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--- |
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title: TensorView - NetCDF/HDF/GRIB Viewer |
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emoji: 🌍 |
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colorFrom: blue |
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colorTo: green |
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sdk: gradio |
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sdk_version: 4.44.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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--- |
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# 🌍 TensorView - Interactive Geospatial Data Viewer |
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A powerful browser-based viewer for **NetCDF**, **HDF**, **GRIB**, and **Zarr** datasets with advanced visualization capabilities. |
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## 🚀 Features |
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- **📊 Multi-dimensional data exploration** - Handle complex scientific datasets with automatic slicing |
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- **🗺️ Geographic mapping** - Built-in map projections with coastlines and gridlines |
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- **🎨 Smart color scaling** - Automatic percentile-based color limits for optimal visualization |
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- **🔄 Multiple data formats** - NetCDF, HDF5, GRIB, Zarr support |
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- **🎛️ Interactive controls** - Dynamic sliders for dimension exploration |
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- **📤 Dual input modes** - File upload or direct file path input |
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- **🌐 Remote data support** - Load from URLs, OPeNDAP, THREDDS servers |
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## 🎯 Quick Start |
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1. **Upload a file** or enter a file path |
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2. **Select a variable** from the dropdown |
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3. **Choose plot type**: 2D Image or Map (for geographic data) |
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4. **Adjust dimension sliders** to explore different time steps, pressure levels, etc. |
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5. **Create plot** and explore your data! |
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## 📊 Supported Data Sources |
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- **NetCDF files** (.nc, .netcdf) - Climate and weather data |
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- **HDF5 files** (.h5, .hdf) - Scientific datasets |
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- **GRIB files** (.grib, .grb) - Meteorological data |
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- **Zarr stores** - Cloud-optimized arrays |
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- **Remote URLs** - HTTP/HTTPS links to data files |
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- **OPeNDAP/THREDDS** - Direct server access |
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## 🌟 Example Use Cases |
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- **Climate Data**: ERA5 reanalysis, CMIP model outputs |
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- **Weather Data**: GFS/ECMWF forecasts, radar data |
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- **Air Quality**: CAMS atmospheric composition data |
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- **Oceanography**: Sea surface temperature, currents |
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- **Satellite Data**: Remote sensing products |
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## 🔧 Technical Details |
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Built with: |
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- **xarray + Dask** - Efficient handling of large datasets |
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- **matplotlib + Cartopy** - High-quality plotting and maps |
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- **Gradio** - Interactive web interface |
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- **Multi-engine support** - h5netcdf, netcdf4, cfgrib, zarr |
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### Smart Features |
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- **Automatic color scaling** using 2nd-98th percentiles |
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- **Dimension detection** with dynamic slider generation |
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- **Geographic coordinate recognition** for map plotting |
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- **Memory-efficient** lazy loading with Dask |
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## 💡 Tips |
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- For **5D data** (like CAMS forecasts): Use sliders to select time, pressure level, etc. |
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- For **geographic data**: Choose "Map" plot type for proper projections |
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- **Large files**: The app handles big datasets efficiently with lazy loading |
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- **Color issues**: The app automatically optimizes color scaling to avoid uniform plots |
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## 🏗️ Architecture |
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``` |
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tensorview/ |
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├── io.py # Data loading (NetCDF, HDF, GRIB, Zarr) |
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├── plot.py # Visualization (1D, 2D, maps) |
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├── grid.py # Data operations and alignment |
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├── colors.py # Colormap handling |
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├── utils.py # Coordinate inference |
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└── ... |
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``` |
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## 📝 Example Datasets |
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The app works great with: |
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- NASA Goddard Earth Sciences Data |
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- ECMWF ERA5 reanalysis |
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- NOAA climate datasets |
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- Copernicus atmosphere monitoring (CAMS) |
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- CMIP climate model outputs |
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--- |
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**🔗 Links**: [GitHub Repository](https://github.com/user/tensorview) | [Documentation](https://docs.tensorview.io) |
