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| Author | SHA1 | Date | |
|---|---|---|---|
| 2f4ceba8f1 | |||
| 9f34d61a0a | |||
| b1711d4d56 |
24 changed files with 48 additions and 1674 deletions
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@ -3,7 +3,7 @@ set -e
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python3 -m venv .env
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source ./.env/bin/activate
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pip install -r src/requirements/production.txt -r src/requirements/dev.txt
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pip install psycopg2
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pip install psycopg2 pylibmc
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sudo pacman -Sy librsvg
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./start_db.sh db
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@ -1,152 +0,0 @@
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# NOI Sensor Management System
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This system allows you to manage environmental sensors from the NOI Open Data Hub in c3nav, displaying them as overlay features on different levels/floors.
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## Overview
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The system supports:
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- Multiple sensors on the same overlay but on different levels
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- Dynamic addition of new sensors through Django management commands
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- Automatic data scraping from NOI Open Data Hub APIs
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- Real-time display of CO2, temperature, humidity and other environmental data
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## Architecture
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- **Single Overlay**: All NOI environmental sensors are managed under one `DataOverlay`
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- **Multiple Levels**: Sensors can be placed on different floors (floor0, floor1, etc.)
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- **Flexible Configuration**: Sensor locations and properties are configurable via the overlay's `sensor_config` field
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- **Dynamic Discovery**: The system can automatically discover and display any sensor data from the NOI API
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## Setup
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The main setup is handled by the `up.sh` script, which:
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1. Creates a single "NOI Environmental Sensors" overlay
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2. Configures initial sensors with their coordinates and levels
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3. Scrapes initial data from the NOI Open Data Hub
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4. Applies necessary database migrations
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## Managing Sensors
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### 1. List All Sensors
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```bash
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# Using the helper script
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./manage_noi_sensors.sh list
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# Or directly
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docker compose exec -T c3nav-core python manage.py list_sensors --overlay-id 1
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```
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### 2. Add a New Sensor
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```bash
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# Using the helper script
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./manage_noi_sensors.sh add 'NOI:YourSensorID' 'Sensor Display Name' 300.0 250.0 floor1
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# Or directly
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docker compose exec -T c3nav-core python manage.py add_sensor \
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--overlay-id 1 \
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--sensor-id 'NOI:YourSensorID' \
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--name 'Sensor Display Name' \
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--x 300.0 \
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--y 250.0 \
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--level floor1
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```
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### 3. Scrape Data for All Sensors
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```bash
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# Using the helper script
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./manage_noi_sensors.sh scrape
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# Or directly
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docker compose exec -T c3nav-core python manage.py manage_sensors --scrape-data --overlay-id 1
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```
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## Configuration Structure
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The overlay's `sensor_config` field contains:
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```json
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{
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"data_path": "data",
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"mappings": {
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"id_field": "scode",
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"name_field": "sname",
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"x_field": "scoordinate.x",
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"y_field": "scoordinate.y"
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},
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"sensors": [
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{
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"id": "NOI:FreeSoftwareLab-Temperature",
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"coordinates": {"x": 291.0, "y": 241.0},
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"level": "floor1"
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},
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{
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"id": "NOI:NOI-A1-Floor1-CO2",
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"coordinates": {"x": 270.0, "y": 241.0},
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"level": "floor1"
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}
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]
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}
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```
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## Database Schema
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### DataOverlay fields:
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- `data_source_url`: URL to scrape sensor data from
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- `sensor_config`: JSON configuration for sensor mapping and processing
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### DataOverlayFeature fields:
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- `sensor_id`: Unique identifier for the sensor
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- `sensor_type`: Type of sensor (e.g., 'environmental')
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- `sensor_value`: Single sensor value (nullable for multi-measurement sensors)
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- `sensor_unit`: Unit of measurement (nullable for multi-measurement sensors)
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- `coordinates_x`, `coordinates_y`: Position in c3nav coordinate system
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- `last_updated`: Timestamp of last data update
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- `sensor_data`: Raw sensor data for debugging
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- `extra_data`: Processed sensor readings for display
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## Data Flow
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1. **Configuration**: Sensors are configured in the overlay's `sensor_config`
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2. **Scraping**: The `manage_sensors` command fetches data from NOI Open Data Hub
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3. **Processing**: Data is processed according to sensor configuration
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4. **Storage**: Sensor features are created/updated in the database
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5. **Display**: Sensors appear as interactive points on the map
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## Adding New Sensor Types
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To add a new sensor from the NOI Open Data Hub:
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1. Find the sensor ID in the NOI API (usually starts with "NOI:")
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2. Determine the coordinates where it should appear on the map
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3. Choose the appropriate level/floor
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4. Add it using the `add_sensor` command
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5. Run the scrape command to fetch initial data
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## Troubleshooting
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### Sensor not appearing on map
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- Check if the level exists: `docker compose exec -T c3nav-core python manage.py shell -c "from c3nav.mapdata.models import Level; print([l.short_label for l in Level.objects.all()])"`
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- Verify coordinates are within the map bounds
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- Check if the overlay is enabled and visible
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### No data being scraped
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- Verify the sensor ID exists in the NOI Open Data Hub API
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- Check the API URL is accessible: https://mobility.api.opendatahub.com/v2/flat/IndoorStation/*/latest
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- Review logs during scraping for errors
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### Data not updating
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- Check the `last_updated` field in the sensor feature
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- Verify the scraping command completed successfully
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- Consider running the scrape command more frequently
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## Files
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- `up.sh`: Main setup script
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- `manage_noi_sensors.sh`: Helper script for sensor management
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- `src/c3nav/mapdata/management/commands/manage_sensors.py`: Core sensor management command
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- `src/c3nav/mapdata/management/commands/add_sensor.py`: Command to add new sensors
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- `src/c3nav/mapdata/management/commands/list_sensors.py`: Command to list sensors
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- `src/c3nav/mapdata/models/overlay.py`: Database models
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- `src/c3nav/mapdata/migrations/0140_add_temperature_fields.py`: Migration for sensor fields
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- `src/c3nav/mapdata/migrations/0141_add_sensor_data_field.py`: Migration for sensor_data field
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@ -15,7 +15,7 @@ x-healthcheck_defaults: &healthcheck_defaults
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interval: 10s
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timeout: 2s
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retries: 5
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start_period: 10s
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start_period: 5s
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x-c3nav-defaults: &c3nav-defaults
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build:
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context: ..
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@ -81,7 +81,7 @@ services:
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image: postgres:16
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healthcheck:
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<<: *healthcheck_defaults
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test: pg_isready -U postgres && psql -U postgres -d ${C3NAV_DATABASE_NAME:-c3nav} -c "SELECT 1;"
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test: pg_isready -U postgres
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environment:
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POSTGRES_DB: ${C3NAV_DATABASE_NAME:-c3nav}
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POSTGRES_HOST_AUTH_METHOD: "trust"
