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Add progress on overhead allocation conversion from ppm format

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This commit is contained in:
Piv
2023-02-09 22:17:24 +10:30
parent 1bd7233c05
commit d1eb0b6e35
2 changed files with 198 additions and 35 deletions
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1
src/move_money.rs
View File

@@ -211,7 +211,6 @@ where
// Then run move_money
let moved = move_money_2(lines, &rules);
let mut output = output;
// Ouput the list moved moneys
for money in moved {

232
src/overhead_allocation.rs
View File

@@ -12,6 +12,16 @@ pub enum DepartmentType {
Overhead,
}
impl DepartmentType {
pub fn from(s: &str) -> DepartmentType {
if s == "P" {
DepartmentType::Operating
} else {
DepartmentType::Overhead
}
}
}
#[derive(Deserialize)]
pub struct CsvAllocationStatistic {
#[serde(rename = "Name")]
@@ -92,7 +102,7 @@ pub fn reciprocal_allocation<Lines, Account, AllocationStatistic, Area, CostCent
allocation_statistics: csv::Reader<AllocationStatistic>,
areas: csv::Reader<Area>,
cost_centres: csv::Reader<CostCentre>,
output: csv::Writer<Output>,
output: &mut csv::Writer<Output>,
use_numeric_accounts: bool,
) -> anyhow::Result<()>
where
@@ -108,18 +118,21 @@ where
.deserialize()
.collect::<Result<Vec<CsvCost>, csv::Error>>()?;
let mut accounts = accounts;
// TODO: Accounts need to come from actual account fiile
let all_accounts_sorted: Vec<String> = if use_numeric_accounts {
lines
.iter()
.map(|line| line.account.clone().parse::<i32>().unwrap())
accounts
.deserialize::<CsvAccount>()
.map(|line| line.unwrap().code.clone().parse::<i32>().unwrap())
.unique()
.sorted()
.map(|account| account.to_string())
.collect()
} else {
lines
.iter()
.map(|line| line.account.clone())
accounts
.deserialize::<CsvAccount>()
.map(|line| line.unwrap().code.clone())
.unique()
.sorted()
.collect()
@@ -131,7 +144,9 @@ where
.collect::<Result<Vec<CsvAllocationStatistic>, csv::Error>>()?;
// For each allocation statistic, sum the cost centres across accounts in the allocaiton statistic range
let flat_department_costs: Vec<(String, String, f64)> = allocation_statistics
// value is (cc, allocation_statistic, total)
// TODO: This is super slow
let flat_department_costs: HashMap<(String, String), f64> = allocation_statistics
.iter()
.map(|allocation_statistic| {
(
@@ -163,52 +178,181 @@ where
.iter()
.map(|entry| {
(
entry.0.clone(),
allocation_statistic.0.name.clone(),
(entry.0.clone(), allocation_statistic.0.name.clone()),
*entry.1,
)
})
.collect::<Vec<(String, String, f64)>>()
.collect::<Vec<((String, String), f64)>>()
})
.collect();
// TODO: If ignore negative is used, then set values < 0 to 0
let mut rollups: HashMap<String, HashMap<String, Vec<String>>> = HashMap::new();
let mut area_ccs: HashMap<String, Vec<String>> = HashMap::new();
let mut cost_centres = cost_centres;
for cost_centre in cost_centres.records() {
let cost_centre = cost_centre?;
// Extract rollups, used later with the areas... I could do a map of rollups -> cc's, or just a list of rollups on each cc struct
// I think map of rollup -> cc would be better, although this would need to be for each rollup slot... so a map of maps?
