code: def test_fit_custom_channel_activations():
      i2 = InvertedEncoding2D(
          stim_xlim=xlim,
          stim_ylim=ylim,
          stimulus_resolution=res,
          stim_radius=12,
      )
      i2.define_basis_functions_sqgrid(nchannels=[12, 6])
      # Define C by expanding y & adding noise to avoid singular W matrix error
      C0 = np.repeat(
          np.expand_dims(yd[:, 0], 1), 12 * 3, axis=1
      ) + np.random.rand(nobs, 12 * 3)
      C1 = np.repeat(
          np.expand_dims(yd[:, 1], 1), 12 * 3, axis=1
      ) + np.random.rand(nobs, 12 * 3)
      i2.fit(Xd, yd, np.hstack((C0, C1)))
      assert np.all(i2.W_)
  
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 16 for calling a global function with example usage: test_fit_custom_channel_activations() without return types