class_docstr: Event handler triggered on completing every iteration to calculate and save the probability map.
  This handler use metadata from MetaTensor to create the probability map. This can be simply achieved by using
  `monai.data.SlidingPatchWSIDataset` or `monai.data.MaskedPatchWSIDataset` as the dataset.
docstr: This method save the probability map for an image, when its inference is finished,
  and delete that probability map from memory.
  
  Args:
      name: the name of image to be saved.
docstr_tok: ["This","method","save","the","probability","map","for","an","image",",","when","its","inference","is","finished",",","and","delete","that","probability","map","from","memory",".","Args",":","name",":","the","name","of","image","to","be","saved","."]
code: def save_prob_map(self, name: str) -> None:
      """
      This method save the probability map for an image, when its inference is finished,
      and delete that probability map from memory.
  
      Args:
          name: the name of image to be saved.
      """
      file_path = self.folder_layout.filename(name)
      np.save(file_path, self.prob_map[name])
  
      self.num_done_images += 1
      self.logger.info(
          f"Inference of '{name}' is done [{self.num_done_images}/{self.num_images}]!"
      )
      del self.prob_map[name]
      del self.counter[name]
  
file_path: MONAI/monai/handlers/probability_maps.py
imports: from __future__ import annotations
  import logging
  import threading
  from typing import TYPE_CHECKING
  import numpy
  from monai.config import DtypeLike, IgniteInfo
  from monai.data.folder_layout import FolderLayout
  from monai.utils import ProbMapKeys, min_version, optional_import
  from monai.utils.enums import CommonKeys
label_desc: Use image node_id 4 for calling the ProbMapProducer obj's underlying member method code with example usage: obj.save_prob_map(name) without return types