mgConfig = ({
edgeWeight: "time",
travelType: "walk",
maxEdgeWeight: "1800",
multiGraphReferencedStatisticIds: { wStats: statisticId },
multiGraphAggregationType: "none",
multiGraphAggregationInputParameters: {
wGrav: {},
wStats: {},
wStatsAgg: {}
},
multiGraphPreAggregationPipeline: {
wGrav: {
type: "gravitation_huff",
minSourcesCount: "1",
maxResultValueRatio: 1,
ignoreOutliers: true,
gravitationExponent: "-2.5",
probabilityDecay: 0.001, // as we move away from the source, we become less likely to visit
aggregationInputParameters: sources.reduce((acc, cur) => {
acc[cur.id] = {
gravitationAttractionStrength: 1,
gravitationPositiveInfluence: cur.positive
};
return acc;
}, {})
},
wStatsAgg: {
type: "math",
mathExpression: "{wGrav} * {wStats}",
aggregationInputParameters: { wGrav: {}, wStats: {} }
}
},
multiGraphLayerGeometryDetailPerTile: "5",
multiGraphLayerMinGeometryDetailLevel: "5",
multiGraphLayerMaxGeometryDetailLevel: "25",
multiGraphLayerType: "identity",
multiGraphDomainType: "statistic_geometry",
multiGraphDomainEdgeAggregationType: "max",
multiGraphDomainStatisticGroupId: statisticGroup,
multiGraphSerializationFormat: "geojson",
multiGraphSerializationMaxGeometryCount: 100000,
serviceKey: targomoKey(),
serviceUrl: "https://api.targomo.com/westcentraleurope",
multiGraphAggregationIgnoreOutliers: true,
sources: sources.map(({ x, y, id }) => {
return { x, y, id };
})
})
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
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