feat: documentation update
- Completed export workflow implementation (query builders, CSV/XLSX serializers, streaming API endpoints, UI modals, automated tests). - Added export modal UI and client script to trigger downloads directly from dashboard. - Documented import/export field mapping and usage guidelines in FR-008. - Updated installation guide with export environment variables, dependencies, and CLI/CI usage instructions.
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@@ -75,6 +75,8 @@ The system employs a relational data model to manage and store information effic
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A detailed [Data Model](08_concepts/02_data_model.md) documentation is available.
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Discounted cash-flow metrics (NPV, IRR, Payback) referenced by the economic portion of the data model are described in the [Financial Metrics Specification](../specifications/financial_metrics.md), while stochastic extensions leverage the Monte Carlo engine documented in the [Monte Carlo Simulation Specification](../specifications/monte_carlo_simulation.md).
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All data interactions are handled through the [Data Access Layer](05_building_block_view.md#data-access-layer), ensuring consistency and integrity across operations.
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## Security
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@@ -32,6 +32,7 @@ The data model for the system is designed to capture the essential entities and
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- [Product Sales](#product-sales)
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- [Investment Model](#investment-model)
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- [Economic Model](#economic-model)
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- [Discounted Cash Flow Metrics](#discounted-cash-flow-metrics)
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- [Risk Model](#risk-model)
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- [Parameter](#parameter)
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- [Scenario](#scenario)
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@@ -74,6 +75,9 @@ erDiagram
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Unit ||--o{ QualityMetric : used_in
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Unit ||--o{ Parameter : used_in
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MiningTechnology ||--o{ Parameter : has_many
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MiningTechnology ||--o{ QualityMetric : has_many
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MiningTechnology ||--o{ MonteCarloSimulation : has_many
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```
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## User
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@@ -483,6 +487,14 @@ erDiagram
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FinancialModel ||--o{ EconomicModel : includes
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```
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#### Discounted Cash Flow Metrics
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CalMiner standardises the computation of NPV, IRR, and Payback Period through the shared helpers in `services/financial.py`. The detailed algorithms, assumptions (compounding frequency, period anchoring, residual handling), and regression coverage are documented in [Financial Metrics Specification](../../specifications/financial_metrics.md). Scenario evaluation services and downstream analytics should rely on these helpers to ensure consistency across API, UI, and reporting features.
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#### Monte Carlo Simulation
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Stochastic profitability analysis builds on the deterministic helpers by sampling cash-flow distributions defined per scenario. The configuration contracts, supported distributions, and result schema are described in [Monte Carlo Simulation Specification](../../specifications/monte_carlo_simulation.md). Scenario evaluation flows should call `services/simulation.py` to generate iteration summaries and percentile data for reporting and visualisation features.
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### Risk Model
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The Risk Model identifies and evaluates potential risks associated with mining projects. It includes risk factors, their probabilities, and potential impacts on project outcomes.
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