def testModfExecution(self):
data1 = np.random.random((5, 9))
arr1 = tensor(data1.copy(), chunk_size=3)
o1, o2 = modf(arr1)
o = o1 + o2
res = self.executor.execute_tensor(o, concat=True)[0]
expected = sum(np.modf(data1))
self.assertTrue(np.allclose(res, expected))
arr1 = tensor(data1.copy(), chunk_size=3)
o1 = zeros(data1.shape, chunk_size=3)
o2 = zeros(data1.shape, chunk_size=3)
modf(arr1, o1, o2)
o = o1 + o2
res = self.executor.execute_tensor(o, concat=True)[0]
expected = sum(np.modf(data1))
self.assertTrue(np.allclose(res, expected))
data1 = sps.random(5, 9, density=.1)
arr1 = tensor(data1.copy(), chunk_size=3)
o1, o2 = modf(arr1)
o = o1 + o2
res = self.executor.execute_tensor(o, concat=True)[0]
expected = sum(np.modf(data1.toarray()))
np.testing.assert_equal(res.toarray(), expected)
def testModfOrderExecution(self):
data1 = np.random.random((5, 9))
t = tensor(data1, chunk_size=3)
o1, o2 = modf(t, order='F')
res1, res2 = self.executor.execute_tileables([o1, o2])
expected1, expected2 = np.modf(data1, order='F')
np.testing.assert_allclose(res1, expected1)
self.assertTrue(res1.flags['F_CONTIGUOUS'])
self.assertFalse(res1.flags['C_CONTIGUOUS'])
np.testing.assert_allclose(res2, expected2)
self.assertTrue(res2.flags['F_CONTIGUOUS'])
self.assertFalse(res2.flags['C_CONTIGUOUS'])
def test_modf_order_execution(setup):
data1 = np.random.random((5, 9))
t = tensor(data1, chunk_size=3)
o1, o2 = modf(t, order='F')
res1, res2 = execute(o1, o2)
expected1, expected2 = np.modf(data1, order='F')
np.testing.assert_allclose(res1, expected1)
assert res1.flags['F_CONTIGUOUS'] is True
assert res1.flags['C_CONTIGUOUS'] is False
np.testing.assert_allclose(res2, expected2)
assert res2.flags['F_CONTIGUOUS'] is True
assert res2.flags['C_CONTIGUOUS'] is False
def test_modf_execution(setup):
data1 = np.random.random((5, 9))
arr1 = tensor(data1.copy(), chunk_size=3)
o1, o2 = modf(arr1)
o = o1 + o2
res = o.execute().fetch()
expected = sum(np.modf(data1))
np.testing.assert_array_almost_equal(res, expected)
o1, o2 = modf([0, 3.5])
o = o1 + o2
res = o.execute().fetch()
expected = sum(np.modf([0, 3.5]))
np.testing.assert_array_almost_equal(res, expected)
arr1 = tensor(data1.copy(), chunk_size=3)
o1 = zeros(data1.shape, chunk_size=3)
o2 = zeros(data1.shape, chunk_size=3)
modf(arr1, o1, o2)
o = o1 + o2
res = o.execute().fetch()
expected = sum(np.modf(data1))
np.testing.assert_array_almost_equal(res, expected)
data1 = sps.random(5, 9, density=.1)
arr1 = tensor(data1.copy(), chunk_size=3)
o1, o2 = modf(arr1)
o = o1 + o2
res = o.execute().fetch()
expected = sum(np.modf(data1.toarray()))
np.testing.assert_equal(res.toarray(), expected)
