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#[cfg(feature = "estimator")]
use crate::estimator::*;
#[cfg(feature = "gc_pcsaft")]
use crate::gc_pcsaft::python::PyGcPcSaftEosParameters;
#[cfg(feature = "gc_pcsaft")]
use crate::gc_pcsaft::{GcPcSaft, GcPcSaftOptions};
#[cfg(feature = "estimator")]
use crate::impl_estimator;
#[cfg(all(feature = "estimator", feature = "pcsaft"))]
use crate::impl_estimator_entropy_scaling;
#[cfg(feature = "pcsaft")]
use crate::pcsaft::python::PyPcSaftParameters;
#[cfg(feature = "pcsaft")]
use crate::pcsaft::{PcSaft, PcSaftOptions};
#[cfg(feature = "pets")]
use crate::pets::python::PyPetsParameters;
#[cfg(feature = "pets")]
use crate::pets::{Pets, PetsOptions};
#[cfg(feature = "uvtheory")]
use crate::uvtheory::python::PyUVParameters;
#[cfg(feature = "uvtheory")]
use crate::uvtheory::{Perturbation, UVTheory, UVTheoryOptions};
use feos_core::cubic::PengRobinson;
use feos_core::python::cubic::PyPengRobinsonParameters;
use feos_core::python::user_defined::PyEoSObj;
use feos_core::*;
use ndarray::Array1;
use numpy::convert::ToPyArray;
use numpy::{PyArray1, PyArray2};
use pyo3::exceptions::{PyIndexError, PyValueError};
use pyo3::prelude::*;
#[cfg(feature = "estimator")]
use pyo3::wrap_pymodule;
use quantity::python::*;
use quantity::si::*;
use std::collections::HashMap;
use std::rc::Rc;
pub enum EosVariant {
#[cfg(feature = "pcsaft")]
PcSaft(PcSaft),
#[cfg(feature = "gc_pcsaft")]
GcPcSaft(GcPcSaft),
PengRobinson(PengRobinson),
Python(PyEoSObj),
#[cfg(feature = "pets")]
Pets(Pets),
#[cfg(feature = "uvtheory")]
UVTheory(UVTheory),
}
impl EquationOfState for EosVariant {
fn components(&self) -> usize {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.components(),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => eos.components(),
EosVariant::PengRobinson(eos) => eos.components(),
EosVariant::Python(eos) => eos.components(),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => eos.components(),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(eos) => eos.components(),
}
}
fn compute_max_density(&self, moles: &Array1<f64>) -> f64 {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.compute_max_density(moles),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => eos.compute_max_density(moles),
EosVariant::PengRobinson(eos) => eos.compute_max_density(moles),
EosVariant::Python(eos) => eos.compute_max_density(moles),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => eos.compute_max_density(moles),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(eos) => eos.compute_max_density(moles),
}
}
fn subset(&self, component_list: &[usize]) -> Self {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => Self::PcSaft(eos.subset(component_list)),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => Self::GcPcSaft(eos.subset(component_list)),
EosVariant::PengRobinson(eos) => Self::PengRobinson(eos.subset(component_list)),
EosVariant::Python(eos) => Self::Python(eos.subset(component_list)),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => Self::Pets(eos.subset(component_list)),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(eos) => Self::UVTheory(eos.subset(component_list)),
}
}
fn residual(&self) -> &[Box<dyn HelmholtzEnergy>] {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.residual(),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => eos.residual(),
EosVariant::PengRobinson(eos) => eos.residual(),
EosVariant::Python(eos) => eos.residual(),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => eos.residual(),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(eos) => eos.residual(),
}
}
fn ideal_gas(&self) -> &dyn IdealGasContribution {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.ideal_gas(),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => eos.ideal_gas(),
EosVariant::PengRobinson(eos) => eos.ideal_gas(),
EosVariant::Python(eos) => eos.ideal_gas(),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => eos.ideal_gas(),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(eos) => eos.ideal_gas(),
}
}
