code: def predict(self, X):
      return np.random.random(len(X))
  
file_path: fairlearn/test/install/test_no_matplotlib.py
imports: import numpy
  import pytest
  from sklearn.base import BaseEstimator, ClassifierMixin
  from fairlearn.postprocessing import ThresholdOptimizer, plot_threshold_optimizer
  from fairlearn.postprocessing._constants import _MATPLOTLIB_IMPORT_ERROR_MESSAGE
  from fairlearn.metrics import plot_model_comparison
  from fairlearn.postprocessing._threshold_optimizer import SIMPLE_CONSTRAINTS
label_desc: Use image node_id 2 for calling the FakePredictor obj's underlying member method code with example usage: obj.predict(X) and returns: np