Gist eafff0441de1209802edaacd56203985

100%

Gist eafff0441de1209802edaacd56203985

✓ Published0🌍 Public

Last edited Apr 14, 2023

Created on Apr 14, 2023

This example visualizes the hierarchical timing profile of a QGIS application, rendering each profiler entry as a node with its name and measured duration. It extracts the profiler tree via the QGIS `QgsApplication.profiler()` API, iterating rows and columns to build nested parent-child relationships. The code uses Python’s `json` module to serialize the resulting structure into a JSON file, preserving two levels of detail with child arrays. The visualization itself is not rendered here; only the data extraction and export to `/tmp/tree.json` are demonstrated.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 56db21b335e25668ff86c2e8359bf3d1

This example visualizes tree inventory data from a CSV file, mapping each tree’s location as a point based on longitude and latitude coordinates. The data includes attributes such as species, planting date, height, and diameter. The implementation uses a VRT file to define the CSV’s geometry, with the QGIS XML configuration specifying the point layer’s symbology and coordinate system. The visualization is rendered through QGIS, leveraging the OGR provider to read the spatial data and display it as a map layer with a single symbol renderer.

TThomasG77

71% match

Loading thumbnail…

IGN API elevation line

This example shows elevation profiles extracted from a user-selected line feature in QGIS. It calls the IGN REST elevationLine API with sampled lon/lat coordinates, then builds a GeoJSON FeatureCollection of 3D points with elevation (z) and accuracy values. The script uses `urllib.request` to fetch JSON data and `json.dump` to write a temporary GeoJSON file, which QGIS then loads as a vector layer. Users subsequently convert to a projected CRS and apply the Profile tool plugin to render the elevation graph.

TThomasG77

62% match

Loading thumbnail…

Gist 80f99a186a44e6fa1930f2a08618d498

This visualization displays a QGIS project containing world map layers—countries, states, provinces, and disputed borders—from the bundled `world_map.gpkg` GeoPackage, alongside JSON-derived point layers for contributors, hackfests, and user groups. Using the QGIS Python API, the script loads each vector layer via `QgsVectorLayer` with OGR drivers, adds them to the project through `QgsProject.instance().addMapLayers`, and enables a retro canvas style by setting `iface.mapCanvas().setProperty("retro", True)` before refreshing. The example demonstrates procedural map composition from built-in geodata files.

TThomasG77

61% match

Loading thumbnail…

Gist e3a7564e0daaea9e8d19

This example shows a hierarchical tree layout rendered with D3.js, using the cluster layout to display the Flare visualization toolkit’s class hierarchy. The SVG visualization is organized as an indented dendrogram, with circular nodes connected by elbow-shaped paths. Parent nodes are labeled to the left of their circles, while leaf nodes are labeled to the right. The layout encodes the data’s parent-child relationships through vertical positioning, with the tree flowing horizontally across the 960×2200 pixel canvas.

CCBasis

60% match

Loading thumbnail…

Gist 8bb4970e2700b40a3dce1d785654d907

This visualization uses a force-directed graph to map the relationships between identifiers extracted from a Power Query M codebase. The data originates from a gist by Hugoberry, showing dependencies among functions, modules, and error-handling patterns. The rendering relies on D3.js’s `forceSimulation` with custom link and node positioning, while each node’s label is drawn using SVG text. The code specifically highlights groupings like `TableAction.*`, `ValueAction.*`, and `Pattern.*`, revealing hierarchical clusters of related API calls. The graph’s layout is animated via D3’s tick handler, and the visible node sizes suggest a metric like degree centrality, though the exact encoding is not explicit in the snippet.

HHugoberry

60% match

Loading thumbnail…

Gist 3479d944f561ed81b080d524d9c0a80b

This visualization maps hiking trails fetched from the Hiking Project API, with each trail positioned according to dynamic geographic coordinates passed to the API. The code builds a network-style graph where nodes represent trails, linked by proximity or shared attributes, using D3.js’s force simulation for layout. The rendering relies on `d3.forceSimulation` to compute node positions, while trail data is loaded asynchronously via HTTP requests and parsed from JSON. The display emphasizes spatial relationships between trails, with the simulation running in real time to reveal clusters and connections based on the fetched coordinates.

WWill Carter

60% match

Loading thumbnail…

Gist 2784668

This example visualizes the structure of the YARD Ruby documentation library as a navigable tree, starting from its root module and expanding through child namespaces, methods, and constants. It renders this hierarchy using JSON-LD formatted data, which is generated from YARD’s Registry API to capture relationships like children and namespaces. The visualization relies on the `json` and `cgi` libraries to process and encode the data, while the tree layout itself is implemented with D3’s `d3.forceSimulation` and related tree-layout functions.

RRichMorin

60% match

Loading thumbnail…

Gist b2644a6ec6b1fd1a95ef87d5a93ec93c

This example visualizes a GPS track as a three-dimensional path using a MultiLineString GeoJSON feature. The data, sourced from a gist by FergusDevelopmentLLC, is rendered with altitude encoded as the third coordinate in each vertex. The visualization highlights the elevation changes along the path through a continuous line, with the points tracing a looping route. The use of 3D coordinates allows the viewer to perceive the terrain's vertical profile alongside its horizontal extent, making it useful for analyzing elevation gain, slope, and path shape in a compact, geographic context.

WWill Carter

60% match