class_docstr: Class to make diffusions for a given graph.
  
  Args:
      diffusion_number (int): Number of diffusions
      diffusion_cover (int): Number of nodes in diffusion.
class_docstr_tok: ["Class","to","make","diffusions","for","a","given","graph",".","Args",":","diffusion_number","(","int",")",":","Number","of","diffusions","diffusion_cover","(","int",")",":","Number","of","nodes","in","diffusion","."]
code: def __init__(self, diffusion_number: int, diffusion_cover: int):
      self.diffusion_number = diffusion_number
      self.diffusion_cover = diffusion_cover
  
imports: import random
  import networkx
label_desc: Use image node_id 1 to create a new EulerianDiffuser object  with example: obj = EulerianDiffuser(diffusion_number, diffusion_cover)