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Copy pathpython.rs
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251 lines (228 loc) · 7.33 KB
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use super::parameters::*;
use feos_core::parameter::*;
use feos_core::python::parameter::*;
use feos_core::{impl_binary_record, impl_json_handling, impl_parameter, impl_pure_record};
use numpy::{PyArray2, PyReadonlyArray2, ToPyArray};
use pyo3::exceptions::{PyTypeError, PyValueError};
use pyo3::prelude::*;
use std::convert::{TryFrom, TryInto};
use std::sync::Arc;
/// Create a set of PeTS parameters from records.
#[pyclass(name = "PetsRecord")]
#[derive(Clone)]
pub struct PyPetsRecord(PetsRecord);
#[pymethods]
impl PyPetsRecord {
#[new]
#[pyo3(
text_signature = "(sigma, epsilon_k, viscosity=None, diffusion=None, thermal_conductivity=None)"
)]
fn new(
sigma: f64,
epsilon_k: f64,
viscosity: Option<[f64; 4]>,
diffusion: Option<[f64; 5]>,
thermal_conductivity: Option<[f64; 4]>,
) -> Self {
Self(PetsRecord::new(
sigma,
epsilon_k,
viscosity,
diffusion,
thermal_conductivity,
))
}
#[getter]
fn get_sigma(&self) -> f64 {
self.0.sigma
}
#[getter]
fn get_epsilon_k(&self) -> f64 {
self.0.epsilon_k
}
#[getter]
fn get_viscosity(&self) -> Option<[f64; 4]> {
self.0.viscosity
}
#[getter]
fn get_diffusion(&self) -> Option<[f64; 5]> {
self.0.diffusion
}
#[getter]
fn get_thermal_conductivity(&self) -> Option<[f64; 4]> {
self.0.thermal_conductivity
}
fn __repr__(&self) -> PyResult<String> {
Ok(self.0.to_string())
}
}
impl_json_handling!(PyPetsRecord);
impl_pure_record!(PetsRecord, PyPetsRecord);
#[pyclass(name = "PetsBinaryRecord")]
#[derive(Clone)]
pub struct PyPetsBinaryRecord(PetsBinaryRecord);
impl_binary_record!(PetsBinaryRecord, PyPetsBinaryRecord);
#[pyclass(name = "PetsParameters")]
#[derive(Clone)]
pub struct PyPetsParameters(pub Arc<PetsParameters>);
#[pymethods]
impl PyPetsParameters {
// Create a set of PeTS parameters from lists.
///
/// Parameters
/// ----------
/// sigma : List[float]
/// PeTS segment diameter in units of Angstrom.
/// epsilon_k : List[float]
/// PeTS energy parameter in units of Kelvin.
/// k_ij: numpy.ndarray[float]
/// matrix of binary interaction parameters.
/// molarweight: List[float], optional
/// molar weight in units of Gram per Mol.
/// viscosity: List[List[float]], optional
/// entropy scaling parameters for viscosity.
/// diffusion: List[List[float]], optional
/// entropy scaling parameters for self-diffusion.
/// thermal_conductivity: List[List[float]], optional
/// entropy scaling parameters for thermal conductivity.
/// Returns
/// -------
/// PetsParameters
#[pyo3(
text_signature = "(sigma, epsilon_k, k_ij=None, molarweight=None, viscosity=None, diffusion=None, thermal_conductivity=None)"
)]
#[staticmethod]
fn from_lists(
sigma: Vec<f64>,
epsilon_k: Vec<f64>,
k_ij: Option<&PyArray2<f64>>,
molarweight: Option<Vec<f64>>,
viscosity: Option<Vec<[f64; 4]>>,
diffusion: Option<Vec<[f64; 5]>>,
thermal_conductivity: Option<Vec<[f64; 4]>>,
) -> PyResult<Self> {
// Check if all inputs have the same length
let n = sigma.len();
let input_length = [
Some(sigma.len()),
Some(epsilon_k.len()),
k_ij.as_ref().map(|v| v.shape()[0]),
k_ij.as_ref().map(|v| v.shape()[1]),
molarweight.as_ref().map(|v| v.len()),
viscosity.as_ref().map(|v| v.len()),
diffusion.as_ref().map(|v| v.len()),
thermal_conductivity.as_ref().map(|v| v.len()),
]
.into_iter()
.flatten()
.all(|v| v == n);
if !input_length {
return Err(PyValueError::new_err(
"shape of arguments could not be used together.",
));
}
// Define `PureRecord`s
let pure_records = (0..n)
.map(|i| {
let identifier = Identifier::new(
Some(format!("{}", i).as_str()),
None,
None,
None,
None,
None,
);
let model_record = PetsRecord::new(
sigma[i],
epsilon_k[i],
viscosity.as_ref().map(|v| v[i]),
diffusion.as_ref().map(|v| v[i]),
thermal_conductivity.as_ref().map(|v| v[i]),
);
PureRecord::new(
identifier,
molarweight.as_ref().map_or(1.0, |v| v[i]),
model_record,
)
// Hier Ideal Gas anstatt None???
})
.collect();
let binary = k_ij.map(|v| v.to_owned_array().mapv(f64::into));
Ok(Self(Arc::new(PetsParameters::from_records(
pure_records,
binary,
)?)))
}
// Create a set of PeTS parameters from values.
///
/// Parameters
/// ----------
/// sigma : float
/// PeTS segment diameter in units of Angstrom.
/// epsilon_k : float
/// PeTS energy parameter in units of Kelvin.
/// molarweight: float, optional
/// molar weight in units of Gram per Mol.
/// viscosity: List[float], optional
/// entropy scaling parameters for viscosity.
/// diffusion: List[float], optional
/// entropy scaling parameters for self-diffusion.
/// thermal_conductivity: List[float], optional
/// entropy scaling parameters for thermal conductivity.
/// Returns
/// -------
/// PetsParameters
#[pyo3(
text_signature = "(sigma, epsilon_k, molarweight=None, viscosity=None, diffusion=None, thermal_conductivity=None)"
)]
#[staticmethod]
fn from_values(
sigma: f64,
epsilon_k: f64,
molarweight: Option<f64>,
viscosity: Option<[f64; 4]>,
diffusion: Option<[f64; 5]>,
thermal_conductivity: Option<[f64; 4]>,
) -> PyResult<Self> {
let pure_record = PureRecord::new(
Identifier::new(
Some(format!("{}", 1).as_str()),
None,
None,
None,
None,
None,
),
molarweight.map_or(1.0, |v| v),
PetsRecord::new(sigma, epsilon_k, viscosity, diffusion, thermal_conductivity),
);
Ok(Self(Arc::new(PetsParameters::new_pure(pure_record)?)))
}
#[getter]
fn get_k_ij<'py>(&self, py: Python<'py>) -> Option<&'py PyArray2<f64>> {
self.0.k_ij.as_ref().map(|k| k.view().to_pyarray(py))
}
fn _repr_markdown_(&self) -> String {
self.0.to_markdown()
}
fn __repr__(&self) -> PyResult<String> {
Ok(self.0.to_string())
}
}
impl_parameter!(
PetsParameters,
PyPetsParameters,
PyPetsRecord,
PyPetsBinaryRecord
);
#[pymodule]
pub fn pets(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
m.add_class::<PyIdentifier>()?;
m.add_class::<IdentifierOption>()?;
m.add_class::<PyChemicalRecord>()?;
m.add_class::<PyPetsRecord>()?;
m.add_class::<PyPureRecord>()?;
m.add_class::<PyBinaryRecord>()?;
m.add_class::<PyPetsParameters>()?;
Ok(())
}