code: def plot(Y, classes, name):
      digits = set(classes)
      fig = plt.figure()
      colormap = plt.cm.spectral
      plt.gca().set_prop_cycle(
          cycler(
              "color", [colormap(i) for i in np.linspace(0, 0.9, 10)]
          )
      )
      ax = fig.add_subplot(111)
      labels = []
      for d in digits:
          idx = classes == d
          if Y.shape[1] == 1:
              ax.plot(Y[idx], np.random.randn(Y[idx].shape[0]), "o")
          else:
              ax.plot(Y[idx, 0], Y[idx, 1], "o")
  
          labels.append(d)
      ax.legend(labels, numpoints=1, fancybox=True)
      fig.savefig(name)
      if Y.shape[1] > 2:
          print("Warning! Plot shows only first two components!")
  
file_path: Multicore-TSNE/MulticoreTSNE/examples/test.py
imports: import matplotlib
  import numpy
  from cycler import cycler
  from sklearn.datasets import fetch_openml
  from MulticoreTSNE import MulticoreTSNE
  import argparse
  import matplotlib.pyplot
label_desc: Use image node_id 2 for calling a global function with example usage: plot(Y, classes, name) without return types