def __init__(
      self,
      model: language_model.LanguageModel,
      player_name: str,
      context_fn: Callable[[], str],
      clock: game_clock.GameClock,
      name: str = 'Stress',
      verbose: bool = False,
      measurements: measurements_lib.Measurements | None = None,
      channel: str = 'stress',
  ):
    """Initializes the metric.

    Args:
      model: The language model to use.
      player_name: The player to ask about.
      context_fn: The function to get the context text for the question.
        (typically this is the player state). This function will be called on
        `update`.
      clock: The clock to use.
      name: The name of the metric.
      verbose: Whether to print the metric.
      measurements: The measurements to use.
      channel: The name of the channel to push data
    """
    questionnaire = [
        {'statement': (
            'I found myself getting upset by quite trivial things.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I tended to over-react to situations.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found it difficult to relax.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found myself getting upset rather easily.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I felt that I was using a lot of nervous energy.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found myself getting impatient when I was delayed in any way ' +
            '(eg, elevators, traffic lights, being kept waiting).'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I felt that I was rather touchy.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found it hard to wind down.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found that I was very irritable.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found it hard to calm down after something upset me.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found it difficult to tolerate interruptions to what I was ' +
            'doing.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I was in a state of nervous tension.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I was intolerant of anything that kept me from getting on with ' +
            'what I was doing.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},

        {'statement': (
            'I found myself getting agitated.'),
         'choices': AGREEMENT_SCALE_CHOICES,
         'ascending_scale': True},
    ]

    self.metric = Questionnaire(
        model=model,
        player_name=player_name,
        context_fn=context_fn,
        clock=clock,
        questionnaire=questionnaire,
        name=name,
        verbose=verbose,
        measurements=measurements,
        channel=channel,
    )
Initializes the metric.

    Args:
      model: The language model to use.
      player_name: The player to ask about.
      context_fn: The function to get the context text for the question.
        (typically this is the player state). This function will be called on
        `update`.
      clock: The clock to use.
      name: The name of the metric.
      verbose: Whether to print the metric.
      measurements: The measurements to use.
      channel: The name of the channel to push data
    
concordia/deprecated/metrics/dass_questionnaire.py