}
impl MolarWeight<SIUnit> for EosVariant {
fn molar_weight(&self) -> SIArray1 {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.molar_weight(),
#[cfg(feature = "gc_pcsaft")]
EosVariant::GcPcSaft(eos) => eos.molar_weight(),
EosVariant::PengRobinson(eos) => eos.molar_weight(),
EosVariant::Python(eos) => eos.molar_weight(),
#[cfg(feature = "pets")]
EosVariant::Pets(eos) => eos.molar_weight(),
#[cfg(feature = "uvtheory")]
EosVariant::UVTheory(_) => unimplemented!(),
}
}
}
#[cfg(feature = "pcsaft")]
impl EntropyScaling<SIUnit> for EosVariant {
fn viscosity_reference(
&self,
temperature: SINumber,
volume: SINumber,
moles: &SIArray1,
) -> EosResult<SINumber> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.viscosity_reference(temperature, volume, moles),
_ => unimplemented!(),
}
}
fn viscosity_correlation(&self, s_res: f64, x: &Array1<f64>) -> EosResult<f64> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.viscosity_correlation(s_res, x),
_ => unimplemented!(),
}
}
fn diffusion_reference(
&self,
temperature: SINumber,
volume: SINumber,
moles: &SIArray1,
) -> EosResult<SINumber> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.diffusion_reference(temperature, volume, moles),
_ => unimplemented!(),
}
}
fn diffusion_correlation(&self, s_res: f64, x: &Array1<f64>) -> EosResult<f64> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.diffusion_correlation(s_res, x),
_ => unimplemented!(),
}
}
fn thermal_conductivity_reference(
&self,
temperature: SINumber,
volume: SINumber,
moles: &SIArray1,
) -> EosResult<SINumber> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => {
eos.thermal_conductivity_reference(temperature, volume, moles)
}
_ => unimplemented!(),
}
}
fn thermal_conductivity_correlation(&self, s_res: f64, x: &Array1<f64>) -> EosResult<f64> {
match self {
#[cfg(feature = "pcsaft")]
EosVariant::PcSaft(eos) => eos.thermal_conductivity_correlation(s_res, x),
_ => unimplemented!(),
}
}
}
#[pyclass(name = "EquationOfState", unsendable)]
#[derive(Clone)]
pub struct PyEosVariant(pub Rc<EosVariant>);
#[pymethods]
impl PyEosVariant {
/// Initialize PC-SAFT equation of state.
///
/// Parameters
/// ----------
/// parameters : PcSaftParameters
/// The parameters of the PC-Saft equation of state to use.
/// max_eta : float, optional
/// Maximum packing fraction. Defaults to 0.5.
/// max_iter_cross_assoc : unsigned integer, optional
/// Maximum number of iterations for cross association. Defaults to 50.
/// tol_cross_assoc : float
/// Tolerance for convergence of cross association. Defaults to 1e-10.
/// dq_variant : {'dq35', 'dq44'}, optional
/// Combination rule used in the dipole/quadrupole term. Defaults to 'dq35'
///
/// Returns
/// -------
/// EquationOfState
/// The PC-SAFT equation of state that can be used to compute thermodynamic
/// states.
#[cfg(feature = "pcsaft")]
#[args(
max_eta = "0.5",
max_iter_cross_assoc = "50",
tol_cross_assoc = "1e-10",
dq_variant = "\"dq35\""
)]
#[staticmethod]
#[pyo3(
text_signature = "(parameters, max_eta, max_iter_cross_assoc, tol_cross_assoc, dq_variant)"
)]
pub fn pcsaft(
parameters: PyPcSaftParameters,
max_eta: f64,
max_iter_cross_assoc: usize,
tol_cross_assoc: f64,
dq_variant: &str,
) -> Self {
let options = PcSaftOptions {
max_eta,
max_iter_cross_assoc,
tol_cross_assoc,
dq_variant: dq_variant.into(),
};
Self(Rc::new(EosVariant::PcSaft(PcSaft::with_options(
parameters.0,
options,
))))
}
/// Initialize the (heterosegmented) group contribution PC-SAFT equation of state.
///
/// Parameters
/// ----------
/// parameters : GcPcSaftEosParameters
/// The parameters of the PC-Saft equation of state to use.
/// max_eta : float, optional
/// Maximum packing fraction. Defaults to 0.5.
/// max_iter_cross_assoc : unsigned integer, optional
/// Maximum number of iterations for cross association. Defaults to 50.
/// tol_cross_assoc : float
/// Tolerance for convergence of cross association. Defaults to 1e-10.
///
/// Returns
/// -------
/// EquationOfState
/// The gc-PC-SAFT equation of state that can be used to compute thermodynamic
/// states.
