code: def _get_scaler_function(scaler_algo):
      scaler = None
      if scaler_algo == "normcdf":
          scaler = lambda x: norm.cdf(x, x.mean(), x.std())
      elif scaler_algo == "lognormcdf":
          scaler = lambda x: norm.cdf(
              np.log(x), np.log(x).mean(), np.log(x).std()
          )
      elif scaler_algo == "percentile":
          scaler = lambda x: rankdata(x).astype(np.float64) / len(x)
      elif scaler_algo == "percentiledense":
          scaler = lambda x: rankdata(x, method="dense").astype(
              np.float64
          ) / len(x)
      elif scaler_algo == "ecdf":
          from statsmodels.distributions import ECDF
  
          scaler = lambda x: ECDF(x)
      elif scaler_algo == "none":
          scaler = lambda x: x
      else:
          raise InvalidScalerException(
              "Invalid scaler alogrithm.  Must be either percentile or normcdf."
          )
      return scaler
  
imports: from abc import ABC, abstractmethod
  import numpy
  import pandas
  from scipy.stats import norm, rankdata
  from scattertext.Common import DEFAULT_SCALER_ALGO, DEFAULT_BETA
label_desc: Use image node_id 6 for calling the ScaledFScore obj's underlying member method code with example usage: obj._get_scaler_function(scaler_algo) and returns: scaler