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|
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@ -1,44 +0,0 @@
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# SPDX-FileCopyrightText: 2024 NOI Techpark <digital@noi.bz.it>
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#
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# SPDX-License-Identifier: CC0-1.0
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[c3nav]
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svg_renderer=rsvg
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editor=False
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user_registration=false
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initial_level=2
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header_logo=/data/logo/sfscon.svg
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imprint_link=https://www.sfscon.it/impressum/
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branding=SFSCON map
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app_enabled=False
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[locale]
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languages=en
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[theme]
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#is_dark=False
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#randomize_primary_color=False
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map_background=#f7f8f8
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map_wall_fill=#e5e4e5
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map_wall_border=#c1bfbe
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#map_door_fill=#ffffff
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map_ground_fill=#f7f8f8
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#map_obstacles_default_fill=#b7b7b7
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#map_obstacles_default_border=#888888
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#css_primary=#9b4dca
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#css_initial=#ffffff
|
||||
#css_primary=#9b4dca
|
||||
#css_logo=None
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||||
#css_secondary=#525862
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||||
#css_tertiary=#f0f0f0
|
||||
#css_quaternary=#767676
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#css_quinary=#cccccc
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css_header_text=#000000
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||||
#css_header_text_hover=#eeeeee
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css_header_background=#ffffff
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#css_shadow=#000000
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#css_overlay_background=#ffffff
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#css_grid=#000000
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#css_modal_backdrop=#000000
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#css_route_dots_shadow=#ffffff
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#map_background=#dcdcdc
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6
local_run/data/logo/sfscon.svg
Normal file
6
local_run/data/logo/sfscon.svg
Normal file
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@ -0,0 +1,6 @@
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<!--
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SPDX-FileCopyrightText: 2024 NOI Techpark <digital@noi.bz.it>
|
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|
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SPDX-License-Identifier: CC0-1.0
|
||||
-->
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 186.5 37.18"><defs><style>.a{isolation:isolate;}.b{fill:#1c1c1c;}</style></defs><title>logo</title><g class="a"><g class="a"><path class="b" d="M15.85,54.66a20.05,20.05,0,0,1-7-1.29,18.42,18.42,0,0,1-6.25-3.88l4.62-5.56a17.43,17.43,0,0,0,4.27,2.7,11.07,11.07,0,0,0,4.59,1,6.29,6.29,0,0,0,3.77-.93,3,3,0,0,0,1.23-2.53,2.83,2.83,0,0,0-.35-1.43,3.44,3.44,0,0,0-1-1.07A9.71,9.71,0,0,0,18,40.83l-2.12-.91-4.67-2a13.8,13.8,0,0,1-2.67-1.43,11.92,11.92,0,0,1-2.31-2.06A9.29,9.29,0,0,1,4.63,31.7,9.68,9.68,0,0,1,4,28.15,9.38,9.38,0,0,1,5,24,10.22,10.22,0,0,1,7.6,20.59a12.74,12.74,0,0,1,4-2.29,15.35,15.35,0,0,1,5.14-.82A16.59,16.59,0,0,1,23,18.69a15.66,15.66,0,0,1,5.36,3.52l-4.12,5.12a15.54,15.54,0,0,0-3.52-2.12,9.91,9.91,0,0,0-3.91-.75,5.73,5.73,0,0,0-3.32.86,2.73,2.73,0,0,0-1.24,2.39,2.36,2.36,0,0,0,.41,1.4,4,4,0,0,0,1.16,1.05,12.08,12.08,0,0,0,1.73.88c.66.27,1.37.58,2.14.91l4.62,1.87a12.6,12.6,0,0,1,5.2,3.63,9.27,9.27,0,0,1,1.9,6.1,10.19,10.19,0,0,1-3.55,7.78,13,13,0,0,1-4.26,2.42A16.79,16.79,0,0,1,15.85,54.66Z" transform="translate(-2.59 -17.48)"/><path class="b" d="M35.48,54V18.14H58.09V25H43.57v8.3H56v6.82H43.57V54Z" transform="translate(-2.59 -17.48)"/><path class="b" d="M73.76,54.66a20.13,20.13,0,0,1-7-1.29,18.29,18.29,0,0,1-6.24-3.88l4.62-5.56a17.18,17.18,0,0,0,4.26,2.7,11.14,11.14,0,0,0,4.59,1,6.27,6.27,0,0,0,3.77-.93A3,3,0,0,0,79,44.21a2.74,2.74,0,0,0-.36-1.43,3.44,3.44,0,0,0-1-1.07,9.22,9.22,0,0,0-1.64-.88l-2.12-.91-4.68-2a14,14,0,0,1-2.66-1.43,11.36,11.36,0,0,1-2.31-2.06,9.53,9.53,0,0,1-1.63-2.75,9.9,9.9,0,0,1-.6-3.55A9.51,9.51,0,0,1,62.87,24a10.49,10.49,0,0,1,2.64-3.41,12.9,12.9,0,0,1,4-2.29,15.31,15.31,0,0,1,5.14-.82,16.63,16.63,0,0,1,6.19,1.21,15.76,15.76,0,0,1,5.36,3.52l-4.13,5.12a15.12,15.12,0,0,0-3.52-2.12,9.83,9.83,0,0,0-3.9-.75,5.74,5.74,0,0,0-3.33.86,2.73,2.73,0,0,0-1.24,2.39,2.36,2.36,0,0,0,.41,1.4,4.1,4.1,0,0,0,1.16,1.05,12.08,12.08,0,0,0,1.73.88l2.15.91,4.62,1.87a12.66,12.66,0,0,1,5.2,3.63,9.33,9.33,0,0,1,1.89,6.1,10.14,10.14,0,0,1-3.54,7.78,13.09,13.09,0,0,1-4.27,2.42A16.71,16.71,0,0,1,73.76,54.66Z" transform="translate(-2.59 -17.48)"/><path class="b" d="M108.36,54.66a17.49,17.49,0,0,1-6.44-1.18A15.15,15.15,0,0,1,96.62,50,16.35,16.35,0,0,1,93,44.24a22.08,22.08,0,0,1-1.32-8,21.51,21.51,0,0,1,1.38-7.95,17.81,17.81,0,0,1,3.68-5.91,15.55,15.55,0,0,1,5.39-3.68,16.83,16.83,0,0,1,6.49-1.27,13.59,13.59,0,0,1,6.22,1.4,17.22,17.22,0,0,1,4.56,3.28l-4.29,5.17a13.28,13.28,0,0,0-2.89-2.07,7.23,7.23,0,0,0-3.43-.8,7.72,7.72,0,0,0-3.44.8,8.18,8.18,0,0,0-2.81,2.28,11.5,11.5,0,0,0-1.86,3.63A15.85,15.85,0,0,0,100,36q0,5.57,2.36,8.61a7.59,7.59,0,0,0,6.33,3.05,8,8,0,0,0,3.93-1,12.09,12.09,0,0,0,3-2.39L120,49.38A14.55,14.55,0,0,1,108.36,54.66Z" transform="translate(-2.59 -17.48)"/><path class="b" d="M138,54.66a16.61,16.61,0,0,1-6.63-1.29,14.4,14.4,0,0,1-5.14-3.71,17.17,17.17,0,0,1-3.33-5.89,24.22,24.22,0,0,1-1.18-7.86,24,24,0,0,1,1.18-7.84,16.29,16.29,0,0,1,3.33-5.78,14.17,14.17,0,0,1,5.14-3.57,18.34,18.34,0,0,1,13.26,0,14.09,14.09,0,0,1,5.14,3.6,16.39,16.39,0,0,1,3.32,5.8,23.82,23.82,0,0,1,1.19,7.79A24.22,24.22,0,0,1,153,43.77a17,17,0,0,1-3.32,5.89,14.49,14.49,0,0,1-5.14,3.71A16.61,16.61,0,0,1,138,54.66Zm0-7a6.7,6.7,0,0,0,5.83-3.16c1.43-2.11,2.14-5,2.14-8.6s-.71-6.4-2.14-8.42a7.12,7.12,0,0,0-11.66,0c-1.43,2-2.15,4.82-2.15,8.42s.72,6.49,2.15,8.6A6.69,6.69,0,0,0,138,47.67Z" transform="translate(-2.59 -17.48)"/><path class="b" d="M161,54V18.14h8.31L178.65,36l3.52,7.92h.22c-.19-1.91-.4-4-.64-6.38s-.35-4.58-.35-6.71V18.14h7.7V54h-8.31l-9.35-17.87-3.52-7.81h-.22c.18,2,.4,4.1.63,6.38a62.75,62.75,0,0,1,.36,6.59V54Z" transform="translate(-2.59 -17.48)"/></g></g></svg>
|
||||
|
After Width: | Height: | Size: 3.7 KiB |
|
|
@ -1,46 +0,0 @@
|
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#!/bin/bash
|
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|
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# Helper script to manage NOI sensors
|
||||
# Usage: ./manage_noi_sensors.sh [add|list|scrape] [args...]
|
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|
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COMPOSE_EXEC="docker compose exec -T c3nav-core python manage.py"
|
||||
|
||||
case "$1" in
|
||||
"add")
|
||||
if [ $# -lt 6 ]; then
|
||||
echo "Usage: $0 add <sensor-id> <name> <x> <y> <level>"
|
||||
echo "Example: $0 add 'NOI:MyNewSensor' 'My New Sensor' 300.0 250.0 floor1"
|
||||
exit 1
|
||||
fi
|
||||
SENSOR_ID="$2"
|
||||
NAME="$3"
|
||||
X="$4"
|
||||
Y="$5"
|
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LEVEL="$6"
|
||||
echo "Adding sensor: $NAME ($SENSOR_ID) at ($X, $Y) on $LEVEL"
|
||||
$COMPOSE_EXEC add_sensor --overlay-id 1 --sensor-id "$SENSOR_ID" --name "$NAME" --x "$X" --y "$Y" --level "$LEVEL"
|
||||
;;
|
||||
"list")
|
||||
echo "Listing all sensors in overlay 1:"
|
||||
$COMPOSE_EXEC list_sensors --overlay-id 1
|
||||
;;
|
||||
"scrape")
|
||||
echo "Scraping data for all sensors in overlay 1:"
|
||||
$COMPOSE_EXEC manage_sensors --scrape-data --overlay-id 1
|
||||
;;
|
||||
*)
|
||||
echo "NOI Sensor Management Helper"
|
||||
echo "Usage: $0 [add|list|scrape] [args...]"
|
||||
echo ""
|
||||
echo "Commands:"
|
||||
echo " add <sensor-id> <name> <x> <y> <level> - Add a new sensor"
|
||||
echo " list - List all sensors"
|
||||
echo " scrape - Scrape data for all sensors"
|
||||
echo ""
|
||||
echo "Examples:"
|
||||
echo " $0 add 'NOI:NewSensor' 'My Sensor' 300.0 250.0 floor1"
|
||||
echo " $0 list"
|
||||
echo " $0 scrape"
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
|
|
@ -1,4 +1,7 @@
|
|||
|
||||
#cd ../docker
|
||||
#docker buildx rm c3nav-local 2>/dev/null || true
|
||||
#docker buildx create --name c3nav-local --driver=docker-container --bootstrap --use
|
||||
#cd ../local_run
|
||||
docker compose down --remove-orphans
|
||||
rm -rf data || true
|
||||
cp -r data-copy data
|
||||
|
|
@ -9,13 +12,17 @@ docker volume create c3nav-redis
|
|||
|
||||
# Start only postgres and redis first (no build since we pre-built)
|
||||
docker compose up -d postgres redis
|
||||
|
||||
sleep 10
|
||||
|
||||
|
||||
cat ./db/auth_user.sql | docker exec -i local_run-postgres-1 su - postgres -c 'psql c3nav'
|
||||
|
||||
# Create Django superuser
|
||||
|
||||
sleep 1
|
||||
|
||||
# Load database dump before starting the main app
|
||||
cat ./db/dump.sql | docker exec -i local_run-postgres-1 su - postgres -c 'psql c3nav' > /dev/null
|
||||
cat ./db/dump.sql | docker exec -i local_run-postgres-1 su - postgres -c 'psql c3nav'
|
||||
|
||||
# Fix geometry access permissions for anonymous users
|
||||
docker exec -i local_run-postgres-1 psql -U postgres -d c3nav -c "UPDATE mapdata_space SET base_mapdata_accessible = true;"
|
||||
|
|
@ -31,15 +38,11 @@ user.set_password('admin')
|
|||
user.save()
|
||||
print('Password set successfully for user:', user.username)
|
||||
\" | /app/env/bin/python manage.py shell"
|
||||
sleep 30
|
||||
|
||||
|
||||
# Apply migrations after loading dump
|
||||
echo "Applying migrations..."
|
||||
# Fake apply all migrations since we loaded from dump
|
||||
docker exec -i local_run-c3nav-core-1 sh -c '/app/env/bin/python manage.py migrate --fake'
|
||||
echo "Creating new migrations for sensor_data field..."
|
||||
docker exec -i local_run-c3nav-core-1 sh -c '/app/env/bin/python manage.py makemigrations mapdata'
|
||||
echo "Applying new migrations..."
|
||||
docker exec -i local_run-c3nav-core-1 sh -c '/app/env/bin/python manage.py migrate mapdata'
|
||||
|
||||
docker compose ps -a
|
||||
docker exec -i local_run-c3nav-core-1 sh -c '/app/env/bin/python manage.py clearmapcache --include-history --include-geometries && /app/env/bin/python manage.py collectstatic -l --no-input'
|
||||
|
|
@ -52,66 +55,3 @@ echo "Applying NumPy compatibility fix..."
|
|||
echo "Processing map updates to rebuild cache..."
|
||||
docker exec -i local_run-c3nav-core-1 sh -c '/app/env/bin/python manage.py processupdates'
|
||||
|
||||
# Setup sensor overlays
|
||||
echo "Setting up sensor overlays..."
|
||||
docker compose exec -T c3nav-core python manage.py shell << 'EOF'
|
||||
from c3nav.mapdata.models import DataOverlay, DataOverlayFeature
|
||||
|
||||
# Clear old overlays to avoid conflicts
|
||||
DataOverlay.objects.filter(titles__en__icontains='Environmental').delete()
|
||||
DataOverlay.objects.filter(titles__en__icontains='Temperature').delete()
|
||||
|
||||
# Create single NOI environmental sensor overlay with multiple sensors configuration
|
||||
overlay = DataOverlay.objects.create(
|
||||
titles={'en': 'NOI Environmental Sensors'},
|
||||
description='Real-time CO2 and temperature sensors from NOI Open Data Hub - displays current readings with values and units',
|
||||
default_geomtype='point',
|
||||
data_source_url='https://mobility.api.opendatahub.com/v2/flat/IndoorStation/*/latest',
|
||||
sensor_config={
|
||||
'data_path': 'data',
|
||||
'mappings': {
|
||||
'id_field': 'scode',
|
||||
'name_field': 'sname',
|
||||
'x_field': 'scoordinate.x',
|
||||
'y_field': 'scoordinate.y'
|
||||
},
|
||||
'sensors': [
|
||||
{
|
||||
'id': 'NOI:FreeSoftwareLab-Temperature',
|
||||
'coordinates': {'x': 291.0, 'y': 241.0},
|
||||
'level': 'floor1'
|
||||
},
|
||||
{
|
||||
'id': 'NOI:NOI-A1-Floor1-CO2',
|
||||
'coordinates': {'x': 270.0, 'y': 241.0},
|
||||
'level': 'floor1'
|
||||
}
|
||||
]
|
||||
},
|
||||
update_interval=120
|
||||
)
|
||||
print(f"NOI sensor overlay created with ID {overlay.id}")
|
||||
|
||||
EOF
|
||||
|
||||
# Scrape real NOI sensor data
|
||||
echo "Scraping NOI sensor data..."
|
||||
# Give the database a moment to settle after overlay creation
|
||||
sleep 2
|
||||
|
||||
# Scrape the overlay data (should automatically discover all configured sensors)
|
||||
echo "Scraping overlay data (ID: 1)..."
|
||||
docker compose exec -T c3nav-core python manage.py manage_sensors --scrape-data --overlay-id 1
|
||||
|
||||
# List all sensors to verify setup
|
||||
echo "Listing all sensors in the overlay..."
|
||||
docker compose exec -T c3nav-core python manage.py list_sensors --overlay-id 1
|
||||
|
||||
echo "Sensor setup completed!"
