fix(docs): Adding explorer documentation

docs/README.md

@@ -81,11 +81,69 @@ You may have to install the required dependencies:
 > To launch without opening your browser, add the `--server` argument to your
 > command.
 
+## Explorers
+
+Another key component of Pan3D is its modular, web-based 3D visualization system
+built using trame. This system powers a suite of focused tools called Explorers,
+designed to be modular, reusable, and easily extended. Each Explorer is built
+around a specific task—think of them as "one-trick ponies" with clean interfaces
+tailored to their purpose. This avoids the clutter and complexity of
+general-purpose tools.
+
+Pan3D currently includes four Explorer tools:
+
+- **Slice Explorer** – Navigate through 3D datasets by extracting 2D slices
+  along any axis. Features interactive slice controls, dual 2D/3D view modes,
+  and the ability to visualize slices within their 3D context using transparency
+  and outlines. Perfect for exploring internal structures of volumetric data.
+
+- **Globe Explorer** – Visualize geographic data on a realistic 3D Earth.
+  Projects latitude/longitude data onto a spherical surface with various texture
+  options (satellite imagery, topography), continental outlines, and terrain
+  elevation effects. Includes specialized camera controls optimized for globe
+  navigation.
+
+- **Contour Explorer** – Generate smooth contour visualizations with
+  color-banded regions between isolevels. Creates both filled contour bands and
+  contour lines, with automatic surface refinement for publication-quality
+  results. Ideal for visualizing scalar fields and identifying data patterns
+  through isosurfaces.
+
+- **Analytics Explorer** – Combines interactive 3D visualization with
+  statistical analysis powered by xCDAT. Provides multiple plot types including
+  zonal averages, time series, and global statistics. Features a side panel with
+  Plotly charts that update based on your 3D data selection, enabling deep data
+  exploration through both visual and quantitative analysis
+
+### Launching the Explorers
+
+Similar to the main XArray Viewer (`xr-viewer`), each explorer can be launched
+from the command line:
+
+```bash
+# Launch Slice Explorer
+xr-slicer
+
+# Launch Globe Explorer
+xr-globe
+
+# Launch Contour Explorer
+xr-contour
+
+# Launch Analytics Explorer
+xr-analytics
+```
+
+Each explorer will automatically open your default browser to `localhost:8080`.
+To launch without opening your browser, add the `--server` argument to any
+command.
+
 ## Tutorials
 
 - [How to use XArray Viewer](tutorials/dataset_viewer.md)
 - [XArray Viewer command line](tutorials/command_line.md)
 - [Catalogs Tutorial](tutorials/catalogs.md)
+- [How to use Pan3D Explorers](tutorials/explorers.md)
 - [How to use Pan3D in a Jupyter notebook](tutorials/jupyter_notebook.md)
 
