More progress towards reciprocal allocation algorithm

src/lib.rs

@@ -1,8 +1,8 @@
 extern crate nalgebra as na;
 
-use core::slice;
+use itertools::Itertools;
 use na::{DMatrix, Dynamic, LU};
-use std::{collections::HashMap, ops::Mul, error::Error};
+use std::{collections::HashMap, error::Error, ops::Mul};
 
 // TODO: Look into serde for serialisation, can also use it to serialise/deserialise
 // records from a csv file using the csv crate
@@ -117,15 +117,22 @@ pub fn move_money_2(
     running_total
 }
 
+#[derive(Debug, PartialEq, Eq)]
+pub enum DepartmentType {
+    Operating,
+    Overhead,
+}
+
 // TODO: Could also look at BigDecimal rather than f64 for higher precision (even i64 might be fine if we don't need to divide...)
 // Note: remember these are overhead departments only when calculating the lu decomposition or pseudoinverse, and for each department,
 // you either need -1 or rest negative for a row to subtract the initial amounts so we end up effectively 0 (simultaneous equations end
 // up with negative there so yes this is expected)
 // Also, we could potentially use this same struct for non-overhead departments when mapping from overhead to
 pub struct OverheadAllocationRule {
-    from_department: String,
+    from_overhead_department: String,
     to_department: String,
     percent: f64,
+    to_department_type: DepartmentType,
 }
 
 pub struct TotalDepartmentCost {
@@ -155,6 +162,24 @@ impl ReciprocalAllocationSolver for DMatrix<f64> {
     }
 }
 
+fn get_rules_indexes(
+    allocations: &Vec<OverheadAllocationRule>,
+    department_type: DepartmentType,
+) -> HashMap<String, usize> {
+    allocations
+        .iter()
+        .filter(|allocation| allocation.to_department_type == department_type)
+        .flat_map(|department| {
+            [
+                department.from_overhead_department.clone(),
+                department.to_department.clone(),
+            ]
+        })
+        .unique()
+        .enumerate()
+        .map(|(index, department)| (department, index))
+        .collect()
+}
 
 // Perform the reciprocal allocation (matrix) method to allocate servicing departments (indirect) costs
 // to functional departments. Basically just a matrix solve, uses regression (moore-penrose pseudoinverse) when
@@ -164,23 +189,35 @@ pub fn reciprocal_allocation(
     account_costs: Vec<AccountCost>,
     // TODO: Throw an appropriate error
 ) -> Result<Vec<AccountCost>, Box<dyn Error>> {
-    // TODO: Need to split up the rules so that we only pass overhead departments into the getreciprocal matrix method,
-    // and
-    let mut department_mappings: HashMap<String, usize> = HashMap::new();
-    for allocation in allocations.iter() {
-        let map_size = department_mappings.len();
-        department_mappings
-            .entry(allocation.from_department.clone())
-            .or_insert(map_size);
-        let map_size = department_mappings.len();
-        department_mappings
-            .entry(allocation.to_department.clone())
-            .or_insert(map_size);
+    let overhead_department_mappings: HashMap<String, usize> =
+        get_rules_indexes(&allocations, DepartmentType::Overhead);
+    let operating_department_mappings: HashMap<String, usize> =
+        get_rules_indexes(&allocations, DepartmentType::Operating);
+
+    let mut slice_allocations =
+        vec![0.; overhead_department_mappings.len() * overhead_department_mappings.len()];
+
+    for allocation in allocations
+        .iter()
+        .filter(|allocation| allocation.to_department_type == DepartmentType::Overhead)
+    {
+        // TODO: Check if we need to flp this around
+        let from_index = overhead_department_mappings
+            .get(&allocation.from_overhead_department)
+            .unwrap();
+        let to_index = operating_department_mappings
+            .get(&allocation.to_department)
+            .unwrap();
+        let elem = &mut slice_allocations
+            [(*from_index) + (overhead_department_mappings.len() * (*to_index))];
+        *elem = allocation.percent;
     }
 
+    // TODO: Also need ones along the diagonal, and negatives in some places...
+
     let mat: DMatrix<f64> = DMatrix::from_row_slice(
-        department_mappings.len(),
-        department_mappings.len(),
+        overhead_department_mappings.len(),
+        overhead_department_mappings.len(),
         &slice_allocations,
     );
 
@@ -189,14 +226,14 @@ pub fn reciprocal_allocation(
         do_solve_reciprocal(
             pseudo_inverse.unwrap(),
             account_costs,
-            department_mappings,
+            overhead_department_mappings,
             allocations,
         )
     } else {
         do_solve_reciprocal(
             mat.lu(),
             account_costs,
-            department_mappings,
+            overhead_department_mappings,
             allocations,
         )
     }
@@ -210,14 +247,7 @@ fn do_solve_reciprocal<T: ReciprocalAllocationSolver>(
 ) -> Result<Vec<AccountCost>, Box<dyn Error>> {
     // TODO: Could batch the accounts, although probably won't see to big a speed increase, compiler should help us out
     for total_costs in account_costs {
-        let mut slice_allocations = vec![0.; department_mappings.len()];
         let mut slice_costs = vec![0.; department_mappings.len()];
-        for allocation in allocations {
-            let elem = &mut slice_allocations[*department_mappings
-                .get(&allocation.from_department)
-                .unwrap()];
-            *elem = allocation.percent;
-        }
 
         for cost in total_costs.summed_department_costs {
             let elem = &mut slice_costs[*department_mappings.get(&cost.department).unwrap()];
@@ -233,7 +263,6 @@ fn do_solve_reciprocal<T: ReciprocalAllocationSolver>(
         // Where operating_overhead_usage is the direct mapping from overhead -> operating department, calculated overheads is the
         // solved overheads usages after taking into account usage between departments, and initial_totals is the initial values
         // for the operating departments.
-        
     }
     // TODO: return something appropriate
     Ok(vec![])