|
||||
echo ""
|
||||
echo "To add a new sensor to the overlay, use:"
|
||||
echo "docker compose exec -T c3nav-core python manage.py add_sensor --overlay-id 1 --sensor-id 'NOI:YourSensorID' --name 'Your Sensor Name' --x 300.0 --y 250.0 --level floor1"
|
||||
echo ""
|
||||
echo "To scrape data for all sensors:"
|
||||
echo "docker compose exec -T c3nav-core python manage.py manage_sensors --scrape-data --overlay-id 1"
|
||||
|
||||
|
|
|
|||
|
|
@ -186,8 +186,6 @@ editor = {
|
|||
|
||||
// Clear snap indicators when unloading
|
||||
editor._clear_snap_indicators();
|
||||
|
||||
editor._destroy_staircase_editing();
|
||||
},
|
||||
_fill_level_control: function (level_control, level_list, geometryURLs) {
|
||||
var levels = level_list.find('a');
|
||||
|
|
@ -502,10 +500,6 @@ editor = {
|
|||
// listener for form submits in the sidebar.
|
||||
e.preventDefault();
|
||||
if (editor._loading_geometry || $(this).is('.creation-lock') || $(this).is('.scan-lock')) return;
|
||||
if (editor._staircase_layer) {
|
||||
editor._staircase_submit($(this))
|
||||
return
|
||||
}
|
||||
var data = $(this).serialize();
|
||||
var btn = $(this).data('btn');
|
||||
if (btn !== undefined && btn !== null) {
|
||||
|
|
@ -1378,7 +1372,7 @@ editor = {
|
|||
} else if (mapitem_type) {
|
||||
// creating a new geometry, already drawn but form was rejected
|
||||
options = editor._get_mapitem_type_style(mapitem_type);
|
||||
if (mapitem_type === 'area' || mapitem_type === 'staircase') {
|
||||
if (mapitem_type === 'area') {
|
||||
options.fillOpacity = 0.5;
|
||||
}
|
||||
}
|
||||
|
|
@ -1398,7 +1392,7 @@ editor = {
|
|||
} else if (form.is('[data-new]')) {
|
||||
// create new geometry
|
||||
options = editor._get_mapitem_type_style(mapitem_type);
|
||||
if (mapitem_type === 'area' || mapitem_type === 'staircase') {
|
||||
if (mapitem_type === 'area') {
|
||||
options.fillOpacity = 0.5;
|
||||
}
|
||||
form.addClass('creation-lock');
|
||||
|
|
@ -1447,10 +1441,6 @@ editor = {
|
|||
}
|
||||
startGeomEditing(selected_geomtype);
|
||||
}
|
||||
|
||||
if (mapitem_type === 'staircase') {
|
||||
editor._setup_staircase_editing()
|
||||
}
|
||||
}
|
||||
},
|
||||
_cancel_editing: function () {
|
||||
|
|
@ -1740,7 +1730,7 @@ editor = {
|
|||
var snapTo90Control = L.control({position: 'topleft'});
|
||||
snapTo90Control.onAdd = function() {
|
||||
var container = L.DomUtil.create('div', 'leaflet-bar leaflet-control leaflet-control-snap');
|
||||
container.innerHTML = '<a href="#" title="[UNSTABLE] Toggle Snap to 90°" class="snap-to-90-toggle ' +
|
||||
container.innerHTML = '<a href="#" title="[UNSTABLE][ALSO ENABLE SNAP TO EDGES] Toggle Snap to 90°" class="snap-to-90-toggle ' +
|
||||
(editor._snap_to_90_enabled ? 'active' : '') + '"></a>';
|
||||
|
||||
L.DomEvent.on(container.querySelector('.snap-to-90-toggle'), 'click', function(e) {
|
||||
|
|
@ -1870,16 +1860,20 @@ editor = {
|
|||
// check if layer is within the area limit for infinite extension
|
||||
var allowInfiniteExtension = editor._is_layer_in_extension_area(layer, latlng, mapPoint);
|
||||
|
||||
var snapPoints = editor._find_closest_point_on_geometry(layer, latlng, mapPoint, allowInfiniteExtension);
|
||||
candidates.push(...snapPoints);
|
||||
var snapPoint = editor._find_closest_point_on_geometry(layer, latlng, mapPoint, allowInfiniteExtension);
|
||||
if (snapPoint && snapPoint.distance < editor._snap_distance) {
|
||||
candidates.push(snapPoint);
|
||||
}
|
||||
});
|
||||
|
||||
// check current editing shape with infinite extension enabled
|
||||
if (editor._current_editing_shape) {
|
||||
var currentShapeSnapPoints = editor._find_closest_point_on_geometry(
|
||||
var currentShapeSnap = editor._find_closest_point_on_geometry(
|
||||
editor._current_editing_shape, latlng, mapPoint, true // Always enable infinite extension for current shape
|
||||
);
|
||||
candidates.push(...currentShapeSnapPoints);
|
||||
if (currentShapeSnap && currentShapeSnap.distance < editor._snap_distance) {
|
||||
candidates.push(currentShapeSnap);
|
||||
}
|
||||
}
|
||||
|
||||
// find closest candidate
|
||||
|
|
@ -1887,30 +1881,6 @@ editor = {
|
|||
candidates.sort(function(a, b) { return a.distance - b.distance; });
|
||||
var best = candidates[0];
|
||||
|
||||
// see if we can snap to a corner, i.e. an edge intersection
|
||||
if (candidates.length >= 2 && candidates[0].isLine && candidates[1].isLine) {
|
||||
console.log(candidates.slice(0,2))
|
||||
var inters = editor._intersect_infinite(
|
||||
[candidates[0].edgeStart, candidates[0].edgeEnd],
|
||||
[candidates[1].edgeStart, candidates[1].edgeEnd]
|
||||
)
|
||||
if (inters) {
|
||||
intersMap = editor.map.latLngToContainerPoint(inters)
|
||||
var distance = Math.sqrt(
|
||||
Math.pow(intersMap.x - mapPoint.x, 2) +
|
||||
Math.pow(intersMap.y - mapPoint.y, 2)
|
||||
)
|
||||
if (distance < editor._snap_distance) {
|
||||
best = {
|
||||
latlng: inters,
|
||||
distance: distance,
|
||||
referenceVertex: inters,
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// show snap indicator with edge highlighting
|
||||
editor._show_snap_indicator(best.latlng, best);
|
||||
|
||||
|
|
@ -1921,24 +1891,6 @@ editor = {
|
|||
}
|
||||
},
|
||||
|
||||
_intersect_infinite: function(line1, line2) {
|
||||
const [p1, p2] = line1;
|
||||
const [p3, p4] = line2;
|
||||
|
||||
const x1 = p1.lng, y1 = p1.lat;
|
||||
const x2 = p2.lng, y2 = p2.lat;
|
||||
const x3 = p3.lng, y3 = p3.lat;
|
||||
const x4 = p4.lng, y4 = p4.lat;
|
||||
|
||||
const denom = (x1-x2)*(y3-y4) - (y1-y2)*(x3-x4);
|
||||
if (denom === 0) return null; // parallel
|
||||
|
||||
const px = ((x1*y2 - y1*x2)*(x3-x4) - (x1-x2)*(x3*y4 - y3*x4)) / denom;
|
||||
const py = ((x1*y2 - y1*x2)*(y3-y4) - (y1-y2)*(x3*y4 - y3*x4)) / denom;
|
||||
|
||||
return {lng: px, lat: py};
|
||||
},
|
||||
|
||||
_is_layer_in_extension_area: function(layer, targetLatLng, targetMapPoint) {
|
||||
if (!layer.getLatLngs) return false;
|
||||
|
||||
|
|
@ -2102,9 +2054,10 @@ editor = {
|
|||
},
|
||||
|
||||
_find_closest_point_on_geometry: function(layer, targetLatLng, targetMapPoint, allowInfiniteExtension) {
|
||||
if (!layer.getLatLngs) return [];
|
||||
if (!layer.getLatLngs) return null;
|
||||
|
||||
var closestPoints = [];
|
||||
var closestPoint = null;
|
||||
var closestDistance = Infinity;
|
||||
|
||||
try {
|
||||
var coordinates = [];
|
||||
|
|
@ -2120,16 +2073,16 @@ editor = {
|
|||
var centerMapPoint = editor.map.latLngToContainerPoint(center);
|
||||
var distance = centerMapPoint.distanceTo(targetMapPoint);
|
||||
if (distance < editor._snap_distance) {
|
||||
return [{
|
||||
return {
|
||||
latlng: center,
|
||||
distance: distance,
|
||||
edgeStart: center,
|
||||
edgeEnd: center,
|
||||
isInfiniteExtension: false,
|
||||
isRightAngle: false
|
||||
}];
|
||||
};
|
||||
}
|
||||
return [];
|
||||
return null;
|
||||
}
|
||||
|
||||
// check each edge of the geometry
|
||||
|
|
@ -2139,16 +2092,17 @@ editor = {
|
|||
var p2 = coordinates[(i + 1) % coordinates.length];
|
||||
|
||||
var snapPoint = editor._find_closest_point_on_edge(p1, p2, targetLatLng, targetMapPoint, allowInfiniteExtension);
|
||||
if (snapPoint && snapPoint.distance < editor._snap_distance) {
|
||||
closestPoints.push(snapPoint);
|
||||
if (snapPoint && snapPoint.distance < closestDistance) {
|
||||
closestDistance = snapPoint.distance;
|
||||
closestPoint = snapPoint;
|
||||
}
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
return [];
|
||||
return null;
|
||||
}
|
||||
|
||||
return closestPoints;
|
||||
return closestPoint;
|
||||
},
|
||||
|
||||
_find_closest_point_on_edge: function(p1, p2, targetLatLng, targetMapPoint, allowInfiniteExtension) {
|
||||
|
|
@ -2168,7 +2122,6 @@ editor = {
|
|||
distance: distance,
|
||||
edgeStart: p1,
|
||||
edgeEnd: p2,
|
||||
isLine: true,
|
||||
isInfiniteExtension: false,
|
||||
isRightAngle: false
|
||||
};
|
||||
|
|
@ -2204,7 +2157,6 @@ editor = {
|
|||
distance: distance,
|
||||
edgeStart: p1,
|
||||
edgeEnd: p2,
|
||||
isLine: true,
|
||||
isInfiniteExtension: isInfiniteExtension,
|
||||
isRightAngle: false,
|
||||
t: originalT
|
||||
|
|
@ -2233,26 +2185,9 @@ editor = {
|
|||
editor._show_90_degree_highlight(snapInfo);
|
||||
} else if (snapInfo && snapInfo.edgeStart && snapInfo.edgeEnd) {
|
||||
editor._show_edge_highlight(snapInfo);
|
||||
} else if (snapInfo && snapInfo.referenceVertex) {
|
||||
editor._show_intersect_highlight(snapInfo);
|
||||
}
|
||||
},
|
||||
|
||||
_show_intersect_highlight: function(snapInfo) {
|
||||
var referenceVertex = snapInfo.referenceVertex;
|
||||
var snapPoint = snapInfo.latlng;
|
||||
|
||||
// Draw line from reference vertex to snap point
|
||||
var guideLine = L.polyline([referenceVertex, snapPoint], {
|
||||
color: '#00aaff',
|
||||
weight: 2,
|
||||
opacity: 0.8,
|
||||
dashArray: '4, 4',
|
||||
className: '90-degree-guide'
|
||||
});
|
||||
editor._snap_indicator.addLayer(guideLine);
|
||||
},
|
||||
|
||||
_show_90_degree_highlight: function(snapInfo) {
|
||||
var referenceVertex = snapInfo.referenceVertex;
|
||||
var snapPoint = snapInfo.latlng;
|
||||
|
|
@ -2366,150 +2301,6 @@ editor = {
|
|||
if (editor._snap_indicator) {
|
||||
editor._snap_indicator.clearLayers();
|
||||
}
|
||||
},
|
||||
|
||||
_setup_staircase_editing: function() {
|
||||
editor._staircase_steps_count = 10
|
||||
editor._staircase_layer = L.layerGroup().addTo(editor.map);
|
||||
$('#stairway-steps').on('input', function() {
|
||||
editor._staircase_steps_count = parseInt($(this).val()) || 10;
|
||||
editor._update_staircase_preview();
|
||||
});
|
||||
|
||||
editor.map.on('editable:editing', editor._update_staircase_preview);
|
||||
},
|
||||
|
||||
_destroy_staircase_editing: function() {
|
||||
if (editor._staircase_layer) {
|
||||
editor.map.removeLayer(editor._staircase_layer)
|
||||
editor._staircase_layer = null
|
||||
}
|
||||
editor.map.off('editable:editing', editor._update_staircase_preview)
