Generate trajectories from python

reCTBN/src/tools.rs

@@ -3,6 +3,7 @@ use ndarray::prelude::*;
 use crate::sampling::{ForwardSampler, Sampler};
 use crate::{network, params};
 
+#[derive(Clone)]
 pub struct Trajectory {
     time: Array1<f64>,
     events: Array2<usize>,

reCTBNpy/src/lib.rs

@@ -1,6 +1,7 @@
 use pyo3::prelude::*;
 pub mod pyctbn;
 pub mod pyparams;
+pub mod pytools;
 
 
 
@@ -13,6 +14,8 @@ fn reCTBNpy(py: Python, m: &PyModule) -> PyResult<()> {
 
     let params_module = PyModule::new(py, "params")?;
     params_module.add_class::<pyparams::PyDiscreteStateContinousTime>()?;
+    params_module.add_class::<pyparams::PyStateType>()?;
+    params_module.add_class::<pyparams::PyParams>()?;
     m.add_submodule(params_module)?;
     Ok(())
 }

reCTBNpy/src/pyctbn.rs

@@ -1,35 +1,68 @@
 use std::collections::BTreeSet;
 
+use crate::{pyparams, pytools};
 use pyo3::prelude::*;
-use reCTBN::{ctbn, network::Network};
+use reCTBN::{ctbn, network::Network, params, tools, params::Params};
 
 #[pyclass]
-pub struct PyCtbnNetwork {
+pub struct PyCtbnNetwork(pub ctbn::CtbnNetwork);
-    ctbn_network: ctbn::CtbnNetwork,
-}
 
 #[pymethods]
 impl PyCtbnNetwork {
     #[new]
     pub fn new() -> Self {
-        PyCtbnNetwork {
+        PyCtbnNetwork(ctbn::CtbnNetwork::new())
-            ctbn_network: ctbn::CtbnNetwork::new(),
     }
+
+    pub fn add_node(&mut self, n: pyparams::PyParams) {
+        self.0.add_node(n.0);
     }
 
     pub fn get_number_of_nodes(&self) -> usize {
-        self.ctbn_network.get_number_of_nodes()
+        self.0.get_number_of_nodes()
     }
 
     pub fn add_edge(&mut self, parent: usize, child: usize) {
-        self.ctbn_network.add_edge(parent, child);
+        self.0.add_edge(parent, child);
+    }
+
+    pub fn get_node_indices(&self) -> BTreeSet<usize> {
+        self.0.get_node_indices().collect()
     }
 
     pub fn get_parent_set(&self, node: usize) -> BTreeSet<usize> {
-        self.ctbn_network.get_parent_set(node)
+        self.0.get_parent_set(node)
     }
 
     pub fn get_children_set(&self, node: usize) -> BTreeSet<usize> {
-        self.ctbn_network.get_children_set(node)
+        self.0.get_children_set(node)
+    }
+
+    pub fn set_node(&mut self, node_idx: usize, n: pyparams::PyParams) {
+        match &n.0 {
+            Params::DiscreteStatesContinousTime(new_p) => {
+                if let Params::DiscreteStatesContinousTime(p) = self.0.get_node_mut(node_idx){
+                    p.set_cim(new_p.get_cim().as_ref().unwrap().clone()).unwrap();
+
+                }
+                else {
+                    panic!("Node type mismatch")
+                }
+            }
+        }
+    }
+
+    pub fn trajectory_generator(
+        &self,
+        n_trajectories: u64,
+        t_end: f64,
+        seed: Option<u64>,
+    ) -> pytools::PyDataset {
+        pytools::PyDataset(tools::trajectory_generator(
+            &self.0,
+            n_trajectories,
+            t_end,
+            seed,
+        ))
     }
 }

reCTBNpy/src/pyparams.rs

@@ -18,32 +18,85 @@ impl From<params::ParamsError> for PyParamsError {
 }
 
 #[pyclass]
-pub struct PyDiscreteStateContinousTime {
+pub struct PyStateType(pub params::StateType);
-    param: params::DiscreteStatesContinousTimeParams,
+
+#[pyclass]
+#[derive(Clone)]
+pub struct PyParams(pub params::Params);
+
+#[pymethods]
+impl PyParams {
+    #[staticmethod]
+    pub fn new_discrete_state_continous_time(p: PyDiscreteStateContinousTime) -> Self{
+        PyParams(params::Params::DiscreteStatesContinousTime(p.0))
+    }
+
+    pub fn get_reserved_space_as_parent(&self) -> usize {
+        self.0.get_reserved_space_as_parent()
+    }
+
+    pub fn get_label(&self) -> String {
+        self.0.get_label().to_string()
+    }
 }
 
