code: def test_can_predict_from_data():
      Invt_model = InvertedEncoding1D()
      Invt_model.fit(X, y)
      m_reconstruct = []
      for j in np.arange(dim):
          preds = Invt_model.predict(X2[n_ * j : n_ * (j + 1), :])
          tmp = circmean(np.deg2rad(preds))
          m_reconstruct.append(np.rad2deg(tmp))
      logger.info("Reconstructed angles: " + str(m_reconstruct))
  
imports: import pytest
  import numpy
  import logging
  from brainiak.reconstruct.iem import InvertedEncoding1D, InvertedEncoding2D
  from brainiak.utils.fmrisim import generate_1d_gaussian_rfs, generate_1d_rf_responses
  from scipy.stats import circmean
label_desc: Use image node_id 39 for calling a global function with example usage: test_can_predict_from_data() without return types