|
||||
if (editor._current_editing_shape && editor._current_editing_shape.editor) {
|
||||
editor._current_editing_shape.editor.cancelDrawing()
|
||||
editor._current_editing_shape.remove()
|
||||
editor._current_editing_shape = null
|
||||
}
|
||||
},
|
||||
|
||||
_transform_point_for_staircase: function(p, p0, cos_a, sin_a) {
|
||||
return {
|
||||
x: + (p.x - p0.x) * cos_a + (p.y - p0.y) * sin_a + p0.x,
|
||||
y: - (p.x - p0.x) * sin_a + (p.y - p0.y) * cos_a + p0.y,
|
||||
}
|
||||
},
|
||||
|
||||
_transform_for_staircase: function(xs, ys, num_stairs) {
|
||||
let base_length = Math.sqrt((xs[1]-xs[0])**2 + (ys[1]-ys[0])**2)
|
||||
let cos_a = (xs[1] - xs[0]) / base_length
|
||||
let sin_a = (ys[1] - ys[0]) / base_length
|
||||
let p0 = { x: xs[0], y: ys[0] }
|
||||
|
||||
xs = points.map(p => editor._transform_point_for_staircase(p, p0, cos_a, sin_a).x)
|
||||
ys = points.map(p => editor._transform_point_for_staircase(p, p0, cos_a, sin_a).y)
|
||||
n = xs.length
|
||||
|
||||
if (Math.abs(Math.max(...ys) - ys[0]) > Math.abs(Math.min(...ys) - ys[0])) {
|
||||
height = Math.max(...ys) - ys[0]
|
||||
} else {
|
||||
height = Math.min(...ys) - ys[0]
|
||||
}
|
||||
|
||||
lines = [{p1: { x: xs[0], y: ys[0] }, p2: { x: xs[1], y: ys[1] }}]
|
||||
for (i = 1; i < num_stairs; ++i) {
|
||||
// intersect line y=y0+height/num_stairs*i with all transformed (xs,ys)
|
||||
y = ys[0] + height/num_stairs*i
|
||||
inters_xs = []
|
||||
for (j = 0; j < n; ++j) {
|
||||
y1 = ys[j]
|
||||
y2 = ys[(j+1)%n]
|
||||
x1 = xs[j]
|
||||
x2 = xs[(j+1)%n]
|
||||
if ((y1 > y && y2 > y) || (y1 < y && y2 < y)) {
|
||||
continue
|
||||
}
|
||||
|
||||
if (Math.abs(x2 - x1) < 0.0001) {
|
||||
// vertical line, m would be infinity
|
||||
inters_xs.push(x1)
|
||||
continue
|
||||
}
|
||||
|
||||
m = (y2 - y1) / (x2 - x1)
|
||||
q = y2 - m * x2
|
||||
inters_xs.push((y - q) / m)
|
||||
}
|
||||
|
||||
if (inters_xs.length < 2) {
|
||||
continue
|
||||
}
|
||||
|
||||
min_xs = Math.min(...inters_xs)
|
||||
max_xs = Math.max(...inters_xs)
|
||||
lines.push({p1: {x: min_xs-2, y: y}, p2: {x: max_xs+2, y: y}})
|
||||
}
|
||||
|
||||
lines = lines.map(l => ({
|
||||
p1: editor._transform_point_for_staircase(l.p1, p0, cos_a, -sin_a),
|
||||
p2: editor._transform_point_for_staircase(l.p2, p0, cos_a, -sin_a),
|
||||
}))
|
||||
|
||||
return lines
|
||||
},
|
||||
|
||||
_get_staircase_lines: function() {
|
||||
if (!editor._current_editing_shape || !editor._current_editing_shape._parts) {
|
||||
return []
|
||||
}
|
||||
points = editor._current_editing_shape._parts[0] || []
|
||||
if (points.length < 3) {
|
||||
return []
|
||||
}
|
||||
|
||||
xs = points.map(p => p.x)
|
||||
ys = points.map(p => p.y)
|
||||
lines = editor._transform_for_staircase(xs, ys, editor._staircase_steps_count)
|
||||
lines = lines.map(l => [
|
||||
editor.map.layerPointToLatLng([l.p1.x, l.p1.y]),
|
||||
editor.map.layerPointToLatLng([l.p2.x, l.p2.y]),
|
||||
])
|
||||
return lines
|
||||
},
|
||||
|
||||
_update_staircase_preview: function(e = null) {
|
||||
if (editor._staircase_layer) {
|
||||
editor._staircase_layer.clearLayers()
|
||||
}
|
||||
lines = editor._get_staircase_lines()
|
||||
lines.forEach(l => {
|
||||
L.polyline(l, {color: "red"}).addTo(editor._staircase_layer);
|
||||
})
|
||||
},
|
||||
|
||||
_staircase_submit: function(form) {
|
||||
csrfmiddlewaretoken = form.find('input[name=csrfmiddlewaretoken]').attr('value')
|
||||
import_tag = form.find('input[name=import_tag]').val()
|
||||
space = form.attr('space')
|
||||
lines = editor._get_staircase_lines()
|
||||
|
||||
Promise.all(lines.map(l =>
|
||||
fetch("/editor/spaces/" + space + "/stairs/create", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
|
||||
"X-Requested-With": "XMLHttpRequest",
|
||||
},
|
||||
body: "csrfmiddlewaretoken=" + encodeURIComponent(csrfmiddlewaretoken) +
|
||||
"&geometry=" + encodeURIComponent(JSON.stringify({
|
||||
type: "LineString",
|
||||
coordinates: [[l[0]["lng"], l[0]["lat"]], [l[1]["lng"], l[1]["lat"]]]
|
||||
})) +
|
||||
"&import_tag=" + encodeURIComponent(import_tag)
|
||||
})
|
||||
)).then(() => {
|
||||
form.remove()
|
||||
window.location.href = "/editor/spaces/" + space + "/stairs"
|
||||
})
|
||||
}
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -1,40 +0,0 @@
|
|||
{% load bootstrap3 %}
|
||||
{% load i18n %}
|
||||
|
||||
{% include 'editor/fragment_levels.html' %}
|
||||
|
||||
<h3>
|
||||
{% blocktrans %}Add staircase{% endblocktrans %}
|
||||
</h3>
|
||||
{% bootstrap_messages %}
|
||||
|
||||
<form space="{{ space }}" {% if nozoom %}data-nozoom {% endif %}data-onbeforeunload data-new="staircase" data-geomtype="polygon" {% if access_restriction_select %} data-access-restriction-select{% endif %}>
|
||||
{% csrf_token %}
|
||||
{% bootstrap_form form %}
|
||||
<div class="form-group">
|
||||
<label for="stairway-steps">Number of Steps:</label>
|
||||
<input type="number" id="stairway-steps" class="form-control" value="10">
|
||||
</div>
|
||||
{% buttons %}
|
||||
<button class="invisiblesubmit" type="submit"></button>
|
||||
<!-- <div class="btn-group">
|
||||
<button type="button" id="generate-staircase" accesskey="g" class="btn btn-primary pull-right">
|
||||
{% trans 'Generate stairs' %}
|
||||
</button>
|
||||
</div> -->
|
||||
{% if can_edit %}
|
||||
{% if not nosave %}
|
||||
<button type="submit" accesskey="m" class="btn btn-primary pull-right">
|
||||
{% trans 'Save' %}
|
||||
</button>
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
<a class="btn {% if new %}btn-danger{% else %}btn-default {% if can_edit %}pull-right{% endif %}{% endif %} cancel-btn" href="{{ back_url }}">
|
||||
{% if can_edit %}
|
||||
{% trans 'Cancel' %}
|
||||
{% else %}
|
||||
{% trans 'Back' %}
|
||||
{% endif %}
|
||||
</a>
|
||||
{% endbuttons %}
|
||||
</form>
|
||||
|
|
@ -20,11 +20,6 @@
|
|||
<a class="btn btn-default btn-xs" accesskey="n" href="{{ create_url }}">
|
||||
<i class="glyphicon glyphicon-plus"></i> {% blocktrans %}New {{ model_title }}{% endblocktrans %}
|
||||
</a>
|
||||
{% if model_title == "Stair" %}
|
||||
<a class="btn btn-default btn-xs" accesskey="n" href="/editor/spaces/{{ space.id }}/staircase">
|
||||
<i class="glyphicon glyphicon-plus"></i> {% blocktrans %}New staircase{% endblocktrans %}
|
||||
</a>
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
|
||||
{% if explicit_edit %}
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@ from django.views.generic import TemplateView
|
|||
|
||||
from c3nav.editor.views.account import change_password_view, login_view, logout_view, register_view
|
||||
from c3nav.editor.views.changes import changeset_detail, changeset_edit, changeset_redirect
|
||||
from c3nav.editor.views.edit import edit, graph_edit, level_detail, list_objects, main_index, staircase_edit, sourceimage, space_detail
|
||||
from c3nav.editor.views.edit import edit, graph_edit, level_detail, list_objects, main_index, sourceimage, space_detail
|
||||
from c3nav.editor.views.overlays import overlays_list, overlay_features, overlay_feature_edit
|
||||
from c3nav.editor.views.quest import QuestFormView
|
||||
from c3nav.editor.views.users import user_detail, user_redirect
|
||||
|
|
@ -33,6 +33,7 @@ def add_editor_urls(model_name, parent_model_name=None, with_list=True, explicit
|
|||
])
|
||||
return result
|
||||
|
||||
|
||||
# todo: custom path converters
|
||||
urlpatterns = [
|
||||
path('levels/<int:pk>/', level_detail, name='editor.levels.detail'),
|
||||
|
|
@ -90,4 +91,3 @@ urlpatterns.extend(add_editor_urls('LeaveDescription', 'Space'))
|
|||
urlpatterns.extend(add_editor_urls('CrossDescription', 'Space'))
|
||||
urlpatterns.extend(add_editor_urls('BeaconMeasurement', 'Space'))
|
||||
urlpatterns.extend(add_editor_urls('RangingBeacon', 'Space'))
|
||||
urlpatterns.append(path('spaces/<int:space>/staircase', edit, name='editor.stairs.staircase', kwargs={'model': apps.get_model('mapdata', 'Stair')}))
|
||||
|
|
|
|||
|
|
@ -70,12 +70,6 @@ def main_index(request):
|
|||
})
|
||||
|
||||
|
||||
@etag(editor_etag_func)
|
||||
@accesses_mapdata
|
||||
@sidebar_view
|
||||
def staircase_edit(request, space):
|
||||
return render(request, "editor/create_staircase.html")
|
||||
|
||||
@etag(editor_etag_func)
|
||||
@accesses_mapdata
|
||||
@sidebar_view
|
||||
|
|
@ -411,11 +405,7 @@ def edit(request, pk=None, model=None, level=None, space=None, on_top_of=None, e
|
|||
"access_restriction_select": True,
|
||||
})
|
||||
|
||||
if request.path.endswith("staircase"):
|
||||
ctx["space"] = space_id
|
||||
return render(request, 'editor/create_staircase.html', ctx)
|
||||
else:
|
||||
return render(request, 'editor/edit.html', ctx)
|
||||
return render(request, 'editor/edit.html', ctx)
|
||||
|
||||
|
||||
def get_visible_spaces(request):
|
||||
|
|
|
|||
|
|
@ -1,141 +0,0 @@
|
|||
import json
|
||||
from django.core.management.base import BaseCommand
|
||||
from django.utils import timezone
|
||||
from shapely.geometry import Point
|
||||
|
||||
from c3nav.mapdata.models import DataOverlay, DataOverlayFeature, Level
|
||||
|
||||
|
||||
class Command(BaseCommand):
|
||||
help = 'Add a new sensor to an existing overlay'
|
||||
|
||||
def add_arguments(self, parser):
|
||||
parser.add_argument(
|
||||
'--overlay-id',
|
||||
type=int,
|
||||
required=True,
|
||||
help='ID of the overlay to add the sensor to',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--sensor-id',
|
||||
type=str,
|
||||
required=True,
|
||||
help='Unique ID for the sensor (e.g., NOI:Sensor-ID)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--name',
|
||||
type=str,
|
||||
required=True,
|
||||
help='Display name for the sensor',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--x',
|
||||
type=float,
|
||||
required=True,
|
||||
help='X coordinate in c3nav coordinate system',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--y',
|
||||
type=float,
|
||||
required=True,
