code: def test_linear_mixed_models_flow():
      with TemporaryDirectory() as dirpath:
          out_dir = os.path.join(dirpath, "output")
          os.mkdir(out_dir)
  
          d = {
              "disk": [1, 2, 3, 4, 5, 1, 2, 3, 4, 5] * 10,
              "fa": [
                  0.21,
                  0.234,
                  0.44,
                  0.44,
                  0.5,
                  0.23,
                  0.55,
                  0.34,
                  0.76,
                  0.34,
              ]
              * 10,
              "subject": [
                  "10001",
                  "10001",
                  "10001",
                  "10001",
                  "10001",
                  "20002",
                  "20002",
                  "20002",
                  "20002",
                  "20002",
              ]
              * 10,
              "group": [0, 0, 0, 0, 0, 1, 1, 1, 1, 1] * 10,
          }
  
          df = pd.DataFrame(data=d)
          store = pd.HDFStore(os.path.join(out_dir, "temp_fa.h5"))
          store.append("fa", df, data_columns=True)
          store.close()
  
          lmm_flow = LinearMixedModelsFlow()
  
          out_dir2 = os.path.join(dirpath, "output2")
          os.mkdir(out_dir2)
  
          input_path = os.path.join(out_dir, "*")
  
          lmm_flow.run(input_path, no_disks=5, out_dir=out_dir2)
  
          assert_true(
              os.path.exists(
                  os.path.join(out_dir2, "temp_fa_pvalues.npy")
              )
          )
          assert_true(
              os.path.exists(os.path.join(out_dir2, "temp_fa.png"))
          )
  
          # test error
          d2 = {
              "disk": [1, 2, 3, 4, 5, 1, 2, 3, 4, 5] * 1,
              "fa": [
                  0.21,
                  0.234,
                  0.44,
                  0.44,
                  0.5,
                  0.23,
                  0.55,
                  0.34,
                  0.76,
                  0.34,
              ]
              * 1,
              "subject": [
                  "10001",
                  "10001",
                  "10001",
                  "10001",
                  "10001",
                  "20002",
                  "20002",
                  "20002",
                  "20002",
                  "20002",
              ]
              * 1,
              "group": [0, 0, 0, 0, 0, 1, 1, 1, 1, 1] * 1,
          }
  
          df = pd.DataFrame(data=d2)
  
          out_dir3 = os.path.join(dirpath, "output3")
          os.mkdir(out_dir3)
  
          store = pd.HDFStore(os.path.join(out_dir3, "temp_fa.h5"))
          store.append("fa", df, data_columns=True)
          store.close()
  
          out_dir4 = os.path.join(dirpath, "output4")
          os.mkdir(out_dir4)
  
          input_path = os.path.join(out_dir3, "f*")
          # OS error raised if path is wrong or file does not exist
          npt.assert_raises(
              OSError,
              lmm_flow.run,
              input_path,
              no_disks=5,
              out_dir=out_dir4,
          )
  
          input_path = os.path.join(out_dir3, "*")
          # value error raised if length of data frame is less than 100
          npt.assert_raises(
              ValueError,
              lmm_flow.run,
              input_path,
              no_disks=5,
              out_dir=out_dir4,
          )
  
imports: import os
  from os.path import join
  from tempfile import TemporaryDirectory
  import numpy
  import numpy.testing
  import pytest
  from dipy.data import get_fnames
  from dipy.io.image import save_nifti, load_nifti
  from dipy.io.stateful_tractogram import Space, StatefulTractogram
  from dipy.io.streamline import load_tractogram, save_tractogram
  from dipy.testing import assert_true
  from dipy.testing.decorators import set_random_number_generator
  from dipy.tracking.streamline import Streamlines
  from dipy.utils.optpkg import optional_package
  from dipy.workflows.stats import SNRinCCFlow
  from dipy.workflows.stats import BundleAnalysisTractometryFlow
  from dipy.workflows.stats import LinearMixedModelsFlow
  from dipy.workflows.stats import BundleShapeAnalysis
  from dipy.workflows.stats import buan_bundle_profiles
label_desc: Use image node_id 4 for calling a global function with example usage: test_linear_mixed_models_flow() without return types