docstr: Return the smoothing filter size based on the settings and image size
  
          
docstr_tok: ["Return","the","smoothing","filter","size","based","on","the","settings","and","image","size"]
code: def smoothing_filter_size(self, image_shape):
      """Return the smoothing filter size based on the settings and image size"""
      if self.automatic_object_width == FI_MANUALLY:
          # Convert from full-width at half-maximum to standard deviation
          # (or so says CPsmooth.m)
          return self.size_of_smoothing_filter.value
      elif self.automatic_object_width == FI_OBJECT_SIZE:
          return self.object_width.value * 2.35 / 3.5
      elif self.automatic_object_width == FI_AUTOMATIC:
          return min(30, float(numpy.max(image_shape)) / 40.0)
  
imports: import centrosome.bg_compensate
  import centrosome.cpmorphology
  import centrosome.cpmorphology
  import centrosome.filter
  import centrosome.smooth
  import numpy
  import scipy.ndimage
  import skimage.filters
  from cellprofiler_core.image import AbstractImage
  from cellprofiler_core.image import Image
  from cellprofiler_core.measurement import Measurements
  from cellprofiler_core.module import Module
  from cellprofiler_core.pipeline import Pipeline
  from cellprofiler_core.setting import Binary
  from cellprofiler_core.setting import ValidationError
  from cellprofiler_core.setting.choice import Choice
  from cellprofiler_core.setting.subscriber import ImageSubscriber
  from cellprofiler_core.setting.text import Float
  from cellprofiler_core.setting.text import ImageName
  from cellprofiler_core.setting.text import Integer
label_desc: Use image node_id 11 for calling the CorrectIlluminationCalculate obj's underlying member method code with example usage: obj.smoothing_filter_size(image_shape) and returns: self, unknown, min