|
||||
help='Y coordinate in c3nav coordinate system',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--level',
|
||||
type=str,
|
||||
default='floor0',
|
||||
help='Level/floor where the sensor is located (default: floor0)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--sensor-type',
|
||||
type=str,
|
||||
default='environmental',
|
||||
help='Type of sensor (default: environmental)',
|
||||
)
|
||||
|
||||
def handle(self, *args, **options):
|
||||
try:
|
||||
overlay = DataOverlay.objects.get(id=options['overlay_id'])
|
||||
except DataOverlay.DoesNotExist:
|
||||
self.stderr.write(f'Overlay with ID {options["overlay_id"]} not found')
|
||||
return
|
||||
|
||||
try:
|
||||
level = Level.objects.get(short_label=options['level'])
|
||||
except Level.DoesNotExist:
|
||||
self.stderr.write(f'Level "{options["level"]}" not found')
|
||||
return
|
||||
|
||||
# Update overlay configuration to include the new sensor
|
||||
sensor_config = overlay.sensor_config or {}
|
||||
if 'sensors' not in sensor_config:
|
||||
sensor_config['sensors'] = []
|
||||
|
||||
# Check if sensor already exists in config
|
||||
existing_sensor = None
|
||||
for i, sensor in enumerate(sensor_config['sensors']):
|
||||
if sensor['id'] == options['sensor_id']:
|
||||
existing_sensor = i
|
||||
break
|
||||
|
||||
new_sensor_config = {
|
||||
'id': options['sensor_id'],
|
||||
'coordinates': {'x': options['x'], 'y': options['y']},
|
||||
'level': options['level']
|
||||
}
|
||||
|
||||
if existing_sensor is not None:
|
||||
sensor_config['sensors'][existing_sensor] = new_sensor_config
|
||||
self.stdout.write(f'Updated sensor configuration for {options["sensor_id"]}')
|
||||
else:
|
||||
sensor_config['sensors'].append(new_sensor_config)
|
||||
self.stdout.write(f'Added sensor configuration for {options["sensor_id"]}')
|
||||
|
||||
overlay.sensor_config = sensor_config
|
||||
overlay.save()
|
||||
|
||||
# Create the sensor feature (or update if it exists)
|
||||
point = Point(options['x'], options['y'])
|
||||
|
||||
feature, created = DataOverlayFeature.objects.update_or_create(
|
||||
overlay=overlay,
|
||||
sensor_id=options['sensor_id'],
|
||||
defaults={
|
||||
'titles': {'en': options['name']},
|
||||
'geometry': point,
|
||||
'level': level,
|
||||
'sensor_type': options['sensor_type'],
|
||||
'coordinates_x': options['x'],
|
||||
'coordinates_y': options['y'],
|
||||
'fill_color': '#95A5A6', # Default gray
|
||||
'stroke_color': '#95A5A6',
|
||||
'stroke_width': 2,
|
||||
'fill_opacity': 0.8,
|
||||
'show_label': True,
|
||||
'show_geometry': True,
|
||||
'interactive': True,
|
||||
'point_icon': 'sensors',
|
||||
'last_updated': timezone.now(),
|
||||
'extra_data': {
|
||||
'Status': 'No data yet',
|
||||
'Last Updated': timezone.now().strftime('%Y-%m-%d %H:%M:%S'),
|
||||
'Data Source': 'Manual configuration',
|
||||
'Station ID': options['sensor_id']
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
action = 'Created' if created else 'Updated'
|
||||
self.stdout.write(
|
||||
self.style.SUCCESS(
|
||||
f'{action} sensor "{options["name"]}" (ID: {options["sensor_id"]}) '
|
||||
f'at coordinates ({options["x"]}, {options["y"]}) on level {options["level"]}'
|
||||
)
|
||||
)
|
||||
|
||||
self.stdout.write(
|
||||
'You can now run the scrape command to fetch data for this sensor:'
|
||||
)
|
||||
self.stdout.write(
|
||||
f'python manage.py manage_sensors --scrape-data --overlay-id {options["overlay_id"]}'
|
||||
)
|
||||
|
|
@ -1,60 +0,0 @@
|
|||
from django.core.management.base import BaseCommand
|
||||
from c3nav.mapdata.models import DataOverlay, DataOverlayFeature
|
||||
|
||||
|
||||
class Command(BaseCommand):
|
||||
help = 'List all sensors in overlays'
|
||||
|
||||
def add_arguments(self, parser):
|
||||
parser.add_argument(
|
||||
'--overlay-id',
|
||||
type=int,
|
||||
help='ID of a specific overlay to list sensors for',
|
||||
)
|
||||
|
||||
def handle(self, *args, **options):
|
||||
if options['overlay_id']:
|
||||
try:
|
||||
overlay = DataOverlay.objects.get(id=options['overlay_id'])
|
||||
overlays = [overlay]
|
||||
except DataOverlay.DoesNotExist:
|
||||
self.stderr.write(f'Overlay with ID {options["overlay_id"]} not found')
|
||||
return
|
||||
else:
|
||||
overlays = DataOverlay.objects.all()
|
||||
|
||||
for overlay in overlays:
|
||||
self.stdout.write(f'\n=== Overlay {overlay.id}: {overlay.titles.get("en", "Unknown")} ===')
|
||||
|
||||
# Show overlay configuration
|
||||
sensor_config = overlay.sensor_config or {}
|
||||
configured_sensors = sensor_config.get('sensors', [])
|
||||
if configured_sensors:
|
||||
self.stdout.write('Configured sensors:')
|
||||
for sensor in configured_sensors:
|
||||
self.stdout.write(f' - {sensor["id"]} at ({sensor["coordinates"]["x"]}, {sensor["coordinates"]["y"]}) on level {sensor.get("level", "default")}')
|
||||
|
||||
# Show actual sensor features in database
|
||||
features = DataOverlayFeature.objects.filter(overlay=overlay)
|
||||
if features:
|
||||
self.stdout.write(f'\nSensor features in database ({features.count()}):')
|
||||
for feature in features:
|
||||
title = feature.titles.get('en', 'Unknown') if feature.titles else 'Unknown'
|
||||
level_name = feature.level.short_label if feature.level else 'No level'
|
||||
coords = f'({feature.coordinates_x}, {feature.coordinates_y})' if feature.coordinates_x is not None else 'No coords'
|
||||
last_updated = feature.last_updated.strftime('%Y-%m-%d %H:%M:%S') if feature.last_updated else 'Never'
|
||||
|
||||
self.stdout.write(f' - {feature.sensor_id}: {title}')
|
||||
self.stdout.write(f' Level: {level_name}, Coords: {coords}')
|
||||
self.stdout.write(f' Type: {feature.sensor_type or "Unknown"}, Last updated: {last_updated}')
|
||||
|
||||
if feature.extra_data:
|
||||
readings = [f'{k}: {v}' for k, v in feature.extra_data.items()
|
||||
if k not in ['Last Updated', 'Data Source', 'Station ID']]
|
||||
if readings:
|
||||
self.stdout.write(f' Readings: {", ".join(readings)}')
|
||||
else:
|
||||
self.stdout.write('No sensor features found in database')
|
||||
|
||||
if not overlays:
|
||||
self.stdout.write('No overlays found')
|
||||
|
|
@ -1,461 +0,0 @@
|
|||
import json
|
||||
import requests
|
||||
from django.core.management.base import BaseCommand
|
||||
from django.utils import timezone
|
||||
from shapely.geometry import Point
|
||||
|
||||
from c3nav.mapdata.models import DataOverlay, DataOverlayFeature, Level
|
||||
|
||||
class Command(BaseCommand):
|
||||
help = 'Setup and manage sensor overlays with generic sensor data'
|
||||
|
||||
def add_arguments(self, parser):
|
||||
parser.add_argument(
|
||||
'--create-overlay',
|
||||
type=str,
|
||||
help='Create a new sensor overlay with given name',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--data-source-url',
|
||||
type=str,
|
||||
help='URL to scrape sensor data from',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--sensor-config',
|
||||
type=str,
|
||||
help='JSON configuration for sensor data mapping',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--add-sensor',
|
||||
action='store_true',
|
||||
help='Add sensors manually with provided coordinates',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--scrape-data',
|
||||
action='store_true',
|
||||
help='Scrape data from configured data sources',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--overlay-id',
|
||||
type=int,
|
||||
help='ID of the overlay to work with',
|
||||
)
|
||||
|
||||
def handle(self, *args, **options):
|
||||
if options['create_overlay']:
|
||||
self.create_overlay(options)
|
||||
elif options['add_sensor']:
|
||||
self.add_sensors_manually(options)
|
||||
elif options['scrape_data']:
|
||||
self.scrape_sensor_data(options)
|
||||
else:
|
||||
self.stdout.write('Please specify an action: --create-overlay, --add-sensor, or --scrape-data')
|
||||
|
||||
def create_overlay(self, options):
|
||||
"""Create a new sensor overlay"""
|
||||
name = options['create_overlay']
|
||||
|
||||
# Parse sensor configuration
|
||||
sensor_config = {}
|
||||
if options['sensor_config']:
|
||||
try:
|
||||
sensor_config = json.loads(options['sensor_config'])
|
||||
except json.JSONDecodeError:
|
||||
self.stderr.write('Invalid JSON in sensor_config')
|
||||
return
|
||||
|
||||
overlay = DataOverlay.objects.create(
|
||||
titles={'en': name},
|
||||
description=f'Sensor overlay for {name}',
|
||||
default_geomtype=DataOverlay.GeometryType.POINT,
|
||||
data_source_url=options['data_source_url'],
|
||||
sensor_config=sensor_config,
|
||||
update_interval=30, # Update every 30 seconds
|
||||
)
|
||||
|
||||
self.stdout.write(
|
||||
self.style.SUCCESS(f'Created overlay "{name}" with ID {overlay.id}')
|
||||
)
|
||||
|
||||
def add_sensors_manually(self, options):
|
||||
"""Add sensors manually with coordinates"""
|
||||
if not options['overlay_id']:
|
||||
self.stderr.write('--overlay-id required when adding sensors manually')
|
||||
return
|
||||
|
||||
try:
|
||||
overlay = DataOverlay.objects.get(id=options['overlay_id'])
|
||||
except DataOverlay.DoesNotExist:
|
||||
self.stderr.write(f'Overlay with ID {options["overlay_id"]} not found')
|
||||
return
|
||||
|
||||
# Get the ground floor level (floor0)
|
||||
try:
|
||||
level = Level.objects.get(short_label='floor0')
|
||||
except Level.DoesNotExist:
|
||||
level = Level.objects.first() # Fallback to first level
|
||||
if not level:
|
||||
self.stderr.write('No levels found in database')
|
||||
return
|
||||
|
||||
# Example sensors - this should be configurable via command line or config file
|
||||
sensors = [
|
||||
{
|
||||
'sensor_id': 'temp_001',
|
||||
'sensor_type': 'temperature',
|
||||
'name': 'Meeting Room A1 - Temperature',
|
||||
'coordinates_x': 500,
|
||||
'coordinates_y': 300,
|
||||
'value': 22.5,
|
||||
'unit': '°C'
|
||||
},
|
||||
{
|
||||
'sensor_id': 'hum_001',
|
||||
'sensor_type': 'humidity',
|
||||
'name': 'Meeting Room A1 - Humidity',
