code: def metrics_at_thresholds(
      fn, y_true, y_score, n_thresholds=10, start=0.0, ax=None
  ):
      """Plot metrics at increasing thresholds"""
      th, m = compute_at_thresholds(
          fn, y_true, y_score, n_thresholds, start
      )
  
      ax.plot(th, np.array(m).T, ".--")
      ax.legend([fn_.__name__ for fn_ in fn])
      ax.set_xlabel("Threshold")
      ax.set_ylabel("Metric value")
      ax.grid()
  
      return ax
  
imports: import numpy
  from sklearn_evaluation.metrics import compute_at_thresholds
  from sklearn_evaluation.plot.util import set_default_ax
  from ..telemetry import SKLearnEvaluationLogger
  from ploomber_core.exceptions import modify_exceptions
label_desc: Use image node_id 1 for calling a global function with example usage: metrics_at_thresholds(fn, y_true, y_score, n_thresholds, start, ax) and returns: ax