class_docstr: Evaluate the average performance (objective value) between different search algorithms from
  the rank perspective at different time steps (trial number).
  The performance (objective value) used for a trial will the best result until the trial.
docstr: Generate a `plotly.graph_objects.Figure` to display average rankings
  between different search algorithms.
  
  task: str
      Name of the task
  experiments: list
      A list of (task_index, experiment), where task_index is the index of task to run for
      this assessment, and experiment is an instance of `orion.core.worker.experiment`.
docstr_tok: ["Generate","a","`","plotly.graph_objects.Figure","`","to","display","average","rankings","between","different","search","algorithms",".","task",":","str","Name","of","the","task","experiments",":","list","A","list","of","(","task_index",",","experiment",")",",","where","task_index","is","the","index","of","task","to","run","for","this","assessment",",","and","experiment","is","an","instance","of","`","orion.core.worker.experiment","`","."]
code: def analysis(self, task, experiments):
      """
      Generate a `plotly.graph_objects.Figure` to display average rankings
      between different search algorithms.
  
      task: str
          Name of the task
      experiments: list
          A list of (task_index, experiment), where task_index is the index of task to run for
          this assessment, and experiment is an instance of `orion.core.worker.experiment`.
      """
      algorithm_groups = defaultdict(list)
  
      for _, exp in experiments:
          algorithm_name = list(exp.configuration["algorithm"].keys())[
              0
          ]
          algorithm_groups[algorithm_name].append(exp)
  
      return {rankings.__name__: rankings(algorithm_groups)}
  
imports: from collections import defaultdict
  from orion.benchmark.assessment.base import BenchmarkAssessment
  from orion.plotting.base import rankings
label_desc: Use image node_id 2 for calling the AverageRank obj's underlying member method code with example usage: obj.analysis(task, experiments) and returns: dict