Rework reciprocal allocation to be closer to final algorithm, perform calculations off heap

src/lib.rs

@@ -1,7 +1,8 @@
 extern crate nalgebra as na;
 
-use na::DMatrix;
-use std::{collections::HashMap, ops::Mul};
+use core::slice;
+use na::{DMatrix, Dynamic, LU};
+use std::{collections::HashMap, ops::Mul, error::Error};
 
 // TODO: Look into serde for serialisation, can also use it to serialise/deserialise
 // records from a csv file using the csv crate
@@ -132,22 +133,39 @@ pub struct TotalDepartmentCost {
     value: f64,
 }
 
+pub struct AccountCost {
+    account: String,
+    summed_department_costs: Vec<TotalDepartmentCost>,
+}
+
+// TODO: Also need a way to dictate the order of the departments?
+pub trait ReciprocalAllocationSolver {
+    fn solve(&self, costs: &DMatrix<f64>) -> DMatrix<f64>;
+}
+
+impl ReciprocalAllocationSolver for LU<f64, Dynamic, Dynamic> {
+    fn solve(&self, costs: &DMatrix<f64>) -> DMatrix<f64> {
+        self.solve(costs).unwrap()
+    }
+}
+
+impl ReciprocalAllocationSolver for DMatrix<f64> {
+    fn solve(&self, costs: &DMatrix<f64>) -> DMatrix<f64> {
+        self.mul(costs)
+    }
+}
+
+
 // 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
 // matrix is singular
-// TODO: Could also reduce memory by just calculating overhead costs in a first step (service departments), then
-// calculating operating department costs in a second step using the output from the service departments (multiply
-// by service department output rather than original). The second step can be a vector multiply or a loop, basically
-// same as move money step, might bven be able to just repeat it
-// Note: PPM currently does the invert for the cost centres only (so can be up to 6000 ccs), as the cost centres are the actual departments,
-// and a previous step calculates the percentages for overhead areas using their allocation statistics. Then for each account,
-// it will use the overhead allocation matrix to calculate the moved/overhead allocations from the line items calculated from the previous
-// cost definiteions/reclass rules steps. Really we'd want to batch this out so we multiple a couple hundred or so accounts at a time (maybe
-// with a batch size property)
-pub fn get_reciprocal_allocation_matrix(
+pub fn reciprocal_allocation(
     allocations: Vec<OverheadAllocationRule>,
-    total_costs: Vec<TotalDepartmentCost>,
-) -> DMatrix<f64> {
+    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();
@@ -160,39 +178,63 @@ pub fn get_reciprocal_allocation_matrix(
             .or_insert(map_size);
     }
 
-    let mut slice_allocations = vec![0.; department_mappings.len()];
-
-    // TODO: This needs to be passed in another time
-    let mut slice_costs = vec![0.; department_mappings.len()];
-    for allocation in allocations {
-        // TODO: Is there a more idiomatic way to do this?
-        let elem = &mut slice_allocations[*department_mappings
-            .get(&allocation.from_department)
-            .unwrap()];
-        *elem = allocation.percent;
-    }
-
-    for cost in total_costs {
-        let elem = &mut slice_costs[*department_mappings.get(&cost.department).unwrap()];
-        *elem = cost.value;
-    }
-
     let mat: DMatrix<f64> = DMatrix::from_row_slice(
         department_mappings.len(),
         department_mappings.len(),
         &slice_allocations,
     );
 
-    let costs_vec: DMatrix<f64> =
-        DMatrix::from_row_slice(department_mappings.len(), 1, &slice_costs);
-
-    // TODO: Only calculate lu/pseudoinverse once. We then do the solve for the overhead department totals for each account, and use this to
-    // calculate the final totals.
     if mat.determinant() == 0. {
         let pseudo_inverse = mat.svd(true, true).pseudo_inverse(0.000001);
-        pseudo_inverse.unwrap().mul(&costs_vec)
+        do_solve_reciprocal(
+            pseudo_inverse.unwrap(),
+            account_costs,
+            department_mappings,
+            allocations,
+        )
     } else {
-        let lup = mat.lu();
-        lup.solve(&costs_vec).unwrap()
+        do_solve_reciprocal(
+            mat.lu(),
+            account_costs,
+            department_mappings,
+            allocations,
+        )
     }
 }
+
+fn do_solve_reciprocal<T: ReciprocalAllocationSolver>(
+    solver: T,
+    account_costs: Vec<AccountCost>,
+    department_mappings: HashMap<String, usize>,
+    allocations: Vec<OverheadAllocationRule>,
+) -> 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()];
+            *elem = cost.value;
+        }
+
+        let costs_vec: DMatrix<f64> =
+            DMatrix::from_row_slice(department_mappings.len(), 1, &slice_costs);
+
+        let calculated_overheads = solver.solve(&costs_vec);
+
+        // Calculation: operating_overhead_usage . calculated_overheads + initial_totals
+        // 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![])
+}