code: def make_classifier(
      module,
      answer,
      classes=None,
      class_names=None,
      rules_classes=None,
      name="Classifier",
      n_features=1,
  ):
      assert isinstance(
          module, cellprofiler.modules.flagimage.FlagImage
      )
      feature_names = [
          image_measurement_name(i) for i in range(n_features)
      ]
      if classes is None:
          classes = numpy.arange(1, max(3, answer + 1))
      if class_names is None:
          class_names = ["Class%d" for _ in classes]
      if rules_classes is None:
          rules_classes = [class_names[0]]
      s = test_filterobjects.make_classifier_pickle(
          numpy.array([answer]),
          classes,
          class_names,
          name,
          feature_names,
      )
      fd, filename = tempfile.mkstemp(".model")
      os.write(fd, s)
      os.close(fd)
      measurement = module.flags[0].measurement_settings[0]
      measurement.source_choice.value = (
          cellprofiler.modules.flagimage.S_CLASSIFIER
      )
      measurement.rules_directory.set_custom_path(
          os.path.dirname(filename)
      )
      measurement.rules_file_name.value = os.path.split(filename)[1]
      measurement.rules_class.value = rules_classes
      yield
      try:
          os.remove(filename)
      except:
          pass
  
imports: import contextlib
  import os
  import tempfile
  import numpy
  import pytest
  import six.moves
  from cellprofiler_core.constants.measurement import COLTYPE_INTEGER
  from cellprofiler_core.constants.workspace import DISPOSITION_CONTINUE, DISPOSITION_SKIP
  import tests.frontend.modules
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler.modules.flagimage
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.setting
  import cellprofiler_core.workspace
  from .None import test_filterobjects
label_desc: Use image node_id 7 for calling a global function with example usage: make_classifier(module, answer, classes, class_names, rules_classes, name, n_features) without return types