code: def test_fixed_effect_contrast_nonzero_effect():
      X, y = make_regression(n_features=5, n_samples=20, random_state=0)
      y = y[:, None]
      labels, results = run_glm(y, X, "ols")
      coef = LinearRegression(fit_intercept=False).fit(X, y).coef_
      for i in range(X.shape[1]):
          contrast = np.zeros(X.shape[1])
          contrast[i] = 1.0
          fixed_effect = compute_fixed_effect_contrast(
              [labels],
              [results],
              [contrast],
          )
  
          assert_almost_equal(
              fixed_effect.effect_size(), coef.ravel()[i]
          )
  
          fixed_effect = compute_fixed_effect_contrast(
              [labels] * 3, [results] * 3, [contrast] * 3
          )
  
          assert_almost_equal(
              fixed_effect.effect_size(), coef.ravel()[i]
          )
  
imports: import numpy
  import pytest
  import scipy.stats
  from numpy.testing import assert_almost_equal
  from sklearn.datasets import make_regression
  from sklearn.linear_model import LinearRegression
  from nilearn.glm.contrasts import Contrast, _compute_fixed_effects_params, compute_contrast, compute_fixed_effect_contrast, expression_to_contrast_vector
  from nilearn.glm.first_level import run_glm
label_desc: Use image node_id 9 for calling a global function with example usage: test_fixed_effect_contrast_nonzero_effect() without return types