code: def make_workspace_ijv():
      module = (
          cellprofiler.modules.convertobjectstoimage.ConvertToImage()
      )
      shape = (14, 16)
      r = numpy.random.RandomState()
      r.seed(0)
      i = r.randint(0, shape[0], size=numpy.prod(shape))
      j = r.randint(0, shape[1], size=numpy.prod(shape))
      v = r.randint(1, 8, size=numpy.prod(shape))
      order = numpy.lexsort((i, j, v))
      ijv = numpy.column_stack((i, j, v))
      ijv = ijv[order, :]
      same = numpy.all(ijv[:-1, :] == ijv[1:, :], 1)
  
      ijv = ijv[: numpy.prod(shape) - 1][~same, :]
  
      pipeline = cellprofiler_core.pipeline.Pipeline()
      object_set = cellprofiler_core.object.ObjectSet()
      image_set_list = cellprofiler_core.image.ImageSetList()
      image_set = image_set_list.get_image_set(0)
      workspace = cellprofiler_core.workspace.Workspace(
          pipeline,
          module,
          image_set,
          object_set,
          cellprofiler_core.measurement.Measurements(),
          image_set_list,
      )
      objects = cellprofiler_core.object.Objects()
      objects.set_ijv(ijv, shape)
      object_set.add_objects(objects, OBJECTS_NAME)
      assert len(objects.get_labels()) > 1
      module.image_name.value = IMAGE_NAME
      module.object_name.value = OBJECTS_NAME
      return workspace, module, ijv
  
imports: import numpy
  import pytest
  import scipy.sparse.coo
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.module
  import cellprofiler.modules.convertobjectstoimage
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
label_desc: Use image node_id 10 for calling a global function with example usage: make_workspace_ijv() and returns: workspace,  module,  ijv