a.u.\n"
presets += f"x_units = {config['energy_units']}\n"
presets += f"x_label_unit = True\n"
presets += f"[save_plot(yes)]\nplot_file = spectrum/spectrum.png\n"
plot_input = config['plot_spectrum']['plot_inputfile']
if exists_and_isfile(plot_input):
plot_config = Plot.generate_input(plot_input, config=plot_input, presets=presets)
else:
plot_config = Plot.generate_input(plot_input, config=plot_config, presets=presets)
return cls(config, plot_config)
def from_inputfile(cls, inputfile):
if not (exists_and_isfile(inputfile)):
config = cls.generate_input(inputfile, config=None)
else:
config = cls.generate_input(inputfile, config=inputfile)
quests = cls.generate_questions(config=inputfile)
config = quests.check_only(inputfile)
plot_config = {}
if config['plot_population'].value == 'yes':
plot_config = {}
# plot_config['x_label'] = 'time'
plot_config['x_units'] = config['time_units']
plot_config['x_label_unit'] = True
plot_config['y_label_unit'] = False
plot_config['y_label'] = 'population'
plot_config = {'': plot_config}
presets = ''
presets += f"y_start = 0.0\n"
presets += f"y_end = 1.0\n"
presets += f"x_label = time\n"
presets += f"y_label_unit = False\n"
presets += f"y_label = population\n"
presets += f"x_units = {config['time_units']}\n"
presets += f"x_label_unit = True\n"
presets += f"[save_plot(yes)]\nplot_file = population.png\n"
presets += "legend = {}\n"
plot_input = config['plot_population']['plot_inputfile']
if exists_and_isfile(plot_input):
plot_config = Plot.generate_input(plot_input,
config=plot_input,
presets=presets)
else:
plot_config = Plot.generate_input(plot_input,
config=plot_config,
presets=presets)
return cls(config, plot_config)
def __init__(self, config):
db = DynDB.load_database(config['prop_db'], read_only=True)
nstates = db.nstates
npoints = len(db)
data = np.empty((npoints, nstates+1), dtype=float)
data[:, 0] = np.array(db['time'])[:, 0]
data[:, 1:] = np.array(db['energy'])-config['reference_energy']
currstate = np.array(db['currstate'])[:, 0]
plot_config = {}
plot_config['x_label'] = 'time'
plot_config['y_label'] = 'energy'
plot_config['y_units'] = 'eV'
plot_config['x_units'] = 'fs'
plot_config['y_label_unit'] = True
plot_config['x_label_unit'] = True
plot_config = {'': plot_config}
# plot_config['save_plot'] = {'plot_file': 'pes_traj.png'}
presets = """
x_label = time
y_label = energy
y_units = eV
x_units = fs
y_label_unit = True
x_label_unit = True
"""
if exists_and_isfile(self._plot_input):
plot_config = Plot.generate_input(self._plot_input, config=self._plot_input, presets=presets)
else:
plot_config = Plot.generate_input(self._plot_input, config=plot_config, presets=presets)
myplot = Plot(plot_config)
if nstates == 1:
save_plot = True
show_plot = True
else:
save_plot = False
show_plot = False
myax = myplot.line_plot(data[:,[0,1]], x_units_in=['time', 'au'], y_units_in=['energy', 'au'], ax=None, save_plot=save_plot, show_plot=show_plot)
for state in range(1, nstates):
myax = myplot.line_plot(data[:,[0, state+1]], x_units_in=['time', 'au'], y_units_in=['energy', 'au'], ax=myax, show_plot=False, save_plot=False)
curr_plot = np.empty((npoints, 2), dtype=float)
curr_plot[:, 0] = data[:, 0]
for idx, state in enumerate(currstate):
curr_plot[idx, 1] = data[idx, int(state + 1)]
myax = myplot.line_plot(curr_plot, x_units_in=['time', 'au'], y_units_in=['energy', 'au'], ax=myax, save_plot=True, show_plot=True, line_props={'marker': 'o', 'color': 'red'})
def __init__(self, config):
self.logger = get_logger('collect_spectrum.log',
'collect_spectrum.log')
subfolderhandle = SubfolderHandle(self.folder, self.subfolder)
specfile = os.path.join(self.folder, 'spectrum.db')
if exists_and_isfile(specfile):
self.sampling = Sampling.from_db(specfile, logger=self.logger)
self.dimensions = self.sampling.info['dimensions']
self.variables = self.sampling.info['variables']
if not self._check_sampling(self.sampling):
logger.error(f"Existing spectrum db is corrupted")
for counter in range(self.sampling.nconditions,
len(subfolderhandle)):
snew = Sampling.from_db(subfolderhandle.get_file(
self.file, counter),
logger=self.logger)
if self._check_sampling(snew):
self.add_condition(snew)
else:
counter = 0
for file in subfolderhandle.fileiter('init.db'):
snew = Sampling.from_db(file, logger=self.logger)
if counter == 0:
self.sampling = Sampling.create_db(specfile,
snew.info['variables'],
snew.info['dimensions'],
snew.molecule,
snew.modes,
snew.model,
sp=False,
logger=self.logger)
self.dimensions = self.sampling.info['dimensions']
self.variables = self.sampling.info['variables']
self.add_condition(snew)
counter += 1
def __init__(self, config):
model = ModelBase._models[config['model'].value].from_config(
config['model'])
nstates = model.nstates
crd_equi = model.crd
npoints = 100
data = np.empty((npoints, nstates + 1), dtype=float)
data[:, 0] = np.linspace(config['start_plot'], config['end_plot'],
npoints)
for idx, point in enumerate(data[:, 0]):
crd = np.zeros(model.crd.size)
crd[config['mode']] = point
data[idx, 1:] = model.get(
Request(crd,
properties=['energy'],
states=[i for i in range(nstates)]))['energy']
print(data)
plot_config = {}
plot_config['x_label'] = f"mode config['mode']"
plot_config['x_start'] = config['start_plot']
plot_config['x_end'] = config['end_plot']
plot_config['y_label'] = 'energy'
plot_config['y_units'] = 'eV'
plot_config['x_units'] = 'au'
plot_config['y_label_unit'] = True
plot_config['x_label_unit'] = True
plot_config = {'': plot_config}
presets = """
x_label = mode
y_label = energy
y_units = eV
x_units = au
y_label_unit = True
x_label_unit = True
"""
if exists_and_isfile(self._plot_input):
plot_config = Plot.generate_input(self._plot_input,
config=self._plot_input,
presets=presets)
else:
plot_config = Plot.generate_input(self._plot_input,
config=None,
presets=None)
myplot = Plot(plot_config)
if nstates == 1:
save_plot = True
show_plot = True
else:
save_plot = False
show_plot = False
myax = myplot.line_plot(data[:, [0, 1]],
x_units_in=['energy', 'a.u.'],
y_units_in=['energy', 'au'],
ax=None,
save_plot=save_plot,
show_plot=show_plot)
for state in range(1, nstates - 1):
myax = myplot.line_plot(data[:, [0, state + 1]],
x_units_in=['energy', 'a.u.'],
y_units_in=['energy', 'au'],
ax=myax,
show_plot=False,
save_plot=False)
myax = myplot.line_plot(data[:, [0, nstates]],
x_units_in=['energy', 'a.u.'],
y_units_in=['energy', 'au'],
ax=myax,
show_plot=True,
save_plot=True)
