code: def scale_neg_1_to_1_with_zero_mean_log_abs_max(v):
      """
      !!! not working
      """
      df = pd.DataFrame({"v": v, "sign": (v > 0) * 2 - 1})
      df["lg"] = np.log(np.abs(v)) / np.log(1.96)
      df["exclude"] = np.isinf(df.lg) | np.isneginf(df.lg)
      for mask in [
          (df["sign"] == -1) & (df["exclude"] == False),
          (df["sign"] == 1) & (df["exclude"] == False),
      ]:
          df[mask]["lg"] = df[mask]["lg"].max() - df[mask]["lg"]
      df["lg"] *= df["sign"]
      df["lg"] = df["lg"].fillna(0)
      print(df[df["exclude"]]["lg"].values)
      # to_rescale = convention_df['lg'].reindex(v.index)
      df["to_out"] = scale_neg_1_to_1_with_zero_mean_abs_max(df["lg"])
      print("right")
      print(df.sort_values(by="lg").iloc[:5])
      print(df.sort_values(by="lg").iloc[-5:])
      print("to_out")
      print(df.sort_values(by="to_out").iloc[:5])
      print(df.sort_values(by="to_out").iloc[-5:])
      print(len(df), len(df.dropna()))
      return df["to_out"]
  
imports: from typing import Callable
  import numpy
  import pandas
  from scipy.stats import rankdata
label_desc: Use image node_id 11 for calling a global function with example usage: scale_neg_1_to_1_with_zero_mean_log_abs_max(v) and returns: df