class_docstr: Saves the polar coordinates of linked nodes in its edge attributes
  (functional name: :obj:`polar`).
  
  Args:
      norm (bool, optional): If set to :obj:`False`, the output will not be
          normalized to the interval :math:`{[0, 1]}^2`.
          (default: :obj:`True`)
      max_value (float, optional): If set and :obj:`norm=True`, normalization
          will be performed based on this value instead of the maximum value
          found in the data. (default: :obj:`None`)
      cat (bool, optional): If set to :obj:`False`, all existing edge
          attributes will be replaced. (default: :obj:`True`)
class_docstr_tok: ["Saves","the","polar","coordinates","of","linked","nodes","in","its","edge","attributes","(","functional","name",":",":","obj",":","`","polar","`",")",".","Args",":","norm","(","bool",",","optional",")",":","If","set","to",":","obj",":","`","False","`",",","the","output","will","not","be","normalized","to","the","interval",":","math",":","`","{","[","0",",","1","]","}","^2","`",".","(","default",":",":","obj",":","`","True","`",")","max_value","(","float",",","optional",")",":","If","set","and",":","obj",":","`","norm=True","`",",","normalization","will","be","performed","based","on","this","value","instead","of","the","maximum","value","found","in","the","data",".","(","default",":",":","obj",":","`","None","`",")","cat","(","bool",",","optional",")",":","If","set","to",":","obj",":","`","False","`",",","all","existing","edge","attributes","will","be","replaced",".","(","default",":",":","obj",":","`","True","`",")"]
code: def __init__(
      self,
      norm: bool = True,
      max_value: Optional[float] = None,
      cat: bool = True,
  ) -> None:
      self.norm = norm
      self.max = max_value
      self.cat = cat
  
file_path: pytorch_geometric/torch_geometric/transforms/polar.py
imports: from math import pi
  from typing import Optional
  import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 1 to create a new Polar object from inherited base classes: BaseTransform with example: obj = Polar(norm, max_value, cat)