code: def test_summarize(X, mins, maxs):
      for mins_, maxs_ in ((mins, maxs), (None, None)):
          d = Uniform(mins_, maxs_)
          d.summarize(X[:4])
          assert_array_almost_equal(d._x_mins, [0.5, 0.2, 0.5])
          assert_array_almost_equal(d._x_maxs, [3.1, 2.1, 2.2])
  
          d.summarize(X[4:])
          assert_array_almost_equal(d._x_mins, [0.5, 0.2, 0.1])
          assert_array_almost_equal(d._x_maxs, [5.4, 2.1, 4.0])
  
          d = Uniform(mins_, maxs_)
          d.summarize(X)
          assert_array_almost_equal(d._x_mins, [0.5, 0.2, 0.1])
          assert_array_almost_equal(d._x_maxs, [5.4, 2.1, 4.0])
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Uniform
  from ._utils import _test_initialization_raises_two_parameters
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  from ._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 19 for calling a global function with example usage: test_summarize(X, mins, maxs) without return types