118 lines
3.8 KiB
TypeScript
118 lines
3.8 KiB
TypeScript
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/**
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* Pure-math helpers extracted from report-generators.ts so the
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* revenue/forecast/occupancy/funnel computations can be unit-tested
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* deterministically without spinning up a Postgres fixture.
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*
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* The corresponding DB-bound `fetch*Data` functions in report-generators
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* call into these helpers after gathering rows. Tests for the SQL itself
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* remain integration-tier; this module covers the arithmetic so a future
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* weight-tuning change can't silently shift the forecast number.
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*/
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import { STAGE_WEIGHTS, canonicalizeStage } from '@/lib/constants';
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export interface StageRevenueRow {
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stage: string;
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revenue: string | number | null;
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}
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export interface StageCountRow {
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stage: string;
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count: number;
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}
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export interface BerthStatusRow {
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status: string;
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count: number;
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}
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/**
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* Collapse a per-pipeline-stage revenue list into a canonicalized
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* Record<canonicalStage, totalRevenueString>. Handles the legacy 9-stage
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* keys via canonicalizeStage so historical rows fold into the modern
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* 7-stage bucket they belong to.
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*/
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export function rollupStageRevenue(rows: StageRevenueRow[]): Record<string, string> {
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const out: Record<string, string> = {};
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for (const row of rows) {
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const key = canonicalizeStage(row.stage);
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const prior = parseFloat(out[key] ?? '0');
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const next = row.revenue ? parseFloat(String(row.revenue)) : 0;
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out[key] = String(prior + next);
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}
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return out;
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}
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/**
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* Same as rollupStageRevenue but for counts (funnel breakdown).
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*/
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export function rollupStageCounts(rows: StageCountRow[]): Record<string, number> {
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const out: Record<string, number> = {};
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for (const row of rows) {
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const key = canonicalizeStage(row.stage);
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out[key] = (out[key] ?? 0) + row.count;
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}
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return out;
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}
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/**
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* Pipeline-weighted forecast: sum(berth_price × stage_weight) for every
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* active interest. The weight per stage resolves from per-port admin
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* overrides (`system_settings.pipeline_weights`) and falls back to the
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* STAGE_WEIGHTS defaults. Legacy stage keys canonicalize before lookup
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* so the forecast doesn't silently undershoot due to a key miss.
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*
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* Returns the forecast as a 2-decimal-fixed string for stable
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* comparison + downstream PDF rendering.
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*/
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export function computeTotalForecast(
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rows: StageRevenueRow[],
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weights: Record<string, number> = STAGE_WEIGHTS,
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): string {
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let total = 0;
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for (const row of rows) {
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if (!row.revenue) continue;
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const weight = weights[canonicalizeStage(row.stage)] ?? 0;
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total += parseFloat(String(row.revenue)) * weight;
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}
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return total.toFixed(2);
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}
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/**
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* Occupancy rate as a percentage. "Occupied" = sold only — per the
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* 2026-05-14 product decision, under_offer is a hold (blocks sale to
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* other clients) but doesn't count as the berth being occupied yet.
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* Returns the rate to 1 decimal place; returns 0 when totalBerths=0
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* to avoid NaN propagation through the PDF.
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*/
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export function computeOccupancyRate(statusCounts: Record<string, number>): {
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occupancyRate: number;
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totalBerths: number;
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} {
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let totalBerths = 0;
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for (const k of Object.keys(statusCounts)) {
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totalBerths += statusCounts[k] ?? 0;
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}
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const occupiedCount = statusCounts['sold'] ?? 0;
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const occupancyRate =
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totalBerths > 0 ? Math.round((occupiedCount / totalBerths) * 100 * 10) / 10 : 0;
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return { occupancyRate, totalBerths };
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}
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/**
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* Build the per-status count map from a status-grouped query result.
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* Returns the map AND the total count so callers don't have to sum
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* again themselves.
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*/
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export function rollupBerthStatusCounts(rows: BerthStatusRow[]): {
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statusCounts: Record<string, number>;
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totalBerths: number;
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} {
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const statusCounts: Record<string, number> = {};
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let totalBerths = 0;
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for (const row of rows) {
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statusCounts[row.status] = row.count;
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totalBerths += row.count;
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}
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return { statusCounts, totalBerths };
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}
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