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use super::graph_search::Vertice;
use crate::algorithms::offline::graph_search::{Cache, CachedPath};
use crate::algorithms::offline::multi_dimensional::{
graph_search::graph_search, Values,
};
use crate::algorithms::offline::OfflineOptions;
use crate::model::{ModelOutputFailure, ModelOutputSuccess};
use crate::problem::IntegralSimplifiedSmoothedConvexOptimization;
use crate::result::Result;
use log::debug;
use pyo3::prelude::*;
#[pyclass(name = "OptimalGraphSearchOptions")]
#[derive(Clone, Default)]
pub struct Options {
pub cache: Option<Cache<Vertice>>,
}
#[pymethods]
impl Options {
#[new]
fn constructor() -> Self {
Options::default()
}
}
pub fn optimal_graph_search<C, D>(
p: IntegralSimplifiedSmoothedConvexOptimization<'_, C, D>,
Options { cache }: Options,
offline_options: OfflineOptions,
) -> Result<CachedPath<Cache<Vertice>>>
where
C: ModelOutputSuccess,
D: ModelOutputFailure,
{
let max_bound = p.bounds.iter().max().unwrap();
let values = Values {
values: (0..=*max_bound).collect(),
bound_indices: p.bounds.iter().map(|&m| m as usize).collect(),
};
debug!("starting with `{}` values", max_bound);
graph_search(p, values, cache, offline_options)
}