code: def test_explicit_optimize_calls(self):
      embedding1 = TSNE(random_state=42).fit(self.x)
  
      A = affinity.PerplexityBasedNN(self.x)
      I = initialization.pca(self.x, random_state=42)
      embedding2 = TSNEEmbedding(I, A)
      embedding2 = embedding2.optimize(n_iter=25, exaggeration=12)
      embedding2 = embedding2.optimize(n_iter=50)
  
      np.testing.assert_array_equal(
          embedding1,
          embedding2,
          "Calling optimize twice with default parameters produced a different "
          "result compared to the default fit() call",
      )
  
imports: import unittest
  from functools import partial
  import numpy
  from scipy.spatial.distance import pdist, squareform, cdist
  from sklearn import datasets
  from sklearn.metrics import accuracy_score
  from sklearn.neighbors import KNeighborsClassifier, NearestNeighbors
  import openTSNE
  from openTSNE import affinity, initialization, nearest_neighbors, TSNEEmbedding
label_desc: Use image node_id 1 for calling the TestUsageExplicitOptimizeCalls obj's underlying member method code with example usage: obj.test_explicit_optimize_calls() without return types