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@deck.gl/aggregation-layers
Advanced tools
deck.gl layers that aggregate the input data into alternative representations
@deck.gl/aggregation-layers is a collection of Deck.gl layers designed for data aggregation and visualization. These layers are optimized for rendering large datasets and provide various aggregation techniques such as grid-based, hexagon-based, and contour-based visualizations.
GridLayer
The GridLayer aggregates data into a grid-based heatmap. Each cell in the grid represents the aggregated data points within that cell. This is useful for visualizing density and distribution of data points over a geographic area.
const {Deck} = require('@deck.gl/core');
const {GridLayer} = require('@deck.gl/aggregation-layers');
const deck = new Deck({
initialViewState: {
longitude: -122.45,
latitude: 37.8,
zoom: 12
},
controller: true,
layers: [
new GridLayer({
id: 'grid-layer',
data: 'https://raw.githubusercontent.com/visgl/deck.gl-data/master/website/sf-bike-parking.json',
pickable: true,
extruded: true,
cellSize: 200,
elevationScale: 4,
getPosition: d => d.COORDINATES
})
]
});
HexagonLayer
The HexagonLayer aggregates data into hexagonal bins, providing a hexagon-based heatmap. This is useful for visualizing spatial patterns and density in a more visually appealing way compared to grid-based aggregation.
const {Deck} = require('@deck.gl/core');
const {HexagonLayer} = require('@deck.gl/aggregation-layers');
const deck = new Deck({
initialViewState: {
longitude: -122.45,
latitude: 37.8,
zoom: 12
},
controller: true,
layers: [
new HexagonLayer({
id: 'hexagon-layer',
data: 'https://raw.githubusercontent.com/visgl/deck.gl-data/master/website/sf-bike-parking.json',
pickable: true,
extruded: true,
radius: 200,
elevationScale: 4,
getPosition: d => d.COORDINATES
})
]
});
ContourLayer
The ContourLayer generates contour lines based on the density of data points. This is useful for visualizing areas of high and low concentration, similar to topographic maps.
const {Deck} = require('@deck.gl/core');
const {ContourLayer} = require('@deck.gl/aggregation-layers');
const deck = new Deck({
initialViewState: {
longitude: -122.45,
latitude: 37.8,
zoom: 12
},
controller: true,
layers: [
new ContourLayer({
id: 'contour-layer',
data: 'https://raw.githubusercontent.com/visgl/deck.gl-data/master/website/sf-bike-parking.json',
pickable: true,
contours: [{threshold: 1, color: [255, 0, 0], strokeWidth: 2}],
cellSize: 200,
getPosition: d => d.COORDINATES
})
]
});
Leaflet.heat is a simple heatmap plugin for Leaflet. It provides basic heatmap functionality and is easy to use for small to medium-sized datasets. Compared to @deck.gl/aggregation-layers, it is less feature-rich and not optimized for very large datasets.
Heatmap.js is a JavaScript library for creating heatmaps. It is highly customizable and can handle large datasets efficiently. However, it does not provide the same level of integration with mapping libraries as @deck.gl/aggregation-layers.
Kepler.gl is a powerful open-source geospatial analysis tool for large-scale data sets. It offers a wide range of visualization options, including heatmaps, but is more of a standalone application compared to the modular approach of @deck.gl/aggregation-layers.
FAQs
deck.gl layers that aggregate the input data into alternative representations
The npm package @deck.gl/aggregation-layers receives a total of 0 weekly downloads. As such, @deck.gl/aggregation-layers popularity was classified as not popular.
We found that @deck.gl/aggregation-layers demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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