Add core architecture patterns and GIS/weather components from AIOS-Public

Docker/TSYS-AIOS-GIS-Tools-Weather-Analysis/README.md

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+# TSYS-AIOS-GIS-Tools-Weather-Analysis Container
+
+This container is part of the TSYS-AIOS-GIS project and provides advanced weather data analysis capabilities with Jupyter notebooks and specialized meteorological tools.
+
+## Overview
+
+The TSYS-AIOS-GIS-Tools-Weather-Analysis container extends the base weather container with advanced analysis tools, Jupyter notebooks for interactive analysis, and specialized meteorological libraries. This container is designed for in-depth weather data analysis and balloon path prediction work.
+
+## Tools Included
+
+### Extends from Base Container
+- All tools from TSYS-AIOS-GIS-Tools-Weather-Base container
+- Weather data processing libraries, APIs, bulk download tools
+
+### Advanced Analysis Tools
+- **Jupyter Notebook**: Interactive environment for weather analysis
+- **Node.js/npm**: JavaScript runtime and package manager
+- **IPyKernel**: IPython kernel for Jupyter
+- **GNU Octave**: Numerical computations (similar to MATLAB)
+
+### Visualization & Forecasting Libraries
+- **Cartopy**: Geospatial processing and visualization
+- **Geoviews**: Geospatial data visualization
+- **Folium**: Interactive maps with weather data overlays
+- **Plotly**: Interactive weather visualizations
+- **Forecast R package**: Time series forecasting
+
+### Additional R packages
+- **Lubridate**: Time series manipulation
+- **Ggplot2/Tidyr/Dplyr**: Data analysis and visualization
+- **RColorBrewer**: Color palettes for weather maps
+
+## Usage
+
+### Building the Weather Analysis Container
+```bash
+# From this directory
+cd /home/localuser/AIWorkspace/TSYS-AIOS-GIS/Docker/TSYS-AIOS-GIS-Tools-Weather-Analysis
+
+# Use the wrapper script to automatically detect and set user IDs
+./docker-compose-wrapper.sh build
+
+# Or run commands in the analysis container with automatic user mapping
+./docker-compose-wrapper.sh run tsys-weather-analysis [command]
+
+# Example: Start Jupyter notebook server
+./docker-compose-wrapper.sh run tsys-weather-analysis jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root --notebook-dir=/workspace --no-browser
+
+# Example: Start Octave for numerical computations
+./docker-compose-wrapper.sh run tsys-weather-analysis octave
+
+# Example: Start an interactive bash session
+./docker-compose-wrapper.sh run tsys-weather-analysis bash
+```
+
+### Using with docker-compose directly
+```bash
+# Set environment variables and run docker-compose directly
+LOCAL_USER_ID=$(id -u) LOCAL_GROUP_ID=$(id -g) docker-compose up --build
+
+# Or export variables first
+export LOCAL_USER_ID=$(id -u)
+export LOCAL_GROUP_ID=$(id -g) 
+docker-compose up
+```
+
+### Using the wrapper script
+```bash
+# Build and start the analysis container with automatic user mapping
+./docker-compose-wrapper.sh up --build
+
+# Start without rebuilding (Jupyter will be available on port 8889)
+./docker-compose-wrapper.sh up
+
+# View container status
+./docker-compose-wrapper.sh ps
+
+# Stop containers
+./docker-compose-wrapper.sh down
+```
+
+## Jupyter Notebook Access
+
+When running the container with `docker-compose up`, Jupyter notebook will be available at:
+- http://localhost:8889
+
+The notebook server is preconfigured to:
+- Use the workspace directory as the notebook directory
+- Allow access without authentication (in container only)
+- Accept connections from any IP address
+
+## User ID Mapping (For File Permissions)
+
+The container automatically detects and uses the host user's UID and GID to ensure proper file permissions. This means:
+
+- Files created inside the container will have the correct ownership on the host
+- No more root-owned files after container operations
+- Works across different environments (development, production servers)
+
+The container detects the user ID from the mounted workspace volume. If needed, you can override the default values by setting environment variables:
+
+```bash
+# Set specific user ID and group ID before running docker-compose
+export LOCAL_USER_ID=1000
+export LOCAL_GROUP_ID=1000
+docker-compose up
+```
+
+Or run with inline environment variables:
+```bash
+LOCAL_USER_ID=1000 LOCAL_GROUP_ID=1000 docker-compose up
+```
+
+The container runs as a non-root user named `TSYS-Tools` with the detected host user's UID/GID.
+
+## Weather Analysis Workflows
+
+This container is optimized for:
+- Interactive weather data analysis using Jupyter notebooks
+- Balloon path prediction using weather data
+- Advanced meteorological calculations
+- Time series forecasting
+- Weather data visualization
+- Climate analysis workflows