code: def _get_min_max_with_errors(
      x: FloatList, y: FloatList, sd_x: FloatList, sd_y: FloatList
  ) -> Tuple[float, float]:
      """Get min and max of a bivariate dataset (across variables).
  
      Args:
          x: point estimate of x variable.
          y: point estimate of y variable.
          sd_x: standard deviation of x variable.
          sd_y: standard deviation of y variable.
  
      Returns:
          min_: minimum of points, including uncertainty.
          max_: maximum of points, including uncertainty.
  
      """
      min_ = min(
          min(np.array(x) - np.multiply(sd_x, Z)),
          min(np.array(y) - np.multiply(sd_y, Z)),
      )
      max_ = max(
          max(np.array(x) + np.multiply(sd_x, Z)),
          max(np.array(y) + np.multiply(sd_y, Z)),
      )
      return min_, max_
  
imports: from copy import deepcopy
  from typing import Any, Dict, List, Optional, Tuple
  import numpy
  import plotly.graph_objs
  from ax.core.batch_trial import BatchTrial
  from ax.core.data import Data
  from ax.core.experiment import Experiment
  from ax.core.multi_type_experiment import MultiTypeExperiment
  from ax.core.observation import Observation
  from ax.modelbridge.cross_validation import CVResult
  from ax.modelbridge.transforms.convert_metric_names import convert_mt_observations
  from ax.plot.base import AxPlotConfig, AxPlotTypes, PlotData, PlotInSampleArm, PlotMetric, Z
  from ax.plot.helper import compose_annotation
  from ax.plot.scatter import _error_scatter_data, _error_scatter_trace
  from ax.utils.common.typeutils import not_none
  from plotly import subplots
label_desc: Use image node_id 1 for calling a global function with example usage: _get_min_max_with_errors(x, y, sd_x, sd_y) and returns: min_,  max_