def test_get_mode_quantity(self):
sum_obj = self.sum_class(num1=1, num2=2)
self.assertEqual(
pmutt._get_mode_quantity(mode=sum_obj,
method_name='get_sum3',
num3=3), 6)
with self.assertRaises(AttributeError):
pmutt._get_mode_quantity(mode=sum_obj, method_name='get_prod')
self.assertEqual(
pmutt._get_mode_quantity(mode=sum_obj,
method_name='get_prod',
raise_error=False,
raise_warning=False,
default_value=0), 0)
def _get_mix_quantity(misc_models,
method_name,
raise_error=True,
raise_warning=True,
default_value=0.,
**kwargs):
"""Calculate contribution from mixing models to desired quantity
Parameters
----------
misc_models : list (length N) of ``pmutt.mixture`` objects
Mix models to calculate the property
method_name : str
Name of method to use to calculate quantity. Calculates any
quantity as long as the relevant objects have the same method
name
raise_error : bool, optional
If True, raises an error if any of the modes do not have the
quantity of interest. Default is True
raise_warning : bool, optional
Only relevant if raise_error is False. Raises a warning if any
of the modes do not have the quantity of interest. Default is
True
default_value : float, optional
Default value if the object does not contain the method. Default is
0
kwargs : key-word arguments
Arguments to calculate mixture model properties, if any
Returns
-------
mix_quantity : (N,) `numpy.ndarray`_
Mixing quantity of interest. If verbose is True, each element
corresponds to the contribution of each mix_model
.. _`numpy.ndarray`: https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html
"""
# Return default value if no mixture models exist
if misc_models is None:
return np.array([default_value])
# Calculate contribution from mixing models if any
mix_quantity = np.full_like(a=misc_models,
fill_value=default_value,
dtype=np.double)
for i, mix_model in enumerate(misc_models):
if mix_model is None:
continue
try:
specie_kwargs = _get_specie_kwargs(mix_model.name_j, **kwargs)
except AttributeError:
specie_kwargs = kwargs.copy()
mix_quantity[i] = _get_mode_quantity(mode=mix_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs)
return mix_quantity
def get_EoRT(self,
T=c.T0('K'),
include_ZPE=False,
raise_error=True,
raise_warning=True,
**kwargs):
"""Dimensionless electronic energy
Parameters
----------
T : float, optional
Temperature in K. If the electronic mode is
:class:`~pmutt.statmech.elec.GroundStateElec`, then the output is
insensitive to this input. Default is 298.15 K
include_ZPE : bool, optional
If True, includes the zero point energy. Default is False
raise_error : bool, optional
If True, raises an error if any of the modes do not have the
quantity of interest. Default is True
raise_warning : bool, optional
Only relevant if raise_error is False. Raises a warning if any
of the modes do not have the quantity of interest. Default is
True
kwargs : key-word arguments
Parameters passed to electronic mode
Returns
-------
EoRT : float
Dimensionless electronic energy
"""
kwargs['T'] = T
EoRT = _get_mode_quantity(mode=self.elec_model,
method_name='get_UoRT',
raise_error=raise_error,
raise_warning=raise_warning,
default_value=0.,
**kwargs)
if include_ZPE:
EoRT += _get_mode_quantity(mode=self.vib_model,
method_name='get_ZPE',
raise_error=raise_error,
raise_warning=raise_warning,
default_value=0.,
**kwargs) / c.R('eV/K') / T
return EoRT
def get_quantity(self,
method_name,
raise_error=True,
raise_warning=True,
operation='sum',
verbose=False,
use_references=True,
**kwargs):
"""Generic method to get any quantity from modes.
Parameters
----------
method_name : str
Name of method to use to calculate quantity. Calculates any
quantity as long as the relevant objects have the same method
name
raise_error : bool, optional
If True, raises an error if any of the modes do not have the
quantity of interest. Default is True
raise_warning : bool, optional
Only relevant if raise_error is False. Raises a warning if any
of the modes do not have the quantity of interest. Default is
True
operation : str, optional
Operation to apply when combining the modes. Supported options
include:
- sum (Default)
- prod
use_references : bool, optional
If True, adds contribution from references. Default is True
verbose : bool, optional
If False, returns the total Gibbs energy. If True, returns
contribution of each mode.
kwargs : key-word arguments
Parameters passed to each mode
Returns
-------
quantity : float or (N+6,) `numpy.ndarray`_
Desired quantity. N represents the number of misc models. If
verbose is True, contribution to each mode are as follows:
[trans, vib, rot, elec, nucl, references, misc_models (if any)]
.. _`numpy.ndarray`: https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html
"""
# Get the default value
operation = operation.lower()
if operation == 'sum':
default_value = 0.
elif operation == 'prod':
default_value = 1.
else:
err_msg = 'Operation: {} not supported'.format(operation)
raise ValueError(err_msg)
# Calculate the quantity for each mode
specie_kwargs = _get_specie_kwargs(specie_name=self.name, **kwargs)
quantity = np.array([
_get_mode_quantity(mode=self.trans_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs),
_get_mode_quantity(mode=self.vib_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs),
_get_mode_quantity(mode=self.rot_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs),
_get_mode_quantity(mode=self.elec_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs),
_get_mode_quantity(mode=self.nucl_model,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**specie_kwargs)
])
if use_references and self.references is not None:
ref_kwargs = copy(specie_kwargs)
ref_kwargs['descriptors'] = getattr(self,
self.references.descriptor)
refs_quantity = np.atleast_1d(
_get_mode_quantity(mode=self.references,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
**ref_kwargs))
else:
refs_quantity = np.atleast_1d(default_value)
# Calculate contribution from misc models if any
misc_quantity = _get_mix_quantity(misc_models=self.misc_models,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
verbose=verbose,
**kwargs)
# Add misc quantities onto quantity
quantity = np.concatenate([quantity, refs_quantity, misc_quantity])
quantity = _apply_numpy_operation(quantity,
verbose=verbose,
operation=operation)
return quantity