.. _architecture:

=================
Code Architecture
=================

This chapter describes the internal architecture of OMRAT, including
the module structure, class hierarchy, and data flow between components.

.. contents:: In this chapter
   :local:
   :depth: 2


Directory Structure
===================

::

   OMRAT/
   ├── omrat.py                    # Main plugin class (entry point)
   ├── omrat_widget.py             # Main UI dock widget
   ├── __init__.py                 # Plugin initialisation (classFactory)
   │
   ├── compute/                    # Risk calculation engine
   │   ├── basic_equations.py      # Core mathematical formulas
   │   ├── run_calculations.py     # Calculation orchestration
   │   ├── calculation_task.py     # QgsTask wrapper for background exec
   │   ├── database.py             # PostgreSQL/PostGIS connector
   │   └── iwrap_convertion.py     # IWRAP XML import/export
   │
   ├── geometries/                 # Spatial geometry operations
   │   ├── handle_qgis_iface.py    # Route digitisation & layer mgmt
   │   ├── route.py                # Route processing utilities
   │   ├── drift_corridor_v2.py    # Drift corridor API (re-exports)
   │   ├── drift_corridor_task_v2.py  # Background corridor generation
   │   ├── get_drifting_overlap.py # Overlap visualisation
   │   ├── calculate_probability_holes.py  # Monte Carlo integration
   │   ├── result_layers.py        # Result QGIS layer creation
   │   └── drift/                  # Refactored drift submodule
   │       ├── constants.py        # Direction constants (N,NE,E,...)
   │       ├── coordinates.py      # CRS transformations
   │       ├── distribution.py     # Width & projection distance
   │       ├── corridor.py         # Base surface & projected corridor
   │       ├── shadow.py           # Obstacle blocking zones
   │       ├── clipping.py         # Corridor clipping & anchor split
   │       ├── generator.py        # Main corridor generator (~800 lines)
   │       └── probability_integration.py  # Probability hole integration
   │
   ├── omrat_utils/                # Data management utilities
   │   ├── handle_traffic.py       # Traffic table management
   │   ├── handle_object.py        # Depth & structure management
   │   ├── handle_ais.py           # AIS database integration
   │   ├── handle_distributions.py # Lateral distribution modelling
   │   ├── handle_settings.py      # Drift parameter configuration
   │   ├── handle_ship_cat.py      # Ship type classifications
   │   ├── causation_factors.py    # Causation factor management
   │   ├── gather_data.py          # Data serialisation/deserialisation
   │   ├── storage.py              # Project file I/O (.omrat JSON)
   │   ├── validate_data.py        # Pydantic validation schemas
   │   ├── repair_time.py          # Repair time distribution
   │   └── units.py                # Unit conversion utilities
   │
   ├── ui/                         # User interface widgets
   │   ├── drift_settings_widget.py
   │   ├── traffic_data_widget.py
   │   ├── ship_categories_widget.py
   │   ├── ais_connection_widget.py
   │   ├── causation_factor_widget.py
   │   ├── result_widget.py
   │   └── show_geom_res.py
   │
   ├── helpers/                    # Helper utilities
   │   └── qt_conversions.py       # Qt5/Qt6 compatibility
   │
   ├── tests/                      # Test suite
   └── help/                       # Documentation (Sphinx)


Data Flow
=========

The following diagram shows how data flows through OMRAT from input to
output:

.. image:: _static/images/data_flow.svg
   :width: 100%
   :alt: Data flow from inputs through calculations to outputs

The data flow can be summarised in five phases:

1. **Input**: Routes are digitised on the map, traffic data is entered
   or imported from AIS, obstacles are loaded from shapefiles or GEBCO.

2. **Collection**: ``gather_data.py`` aggregates all data into a
   single dictionary for calculation and persistence.

3. **Transformation**: Geometries are transformed from WGS84 to UTM for
   accurate distance-based calculations.

4. **Calculation**: Three parallel pipelines compute drifting risk,
   powered risk, and collision risk.

5. **Output**: Results are visualised as QGIS layers and stored in the
   project file.


