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from bokeh.plotting import figure, output_file, show
from bokeh.models import CategoricalColorMapper, ColumnDataSource
from bokeh.palettes import Category10
import umap
from sklearn.datasets import load_iris
iris = load_iris()
embedding = umap.UMAP(
n_neighbors=50, learning_rate=0.5, init="random", min_dist=0.001
).fit_transform(iris.data)
output_file("iris.html")
targets = [str(d) for d in iris.target_names]
source = ColumnDataSource(
dict(
x=[e[0] for e in embedding],
y=[e[1] for e in embedding],
label=[targets[d] for d in iris.target],
)
)
cmap = CategoricalColorMapper(factors=targets, palette=Category10[10])
p = figure(title="Test UMAP on Iris dataset")
p.circle(
x="x",
y="y",
source=source,
color={"field": "label", "transform": cmap},
legend="label",
)
show(p)
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