Swellcast Sydney API response

buoys scheduler error

This example visualizes the timing and error events from a Heroku scheduler run for the “buoys” app, which fetches ocean wave data from New South Wales government GIF graphs. A timeline chart shows the sequence of log lines, highlighting when specific location fetches (Byron Bay, Sydney, Eden) succeed or fail. The code uses D3’s `d3.forceSimulation` to position nodes representing each log entry, with colors distinguishing app messages, scheduler state changes, and the socket hang-up error. Data comes from the gist’s plain-text log file, parsed and rendered with SVG paths and D3 scales.

64% match

Gist 09dc3605fda7e3165781

This visualization maps wildfire incidents across New South Wales using a GeoJSON dataset, plotting each fire as a point on a geographic canvas. It encodes each incident’s location, alert level, and status through colored markers, with hover interactions likely revealing details like size and council area. The code uses D3’s `d3.geoPath` to project boundaries and a custom force-directed layout to prevent overlapping labels. It also leverages Canvas pixel analysis via `getImageData` to detect and avoid collisions, ensuring readable annotations. Data comes from the provided GeoJSON file, rendered dynamically with D3’s event handling.

62% match

Gist 9991179

This visualization uses the D3.js library to render a live map of current fire incidents across New South Wales, Australia, plotting each incident as a point on a geographic projection. It shows the spatial distribution of fires, with each point colored or styled to reflect its alert level or status. The code relies on `d3.forceSimulation` for layout and `d3.geoPath` to draw the map boundaries, while the underlying incident data comes from the provided GeoJSON file, which includes properties like fire type, council area, and responsible agency. The map updates dynamically to reflect the current incident data.

62% match

Gist 0c13c9decf2cc5a3bf2c

This visualization maps bushfire locations across New South Wales as point features from a GeoJSON feed, using the D3.js library to project and draw the data. It renders the fire incidents as small circles positioned by their coordinates through a `d3.geoPath`-compatible projection, with each point colored or styled according to its alert level and status. The underlying dataset comes from the NSW Rural Fire Service’s public feed, and the code likely uses D3’s data join and enter/update/exit pattern to bind the GeoJSON features, though the visualization focuses on static spatial distribution rather than animation or interaction.

Gist ff1df942a170f1ec9f31

This visualization maps current fire incidents across New South Wales, plotting point locations from a GeoJSON feed onto a geographic backdrop. It shows the spatial distribution of active hazards, differentiating between hazard reductions, motor vehicle accidents, and other fire types. The visualization uses D3.js for data binding and rendering, with a map projection and geographic path generator to draw the state’s coastline and boundaries. Incident points are positioned using a projection function, with a size encoding likely reflecting the reported fire area, while a legend clarifies the categories represented.

Gist 3b609858c3d3d4fa3e9a

This visualization maps wildfire incidents across New South Wales, Australia, using a GeoJSON file of point coordinates. It shows the spatial distribution of various fire types—such as forest, grass, and scrub fires, plus vehicle accidents—by plotting them on a geographic canvas. The code likely uses D3.js’s `d3.geoPath` for map projection and rendering, with points positioned via `d3.forceSimulation` or direct coordinate mapping. Styling encodes fire type through color or symbols, while the underlying data source is the NSW Rural Fire Service feed, as indicated by the linked incident titles.

D3 Example

As more data loads, this D3 example builds a multi-day temperature line chart for San Francisco, one CSV file at a time. Each file holds a day of hourly readings, and the visualization re-renders as each new day is fetched, revealing the dataset’s daily cycles. The SVG line chart, based on a standalone example, shows the temperature curve extending across time with each incremental load, demonstrating how to stream and update data progressively in the browser.

CCurran Kelleher

Gist 6735f16486b5a6d38f99

This visualization maps current wildfire incidents across New South Wales, using GeoJSON data from the RFS. It renders each fire as a point on a geographic backdrop, with symbols encoding alert level and status. The map is drawn with D3’s `d3.geoPath` for vector tiles, while the interactive tooltip relies on D3’s event handling and DOM manipulation. Point positions come directly from the GeoJSON coordinates, and size or color encodes reported fire size in hectares, with a legend clarifying the categories. The visualization updates dynamically from the live incident feed, providing a real-time snapshot of active hazard reductions and forest fires.