code: def test_from_summaries_null():
      d = Uniform([1, 2], [1, 2])
      d.from_summaries()
      assert d.mins[0] != 1 and d.mins[1] != 2
      assert d.maxs[0] != 1 and d.maxs[1] != 2
      assert_array_almost_equal(d._x_mins, [INF, INF])
      assert_array_almost_equal(d._x_maxs, [NEGINF, NEGINF])
  
      d = Uniform([1, 2], [1, 2], inertia=0.5)
      d.from_summaries()
      assert d.mins[0] != 1 and d.mins[1] != 2
      assert d.maxs[0] != 1 and d.maxs[1] != 2
      assert_array_almost_equal(d._x_mins, [INF, INF])
      assert_array_almost_equal(d._x_maxs, [NEGINF, NEGINF])
  
      d = Uniform([1, 2], [1, 2], inertia=0.5, frozen=True)
      d.from_summaries()
      _test_fit_params(d, [1, 2], [1, 2])
  
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 28 for calling a global function with example usage: test_from_summaries_null() without return types