docstr: Tests that `BoxCox` correctly handles situation where `global_fit = True`. More
  specifically, test checks that global fitting with two disjoint series
  produces same fitted parameters as local fitting with a single series formed
  by 'gluing' these two disjoint series together.
docstr_tok: ["Tests","that","`","BoxCox","`","correctly","handles","situation","where","`","global_fit","=","True","`",".","More","specifically",",","test","checks","that","global","fitting","with","two","disjoint","series","produces","same","fitted","parameters","as","local","fitting","with","a","single","series","formed","by","'gluing","'","these","two","disjoint","series","together","."]
code: def test_global_fitting(self):
      """
      Tests that `BoxCox` correctly handles situation where `global_fit = True`. More
      specifically, test checks that global fitting with two disjoint series
      produces same fitted parameters as local fitting with a single series formed
      by 'gluing' these two disjoint series together.
      """
      series_combined = self.sine_series.append_values(
          self.lin_series.all_values()
      )
      local_params = (
          BoxCox(global_fit=False).fit(series_combined)._fitted_params
      )
      global_params = (
          BoxCox(global_fit=True)
          .fit([self.sine_series, self.lin_series])
          ._fitted_params
      )
      assert local_params == global_params
  
file_path: darts/darts/tests/dataprocessing/transformers/test_boxcox.py
imports: from copy import deepcopy
  import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.transformers import BoxCox, Mapper
  from darts.utils.timeseries_generation import linear_timeseries, sine_timeseries
label_desc: Use image node_id 7 for calling the TestBoxCox obj's underlying member method code with example usage: obj.test_global_fitting() without return types