Key Classes
===========

OMRAT (omrat.py)
-----------------

The main plugin class. It owns all other components and orchestrates
the plugin lifecycle:

- **Initialisation**: Creates instances of all manager classes (Traffic,
  OObject, DriftSettings, etc.)
- **Signal management**: Connects UI buttons to handler methods
- **Calculation dispatch**: Creates ``CalculationTask`` or
  ``DriftCorridorTask`` instances for background execution
- **Menu/toolbar**: Registers QGIS menu items and toolbar buttons

.. container:: source-code-ref

   ``omrat.py`` -- `OMRAT <https://github.com/axelande/OMRAT/blob/main/omrat.py>`__ (main plugin entry point)

OMRATMainWidget (omrat_widget.py)
-----------------------------------

The Qt dock widget that provides the user interface. It is built from
``omrat_base.ui`` (Qt Designer file) and contains:

- **Route tab**: Route table, digitisation buttons
- **Traffic tab**: Ship frequency/speed/dimension tables
- **Depths tab**: Depth polygon management, GEBCO download
- **Objects tab**: Structure polygon management
- **Distributions tab**: Lateral distribution configuration and plots
- **Results tab**: Calculation results display
- **Drift Analysis tab**: Corridor generation controls

Calculation (compute/run_calculations.py)
------------------------------------------

The main calculation engine. Key responsibilities:

- ``run_drifting_model(data)``: Computes drifting grounding/allision
  probabilities using Monte Carlo integration
- ``run_ship_collision_model(data)``: Computes ship-ship collision
  frequencies
- ``run_powered_grounding_model(data)``: Computes powered grounding
   (Category I and II) with depth-bin caching and per-bin progress
   updates
- ``run_powered_allision_model(data)``: Computes powered allision
- ``run_drift_visualization(data)``: Creates visual corridor layers

.. container:: source-code-ref

   ``compute/run_calculations.py:44`` -- `Calculation <https://github.com/axelande/OMRAT/blob/main/compute/run_calculations.py#L44>`__ (mixin-based facade) |
   Mixins: `DriftingModelMixin <https://github.com/axelande/OMRAT/blob/main/compute/drifting_model.py>`__,
   `ShipCollisionModelMixin <https://github.com/axelande/OMRAT/blob/main/compute/ship_collision_model.py>`__,
   `PoweredModelMixin <https://github.com/axelande/OMRAT/blob/main/compute/powered_model.py>`__,
   `DriftingReportMixin <https://github.com/axelande/OMRAT/blob/main/compute/drifting_report.py>`__,
   `VisualizationMixin <https://github.com/axelande/OMRAT/blob/main/compute/visualization.py>`__

DriftCorridorGenerator (geometries/drift/generator.py)
-------------------------------------------------------

Orchestrates drift corridor generation for all legs and directions:

- ``precollect_data()``: Gathers UI data in the main thread (required
  because Qt widgets are thread-unsafe)
- ``generate_corridors()``: Generates corridors in a background thread
- ``_create_single_corridor()``: Creates one corridor for one leg in
  one direction

.. container:: source-code-ref

   ``geometries/drift/generator.py:25`` -- `DriftCorridorGenerator <https://github.com/axelande/OMRAT/blob/main/geometries/drift/generator.py#L25>`__ |
   ``geometries/drift/generator.py:65`` -- `precollect_data() <https://github.com/axelande/OMRAT/blob/main/geometries/drift/generator.py#L65>`__ |
   ``geometries/drift/generator.py:360`` -- `generate_corridors() <https://github.com/axelande/OMRAT/blob/main/geometries/drift/generator.py#L360>`__ |
   ``geometries/drift/generator.py:516`` -- `_create_single_corridor() <https://github.com/axelande/OMRAT/blob/main/geometries/drift/generator.py#L516>`__

HandleQGISIface (geometries/handle_qgis_iface.py)
---------------------------------------------------

Manages QGIS layer operations for route digitisation:

- Route creation via map click tool
- Segment data tracking (start/end points, directions, widths)
- Visual offset lines showing route width
- Geometry change detection for interactive editing
- Geometry edit persistence: map edits are synchronised back to
   ``segment_data`` (start/end points, directions, and line length), so
   save/export use the edited geometry

.. container:: source-code-ref

   ``geometries/handle_qgis_iface.py`` -- `HandleQGISIface <https://github.com/axelande/OMRAT/blob/main/geometries/handle_qgis_iface.py>`__


Data Structures
===============

Traffic Data
------------

Traffic data is stored in a nested dictionary::

   traffic_data[segment_id][direction] = {
       'Frequency (ships/year)': [[int, ...], ...],   # [type][size]
       'Speed (knots)':          [[float, ...], ...],
       'Draught (meters)':       [[float, ...], ...],
       'Ship heights (meters)':  [[float, ...], ...],
       'Ship Beam (meters)':     [[float, ...], ...],
   }

Each value is a 2D array indexed by ``[ship_type_index][ship_size_index]``.