#[cfg(feature = "gc_pcsaft")]
#[args(
max_eta = "0.5",
max_iter_cross_assoc = "50",
tol_cross_assoc = "1e-10"
)]
#[staticmethod]
#[pyo3(text_signature = "(parameters, max_eta, max_iter_cross_assoc, tol_cross_assoc)")]
pub fn gc_pcsaft(
parameters: PyGcPcSaftEosParameters,
max_eta: f64,
max_iter_cross_assoc: usize,
tol_cross_assoc: f64,
) -> Self {
let options = GcPcSaftOptions {
max_eta,
max_iter_cross_assoc,
tol_cross_assoc,
};
Self(Rc::new(EosVariant::GcPcSaft(GcPcSaft::with_options(
parameters.0,
options,
))))
}
/// Peng-Robinson equation of state.
///
/// Parameters
/// ----------
/// parameters : PengRobinsonParameters
/// The parameters of the PR equation of state to use.
///
/// Returns
/// -------
/// EquationOfState
/// The PR equation of state that can be used to compute thermodynamic
/// states.
#[staticmethod]
#[pyo3(text_signature = "(parameters)")]
pub fn peng_robinson(parameters: PyPengRobinsonParameters) -> Self {
Self(Rc::new(EosVariant::PengRobinson(PengRobinson::new(
parameters.0,
))))
}
/// Equation of state from a Python class.
///
/// Parameters
/// ----------
/// obj : Class
/// A python class implementing the necessary methods
/// to be used as equation of state.
///
/// Returns
/// -------
/// EquationOfState
#[staticmethod]
#[pyo3(text_signature = "(obj)")]
fn python(obj: Py<PyAny>) -> PyResult<Self> {
Ok(Self(Rc::new(EosVariant::Python(PyEoSObj::new(obj)?))))
}
/// PeTS equation of state.
///
/// Parameters
/// ----------
/// parameters : PetsParameters
/// The parameters of the PeTS equation of state to use.
/// max_eta : float, optional
/// Maximum packing fraction. Defaults to 0.5.
///
/// Returns
/// -------
/// EquationOfState
/// The PeTS equation of state that can be used to compute thermodynamic
/// states.
#[cfg(feature = "pets")]
#[args(max_eta = "0.5")]
#[staticmethod]
#[pyo3(text_signature = "(parameters, max_eta)")]
fn pets(parameters: PyPetsParameters, max_eta: f64) -> Self {
let options = PetsOptions { max_eta };
Self(Rc::new(EosVariant::Pets(Pets::with_options(
parameters.0,
options,
))))
}
/// UV-Theory equation of state.
///
/// Parameters
/// ----------
/// parameters : UVParameters
/// The parameters of the UV-theory equation of state to use.
/// max_eta : float, optional
/// Maximum packing fraction. Defaults to 0.5.
/// perturbation : Perturbation, optional
/// Division type of the Mie potential. Defaults to WCA division.
///
/// Returns
/// -------
/// EquationOfState
/// The UV-Theory equation of state that can be used to compute thermodynamic
/// states.
#[cfg(feature = "uvtheory")]
#[args(max_eta = "0.5", perturbation = "Perturbation::WeeksChandlerAndersen")]
#[staticmethod]
#[pyo3(text_signature = "(parameters, max_eta, perturbation)")]
fn uvtheory(parameters: PyUVParameters, max_eta: f64, perturbation: Perturbation) -> Self {
let options = UVTheoryOptions {
max_eta,
perturbation,
};
Self(Rc::new(EosVariant::UVTheory(UVTheory::with_options(
parameters.0,
options,
))))
}
}
impl_equation_of_state!(PyEosVariant);
impl_virial_coefficients!(PyEosVariant);
impl_state!(EosVariant, PyEosVariant);
impl_state_molarweight!(EosVariant, PyEosVariant);
#[cfg(feature = "pcsaft")]
impl_state_entropy_scaling!(EosVariant, PyEosVariant);
impl_phase_equilibrium!(EosVariant, PyEosVariant);
#[cfg(feature = "estimator")]
impl_estimator!(EosVariant, PyEosVariant);
#[cfg(all(feature = "estimator", feature = "pcsaft"))]
impl_estimator_entropy_scaling!(EosVariant, PyEosVariant);
#[pymodule]
pub fn eos(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
m.add_class::<Contributions>()?;
m.add_class::<Verbosity>()?;
m.add_class::<PyEosVariant>()?;
m.add_class::<PyState>()?;
m.add_class::<PyPhaseDiagram>()?;
m.add_class::<PyPhaseEquilibrium>()?;
#[cfg(feature = "estimator")]
m.add_wrapped(wrap_pymodule!(estimator_eos))?;
Ok(())
}
#[cfg(feature = "estimator")]
#[pymodule]
pub fn estimator_eos(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
m.add_class::<PyDataSet>()?;
m.add_class::<PyEstimator>()?;
m.add_class::<PyLoss>()
}