code: def _apply_boxcox(self, source_ts):
      min_value = np.min(source_ts)
      if min_value > 0:
          pass
      else:
          # Making a shift to positive values
          self.scope = abs(min_value) + 1
          source_ts = source_ts + self.scope
  
      _, self.lambda_value = stats.boxcox(source_ts)
      transformed_ts = boxcox(source_ts, self.lambda_value)
  
      return transformed_ts
  
imports: from copy import copy
  from typing import Optional
  import numpy
  from scipy import stats
  from scipy.special import boxcox, inv_boxcox
  from statsmodels.tsa.api import STLForecast
  from statsmodels.tsa.arima.model import ARIMA
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import ts_to_table
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.utilities.ts_gapfilling import SimpleGapFiller
label_desc: Use image node_id 6 for calling the ARIMAImplementation obj's underlying member method code with example usage: obj._apply_boxcox(source_ts) and returns: transformed_ts