def get_SoR(self, T, raise_error=True, raise_warning=True, **kwargs):
"""Calculate the dimensionless entropy
Parameters
----------
T : float or (N,) `numpy.ndarray`_
Temperature(s) in K
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
Arguments to calculate mixture model properties, if any
Returns
-------
SoR : float or (N,) `numpy.ndarray`_
Dimensionless entropy
.. _`numpy.ndarray`: https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.ndarray.html
"""
if _is_iterable(T):
SoR = np.zeros_like(T)
for i, T_i in enumerate(T):
a = self.get_a(T=T_i)
SoR[i] = get_nasa_SoR(a=a, T=T_i) \
+ np.sum(_get_mix_quantity(mix_models=self.mix_models,
method_name='get_SoR',
raise_error=raise_error,
raise_warning=raise_warning,
default_value=0.,
T=T_i, **kwargs))
else:
a = self.get_a(T=T)
SoR = get_nasa_SoR(a=a, T=T) \
+ np.sum(_get_mix_quantity(mix_models=self.mix_models,
method_name='get_SoR',
raise_error=raise_error,
raise_warning=raise_warning,
default_value=0.,
T=T, **kwargs))
return SoR
def get_CpoR(self, T, raise_error=True, raise_warning=True, **kwargs):
"""Calculate the dimensionless heat capacity
Parameters
----------
T : float or (N,) `numpy.ndarray`_
Temperature(s) in K
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
Arguments to calculate mixture model properties, if any
Returns
-------
CpoR : float or (N,) `numpy.ndarray`_
Dimensionless heat capacity
.. _`numpy.ndarray`: https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.ndarray.html
"""
# Convert T to 1D numpy format
if not _is_iterable(T):
T = [T]
T = np.array(T)
# Calculate pure properties
CpoR = get_shomate_CpoR(a=self.a, T=T)
# Calculate mixing properties
for T_i in T:
CpoR_mix = _get_mix_quantity(mix_models=self.mix_models,
method_name='get_CpoR',
raise_error=raise_error,
raise_warning=raise_warning,
default_value=0.,
T=T_i,
**kwargs)
# Add mixing quantity in appropriate format
if len(T) == 1:
CpoR += CpoR_mix[0]
else:
CpoR += CpoR_mix
return CpoR
def get_quantity(self,
method_name,
raise_error=True,
raise_warning=True,
operation='sum',
verbose=False,
**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
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+5,) `numpy.ndarray`_
Desired quantity. N represents the number of mixing models. If
verbose is True, contribution to each mode are as follows:
[trans, vib, rot, elec, nucl, mixing_models (if any)]
.. _`numpy.ndarray`: https://docs.scipy.org/doc/numpy-1.14.0/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:
raise ValueError('Operation: {} not supported'.format(operation))
# 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)
])
# Calculate contribution from mixing models if any
mix_quantity = _get_mix_quantity(mix_models=self.mix_models,
method_name=method_name,
raise_error=raise_error,
raise_warning=raise_warning,
default_value=default_value,
verbose=verbose,
**kwargs)
# Add mixing quantities onto quantity
quantity = np.concatenate([quantity, mix_quantity])
quantity = _apply_numpy_operation(quantity,
verbose=verbose,
operation=operation)
return quantity