let headers = cost_centres.headers()?;
headers
.iter()
.filter(|name| name.to_lowercase().starts_with("rollupslot:"))
.for_each(|rollupslot| {
rollups.insert(rollupslot.to_owned(), HashMap::new());
});
for cost_centre in cost_centres.deserialize() {
let cost_centre: HashMap<String, String> = cost_centre?;
let name = cost_centre.get("Code").unwrap();
let area = cost_centre.get("Area").unwrap();
area_ccs
.entry(area.clone())
.or_insert(Vec::new())
.push(name.clone());
for rollupslot in rollups.iter_mut() {
let rollup_name = cost_centre.get(rollupslot.0).unwrap();
rollupslot
.1
.entry(rollup_name.clone())
.or_insert(Vec::new())
.push(name.clone());
}
}
let mut areas = areas;
let area_name_index = areas
.headers()?
let headers = areas.headers()?;
let limit_tos: Vec<String> = headers
.iter()
.position(|header| header == "Name")
.unwrap();
let allocation_statistic_index = areas
.headers()?
.iter()
.position(|header| header == "AllocationStatistic")
.unwrap();
.filter(|header| header.to_lowercase().starts_with("limitto:"))
.map(|header| header["limitto:".len()..].to_owned())
.collect();
let mut overhead_other_total: Vec<(String, String, f64)> = Vec::new();
let mut overhead_ccs: Vec<String> = Vec::new();
// For each overhead area, get the cost centres in the area, and get all cost centres
// that fit the limit to criteria for the area (skip any cases of overhead cc = other cc).
// Then get the totals for the other ccs, by looking in the flat_department_costs, where the
// allocation statistic matches the allocation statistic for this area
for area in areas.records() {
let area = area?;
for area in areas.deserialize() {
let area: HashMap<String, String> = area?;
// Check for limitTos, should probably somehow build out the list of allocation rules from this point.
let area_name = area.get(area_name_index).unwrap();
let allocation_statistic = area.get(allocation_statistic_index).unwrap();
let area_name = area.get("Name").unwrap();
let allocation_statistic = area.get("AllocationStatistic").unwrap();
let department_type: DepartmentType = DepartmentType::from(area.get("Type").unwrap());
let current_area_ccs = area_ccs.get(area_name);
if current_area_ccs.is_none() {
continue;
}
let mut current_area_ccs = current_area_ccs.unwrap().clone();
if department_type == DepartmentType::Overhead {
overhead_ccs.append(&mut current_area_ccs);
let overhead_ccs = area_ccs.get(area_name).unwrap();
// TODO: This depends on the area limit criteria. For now just assuming any limit criteria
let mut limited_ccs: Vec<String> = Vec::new();
for limit_to in limit_tos.iter() {
// TODO: It is technically possible to have more than one limit to for a slot, so consider eventually splitting this and doing a foreach
let limit_value = area.get(&("LimitTo:".to_owned() + limit_to)).unwrap();
if limit_value.is_empty() {
continue;
}
if limit_to.eq_ignore_ascii_case("costcentre") {
limited_ccs.push(limit_value.clone());
} else {
let mut found_ccs = rollups
.get(&("RollupSlot:".to_owned() + limit_to))
.map(|rollups| rollups.get(limit_value))
.flatten()
.unwrap()
.clone();
limited_ccs.append(&mut found_ccs);
}
}
if limited_ccs.is_empty() {
let mut other_ccs: Vec<String> = area_ccs
.values()
.flat_map(|ccs| ccs.iter().map(|cc| cc.clone()))
.collect();
// No limit criteria, use all ccs
limited_ccs.append(&mut other_ccs);
}
let mut totals: Vec<(String, String, f64)> = overhead_ccs
.iter()
.flat_map(|overhead_cc| {
limited_ccs
.iter()
.map(|other_cc| {
(
overhead_cc.clone(),
other_cc.clone(),
flat_department_costs
.get(&(other_cc.clone(), allocation_statistic.clone()))
.map(|f| *f)
.unwrap_or(0.),
)
})
.filter(|(_, _, value)| *value != 0.)
