code: def _format_CI(
      estimate: float, sd: float, relative: bool, zval: float = Z
  ) -> str:
      """Format confidence intervals given estimate and standard deviation.
  
      Args:
          estimate: point estimate.
          sd: standard deviation of point estimate.
          relative: if True, '%' is appended.
          zval: z-value associated with desired CI (e.g. 1.96 for 95% CIs)
  
      Returns: formatted confidence interval.
      """
      return "[{lb:.{digits}f}{perc}, {ub:.{digits}f}{perc}]".format(
          lb=estimate - zval * sd,
          ub=estimate + zval * sd,
          digits=DECIMALS,
          perc="%" if relative else "",
      )
  
imports: import math
  from collections import Counter
  from logging import Logger
  from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
  import numpy
  from ax.core.generator_run import GeneratorRun
  from ax.core.observation import Observation, ObservationFeatures
  from ax.core.parameter import ChoiceParameter, FixedParameter, Parameter, ParameterType, RangeParameter
  from ax.core.types import TParameterization
  from ax.modelbridge.base import ModelBridge
  from ax.modelbridge.prediction_utils import _compute_scalarized_outcome, predict_at_point
  from ax.modelbridge.transforms.ivw import IVW
  from ax.plot.base import DECIMALS, PlotData, PlotInSampleArm, PlotOutOfSampleArm, Z
  from ax.utils.common.logger import get_logger
  from ax.utils.common.typeutils import not_none
label_desc: Use image node_id 4 for calling a global function with example usage: _format_CI(estimate, sd, relative, zval) and returns: str