code: def matrix(self, data):
      try:
          features = data[0]
          if features[0] is None and features[1] is None:
              return {WidgetRequestResponseConstants.data: []}
          filters = data[1]
          composite_filters = data[2]
          quantile_binning = data[3]
          num_bins = data[4]
          metric = display_name_to_metric[data[5]]
  
          filtered_data_df = self._prepare_filtered_error_analysis_data(
              features, filters, composite_filters, metric
          )
  
          matrix = self._error_analyzer.compute_matrix_on_dataset(
              features, filtered_data_df, quantile_binning, num_bins
          )
          return {WidgetRequestResponseConstants.data: matrix}
      except Exception as e:
          print(e)
          traceback.print_exc()
          e_str = _format_exception(e)
          return {
              WidgetRequestResponseConstants.error: "Failed to generate json matrix representation,"
              "inner error: {}".format(e_str),
              WidgetRequestResponseConstants.data: [],
          }
  
imports: import traceback
  from typing import List, Optional
  import numpy
  import pandas
  from erroranalysis._internal.constants import display_name_to_metric
  from raiutils.cohort import Cohort, CohortFilter, CohortFilterMethods
  from raiutils.data_processing import convert_to_list, serialize_json_safe
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask, is_classifier
  from raiwidgets.constants import ErrorMessages
  from raiwidgets.error_handling import _format_exception
  from raiwidgets.interfaces import WidgetRequestResponseConstants
  from responsibleai import RAIInsights
  from responsibleai._internal.constants import ManagerNames
label_desc: Use image node_id 7 for calling the ResponsibleAIDashboardInput obj's underlying member method code with example usage: obj.matrix(data) and returns: dict, dict, dict