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Argo Depth & Velocity

Argo Depth & Velocity

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3 installs
| (0) | Free
Argo float profile viewer — depth & velocity chart
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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More Info

Argo Data Monitor

VS Code extension for visualizing Argo float ocean monitoring data — depth & velocity time-series charts.

screenshot


Features

  • 🗂️ TreeView Navigation — browse devices → dates → profiles in a three-level hierarchy
  • 📈 Dual Y-Axis Chart — depth (left) and vertical velocity (right) plotted against time
  • ⚡ High Performance — handles 100k+ data points with uPlot's GPU-grade rendering
  • 🧵 Worker Thread — CSV parsing & downsampling run off the UI thread, zero lag
  • 🔍 Zoom & Pan — interactive time-range exploration with crosshair tooltip
  • 💾 Weighted LRU Cache — 5 profiles / 64 MB in-memory, fast profile switching
  • 📁 Auto-Discovery — automatically detects Argo data directories in your workspace

Quick Start

  1. Open a folder containing Argo device data (or set argoMonitor.dataRoot in settings).
  2. The Argo Devices view appears in the Explorer sidebar.
  3. Expand a device → date → click a profile to open the chart.

Data Directory Structure

{dataRoot}/
  {deviceId}/              # numeric folder, e.g. 6001
    {date}/                 # 6-digit YYMMDD, e.g. 260716
      CSV/
        Argo2_{date}_{profileNum}_level_type2_interval1.csv
      DAT/
      TXT/
      NC/

Settings

Setting Type Default Description
argoMonitor.dataRoot string "" Root path to your Argo data directory

If left empty, the extension auto-detects the data root from your workspace folders.


Chart Controls

Action Gesture
Zoom Scroll wheel / pinch
Pan Click + drag
Crosshair Hover over the chart
Toggle series Click legend items
Reset view Double-click the chart

Technical Details

Component Technology
Chart engine uPlot v1.6
CSV parser PapaParse v5
Encoding iconv-lite (GBK → UTF-8)
Worker Node.js worker_threads
Bundler esbuild
Language TypeScript 5.5

Downsampling Algorithm

Min/Max pixel-bucket downsampling preserves signal extrema:

  1. Binary search the visible time range
  2. Partition into pixel-width buckets
  3. Capture min & max for both depth and velocity per bucket
  4. Merge, sort, deduplicate extreme indices
  5. Preserve boundary points and NaN gap markers
  6. Output ≈ 2–4× chart width data points

Performance

Scenario Target
100k pts cold load → first render < 1 sec
Cache hit → first render < 250 ms
Zoom query → chart update < 100 ms
Extension host blocking < 50 ms

Requirements

  • VS Code ^1.90.0

Known Limitations (MVP)

  • Depth and velocity only — temperature, salinity, and sensor diagnostics planned for future releases
  • No multi-profile overlay yet
  • No automatic file watching (manual refresh via toolbar button)
  • In-memory cache only (disk cache planned)

License

MIT

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