+/// DiscreteStatesContinousTime.
+/// This represents the parameters of a classical discrete node for ctbn and it's composed by the
+/// following elements:
+/// - **domain**: an ordered and exhaustive set of possible states
+/// - **cim**: Conditional Intensity Matrix
+/// - **Sufficient Statistics**: the sufficient statistics are mainly used during the parameter
+///     learning task and are composed by:
+///     - **transitions**: number of transitions from one state to another given a specific
+///     realization of the parent set
+///     - **residence_time**: permanence time in each possible states given a specific
+///     realization of the parent set
+#[derive(Clone)]
+#[pyclass]
+pub struct PyDiscreteStateContinousTime(params::DiscreteStatesContinousTimeParams);
+
+
 #[pymethods]
 impl PyDiscreteStateContinousTime {
     #[new]
     pub fn new(label: String, domain: BTreeSet<String>) -> Self {
-        PyDiscreteStateContinousTime {
+        PyDiscreteStateContinousTime(params::DiscreteStatesContinousTimeParams::new(label, domain))
-            param: params::DiscreteStatesContinousTimeParams::new(label, domain),
-        }
     }
 
     pub fn get_cim<'py>(&self, py: Python<'py>) -> Option<&'py numpy::PyArray3<f64>> {
-        match self.param.get_cim() {
+        match self.0.get_cim() {
             Some(x) => Some(x.to_pyarray(py)),
             None => None,
         }
     }
 
     pub fn set_cim<'py>(&mut self, py: Python<'py>, cim: numpy::PyReadonlyArray3<f64>) -> Result<(), PyParamsError> {
-        self.param.set_cim(cim.as_array().to_owned())?;
+        self.0.set_cim(cim.as_array().to_owned())?;
         Ok(())
     }
 
-    pub fn get_label(&self) -> String {
+
-        self.param.get_label().to_string()
+    pub fn get_transitions<'py>(&self, py: Python<'py>) -> Option<&'py numpy::PyArray3<usize>> {
+        match self.0.get_transitions() {
+            Some(x) => Some(x.to_pyarray(py)),
+            None => None,
+        }
     }
+
+    pub fn set_transitions<'py>(&mut self, py: Python<'py>, cim: numpy::PyReadonlyArray3<usize>){
+        self.0.set_transitions(cim.as_array().to_owned());
+    }
+
+
+    pub fn get_residence_time<'py>(&self, py: Python<'py>) -> Option<&'py numpy::PyArray2<f64>> {
+        match self.0.get_residence_time() {
+            Some(x) => Some(x.to_pyarray(py)),
+            None => None,
+        }
+    }
+
+    pub fn set_residence_time<'py>(&mut self, py: Python<'py>, cim: numpy::PyReadonlyArray2<f64>) {
+        self.0.set_residence_time(cim.as_array().to_owned());
+    }
+
 }

reCTBNpy/src/pytools.rs

@@ -0,0 +1,50 @@
+use numpy::{self, ToPyArray};
+use pyo3::{exceptions::PyValueError, prelude::*};
+use reCTBN::{tools, network};
+
+#[pyclass]
+#[derive(Clone)]
+pub struct PyTrajectory(pub tools::Trajectory);
+
+#[pymethods]
+impl PyTrajectory {
+    #[new]
+    pub fn new(
+        time: numpy::PyReadonlyArray1<f64>,
+        events: numpy::PyReadonlyArray2<usize>,
+    ) -> PyTrajectory {
+        PyTrajectory(tools::Trajectory::new(
+            time.as_array().to_owned(),
+            events.as_array().to_owned(),
+        ))
+    }
+
+    pub fn get_time<'py>(&self, py: Python<'py>) -> &'py numpy::PyArray1<f64> {
+        self.0.get_time().to_pyarray(py)
+    }
+    
+    pub fn get_events<'py>(&self, py: Python<'py>) -> &'py numpy::PyArray2<usize> {
+        self.0.get_events().to_pyarray(py)
+    }
+}
+
+#[pyclass]
+pub struct PyDataset(pub tools::Dataset);
+
+#[pymethods]
+impl PyDataset {
+    #[new]
+    pub fn new(trajectories: Vec<PyTrajectory>) -> PyDataset {
+        PyDataset(tools::Dataset::new(trajectories.into_iter().map(|x| x.0).collect()))
+    }
+
+    pub fn get_number_of_trajectories(&self) -> usize {
+        self.0.get_trajectories().len()
+    }
+
+    pub fn get_trajectory(&self, idx: usize) -> PyTrajectory {
+        PyTrajectory(self.0.get_trajectories().get(idx).unwrap().clone())
+    }
+
+}
+