code: def test_compute(self):
      target = np.array([0, 0, 0, 0, 1, 1, 1, 1])
      pred = np.array([0.1, 0.8, 0.1, 0.1, 0.8, 0.1, 0.8, 0.8])
      info = AdditionalMetrics.compute(
          target, pred, None, BINARY_CLASSIFICATION
      )
      details = info["metric_details"]
      max_metrics = info["max_metrics"]
      conf = info["confusion_matrix"]
      self.assertEqual(conf.iloc[0, 0], 3)
      self.assertEqual(conf.iloc[1, 1], 3)
      self.assertTrue(details is not None)
      self.assertTrue(max_metrics is not None)
  
file_path: mljar-supervised/tests/tests_utils/test_compute_additional_metrics.py
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.utils.additional_metrics import AdditionalMetrics
  from supervised.utils.metric import Metric
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, REGRESSION
label_desc: Use image node_id 1 for calling the ComputeAdditionalMetricsTest obj's underlying member method code with example usage: obj.test_compute() without return types