Merge branch 'serialize'

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "pmcore"
-version = "0.7.1"
+version = "0.7.2"
 edition = "2021"
 authors = [
     "Julián D. Otálvaro <juliandavid347@gmail.com>",
@@ -36,7 +36,9 @@ chrono = "0.4"
 config = { version = "0.14", features = ["preserve_order"] }
 faer = "0.19.3"
 faer-ext = { version = "0.2.0", features = ["nalgebra", "ndarray"] }
-pharmsol = "0.7.1"
+pharmsol = "0.7.2"
+# pharmsol = {path="../pharmsol"}
+# pharmsol = { git = "https://github.com/LAPKB/pharmsol.git", branch = "dev"}
 toml = "0.8.14" #REMOVE
 rand = "0.8.5"
 anyhow = "1.0.86"

examples/debug.rs

@@ -30,58 +30,39 @@ fn main() {
         },
         (1, 1),
     );
-    let net = equation::ODENet::new(
-        vec![dmatrix![-1.0], dmatrix![0.0]],
-        vec![],
-        vec![],
-        vec![],
-        vec![],
-        vec![],
-        vec![OutEq::new(0, Op::Div(X(0), P(1)))],
-        (1, 1),
-    );
 
     let settings = settings::read("examples/bimodal_ke/config.toml").unwrap();
     setup_log(&settings).unwrap();
     let data = data::read_pmetrics("examples/bimodal_ke/bimodal_ke.csv").unwrap();
     let mut alg_ode = NPAG::new(settings.clone(), ode, data.clone()).unwrap();
     let mut alg_an = NPAG::new(settings.clone(), an, data.clone()).unwrap();
-    let mut alg_net = NPAG::new(settings.clone(), net, data.clone()).unwrap();
 
     // Initialize algorithms
     alg_ode.initialize().unwrap();
     alg_an.initialize().unwrap();
-    alg_net.initialize().unwrap();
 
     // evaluate algorithms
     alg_ode.evaluation().unwrap();
     alg_an.evaluation().unwrap();
-    alg_net.evaluation().unwrap();
 
     println!("ODE: \n\t-2ll: {:?}", alg_ode.n2ll());
     println!("Analytical: \n\t-2ll: {:?}", alg_an.n2ll());
-    println!("Net: \n\t-2ll: {:?}", alg_net.n2ll());
     println!("=====================================");
 
     alg_ode.write_psi("examples/bimodal_ke/psi_ode.csv");
     alg_an.write_psi("examples/bimodal_ke/psi_an.csv");
-    alg_net.write_psi("examples/bimodal_ke/psi_net.csv");
 
     alg_ode.write_theta("examples/bimodal_ke/theta_ode.csv");
     alg_an.write_theta("examples/bimodal_ke/theta_an.csv");
-    alg_net.write_theta("examples/bimodal_ke/theta_net.csv");
 
     let psi_ode = alg_ode.psi().clone();
     let psi_an = alg_an.psi().clone();
-    let psi_net = alg_net.psi().clone();
 
     let ll_ode = burke(&psi_ode).unwrap();
     let ll_an = burke(&psi_an).unwrap();
-    let ll_net = burke(&psi_net).unwrap();
 
     println!("ODE: \n\t-2ll: {:?}", -2. * ll_ode.1);
     println!("Analytical: \n\t-2ll: {:?}", -2. * ll_an.1);
-    println!("Net: \n\t-2ll: {:?}", -2. * ll_net.1);
 
     dbg!(&data.get_subjects().get(46));
 }