docstr: Create the settings for the module
  
  Create the settings for the module during initialization.
docstr_tok: ["Create","the","settings","for","the","module","Create","the","settings","for","the","module","during","initialization","."]
code: def create_settings(self):
      """Create the settings for the module
  
      Create the settings for the module during initialization.
      """
      self.image_name = ImageSubscriber(
          "Select the input image",
          "None",
          doc="""\
  The name of a binary image from a previous module. **IdentifyDeadWorms**
  will use this image to establish the foreground and background for the
  fitting operation. You can use **ApplyThreshold** to threshold a
  grayscale image and create the binary mask. You can also use a module
  such as **IdentifyPrimaryObjects** to label each worm and then use
  **ConvertObjectsToImage** to make the result a mask.
  """,
      )
  
      self.object_name = LabelName(
          "Name the dead worm objects to be identified",
          "DeadWorms",
          doc="""\
  This is the name for the dead worm objects. You can refer
  to this name in subsequent modules such as
  **IdentifySecondaryObjects**""",
      )
  
      self.worm_width = Integer(
          "Worm width",
          10,
          minval=1,
          doc="""\
  This is the width (the short axis), measured in pixels,
  of the diamond used as a template when
  matching against the worm. It should be less than the width
  of a worm.""",
      )
  
      self.worm_length = Integer(
          "Worm length",
          100,
          minval=1,
          doc="""\
  This is the length (the long axis), measured in pixels,
  of the diamond used as a template when matching against the
  worm. It should be less than the length of a worm""",
      )
  
      self.angle_count = Integer(
          "Number of angles",
          32,
          minval=1,
          doc="""\
  This is the number of different angles at which the template will be
  tried. For instance, if there are 12 angles, the template will be
  rotated by 0°, 15°, 30°, 45° … 165°. The shape is bilaterally symmetric;
  that is, you will get the same shape after rotating it by 180°.
  """,
      )
  
      self.wants_automatic_distance = Binary(
          "Automatically calculate distance parameters?",
          True,
          doc="""\
  This setting determines whether or not **IdentifyDeadWorms**
  automatically calculates the parameters used to determine whether two
  found-worm centers belong to the same worm.
  
  Select "*Yes*" to have **IdentifyDeadWorms** automatically calculate
  the distance from the worm length and width. Select "*No*" to set the
  distances manually.
  """
          % globals(),
      )
  
      self.space_distance = Float(
          "Spatial distance",
          5,
          minval=1,
          doc="""\
  *(Used only if not automatically calculating distance parameters)*
  
  Enter the distance for calculating the worm centers, in units of pixels.
  The worm centers must be at least many pixels apart for the centers to
  be considered two separate worms.
  """,
      )
  
      self.angular_distance = Float(
          "Angular distance",
          30,
          minval=1,
          doc="""\
  *(Used only if automatically calculating distance parameters)*
  
  **IdentifyDeadWorms** calculates the worm centers at different angles.
  Two worm centers are considered to represent different worms if their
  angular distance is larger than this number. The number is measured in
  degrees.
  """,
      )
  
imports: import matplotlib.cm
  import numpy
  from cellprofiler_core.constants.measurement import COLTYPE_INTEGER, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, M_NUMBER_OBJECT_NUMBER, FF_COUNT, COLTYPE_FLOAT, IMAGE, C_COUNT, C_LOCATION, C_NUMBER, FTR_CENTER_X, FTR_CENTER_Y, FTR_OBJECT_NUMBER
  from cellprofiler_core.measurement import Measurements
  from cellprofiler_core.module import Module
  from cellprofiler_core.object import Objects, ObjectSet
  from cellprofiler_core.preferences import get_default_colormap
  from cellprofiler_core.setting import Binary
  from cellprofiler_core.setting.subscriber import ImageSubscriber
  from cellprofiler_core.setting.text import LabelName, Integer, Float
  from centrosome.cpmorphology import all_connected_components
  from centrosome.cpmorphology import fixup_scipy_ndimage_result
  from centrosome.cpmorphology import get_line_pts
  from scipy.ndimage import binary_erosion, binary_fill_holes
  from scipy.ndimage import mean
label_desc: Use image node_id 1 for calling the IdentifyDeadWorms obj's underlying member method code with example usage: obj.create_settings() without return types