})
.collect();
overhead_other_total.append(&mut totals);
}
}
// Finally, for each cc match total produced previously, sum the overhead cc where overhead cc appears in other cc, then
// divide the other cc by this summed amount
// divide the other cc by this summed amount (thus getting the relative cost)
// do reciprocal allocation (only for variable portion of accounts), for each account
// At this point we convert to our format that's actually used, need to somehow recover the to_cc_type... could build that out from the areas
// Copy across fixed stuff (if necessary, not sure it is)... don't think it's necessary, initial totals handle this
let allocation_rules: Vec<OverheadAllocationRule> = overhead_other_total
.iter()
.map(
|(from_overhead_department, to_department, percent)| OverheadAllocationRule {
from_overhead_department: from_overhead_department.clone(),
to_department: to_department.clone(),
percent: percent
/ overhead_other_total
.iter()
.filter(|cc| cc.1 == *from_overhead_department)
.map(|cc| cc.2)
.sum::<f64>(),
to_department_type: if overhead_ccs.contains(&to_department) {
DepartmentType::Overhead
} else {
DepartmentType::Operating
},
},
)
.collect();
let mut initial_account_costs: HashMap<String, Vec<TotalDepartmentCost>> = HashMap::new();
for line in lines {
initial_account_costs
.entry(line.account)
.or_insert(Vec::new())
.push(TotalDepartmentCost {
department: line.department,
value: line.value,
});
}
let results = reciprocal_allocation_impl(
allocation_rules,
initial_account_costs
.into_iter()
.map(|(account, total_cost)| AccountCost {
account: account,
summed_department_costs: total_cost,
})
.collect(),
)?;
for cost in results {
for department in cost.summed_department_costs {
output.serialize(CsvCost {
account: cost.account.clone(),
department: department.department,
value: department.value,
})?;
}
}
Ok(())
}
@@ -221,9 +365,10 @@ fn split_allocation_statistic_range(
split
.map(|split| {
let range_split = split.split('-').collect::<Vec<_>>();
let start = remove_quote_and_padding(range_split[0]);
let start_index = accounts_sorted
.iter()
.position(|account| *account == range_split[0].to_owned())
.position(|account| *account == start)
.unwrap();
if range_split.len() == 1 {
AllocationStatisticAccountRange {
@@ -231,9 +376,10 @@ fn split_allocation_statistic_range(
end: start_index,
}
} else {
let end = remove_quote_and_padding(range_split[1]);
let end_index = accounts_sorted
.iter()
.position(|account| *account == range_split[1].to_owned())
.position(|account| *account == end)
.unwrap();
AllocationStatisticAccountRange {
start: start_index,
@@ -244,6 +390,10 @@ fn split_allocation_statistic_range(
.collect()
}
fn remove_quote_and_padding(s: &str) -> String {
s.trim()[1..s.trim().len() - 1].to_owned()
}
// 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
@@ -267,7 +417,6 @@ fn reciprocal_allocation_impl(
let to_index = overhead_department_mappings
.get(&allocation.to_department)
.unwrap();
// TODO: Check if dmatrix is row or column major order, would need to flip if column major
slice_allocations[from_index * overhead_department_mappings.len() + to_index] =
allocation.percent * -1.;
}
@@ -401,6 +550,7 @@ fn do_solve_reciprocal<T: ReciprocalAllocationSolver>(
#[cfg(test)]
mod tests {
use crate::reciprocal_allocation;
use crate::AccountCost;
use crate::DepartmentType;
use crate::OverheadAllocationRule;
@@ -486,4 +636,18 @@ mod tests {
let result = reciprocal_allocation_impl(allocation_rules, initial_totals).unwrap();
assert_eq!(expected_final_allocations, result);
}
#[test]
fn test_real() {
let result = reciprocal_allocation(
csv::Reader::from_path("output.csv").unwrap(),
csv::Reader::from_path("account.csv").unwrap(),
csv::Reader::from_path("allocstat.csv").unwrap(),
csv::Reader::from_path("area.csv").unwrap(),
csv::Reader::from_path("costcentre.csv").unwrap(),
&mut csv::Writer::from_path("output_alloc_stat.csv").unwrap(),
false,
);
assert!(result.is_ok())
}
}