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spatial-vtk provides spatial validation tools for ground-motion simulations, with data QC, residual and metric calculations, geologic metadata integration, spatial statistics, extensive mapping capabilities, and interactive dashboards for quantifying and visualizing model performance patterns.

Project description

Spatial-VTK

CI Docs PyPI Python License

spatial-vtk provides spatial validation tools for ground-motion simulations, with data QC, residual and metric calculations, geologic metadata integration, spatial statistics, mapping, and dashboard preparation for understanding model performance patterns.

Spatial-VTK workflow

Install

Install from PyPI:

python -m pip install spatial-vtk

Or create the conda environment and install from a source checkout:

conda env create -f svtk_environment.yaml
conda activate spatial-vtk
python -m pip install -e .

The package imports as spatial_vtk and installs the svtk command:

python -c "import spatial_vtk; print(spatial_vtk.__version__)"
svtk --help

Structure

  • spatial_vtk.io: metadata preparation, input inventories, waveform preprocessing, manifests, and waveform format helpers.
  • spatial_vtk.config: repository paths, bounds, and runtime settings.
  • spatial_vtk.qc: quality-control build, review, and summary workflows.
  • spatial_vtk.metrics: ground-motion metric and residual calculations.
  • spatial_vtk.spatial: metric-field preparation, spatial correlation, PCA spatial modes, REDCAP and residual-feature clustering, geology joins, pattern tests, plots, and map helpers.
  • spatial_vtk.visualize: context figures, QC views, and dashboard data.
  • spatial_vtk.cli: command-line entry points.

See the public documentation for installation, package overview, examples, API reference, support, and changelog pages.

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