code: def get_dataset(dataset, n_samples):
      if dataset == "Noisy Circles":
          return datasets.make_circles(
              n_samples=n_samples, factor=0.5, noise=0.05
          )
  
      elif dataset == "Noisy Moons":
          return datasets.make_moons(n_samples=n_samples, noise=0.05)
  
      elif dataset == "Blobs":
          return datasets.make_blobs(
              n_samples=n_samples, random_state=8
          )
  
      elif dataset == "No Structure":
          return np.random.rand(n_samples, 2), None
  
file_path: bokeh/examples/server/app/clustering/main.py
imports: import numpy
  from sklearn import cluster, datasets
  from sklearn.neighbors import kneighbors_graph
  from sklearn.preprocessing import StandardScaler
  from bokeh.io import curdoc
  from bokeh.layouts import column, row
  from bokeh.models import ColumnDataSource, Select, Slider
  from bokeh.palettes import Spectral6
  from bokeh.plotting import figure
label_desc: Use image node_id 2 for calling a global function with example usage: get_dataset(dataset, n_samples) and returns: datasets, datasets, datasets, np,  None