code: def _generate_slice_subplot(
      subplot_info: _SliceSubplotInfo,
  ) -> list[Scatter]:
      trace = []
  
      feasible = _PlotValues([], [], [])
      infeasible = _PlotValues([], [], [])
  
      for x, y, num, c in zip(
          subplot_info.x,
          subplot_info.y,
          subplot_info.trial_numbers,
          subplot_info.constraints,
      ):
          if (
              x is not None
              or x != "None"
              or y is not None
              or y != "None"
          ):
              if c:
                  feasible.x.append(x)
                  feasible.y.append(y)
                  feasible.trial_numbers.append(num)
              else:
                  infeasible.x.append(x)
                  infeasible.y.append(y)
      trace.append(
          go.Scatter(
              x=feasible.x,
              y=feasible.y,
              mode="markers",
              name="Feasible Trial",
              marker={
                  "line": {"width": 0.5, "color": "Grey"},
                  "color": feasible.trial_numbers,
                  "colorscale": COLOR_SCALE,
                  "colorbar": {
                      "title": "Trial",
                      "x": 1.0,  # Offset the colorbar position with a fixed width `xpad`.
                      "xpad": 40,
                  },
              },
              showlegend=False,
          )
      )
      if len(infeasible.x) > 0:
          trace.append(
              go.Scatter(
                  x=infeasible.x,
                  y=infeasible.y,
                  mode="markers",
                  name="Infeasible Trial",
                  marker={
                      "color": "#cccccc",
                  },
                  showlegend=False,
              )
          )
  
      return trace
  
imports: from __future__ import annotations
  from typing import Any
  from typing import Callable
  from typing import cast
  from typing import NamedTuple
  from optuna.distributions import CategoricalChoiceType
  from optuna.distributions import CategoricalDistribution
  from optuna.logging import get_logger
  from optuna.samplers._base import _CONSTRAINTS_KEY
  from optuna.study import Study
  from optuna.trial import FrozenTrial
  from optuna.trial import TrialState
  from optuna.visualization._plotly_imports import _imports
  from optuna.visualization._utils import _check_plot_args
  from optuna.visualization._utils import _filter_nonfinite
  from optuna.visualization._utils import _is_log_scale
label_desc: Use image node_id 5 for calling a global function with example usage: _generate_slice_subplot(subplot_info) and returns: trace