|
||||
'coordinates_x': 500,
|
||||
'coordinates_y': 300,
|
||||
'value': 55.0,
|
||||
'unit': '%'
|
||||
},
|
||||
{
|
||||
'sensor_id': 'temp_002',
|
||||
'sensor_type': 'temperature',
|
||||
'name': 'Server Room - Temperature',
|
||||
'coordinates_x': 750,
|
||||
'coordinates_y': 400,
|
||||
'value': 18.2,
|
||||
'unit': '°C'
|
||||
},
|
||||
{
|
||||
'sensor_id': 'co2_001',
|
||||
'sensor_type': 'co2',
|
||||
'name': 'Office Space - CO2',
|
||||
'coordinates_x': 300,
|
||||
'coordinates_y': 600,
|
||||
'value': 450,
|
||||
'unit': 'ppm'
|
||||
}
|
||||
]
|
||||
|
||||
for sensor_item in sensors:
|
||||
# Create geometry from c3nav coordinates
|
||||
point = Point(sensor_item['coordinates_x'], sensor_item['coordinates_y'])
|
||||
|
||||
# Get color based on sensor type and value
|
||||
color = self.get_sensor_color(sensor_item['sensor_type'], sensor_item['value'])
|
||||
|
||||
feature = DataOverlayFeature.objects.create(
|
||||
overlay=overlay,
|
||||
titles={'en': sensor_item['name']},
|
||||
geometry=point,
|
||||
level=level,
|
||||
sensor_id=sensor_item['sensor_id'],
|
||||
sensor_type=sensor_item['sensor_type'],
|
||||
sensor_value=sensor_item['value'],
|
||||
sensor_unit=sensor_item['unit'],
|
||||
coordinates_x=sensor_item['coordinates_x'],
|
||||
coordinates_y=sensor_item['coordinates_y'],
|
||||
fill_color=color,
|
||||
stroke_color=color,
|
||||
stroke_width=2,
|
||||
fill_opacity=0.8,
|
||||
show_label=True,
|
||||
show_geometry=True,
|
||||
interactive=True,
|
||||
point_icon=self.get_sensor_icon(sensor_item['sensor_type']),
|
||||
last_updated=timezone.now(),
|
||||
extra_data={
|
||||
'value': str(sensor_item['value']),
|
||||
'unit': sensor_item['unit'],
|
||||
'sensor_type': sensor_item['sensor_type']
|
||||
}
|
||||
)
|
||||
|
||||
self.stdout.write(
|
||||
f'Created sensor {sensor_item["sensor_id"]}: {sensor_item["name"]} '
|
||||
f'({sensor_item["value"]}{sensor_item["unit"]}) at ({sensor_item["coordinates_x"]}, {sensor_item["coordinates_y"]})'
|
||||
)
|
||||
|
||||
def scrape_sensor_data(self, options):
|
||||
"""Scrape sensor data from configured data sources"""
|
||||
overlays = DataOverlay.objects.filter(data_source_url__isnull=False)
|
||||
|
||||
if options['overlay_id']:
|
||||
overlays = overlays.filter(id=options['overlay_id'])
|
||||
|
||||
for overlay in overlays:
|
||||
self.stdout.write(f'Scraping data for overlay: {overlay.titles.get("en", "Unknown")}')
|
||||
|
||||
try:
|
||||
# Fetch data from the source URL
|
||||
response = requests.get(overlay.data_source_url, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
# Process data using sensor configuration
|
||||
self.process_scraped_data(overlay, data)
|
||||
|
||||
except requests.RequestException as e:
|
||||
self.stderr.write(f'Error fetching data from {overlay.data_source_url}: {e}')
|
||||
except json.JSONDecodeError as e:
|
||||
self.stderr.write(f'Error parsing JSON from {overlay.data_source_url}: {e}')
|
||||
except Exception as e:
|
||||
self.stderr.write(f'Error processing data for overlay {overlay.id}: {e}')
|
||||
|
||||
def process_scraped_data(self, overlay, data):
|
||||
"""Process scraped data according to overlay configuration"""
|
||||
sensor_config = overlay.sensor_config or {}
|
||||
|
||||
# Default configuration for NOI Open Data Hub
|
||||
default_config = {
|
||||
"data_path": "data",
|
||||
"mappings": {
|
||||
"id_field": "scode",
|
||||
"name_field": "sname",
|
||||
"x_field": "scoordinate.x",
|
||||
"y_field": "scoordinate.y"
|
||||
},
|
||||
"sensors": [] # List of specific sensors to process
|
||||
}
|
||||
|
||||
config = {**default_config, **sensor_config}
|
||||
|
||||
# Extract sensor data array
|
||||
api_data = data
|
||||
if config.get("data_path"):
|
||||
for path_part in config["data_path"].split("."):
|
||||
api_data = api_data.get(path_part, [])
|
||||
|
||||
updated_count = 0
|
||||
created_count = 0
|
||||
|
||||
# Group measurements by station (scode) first and discover sensor types dynamically
|
||||
stations = {}
|
||||
for item in api_data:
|
||||
station_id = self.get_nested_field(item, config["mappings"]["id_field"])
|
||||
station_name = self.get_nested_field(item, config["mappings"]["name_field"])
|
||||
measurement_type = self.get_nested_field(item, "tname")
|
||||
|
||||
if not station_id or not measurement_type:
|
||||
continue
|
||||
|
||||
if station_id not in stations:
|
||||
stations[station_id] = {
|
||||
'name': station_name,
|
||||
'measurements': {}
|
||||
}
|
||||
|
||||
stations[station_id]['measurements'][measurement_type] = item
|
||||
|
||||
# If specific sensors are configured, only process those
|
||||
configured_sensors = config.get('sensors', [])
|
||||
sensor_configs = {s['id']: s for s in configured_sensors} if configured_sensors else {}
|
||||
|
||||
# Process each station and its measurements
|
||||
for station_id, station_data in stations.items():
|
||||
# Skip if we have specific sensors configured and this isn't one of them
|
||||
if sensor_configs and station_id not in sensor_configs:
|
||||
continue
|
||||
|
||||
# Get sensor-specific configuration
|
||||
sensor_specific_config = sensor_configs.get(station_id, {})
|
||||
|
||||
# Determine coordinates and level for this sensor
|
||||
if sensor_specific_config.get('coordinates'):
|
||||
# Use sensor-specific coordinates
|
||||
x_coord = sensor_specific_config['coordinates']['x']
|
||||
y_coord = sensor_specific_config['coordinates']['y']
|
||||
else:
|
||||
# Get coordinates from measurement data
|
||||
first_measurement = next(iter(station_data['measurements'].values()))
|
||||
x_coord = self.get_nested_field(first_measurement, config["mappings"]["x_field"])
|
||||
y_coord = self.get_nested_field(first_measurement, config["mappings"]["y_field"])
|
||||
|
||||
if x_coord is None or y_coord is None:
|
||||
continue
|
||||
|
||||
# Convert coordinates if needed
|
||||
x_coord = float(x_coord)
|
||||
y_coord = float(y_coord)
|
||||
|
||||
# Determine level for this sensor
|
||||
level_name = sensor_specific_config.get('level', config.get('level', 'floor0'))
|
||||
try:
|
||||
level = Level.objects.get(short_label=level_name)
|
||||
except Level.DoesNotExist:
|
||||
self.stderr.write(f'Level "{level_name}" not found for sensor {station_id}, using ground floor')
|
||||
try:
|
||||
level = Level.objects.get(short_label='floor0')
|
||||
except Level.DoesNotExist:
|
||||
level = Level.objects.first() # Final fallback
|
||||
if not level:
|
||||
self.stderr.write(f'No levels found in database for sensor {station_id}')
|
||||
continue
|
||||
|
||||
# Collect all sensor data for this station in one feature
|
||||
sensor_readings = {}
|
||||
raw_measurements = {}
|
||||
|
||||
# Process ALL measurements found in the API response (dynamically discovered)
|
||||
for measurement_type, measurement in station_data['measurements'].items():
|
||||
# Extract values dynamically from the API response
|
||||
sensor_value = self.get_nested_field(measurement, "mvalue")
|
||||
sensor_unit = self.get_nested_field(measurement, "tunit")
|
||||
sensor_name = self.get_nested_field(measurement, "tname")
|
||||
sensor_description = self.get_nested_field(measurement, "tdescription")
|
||||
|
||||
if sensor_value is None:
|
||||
continue # Skip if no value
|
||||
|
||||
# Convert sensor value to float
|
||||
try:
|
||||
sensor_value = float(sensor_value)
|
||||
except (ValueError, TypeError):
|
||||
continue
|
||||
|
||||
# Store this measurement for the combined sensor
|
||||
display_name = sensor_description or sensor_name or measurement_type
|
||||
unit_str = f" {sensor_unit}" if sensor_unit else ""
|
||||
sensor_readings[display_name] = f"{sensor_value}{unit_str}"
|
||||
raw_measurements[measurement_type] = measurement
|
||||
|
||||
if not sensor_readings:
|
||||
continue # Skip if no valid measurements
|
||||
|
||||
# Create a single sensor feature with all measurements
|
||||
sensor_id = station_id # Use station ID as sensor ID
|
||||
display_name = f"{station_data['name']} - Environmental Sensor"
|
||||
|
||||
# Determine primary color based on the most critical measurement
|
||||
# Priority: CO2 > Temperature > Humidity
|
||||
primary_color = '#95A5A6' # Default gray
|
||||
|
||||
# Look for CO2 measurements (various naming conventions)
|
||||
co2_measurement = None
|
||||
for mtype, measurement in raw_measurements.items():
|
||||
if any(keyword in mtype.lower() for keyword in ['co2', 'carbon']):
|
||||
co2_measurement = measurement
|
||||
break
|
||||
|
||||
if co2_measurement:
|
||||
co2_value = self.get_nested_field(co2_measurement, "mvalue")
|
||||
if co2_value:
|
||||
primary_color = self.get_sensor_color('co2', float(co2_value))
|
||||
else:
|
||||
# Look for temperature measurements
|
||||
temp_measurement = None
|
||||
for mtype, measurement in raw_measurements.items():
|
||||
if any(keyword in mtype.lower() for keyword in ['temperature', 'temp']):
|
||||
temp_measurement = measurement
|
||||
break
|
||||
|
||||
if temp_measurement:
|
||||
temp_value = self.get_nested_field(temp_measurement, "mvalue")
|
||||
if temp_value:
|
||||
primary_color = self.get_sensor_color('temperature', float(temp_value))
|
||||
|
||||
# Create geometry
|
||||
point = Point(x_coord, y_coord)
|
||||
|
||||
feature, created = DataOverlayFeature.objects.update_or_create(
|
||||
overlay=overlay,
|
||||
sensor_id=sensor_id,
|
||||
defaults={
|
||||
'titles': {'en': display_name},
|
||||
'geometry': point,
|
||||
'level': level,
|
||||
'sensor_type': 'environmental', # Combined sensor type
|
||||
'sensor_value': None, # No single value for combined sensor
|
||||
'sensor_unit': None, # No single unit for combined sensor
|
||||
'coordinates_x': x_coord,
|
||||
'coordinates_y': y_coord,
|
||||
'fill_color': primary_color,
|
||||
'stroke_color': primary_color,
|
||||
'stroke_width': 2,
|
||||
'fill_opacity': 0.8,
|
||||
'show_label': True,
|
||||
'show_geometry': True,
|
||||
