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use approx::relative_eq;
use ndarray::prelude::*;
use crate::{
datasets::CatTrjEvT,
models::Labelled,
types::{Labels, Set, States},
};
/// Categorical evidence type.
#[non_exhaustive]
#[derive(Clone, Debug)]
pub enum CatEvT {
/// Certain positive evidence.
CertainPositive {
/// The observed event of the evidence.
event: usize,
/// The state of the evidence.
state: usize,
},
/// Certain negative evidence.
CertainNegative {
/// The observed event of the evidence.
event: usize,
/// The states of the evidence.
not_states: Set<usize>,
},
/// Uncertain positive evidence.
UncertainPositive {
/// The observed event of the evidence.
event: usize,
/// The probabilities of the states.
p_states: Array1<f64>,
},
/// Uncertain negative evidence.
UncertainNegative {
/// The observed event of the evidence.
event: usize,
/// The probabilities of the states.
p_not_states: Array1<f64>,
},
}
impl From<CatTrjEvT> for CatEvT {
fn from(evidence: CatTrjEvT) -> Self {
// Get shortened variable types.
use CatEvT as U;
use CatTrjEvT as T;
// Match the evidence type discard the temporal information.
match evidence {
T::CertainPositiveInterval { event, state, .. } => U::CertainPositive { event, state },
T::CertainNegativeInterval {
event, not_states, ..
} => U::CertainNegative { event, not_states },
T::UncertainPositiveInterval {
event, p_states, ..
} => U::UncertainPositive { event, p_states },
T::UncertainNegativeInterval {
event,
p_not_states,
..
} => U::UncertainNegative {
event,
p_not_states,
},
}
}
}
impl CatEvT {
/// Return the observed event of the evidence.
///
/// # Returns
///
/// The observed event of the evidence.
///
pub const fn event(&self) -> usize {
match self {
Self::CertainPositive { event, .. }
| Self::CertainNegative { event, .. }
| Self::UncertainPositive { event, .. }
| Self::UncertainNegative { event, .. } => *event,
}
}
}
/// Categorical evidence structure.
#[derive(Clone, Debug)]
pub struct CatEv {
labels: Labels,
states: States,
shape: Array1<usize>,
evidences: Vec<Option<CatEvT>>,
}
impl Labelled for CatEv {
fn labels(&self) -> &Labels {
&self.labels
}
}
impl CatEv {
/// Creates a new categorical evidence structure.
///
/// # Arguments
///
/// * `states` - A collection of states, where each state is a tuple of a string and an iterator of strings.
/// * `values` - A collection of values, where each value is a categorical evidence type.
///
/// # Returns
///
/// A new categorical evidence structure.
///
pub fn new<I>(mut states: States, values: I) -> Self
where
I: IntoIterator<Item = CatEvT>,
{
// Get shortened variable type.
use CatEvT as E;
// Get the sorted labels.
let mut labels = states.keys().cloned().collect();
// Get the shape of the states.
let mut shape = Array::from_iter(states.values().map(Set::len));
// Allocate evidences.
let mut evidences = vec![None; states.len()];
// Fill the evidences.
values.into_iter().for_each(|e| {
// Get the event of the evidence.
let event = e.event();
// Push the value into the variable events.
evidences[event] = Some(e);
});
// Sort states, if necessary.
if !states.keys().is_sorted() || !states.values().all(|x| x.iter().is_sorted()) {
// Clone the states.
let mut new_states = states.clone();
// Sort the states.
new_states.sort_keys();
new_states.values_mut().for_each(Set::sort);
// Allocate new evidences.
let mut new_evidences = vec![None; states.len()];
// Iterate over the values and insert them into the events map using sorted indices.
evidences.into_iter().flatten().for_each(|e| {
// Get the event and states of the evidence.
let (event, states) = states
.get_index(e.event())
.expect("Failed to get label of evidence.");
// Sort the event index.
let (event, _, new_states) = new_states
.get_full(event)
.expect("Failed to get full state.");
// Sort the variable states.
let e = match e {
E::CertainPositive { state, .. } => {
// Sort the variable states.
let state = new_states
.get_index_of(&states[state])
.expect("Failed to get index of state.");
// Construct the sorted evidence.
