code: def array_convert_to_int(self, val: ndarray):
      values = self.scaler.fit_transform(val[:, None])[:, 0]
      self.mval = values.min()
      values = values - self.mval
      digits = int(math.log(values.max(), self.base)) + 1
      # extra digits used for 'float' part of the number
      extra_digits = self.code_len - digits
      if extra_digits < 0:
          raise ValueError("need large length to code the nummber")
      self.extra_digits = extra_digits
      values = (values * self.base**self.extra_digits).astype(int)
      return values
  
imports: import math
  from typing import Dict, List, Tuple
  import numpy
  from numpy import ndarray
  from sklearn.preprocessing import PowerTransformer, QuantileTransformer, RobustScaler
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling the FloatCode obj's underlying member method code with example usage: obj.array_convert_to_int(val) and returns: values