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Python Reimplementation

WaveCalKit replaces the historical desktop plotting workflow with Python-native commands that can run locally, in CI, and in reproducible analyst pipelines.

Task Map

Historical task Python implementation Command or module
Read exported satellite SWH text files Historical four-column TXT adapter plus normalized CSV/NetCDF readers `wavecal ingest-altimeter --source legacy-txt
Read buoy spreadsheets Normalized CSV plus optional Excel adapter `wavecal ingest-buoy --source csv
Match satellite and buoy observations Haversine distance windows, exact/tolerance time matching, and aggregation wavecal collocate
Compute correction equations NumPy metrics and linear fit wavecal fit
Produce scatter figures Matplotlib static figures wavecal render-figures
Produce workflow animation Matplotlib FuncAnimation with GIF/MP4 writers wavecal animate
Sweep a plotting variable Optional mpl-animator static-script sweep mpl-animator scripts/render_workflow_animation.py --var frame --range "0,2*pi" --frames 60 --out outputs/scilly/mpl_animator.gif, then python render_workflow_animation_animated.py

Visualization Modes

  • 2D scatter correction plot: buoy SWH versus altimeter SWH with y=x and fitted correction lines.
  • Polar plot: buoy wave direction when direction_deg exists.
  • Subplot dashboard: wavecal animate renders map, correction fit, polar direction, and 3D distance-time-SWH views.
  • GIF/MP4 output: default wavecal animate uses Matplotlib writers; optional mpl-animator is available for variable sweeps and writes a generated script that you run to create the media.
  • Optional mpl-animator demo: keeps the sweep dashboard 2D-only so the generated script preserves all subplots consistently.

Dependency Policy

Core WaveCalKit stays lightweight: matplotlib, numpy, and PyYAML.

Optional visualization extras install animation conveniences:

pip install ".[visual]"

Manim is not a v1 dependency. It is a strong open-source tool for explanatory math videos, but it brings a heavier rendering stack than this validation package needs. Use it later for marketing or education videos, not for the core analyst workflow.

Release Boundary

Raw .m, Office, PDF, spreadsheet, KML/KMZ, and NetCDF archive files stay local and ignored. The public repo ships reproducible Python code, sanitized fixtures, generated visual assets, and instructions for users to normalize their own licensed data.