class_docstr: Adds Guidance Signal to the input image
  
  Args:
      image: key of source image, defaults to ``"image"``
      label: key of source label, defaults to ``"label"``
      others: source others (other labels from the binary mask which are not being used for training)
          defaults to ``"others"``
      drop_rate: probability of dropping the signal, defaults to ``0.5``
      jitter_range: noise added to the points in the point mask for exclusion mask, defaults to ``3``
      gaussian: add gaussian
      sigma: sigma value for gaussian
      truncated: spreads how many stds for gaussian
      add_exclusion_map: add exclusion map/signal
class_docstr_tok: ["Adds","Guidance","Signal","to","the","input","image","Args",":","image",":","key","of","source","image",",","defaults","to","``","``","image","''","``","label",":","key","of","source","label",",","defaults","to","``","``","label","''","``","others",":","source","others","(","other","labels","from","the","binary","mask","which","are","not","being","used","for","training",")","defaults","to","``","``","others","''","``","drop_rate",":","probability","of","dropping","the","signal",",","defaults","to","``","0.5","``","jitter_range",":","noise","added","to","the","points","in","the","point","mask","for","exclusion","mask",",","defaults","to","``","3","``","gaussian",":","add","gaussian","sigma",":","sigma","value","for","gaussian","truncated",":","spreads","how","many","stds","for","gaussian","add_exclusion_map",":","add","exclusion","map\/signal"]
code: def __init__(
      self,
      image: str = NuclickKeys.IMAGE,
      label: str = NuclickKeys.LABEL,
      others: str = NuclickKeys.OTHERS,
      drop_rate: float = 0.5,
      jitter_range: int = 0,
      gaussian: bool = False,
      sigma: float = 1.0,
      truncated: float = 2.0,
      add_exclusion_map: bool = True,
      use_distance: bool = False,
  ):
      MapTransform.__init__(self, image)
  
      self.image = image
      self.label = label
      self.others = others
      self.drop_rate = drop_rate
      self.jitter_range = jitter_range
      self.gaussian = gaussian
      self.sigma = sigma
      self.truncated = truncated
      self.add_exclusion_map = add_exclusion_map
      self.use_distance = use_distance
  
imports: from __future__ import annotations
  import math
  from typing import Any
  import numpy
  import torch
  from monai.config import KeysCollection, NdarrayOrTensor
  from monai.networks.layers import GaussianFilter
  from monai.transforms import MapTransform, Randomizable, SpatialPad
  from monai.utils import StrEnum, convert_to_numpy, optional_import
label_desc: Use image node_id 1 to create a new AddPointGuidanceSignald object from inherited base classes: Randomizable, MapTransform with example: obj = AddPointGuidanceSignald(image, label, others, drop_rate, jitter_range, gaussian, sigma, truncated, add_exclusion_map, use_distance)