code: def test_filter_inf_trials(value: float, expected: int) -> None:
      study = create_study()
      study.add_trial(
          create_trial(
              value=0.0,
              params={"x": 1.0},
              distributions={"x": FloatDistribution(0.0, 1.0)},
          )
      )
      study.add_trial(
          create_trial(
              value=value,
              params={"x": 0.0},
              distributions={"x": FloatDistribution(0.0, 1.0)},
          )
      )
  
      trials = _filter_nonfinite(
          study.get_trials(states=(TrialState.COMPLETE,))
      )
      assert len(trials) == expected
      assert all(
          [t.number == num for t, num in zip(trials, range(expected))]
      )
  
imports: import datetime
  import logging
  from textwrap import dedent
  from typing import cast
  import numpy
  import pytest
  from pytest import LogCaptureFixture
  import optuna
  from optuna.distributions import FloatDistribution
  from optuna.study import create_study
  from optuna.testing.visualization import prepare_study_with_trials
  from optuna.trial import create_trial
  from optuna.trial import FrozenTrial
  from optuna.trial import TrialState
  from optuna.visualization import is_available
  from optuna.visualization._utils import _check_plot_args
  from optuna.visualization._utils import _filter_nonfinite
  from optuna.visualization._utils import _is_log_scale
  from optuna.visualization._utils import _make_hovertext
label_desc: Use image node_id 5 for calling a global function with example usage: test_filter_inf_trials(value, expected) without return types