The avatar for @tomfevrier
Tom Février
Public
Edited
Aug 2, 2023
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maples2003 = maples
.filter((d) => d.Year === 2003)
.map((d) => ({
year: d.Year,
watershed: d.Watershed,
stemLength: d.StemLength,
leafMass: d.LeafDryMass,
stemMass: d.StemDryMass,
leafArea: d.CorrectedLeafArea
}))
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maples2003Prepped = scale(maples2003).map((d) => [
d.stemLength,
d.stemMass,
d.leafArea,
d.leafMass
])
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maples2003Clusters = ML.KMeans(maples2003Prepped, 2)
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maples2003WithClusters = maples2003.map((d, i) => ({
...d,
clusterIndex: maples2003Clusters.clusters[i]
}))
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clustersCorrespondingToWatershed = d3.greatest([
maples2003WithClusters.filter((d) => {
return (d.watershed === 'Reference' && d.clusterIndex === 0)
|| (d.watershed === 'W1' && d.clusterIndex === 1)
}),
maples2003WithClusters.filter((d) => {
return (d.watershed === 'Reference' && d.clusterIndex === 1)
|| (d.watershed === 'W1' && d.clusterIndex === 0)
})
], (data) => data.length)
// We need to account for the fact that the order of the clusters is random
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