code: def custom_condition(value: dict):
      ratio = value["Test"] / value["Train"]
      if low_threshold <= ratio <= high_threshold:
          return ConditionResult(ConditionCategory.PASS)
      elif ratio < low_threshold:
          return ConditionResult(
              ConditionCategory.FAIL,
              f"Test-Train ratio is {ratio:.2}",
              ConditionCategory.FAIL,
          )
      else:
          return ConditionResult(
              ConditionCategory.FAIL,
              f"Test-Train ratio is {ratio:.2}",
              ConditionCategory.WARN,
          )
  
file_path: deepchecks/docs/source/general/usage/customizations/plot_configure_check_conditions.py
imports: from deepchecks.tabular.checks import DatasetsSizeComparison
  import pandas
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.suites import train_test_validation
  import pandas
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.checks import DatasetsSizeComparison
  from deepchecks.core import ConditionResult
  from deepchecks.tabular import Suite
  from deepchecks.core import ConditionCategory, ConditionResult
label_desc: Use image node_id 2 for calling a global function with example usage: custom_condition(value) and returns: ConditionResult, ConditionResult, ConditionResult