import orange import orngClustering data = orange.ExampleTable("iris") sample = data.selectref(orange.MakeRandomIndices2(data, 20), 0) root = orngClustering.hierarchicalClustering(sample) reduced = orange.ExampleTable(orange.Domain(sample.domain[:2], False), sample) my_colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255)] cls = orngClustering.hierarchicalClustering_topClusters(root, 3) colors = dict([(cl, col) for cl, col in zip(cls, my_colors)]) print data.native(2) orngClustering.dendrogram_draw("hclust-colored-dendrogram.png", root, data=reduced, labels=[str(d.getclass()) for d in sample], cluster_colors=colors, color_palette=[(0, 255, 0), (0, 0, 0), (255, 0, 0)], gamma=0.5, minv=2.0, maxv=7.0)
import orange import orngClustering data = orange.ExampleTable("iris") sample = data.selectref(orange.MakeRandomIndices2(data, 20), 0) root = orngClustering.hierarchicalClustering(sample) orngClustering.dendrogram_draw("hclust-dendrogram.png", root, data=sample, labels=[str(d.getclass()) for d in sample])
import orange import orngClustering data = orange.ExampleTable("iris") sample = data.selectref(orange.MakeRandomIndices2(data, 20), 0) root = orngClustering.hierarchicalClustering(sample) reduced = orange.ExampleTable(orange.Domain(sample.domain[:2], False), sample) my_colors = [(255,0,0), (0,255,0), (0,0,255)] cls = orngClustering.hierarchicalClustering_topClusters(root, 3) colors = dict([(cl, col) for cl, col in zip(cls, my_colors)]) print data.native(2) orngClustering.dendrogram_draw("hclust-colored-dendrogram.png", root, data = reduced, labels=[str(d.getclass()) for d in sample], cluster_colors=colors, color_palette=[(0, 255, 0), (0, 0, 0), (255, 0, 0)], gamma=0.5, minv=2.0, maxv=7.0)