code: def test_landscape_gaussian() -> None:
      data = np.arange(6).reshape(3, 2)
      with patch(
          "nevergrad.functions.mlda.datasets.get_data"
      ) as data_getter:
          data_getter.return_value = data
          func = problems.Landscape(transform="gaussian").copy()
      output = (
          func.parametrization.spawn_child()
          .set_standardized_data([-144, -144])
          .args
      )
      np.testing.assert_equal(
          output, [0, 0]
      )  # should be mapped to 0, 0
      output = (
          func.parametrization.spawn_child()
          .set_standardized_data([144, 144])
          .args
      )
      np.testing.assert_array_equal(output, [2, 1])  # last element
      testing.printed_assert_equal(
          func.descriptors,
          {
              "parametrization": "gaussian",
              "function_class": "Landscape",
              "dimension": 2,
          },
      )
  
file_path: nevergrad/nevergrad/functions/mlda/test_problems.py
imports: from unittest.mock import patch
  import numpy
  import pandas
  from ...common import testing
  from .None import problems
label_desc: Use image node_id 8 for calling a global function with example usage: test_landscape_gaussian() without return types