code: def test_initialize(X):
      d = Poisson()
      assert d.d is None
      assert d.lambdas is None
      assert d._initialized == False
      assert_raises(AttributeError, getattr, d, "_w_sum")
      assert_raises(AttributeError, getattr, d, "_xw_sum")
      assert_raises(AttributeError, getattr, d, "_log_lambdas")
  
      d._initialize(3)
      assert d._initialized == True
      assert d.lambdas.shape[0] == 3
      assert d.d == 3
      assert_array_almost_equal(d.lambdas, [0.0, 0.0, 0.0])
      assert_array_almost_equal(d._w_sum, [0.0, 0.0, 0.0])
      assert_array_almost_equal(d._xw_sum, [0.0, 0.0, 0.0])
  
      d._initialize(2)
      assert d._initialized == True
      assert d.lambdas.shape[0] == 2
      assert d.d == 2
      assert_array_almost_equal(d.lambdas, [0.0, 0.0])
      assert_array_almost_equal(d._w_sum, [0.0, 0.0])
      assert_array_almost_equal(d._xw_sum, [0.0, 0.0])
  
      d = Poisson([1.2, 9.3])
      assert d._initialized == True
      assert d.d == 2
  
      d._initialize(3)
      assert d._initialized == True
      assert d.lambdas.shape[0] == 3
      assert d.d == 3
      assert_array_almost_equal(d.lambdas, [0.0, 0.0, 0.0])
  
      d = Poisson()
      d.summarize(X)
      d._initialize(4)
      assert d._initialized == True
      assert d.lambdas.shape[0] == 4
      assert d.d == 4
      assert_array_almost_equal(d._w_sum, [0.0, 0.0, 0.0, 0.0])
      assert_array_almost_equal(d._xw_sum, [0.0, 0.0, 0.0, 0.0])
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Poisson
  from ._utils import _test_initialization_raises_one_parameter
  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 12 for calling a global function with example usage: test_initialize(X) without return types