'interactive': True,
|
||||
'point_icon': 'sensors', # Generic sensor icon
|
||||
'last_updated': timezone.now(),
|
||||
'sensor_data': raw_measurements, # Store all raw measurements
|
||||
'extra_data': {
|
||||
**sensor_readings, # All sensor readings as separate entries
|
||||
'Last Updated': timezone.now().strftime('%Y-%m-%d %H:%M:%S'),
|
||||
'Data Source': 'NOI Open Data Hub',
|
||||
'Station ID': station_id
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
if created:
|
||||
created_count += 1
|
||||
readings_str = ', '.join([f"{k}: {v}" for k, v in sensor_readings.items()])
|
||||
self.stdout.write(f'Created sensor {sensor_id} on level {level.short_label}: {readings_str}')
|
||||
else:
|
||||
updated_count += 1
|
||||
readings_str = ', '.join([f"{k}: {v}" for k, v in sensor_readings.items()])
|
||||
self.stdout.write(f'Updated sensor {sensor_id} on level {level.short_label}: {readings_str}')
|
||||
|
||||
self.stdout.write(
|
||||
f'Processed overlay {overlay.id}: {created_count} created, {updated_count} updated'
|
||||
)
|
||||
|
||||
def get_nested_field(self, data, field_path):
|
||||
"""Get value from nested field path like 'scoordinate.x'"""
|
||||
try:
|
||||
value = data
|
||||
for part in field_path.split('.'):
|
||||
value = value[part]
|
||||
return value
|
||||
except (KeyError, TypeError):
|
||||
return None
|
||||
|
||||
def get_sensor_color(self, sensor_type, value):
|
||||
"""Get color based on sensor type and value"""
|
||||
sensor_type_lower = sensor_type.lower()
|
||||
|
||||
if any(keyword in sensor_type_lower for keyword in ['temperature', 'temp']):
|
||||
if value < 15:
|
||||
return '#0066CC' # Cold - blue
|
||||
elif value < 18:
|
||||
return '#00AAFF' # Cool - light blue
|
||||
elif value < 22:
|
||||
return '#00CC66' # Comfortable - green
|
||||
elif value < 25:
|
||||
return '#FFAA00' # Warm - orange
|
||||
else:
|
||||
return '#FF3333' # Hot - red
|
||||
elif any(keyword in sensor_type_lower for keyword in ['humidity', 'humid']):
|
||||
if value < 30:
|
||||
return '#FF6B6B' # Too dry - red
|
||||
elif value < 60:
|
||||
return '#4ECDC4' # Good - teal
|
||||
else:
|
||||
return '#45B7D1' # Too humid - blue
|
||||
elif any(keyword in sensor_type_lower for keyword in ['co2', 'carbon']):
|
||||
if value < 400:
|
||||
return '#2ECC71' # Excellent - green
|
||||
elif value < 800:
|
||||
return '#F39C12' # Good - orange
|
||||
elif value < 1200:
|
||||
return '#E74C3C' # Poor - red
|
||||
else:
|
||||
return '#8E44AD' # Very poor - purple
|
||||
else:
|
||||
return '#95A5A6' # Default - gray
|
||||
|
||||
def get_sensor_icon(self, sensor_type):
|
||||
"""Get icon based on sensor type"""
|
||||
icons = {
|
||||
'air-temperature': 'thermostat',
|
||||
'air-humidity': 'water_drop',
|
||||
'co2-ppm': 'air',
|
||||
'temperature': 'thermostat',
|
||||
'humidity': 'water_drop',
|
||||
'co2': 'air',
|
||||
'pressure': 'compress',
|
||||
'light': 'light_mode'
|
||||
}
|
||||
return icons.get(sensor_type, 'sensors')
|
||||
|
|
@ -1,187 +0,0 @@
|
|||
import logging
|
||||
import requests
|
||||
from django.core.management.base import BaseCommand
|
||||
from c3nav.mapdata.models import DataOverlay, DataOverlayFeature, MapUpdate, Level
|
||||
from shapely.geometry import Point
|
||||
import json
|
||||
import traceback
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class Command(BaseCommand):
|
||||
help = 'Pull overlay data from external APIs'
|
||||
|
||||
def add_arguments(self, parser):
|
||||
parser.add_argument(
|
||||
'--force',
|
||||
action='store_true',
|
||||
help='Force update even if not enough time has passed',
|
||||
)
|
||||
|
||||
def handle(self, *args, **options):
|
||||
overlays = DataOverlay.objects.all()
|
||||
for overlay in overlays:
|
||||
self.stdout.write(f"Processing overlay: {overlay.title}")
|
||||
try:
|
||||
self.update_overlay(overlay, force=options['force'])
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating overlay {overlay.id}: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
self.stderr.write(f"Error updating overlay {overlay.id}: {e}")
|
||||
|
||||
def update_overlay(self, overlay, force=False):
|
||||
"""Update a single overlay from its API URL"""
|
||||
|
||||
if not overlay.pull_url:
|
||||
self.stdout.write(f"No API URL configured for overlay {overlay.id}")
|
||||
return
|
||||
|
||||
try:
|
||||
self.stdout.write(f"Fetching data from: {overlay.pull_url}")
|
||||
response = requests.get(overlay.pull_url, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
self.stdout.write(f"Received {len(data)} items from API")
|
||||
|
||||
# Process the data based on overlay type
|
||||
if hasattr(overlay, 'description') and overlay.description and 'temperature' in overlay.description.lower():
|
||||
self.process_temperature_data(overlay, data)
|
||||
else:
|
||||
self.stdout.write(f"Unknown overlay type for overlay {overlay.id}")
|
||||
|
||||
except requests.RequestException as e:
|
||||
logger.error(f"HTTP error fetching {overlay.pull_url}: {e}")
|
||||
self.stderr.write(f"HTTP error: {e}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing overlay {overlay.id}: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
self.stderr.write(f"Error: {e}")
|
||||
|
||||
def process_temperature_data(self, overlay, data):
|
||||
"""Process temperature sensor data from NOI Open Data Hub"""
|
||||
|
||||
# Clear existing features for this overlay
|
||||
DataOverlayFeature.objects.filter(overlay=overlay).delete()
|
||||
self.stdout.write(f"Cleared existing features for overlay {overlay.id}")
|
||||
|
||||
# Group measurements by station
|
||||
stations = {}
|
||||
for item in data:
|
||||
scode = item.get('scode')
|
||||
if scode:
|
||||
if scode not in stations:
|
||||
stations[scode] = {
|
||||
'sname': item.get('sname'),
|
||||
'scoordinate': item.get('scoordinate'),
|
||||
'measurements': []
|
||||
}
|
||||
stations[scode]['measurements'].append(item)
|
||||
|
||||
self.stdout.write(f"Found {len(stations)} stations")
|
||||
|
||||
for scode, station_data in stations.items():
|
||||
try:
|
||||
self.create_temperature_feature(overlay, scode, station_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Error creating feature for station {scode}: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
self.stderr.write(f"Error creating feature for {scode}: {e}")
|
||||
|
||||
def create_temperature_feature(self, overlay, scode, station_data):
|
||||
"""Create a DataOverlayFeature for a temperature station"""
|
||||
|
||||
# Extract coordinates from scoordinate object
|
||||
scoordinate = station_data.get('scoordinate')
|
||||
if not scoordinate:
|
||||
self.stdout.write(f"No coordinates for station {scode}")
|
||||
return
|
||||
|
||||
# scoordinate is a dict with x, y coordinates
|
||||
x = scoordinate.get('x')
|
||||
y = scoordinate.get('y')
|
||||
|
||||
if x is None or y is None:
|
||||
self.stdout.write(f"Invalid coordinates for station {scode}: {scoordinate}")
|
||||
return
|
||||
|
||||
self.stdout.write(f"Station {scode} coordinates: x={x}, y={y}")
|
||||
|
||||
# Create point geometry (assuming WGS84/EPSG:4326)
|
||||
point = Point(x, y)
|
||||
|
||||
# Find temperature measurement
|
||||
temperature = None
|
||||
humidity = None
|
||||
|
||||
for measurement in station_data['measurements']:
|
||||
tname = measurement.get('tname', '').lower()
|
||||
if 'temperature' in tname:
|
||||
temperature = measurement.get('mvalue')
|
||||
elif 'humidity' in tname:
|
||||
humidity = measurement.get('mvalue')
|
||||
|
||||
self.stdout.write(f"Station {scode}: temp={temperature}, humidity={humidity}")
|
||||
|
||||
if temperature is None:
|
||||
self.stdout.write(f"No temperature data for station {scode}")
|
||||
return
|
||||
|
||||
# Determine color based on temperature
|
||||
color = self.get_temperature_color(temperature)
|
||||
|
||||
# Try to find appropriate level (ground floor by default)
|
||||
level = None
|
||||
try:
|
||||
# Look for ground floor or level 0
|
||||
level = Level.objects.filter(
|
||||
short_label__in=['0', 'EG', 'Ground', 'G']
|
||||
).first()
|
||||
|
||||
if not level:
|
||||
# Fallback to any level
|
||||
level = Level.objects.first()
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Could not determine level: {e}")
|
||||
|
||||
if not level:
|
||||
self.stdout.write(f"No level found for station {scode}")
|
||||
return
|
||||
|
||||
self.stdout.write(f"Using level: {level.short_label} for station {scode}")
|
||||
|
||||
# Create the feature
|
||||
title = f"{station_data.get('sname', scode)} ({temperature}°C)"
|
||||
|
||||
feature = DataOverlayFeature.objects.create(
|
||||
overlay=overlay,
|
||||
level=level,
|
||||
geometry=point.wkt,
|
||||
title=title,
|
||||
color=color,
|
||||
opacity=0.8,
|
||||
icon='thermometer'
|
||||
)
|
||||
|
||||
self.stdout.write(f"Created feature {feature.id} for station {scode}")
|
||||
|
||||
def get_temperature_color(self, temperature):
|
||||
"""Get color based on temperature value"""
|
||||
try:
|
||||
temp = float(temperature)
|
||||
except (ValueError, TypeError):
|
||||
return '#808080' # Gray for invalid values
|
||||
|
||||
if temp < 10:
|
||||
return '#0000FF' # Blue for very cold
|
||||
elif temp < 15:
|
||||
return '#00BFFF' # Light blue for cold
|
||||
elif temp < 20:
|
||||
return '#00FF00' # Green for cool
|
||||
elif temp < 25:
|
||||
return '#FFFF00' # Yellow for comfortable
|
||||
elif temp < 30:
|
||||
return '#FFA500' # Orange for warm
|
||||
else:
|
||||
return '#FF0000' # Red for hot
|
||||
|
|
@ -9,7 +9,6 @@ class Migration(migrations.Migration):
|
|||
dependencies = [
|
||||
('contenttypes', '0002_remove_content_type_name'),
|
||||
('mapdata', '0138_rangingbeacon_max_observed_num_clients_and_more'),
|
||||
('mapdata', '0141_add_sensor_data_field')
|
||||
]
|
||||
|
||||
operations = [
|
||||
|
|
@ -1,18 +0,0 @@
|
|||
# Generated by Django 5.1.5 on 2025-08-02 06:06
|
||||
|
||||
from django.db import migrations, models
