code: def create_sim_data(dataroot, sim_datalist, sim_dim, **kwargs):
      """
      Create simulated data using create_test_image_3d.
  
      Args:
          dataroot: data directory path that hosts the "nii.gz" image files.
          sim_datalist: a list of data to create.
          sim_dim: the image sizes, e.g. a tuple of (64, 64, 64).
      """
      if not os.path.isdir(dataroot):
          os.makedirs(dataroot)
  
      # Generate a fake dataset
      for d in sim_datalist["testing"] + sim_datalist["training"]:
          im, seg = create_test_image_3d(
              sim_dim[0], sim_dim[1], sim_dim[2], **kwargs
          )
          nib_image = nib.Nifti1Image(im, affine=np.eye(4))
          image_fpath = os.path.join(dataroot, d["image"])
          nib.save(nib_image, image_fpath)
  
          if "label" in d:
              nib_image = nib.Nifti1Image(seg, affine=np.eye(4))
              label_fpath = os.path.join(dataroot, d["label"])
              nib.save(nib_image, label_fpath)
  
imports: from __future__ import annotations
  import os
  import shutil
  import sys
  import tempfile
  import unittest
  import nibabel
  import numpy
  import torch
  from monai.apps.auto3dseg import BundleGen, DataAnalyzer
  from monai.apps.auto3dseg.utils import export_bundle_algo_history, import_bundle_algo_history
  from monai.bundle.config_parser import ConfigParser
  from monai.data import create_test_image_3d
  from monai.utils import set_determinism
  from tests.utils import SkipIfBeforePyTorchVersion, get_testing_algo_template_path, skip_if_downloading_fails, skip_if_no_cuda, skip_if_quick
label_desc: Use image node_id 1 for calling a global function with example usage: create_sim_data(dataroot, sim_datalist, sim_dim) without return types