 ## Examples

docs/tutorials/explorers.md

@@ -0,0 +1,175 @@
+# Pan3D Explorers Tutorial
+
+## Introduction
+
+Pan3D provides four specialized visualization tools called Explorers, each
+designed for specific data exploration tasks. These focused tools offer clean,
+intuitive interfaces tailored to their purpose, avoiding the complexity of
+general-purpose visualization software.
+
+## Getting Started
+
+Install Pan3D with viewer capabilities:
+
+```bash
+pip install "pan3d[viewer]"
+```
+
+Each explorer can be launched from the command line with optional data sources:
+
+```bash
+# Launch with interactive data selection
+xr-slicer
+xr-globe
+xr-contour
+xr-analytics
+
+# Launch with specific data
+xr-slicer --xarray-file ./data.nc
+xr-globe --xarray-url https://example.com/data.zarr
+xr-contour --import-state ./config.json
+```
+
+## Slice Explorer
+
+**Purpose**: Navigate through 3D volumes by extracting 2D slices along any axis.
+
+**Best for**: Atmospheric data, medical imaging, geological surveys, or any
+volumetric dataset requiring cross-sectional analysis.
+
+![Slice Explorer](../images/SliceExplorer.png)
+
+**Key Features:**
+
+- **Axis Slicing**: Extract 2D slices along X, Y, or Z axes
+- **View Modes**: 2D orthogonal or 3D perspective visualization
+- **Volume Context**: Display outline and apply transparency to 3D data
+- **Dynamic Updates**: Real-time slice rendering as position changes
+
+**Example Use Case**: Explore temperature layers in atmospheric data by slicing
+along altitude to understand thermal stratification.
+
+**Launch Command**: `xr-slicer`
+
+## Globe Explorer
+
+**Purpose**: Visualize geographic data on a realistic 3D Earth with accurate
+projection.
+
+**Best for**: Climate data, oceanographic measurements, satellite observations,
+or any dataset with latitude/longitude coordinates.
+
+![Globe Explorer](../images/GlobeExplorer.png)
+
+**Key Features:**
+
+- **Texture Options**: Satellite imagery, topography, political boundaries
+- **Continental Outlines**: Overlay continent boundaries on data
+- **Terrain Elevation**: Apply bump mapping for topographic effects
+- **Sphere Projection**: Map latitude/longitude data to 3D globe
+
+**Example Use Case**: Visualize global temperature anomalies with continental
+context to identify regional climate patterns.
+
+**Launch Command**: `xr-globe`
+
+## Contour Explorer
+
+**Purpose**: Create smooth contour visualizations with color-banded regions
+between isolevels.
+
+**Best for**: Scalar fields, topographic data, gradient analysis, or any dataset
+requiring isoline visualization.
+
+![Contour Explorer](../images/ContourExplorer.png)
+
+**Key Features:**
+
+- **Banded Regions**: Generate filled areas between contour levels
+- **Contour Lines**: Overlay black isolines on banded regions
+- **Level Control**: Set number and range of contour values
+- **Surface Smoothing**: Apply loop subdivision for refined contours
+
+**Example Use Case**: Analyze ocean temperature at specific depths to identify
+thermoclines and current patterns.
+
+**Launch Command**: `xr-contour`
+
+## Analytics Explorer
+
+**Purpose**: Combine 3D visualization with statistical analysis for
+comprehensive data exploration.
+
+**Best for**: Time series analysis, spatial statistics, trend detection, or any
+dataset requiring both visual and quantitative insights.
+
+![Analytics Explorer](../images/AnalyticsExplorer.png)
+
+**Key Features:**
+
+- **Statistical Plots**: Zonal, temporal, and global analysis charts
+- **Temporal Grouping**: Aggregate data by year, month, day, or hour
+- **xCDAT Integration**: Leverage climate analysis algorithms
+- **Data Synchronization**: 3D view and plots update together
+
+**Example Use Case**: Analyze seasonal temperature patterns by combining 3D
+visualization with monthly statistical plots.
+
+**Launch Command**: `xr-analytics`
+
+## Common Features
+
+All explorers share these capabilities:
+
+### Data Management
+
+- Load from files, URLs, or configuration states
+- Support for xarray-compatible formats
+- State export/import for reproducibility
+
+### Visualization Controls
+
+![Common Controls](../images/common.png)
+
+- **Time Navigation**: Slider, play/pause, step controls for temporal data
+- **Color Mapping**: Presets, custom ranges, interactive scalar bar
+- **Scale Controls**: Independent X/Y/Z scaling for different unit scales
+
+### Performance Tips
+
+- Use data stepping/striding for large datasets
+- Crop to regions of interest
+- Start with lower resolution, increase as needed
+
+## Choosing the Right Explorer
+
+| Explorer      | Best For                                                 |
+| ------------- | -------------------------------------------------------- |
+| **Slice**     | Volumetric data, internal structures, cross-sections     |
+| **Globe**     | Geographic data, global patterns, Earth visualization    |
+| **Contour**   | Value ranges, smooth gradients, publication figures      |
+| **Analytics** | Statistical analysis, time series, quantitative insights |
+
+## Integration Example
+
+Use explorers in Jupyter notebooks:
+
+```python
+from pan3d.explorers.slicer import SliceExplorer
+
+# Create and display explorer
+explorer = SliceExplorer()
+await explorer.ui.ready
+
+# Launch the interactive explorer within jypyter notebook
+explorer.ui
+
+# Export configuration
+config = explorer.export_state()
+```
+
+## Additional Resources
+
+- [Configuration API Documentation](../api/configuration.md)
+- [Jupyter Integration Tutorial](jupyter_notebook.md)
+- [Command Line Reference](command_line.md)