E::CertainPositive { event, state }
}
E::CertainNegative { not_states, .. } => {
// Sort the variable states.
let not_states = not_states
.iter()
.map(|&state| {
new_states
.get_index_of(&states[state])
.expect("Failed to get index of state.")
})
.collect();
// Construct the sorted evidence.
E::CertainNegative { event, not_states }
}
E::UncertainPositive { p_states, .. } => {
// Allocate new variable states.
let mut new_p_states = Array::zeros(p_states.len());
// Sort the variable states.
p_states.indexed_iter().for_each(|(i, &p)| {
// Get sorted index.
let state = new_states
.get_index_of(&states[i])
.expect("Failed to get index of state.");
// Assign probability to sorted index.
new_p_states[state] = p;
});
// Substitute the sorted states.
let p_states = new_p_states;
// Construct the sorted evidence.
E::UncertainPositive { event, p_states }
}
E::UncertainNegative { p_not_states, .. } => {
// Allocate new variable states.
let mut new_p_not_states = Array::zeros(p_not_states.len());
// Sort the variable states.
p_not_states.indexed_iter().for_each(|(i, &p)| {
// Get sorted index.
let state = new_states
.get_index_of(&states[i])
.expect("Failed to get index of state.");
// Assign probability to sorted index.
new_p_not_states[state] = p;
});
// Substitute the sorted states.
let p_not_states = new_p_not_states;
// Construct the sorted evidence.
E::UncertainNegative {
event,
p_not_states,
}
}
};
// Push the value into the variable events.
new_evidences[event] = Some(e);
});
// Update the states.
states = new_states;
// Update the evidences.
evidences = new_evidences;
// Update the labels.
labels = states.keys().cloned().collect();
// Update the shape.
shape = states.values().map(Set::len).collect();
}
// For each variable ...
for (i, e) in evidences.iter_mut().enumerate() {
// Assert states distributions have the correct size.
assert!(
e.as_ref().is_none_or(|e| match e {
E::CertainPositive { .. } => true,
E::CertainNegative { .. } => true,
E::UncertainPositive { p_states, .. } => {
p_states.len() == shape[i]
}
E::UncertainNegative { p_not_states, .. } => {
p_not_states.len() == shape[i]
}
}),
"Evidence states distributions must have the correct size."
);
// Assert states distributions are not negative.
assert!(
e.as_ref().is_none_or(|e| match e {
E::CertainPositive { .. } => true,
E::CertainNegative { .. } => true,
E::UncertainPositive { p_states, .. } => {
p_states.iter().all(|&x| x >= 0.)
}
E::UncertainNegative { p_not_states, .. } => {
p_not_states.iter().all(|&x| x >= 0.)
}
}),
"Evidence states distributions must be non-negative."
);
// Assert states distributions sum to 1.
assert!(
e.as_ref().is_none_or(|e| match e {
E::CertainPositive { .. } => true,
E::CertainNegative { .. } => true,
E::UncertainPositive { p_states, .. } => {
relative_eq!(p_states.sum(), 1.)
}
E::UncertainNegative { p_not_states, .. } => {
relative_eq!(p_not_states.sum(), 1.)
}
}),
"Evidence states distributions must sum to 1."
);
}
Self {
labels,
states,
shape,
evidences,
}
}
/// The states of the evidence.
///
/// # Returns
///
/// A reference to the states of the evidence.
///
#[inline]
pub const fn states(&self) -> &States {
&self.states
}
/// The shape of the evidence.
///
/// # Returns
///
/// A reference to the shape of the evidence.
///
#[inline]
pub const fn shape(&self) -> &Array1<usize> {
&self.shape
}
/// The evidences of the evidence.
///
/// # Returns
///
/// A reference to the evidences of the evidence.
///
#[inline]
pub const fn evidences(&self) -> &Vec<Option<CatEvT>> {
&self.evidences
}
}