Segment Data
------------

::

   segment_data[segment_id] = {
       'Start_Point': str,      # WKT point
       'End_Point': str,        # WKT point
       'Dirs': [str, str],      # Direction labels
       'Width': float,          # Lane width (m)
       'line_length': float,    # Segment length (m)
       'Route_Id': int,
       'Leg_name': str,
       'Segment_Id': int,
       # Distribution parameters:
       'mean1_1': float, 'std1_1': float, 'weight1_1': float,
       'mean1_2': float, 'std1_2': float, 'weight1_2': float,
       'mean1_3': float, 'std1_3': float, 'weight1_3': float,
       'u_min1': float, 'u_max1': float, 'u_p1': float,
       # ... same for direction 2 ...
   }

Drift Values
------------

::

   drift_values = {
       'drift_p': float,           # Blackout frequency
       'anchor_p': float,          # Anchor probability
       'anchor_d': float,          # Max anchorable depth (m)
       'speed': float,             # Drift speed (m/s)
       'rose': {                   # Wind rose probabilities
           '0': float,             # North
           '45': float,            # NorthWest
           '90': float,            # West
           '135': float,           # SouthWest
           '180': float,           # South
           '225': float,           # SouthEast
           '270': float,           # East
           '315': float,           # NorthEast
       },
       'repair': {
           'func': str,            # Custom function expression
           'std': float,           # Lognormal shape
           'loc': float,           # Location parameter
           'scale': float,         # Scale parameter
           'use_lognormal': bool,  # Use lognormal or custom
       }
   }


Background Task Execution
==========================

OMRAT uses QGIS's ``QgsTask`` system for long-running calculations.
This keeps the UI responsive while computations run in background
threads.

CalculationTask
----------------

Wraps the full risk calculation pipeline:

1. ``run_drifting_model()`` -- probability holes (60% of time)
2. ``run_ship_collision_model()`` -- collision frequencies (fast)
3. ``run_powered_grounding_model()`` -- powered grounding
4. ``run_powered_allision_model()`` -- powered allision

Signals emitted: ``progress_updated``, ``calculation_finished``,
``calculation_failed``.

.. container:: source-code-ref

   ``compute/calculation_task.py`` -- `CalculationTask <https://github.com/axelande/OMRAT/blob/main/compute/calculation_task.py>`__

DriftCorridorTask
------------------

Wraps the drift corridor generation:

1. ``precollect_data()`` runs in the main thread (before task starts)
2. ``generate_corridors()`` runs in the background thread
3. Layer creation runs in the main thread (via ``finished()`` signal)

Signals emitted: ``progress_updated``, ``corridors_generated``,
``generation_failed``.

.. container:: source-code-ref

   ``geometries/drift_corridor_task_v2.py`` -- `DriftCorridorTask <https://github.com/axelande/OMRAT/blob/main/geometries/drift_corridor_task_v2.py>`__


IWRAP Integration
=================

OMRAT supports bidirectional conversion with IWRAP XML format:

**Export** (``write_iwrap_xml``):

1. Gather project data via ``GatherData``
2. Build XML tree with waypoints, legs, traffic distributions, obstacles
3. Write formatted XML file

**Import** (``parse_iwrap_xml``):

1. Parse XML tree structure
2. Extract waypoints, legs, traffic, causation factors
3. Map to OMRAT's internal data format
4. Validate with Pydantic schema
5. Populate UI via ``GatherData.populate()``

The conversion handles differences in data model between IWRAP and OMRAT,
including coordinate format, traffic representation, and distribution
parameters.

.. container:: source-code-ref

   ``compute/iwrap_convertion.py`` -- `IWRAP conversion module <https://github.com/axelande/OMRAT/blob/main/compute/iwrap_convertion.py>`__


Project Persistence
===================

Projects are saved as ``.omrat`` files (JSON format):

::

   {
     "project_name": "My Analysis",
     "pc": {"p_pc": 1.6e-4, "d_pc": 1.0},
     "drift": {
       "drift_p": 1, "anchor_p": 0.95, "anchor_d": 7,
       "speed": 1.944, "rose": {...}, "repair": {...}
     },
     "traffic_data": {...},
     "segment_data": {...},
     "depths": [[id, depth, wkt], ...],
     "objects": [[id, height, wkt], ...],
     "ship_categories": {...}
   }

The ``validate_data.py`` module defines a Pydantic schema
(``RootModelSchema``) that validates the structure on save and load.
Legacy format conversion is handled by ``Storage._normalize_legacy_to_schema()``.

.. container:: source-code-ref

   ``omrat_utils/storage.py`` -- `Storage <https://github.com/axelande/OMRAT/blob/main/omrat_utils/storage.py>`__ |
   ``omrat_utils/validate_data.py`` -- `Validation schemas <https://github.com/axelande/OMRAT/blob/main/omrat_utils/validate_data.py>`__