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
|
||||
dependencies = [
|
||||
('mapdata', '0138_rangingbeacon_max_observed_num_clients_and_more'),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.AddField(
|
||||
model_name='dataoverlay',
|
||||
name='last_pull_time',
|
||||
field=models.DateTimeField(blank=True, null=True, verbose_name='last pull time'),
|
||||
),
|
||||
]
|
||||
|
|
@ -1,73 +0,0 @@
|
|||
# Generated by Django 5.1.5 on 2025-08-02 07:18
|
||||
|
||||
from django.db import migrations, models
|
||||
import django_pydantic_field
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
|
||||
dependencies = [
|
||||
('mapdata', '0139_add_last_pull_time'),
|
||||
]
|
||||
|
||||
operations = [
|
||||
# Add data source URL to DataOverlay
|
||||
migrations.AddField(
|
||||
model_name='dataoverlay',
|
||||
name='data_source_url',
|
||||
field=models.URLField(blank=True, null=True, verbose_name='Data Source URL',
|
||||
help_text='URL to scrape sensor data from'),
|
||||
),
|
||||
|
||||
# Add sensor configuration to DataOverlay
|
||||
migrations.AddField(
|
||||
model_name='dataoverlay',
|
||||
name='sensor_config',
|
||||
field=django_pydantic_field.SchemaField(
|
||||
schema=dict, blank=True, null=True,
|
||||
verbose_name='Sensor Configuration',
|
||||
help_text='JSON configuration for sensor data mapping and processing'
|
||||
),
|
||||
),
|
||||
|
||||
# Add generic sensor fields to DataOverlayFeature
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='sensor_id',
|
||||
field=models.CharField(max_length=100, blank=True, null=True, verbose_name='Sensor ID'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='sensor_type',
|
||||
field=models.CharField(max_length=50, blank=True, null=True, verbose_name='Sensor Type',
|
||||
help_text='Type of sensor: temperature, humidity, co2, etc.'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='sensor_value',
|
||||
field=models.FloatField(blank=True, null=True, verbose_name='Sensor Value'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='sensor_unit',
|
||||
field=models.CharField(max_length=20, blank=True, null=True, verbose_name='Sensor Unit',
|
||||
help_text='Unit of measurement: °C, %, ppm, etc.'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='coordinates_x',
|
||||
field=models.FloatField(blank=True, null=True, verbose_name='X Coordinate',
|
||||
help_text='X coordinate in c3nav coordinate system'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='coordinates_y',
|
||||
field=models.FloatField(blank=True, null=True, verbose_name='Y Coordinate',
|
||||
help_text='Y coordinate in c3nav coordinate system'),
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='last_updated',
|
||||
field=models.DateTimeField(blank=True, null=True, verbose_name='Last Updated'),
|
||||
),
|
||||
]
|
||||
|
|
@ -1,23 +0,0 @@
|
|||
# Generated by Django 5.1.5 on 2025-08-02 12:00
|
||||
|
||||
from django.db import migrations
|
||||
import django_pydantic_field
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
|
||||
dependencies = [
|
||||
('mapdata', '0140_add_temperature_fields'),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.AddField(
|
||||
model_name='dataoverlayfeature',
|
||||
name='sensor_data',
|
||||
field=django_pydantic_field.SchemaField(
|
||||
schema=dict, blank=True, null=True,
|
||||
verbose_name='Raw Sensor Data',
|
||||
help_text='Raw data from sensor for debugging and additional info'
|
||||
),
|
||||
),
|
||||
]
|
||||
|
|
@ -44,13 +44,6 @@ class DataOverlay(TitledMixin, AccessRestrictionMixin, models.Model):
|
|||
verbose_name=_('Editor Access Restriction'),
|
||||
on_delete=models.PROTECT)
|
||||
|
||||
# Generic sensor data configuration
|
||||
data_source_url = models.URLField(blank=True, null=True, verbose_name=_('Data Source URL'),
|
||||
help_text=_('URL to scrape sensor data from'))
|
||||
sensor_config: Optional[dict] = SchemaField(schema=dict, blank=True, null=True,
|
||||
verbose_name=_('Sensor Configuration'),
|
||||
help_text=_('JSON configuration for sensor data mapping and processing'))
|
||||
|
||||
class Meta:
|
||||
verbose_name = _('Data Overlay')
|
||||
verbose_name_plural = _('Data Overlays')
|
||||
|
|
@ -79,22 +72,6 @@ class DataOverlayFeature(TitledMixin, LevelGeometryMixin, models.Model):
|
|||
null=True,
|
||||
default=None,
|
||||
verbose_name=_('extra data (JSON object)'))
|
||||
|
||||
# Generic sensor fields
|
||||
sensor_id = models.CharField(max_length=100, blank=True, null=True, verbose_name=_('Sensor ID'))
|
||||
sensor_type = models.CharField(max_length=50, blank=True, null=True, verbose_name=_('Sensor Type'),
|
||||
help_text=_('Type of sensor: temperature, humidity, co2, etc.'))
|
||||
sensor_value = models.FloatField(blank=True, null=True, verbose_name=_('Sensor Value'))
|
||||
sensor_unit = models.CharField(max_length=20, blank=True, null=True, verbose_name=_('Sensor Unit'),
|
||||
help_text=_('Unit of measurement: °C, %, ppm, etc.'))
|
||||
coordinates_x = models.FloatField(blank=True, null=True, verbose_name=_('X Coordinate'),
|
||||
help_text=_('X coordinate in c3nav coordinate system'))
|
||||
coordinates_y = models.FloatField(blank=True, null=True, verbose_name=_('Y Coordinate'),
|
||||
help_text=_('Y coordinate in c3nav coordinate system'))
|
||||
last_updated = models.DateTimeField(blank=True, null=True, verbose_name=_('Last Updated'))
|
||||
sensor_data: Optional[dict] = SchemaField(schema=dict, blank=True, null=True,
|
||||
verbose_name=_('Raw Sensor Data'),
|
||||
help_text=_('Raw data from sensor for debugging and additional info'))
|
||||
|
||||
def to_geojson(self, instance=None) -> dict:
|
||||
result = {
|
||||
|
|
|
|||
|
|
@ -82,76 +82,3 @@ def update_ap_names_bssid_mapping(self, map_name, user_id):
|
|||
with changeset.lock_to_edit() as locked_changeset:
|
||||
locked_changeset.title = 'passive update bssids'
|
||||
locked_changeset.apply(user)
|
||||
|
||||
|
||||
@app.task(bind=True, max_retries=3)
|
||||
def pull_overlay_data(self, overlay_id=None):
|
||||
"""
|
||||
Celery task to pull data overlay features from external URLs.
|
||||
|
||||
Args:
|
||||
overlay_id (int, optional): Specific overlay ID to update.
|
||||
If None, updates all overlays with pull_url.
|
||||
"""
|
||||
logger.info('Starting overlay data pull task...')
|
||||
|
||||
from django.core.management import call_command
|
||||
from io import StringIO
|
||||
|
||||
try:
|
||||
# Capture output from the management command
|
||||
output = StringIO()
|
||||
|
||||
if overlay_id:
|
||||
call_command('pulloverlaydata', overlay=overlay_id, stdout=output)
|
||||
else:
|
||||
call_command('pulloverlaydata', stdout=output)
|
||||
|
||||
result = output.getvalue()
|
||||
logger.info(f'Overlay data pull completed: {result}')
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f'Overlay data pull failed: {e}')
|
||||
if self.request.retries < self.max_retries:
|
||||
logger.info(f'Retrying in 60 seconds... (attempt {self.request.retries + 1}/{self.max_retries})')
|
||||
raise self.retry(countdown=60, exc=e)
|
||||
else:
|
||||
logger.error('Max retries exceeded for overlay data pull')
|
||||
raise
|
||||
|
||||
|
||||
@app.task(bind=True)
|
||||
def schedule_overlay_data_pulls(self):
|
||||
"""
|
||||
Periodic task to schedule individual overlay data pulls based on their intervals.
|
||||
This should be called every minute by a periodic task scheduler.
|
||||
"""
|
||||
from c3nav.mapdata.models import DataOverlay
|
||||
from django.utils import timezone
|
||||
|
||||
logger.info('Checking overlays for scheduled pulls...')
|
||||
|
||||
overlays = DataOverlay.objects.exclude(pull_url__isnull=True).exclude(pull_url='').exclude(pull_interval__isnull=True)
|
||||
|
||||
scheduled_count = 0
|
||||
for overlay in overlays:
|
||||
# Check if it's time to update this overlay
|
||||
should_pull = False
|
||||
|
||||
if overlay.last_pull_time is None:
|
||||
# Never pulled before
|
||||
should_pull = True
|
||||
else:
|
||||
# Check if enough time has passed since last pull
|
||||
next_pull_time = overlay.last_pull_time + overlay.pull_interval
|
||||
should_pull = timezone.now() >= next_pull_time
|
||||
|
||||
if should_pull:
|
||||
# Schedule the pull
|
||||
pull_overlay_data.delay(overlay.pk)
|
||||
scheduled_count += 1
|
||||
logger.info(f'Scheduled pull for overlay: {overlay.title}')
|
||||
|
||||
logger.info(f'Scheduled {scheduled_count} overlay pulls')
|
||||
return scheduled_count
|
||||
|
|
|
|||
|
|
@ -8,7 +8,3 @@ if __name__ == "__main__":
|
|||
from django.core.management import execute_from_command_line
|
||||
|
||||
execute_from_command_line(sys.argv)
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -12,8 +12,6 @@ if [[ $# == 1 ]] && [[ $1 == "stop" ]]; then
|
|||
echo "Stopped the postgres container"
|
||||
elif [[ $# == 1 ]] && [[ $1 == "db" ]]; then
|
||||
echo "Setting up database"
|
||||
sudo docker stop postgres
|
||||
sudo docker container rm -f postgres
|
||||
sudo docker run -d --name postgres -p 5432:5432 -e POSTGRES_PASSWORD=test -e POSTGRES_USER=mindshub postgres
|
||||
until psql "postgres://mindshub:test@localhost:5432" <<< "CREATE DATABASE insignorocketdb;"; do
|
||||
sleep 0.5;
|
||||
|
|
@ -34,8 +32,8 @@ elif [[ $# == 1 ]] && [[ $1 == "run" ]]; then
|
|||
elif [[ $# == 1 ]] && [[ $1 == "run_without_output" ]]; then
|
||||
echo "Processing updates and running server without output"
|
||||
pushd src 2>&1 > /dev/null
|
||||
python manage.py processupdates 2>&1 | (grep -vE '^(INFO|DEBUG)|__debug__' || true)
|
||||
python manage.py runserver 2>&1 | (grep -vE '^(INFO|DEBUG)|__debug__' || true)
|
||||
python manage.py processupdates 2>&1 | (grep -e "^ERROR" -e "^WARNING" -e "^HTTP" || true)
|
||||
python manage.py runserver 2>&1 | (grep -e "^ERROR" -e "^WARNING" -e "^HTTP" || true)
|
||||
popd 2>&1 > /dev/null
|
||||
elif [[ $# > 0 ]] && [[ $1 == "manage" ]]; then
|
||||
pushd src
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue