def test_fmod_tensor(self):
t1 = TensorBase(np.array([-3, -2, -1, 1, 2, 3]))
divisor = np.array([2] * 6)
self.assertTrue(np.array_equal(t1.fmod(divisor).data, np.array([-1, 0, -1, 1, 0, 1])))
t2 = TensorBase(np.array([-3.5, -2.5, -1.5, 1.5, 2.5, 3.5]))
divisor = np.array([2.] * 6)
self.assertTrue(np.array_equal(t2.fmod(divisor).data, np.array([-1.5, -0.5, -1.5, 1.5, 0.5, 1.5])))
def test_fmod_broadcasting(self):
t = TensorBase([[-2, -3], [4, 1]])
result = t.fmod([2, -3])
self.assertTrue(np.array_equal(result.data, np.array([[0, 0], [0,
1]])))
def test_fmod_number(self):
t1 = TensorBase(np.array([-3, -2, -1, 1, 2, 3]))
self.assertTrue(np.array_equal(t1.fmod(2).data, np.array([-1, 0, -1, 1, 0, 1])))
t2 = TensorBase(np.array([-3.5, -2.5, -1.5, 1.5, 2.5, 3.5]))
self.assertTrue(np.array_equal(t2.fmod(2.).data, np.array([-1.5, -0.5, -1.5, 1.5, 0.5, 1.5])))
def test_fmod(self):
t = TensorBase([[-2, -3], [4, 1]])
result = t.fmod(1.5)
self.assertTrue(
np.array_equal(result.data, np.array([[-0.5, -0], [1, 1]])))
