use ordered_float::OrderedFloat;
use polars::prelude::*;
use pyo3::prelude::*;
use pyo3_polars::PyDataFrame;
use std::collections::HashMap;
use crate::filtration::Filtration;
use crate::rng::{PseudoRng, Rng, SobolRng};
use crate::sim::simulate;
#[pyfunction]
#[pyo3(name = "simulate")]
pub fn simulate_py(
processes_equations: Vec<String>,
time_steps: Vec<f64>,
scenarios: i32,
initial_values: HashMap<String, f64>,
rng_method: String,
scheme: String,
) -> PyResult<PyDataFrame> {
let mut processes =
crate::process::util::parse_equations(&processes_equations).map_err(|e| {
PyErr::new::<pyo3::exceptions::PyValueError, _>(format!(
"Failed to parse process equations: {}",
e
))
})?;
let time_steps_ordered: Vec<OrderedFloat<f64>> =
time_steps.iter().copied().map(OrderedFloat).collect();
let mut filtration = Filtration::new(
time_steps_ordered.clone(),
(1..=scenarios).collect(),
processes.iter().map(|p| p.name().clone()).collect(),
ndarray::Array3::<f64>::zeros((
time_steps_ordered.len(),
scenarios as usize,
processes.len(),
)),
Some(initial_values),
);
let mut rng: Box<dyn Rng> = if rng_method == "sobol" {
Box::new(SobolRng::new(
processes
.iter_mut()
.flat_map(|p| p.incrementors().iter_mut().map(|i| i.name().clone()))
.collect::<Vec<String>>(),
time_steps_ordered.clone(),
))
} else {
Box::new(PseudoRng::new(
processes
.iter_mut()
.flat_map(|p| p.incrementors().iter_mut().map(|i| i.name().clone()))
.collect::<Vec<String>>(),
))
};
simulate(
&mut filtration,
&mut processes,
&time_steps_ordered,
&scenarios,
&mut *rng,
&scheme,
);
let df: DataFrame = filtration.to_dataframe();
Ok(PyDataFrame(df))
}
#[pymodule]
fn sde_sim_rs(m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_function(wrap_pyfunction!(simulate_py, m)?)?;
Ok(())
}