def gradient(file_prefix):
""" generate gradient DataFile
"""
name = autofile.name.gradient(file_prefix)
writer_ = autofile.write.gradient
reader_ = autofile.read.gradient
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def energy(file_prefix):
""" generate energy DataFile
"""
name = autofile.name.energy(file_prefix)
writer_ = autofile.write.energy
reader_ = autofile.read.energy
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def geometry(file_prefix):
""" generate geometry DataFile
"""
name = autofile.name.geometry(file_prefix)
writer_ = autofile.write.geometry
reader_ = autofile.read.geometry
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def data_series_specifier(file_prefix, map_dct_, spec_keys):
""" data series specifier DataFile
Specifiers are stored in information files according to `map_dct_` and read
back out according to `spec_keys_`. The file may contain auxiliary
information (such as SMILES along with InChI), but for the read to work it
must contain each specifier value.
:param map_dct_: Maps on the specifier list to the values stored in the
information file, by key.
:type map_dct_: dict[key: callable]
:param spec_keys: Keys to the original specifier values.
:type spec_keys: tuple[str]
"""
def writer_(specs):
inf_dct = {key: map_(specs) for key, map_ in map_dct_.items()}
inf_obj = autoinf.object_(inf_dct)
return autofile.write.information(inf_obj)
def reader_(inf_str):
inf_obj = autofile.read.information(inf_str)
inf_dct = dict(inf_obj)
return tuple(map(inf_dct.__getitem__, spec_keys))
name = autofile.name.information(file_prefix)
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def lennard_jones_sigma(file_prefix):
""" generate lennard_jones_sigma DataFile
"""
name = autofile.name.lennard_jones_sigma(file_prefix)
writer_ = autofile.write.lennard_jones_sigma
reader_ = autofile.read.lennard_jones_sigma
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def trajectory(file_prefix):
""" generate trajectory DataFile
"""
name = autofile.name.trajectory(file_prefix)
writer_ = autofile.write.trajectory
reader_ = _not_implemented
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def vmatrix(file_prefix):
""" generate vmatrix DataFile
"""
name = autofile.name.vmatrix(file_prefix)
writer_ = autofile.write.vmatrix
reader_ = autofile.read.vmatrix
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def hessian(file_prefix):
""" generate hessian DataFile
"""
name = autofile.name.hessian(file_prefix)
writer_ = autofile.write.hessian
reader_ = autofile.read.hessian
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def information(file_prefix, function=None):
""" information DataFile
:param function: optional information-generator function, for checking the
function signature against the information object
:type function: callable
"""
def writer_(inf_obj):
if function is not None:
assert autoinf.matches_function_signature(inf_obj, function)
inf_str = autofile.write.information(inf_obj)
return inf_str
def reader_(inf_str):
inf_obj = autofile.read.information(inf_str)
if function is not None:
assert autoinf.matches_function_signature(inf_obj, function)
return inf_obj
name = autofile.name.information(file_prefix)
return model.DataFile(name=name, writer_=writer_, reader_=reader_)
def output_file(file_prefix):
""" generate output file DataFile
"""
name = autofile.name.output_file(file_prefix)
return model.DataFile(name=name)
