code: def get_size_reduction_by_cropping(self):
      size_reduction = OrderedDict()
      for p in self.patient_identifiers:
          props = self.load_properties_of_cropped(p)
          shape_before_crop = props["original_size_of_raw_data"]
          shape_after_crop = props["size_after_cropping"]
          size_red = np.prod(shape_after_crop) / np.prod(
              shape_before_crop
          )
          size_reduction[p] = size_red
      return size_reduction
  
file_path: PaddleSeg/contrib/MedicalSeg/tools/preprocess_utils/dataset_analyzer.py
imports: import json
  import os
  import pickle
  import numpy
  from skimage.morphology import label
  from collections import OrderedDict
  from multiprocessing import Pool
  from .path_utils import join_paths
label_desc: Use image node_id 7 for calling the DatasetAnalyzer obj's underlying member method code with example usage: obj.get_size_reduction_by_cropping() and returns: size_reduction