code: def compute_json_matrix(
      analyzer, features, filters, composite_filters
  ):
      """Compute a matrix of metrics for a given set of features.
  
      :param analyzer: The error analyzer.
      :type analyzer: BaseAnalyzer
      :param features: A list of one or two feature names to compute metrics for.
      :type features: list
      :param filters: A list of filters to apply to the data.
      :type filters: list
      :param composite_filters: A list of composite filters to apply to the data.
      :type composite_filters: list
      :return: A dictionary representation of the computed matrix which can be
          saved to JSON.
      :rtype: dict
      """
      # Note: this is for backcompat for older versions
      # of raiwidgets pypi package
      return compute_matrix(
          analyzer, features, filters, composite_filters
      )
  
imports: import logging
  import math
  import warnings
  from abc import ABC, abstractmethod
  import numpy
  import pandas
  from sklearn.metrics import multilabel_confusion_matrix
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import DIFF, PRED_Y, ROW_INDEX, TRUE_Y, MatrixParams, MetricKeys, Metrics, ModelTask, metric_to_display_name
  from erroranalysis._internal.metrics import get_ordered_classes, is_multi_agg_metric, metric_to_func
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 1 for calling a global function with example usage: compute_json_matrix(analyzer, features, filters, composite_filters) and returns: compute_matrix