def test_mean_not_a_list(self):
with self.assertRaises(TypeError) as context:
gcs.calc_mean(652)
self.assertEqual(str(context.exception),
'Bad Argument, Requires list of numbers')
with self.assertRaises(TypeError) as context:
gcs.calc_mean(8.56)
self.assertEqual(str(context.exception),
'Bad Argument, Requires list of numbers')
def test_mean(self):
self.assertEqual(get_column_stats.calc_mean([1, 1, 1, 1, 1]), 1)
self.assertEqual(get_column_stats.calc_mean([1, 2, 3, 4, 5]), 3)
self.assertEqual(get_column_stats.calc_mean([2, 3, 9, 11, 45]), 14)
self.assertEqual(get_column_stats.calc_mean([2, 2, 2, 10, 6]), 4.4)
with self.assertRaises(ZeroDivisionError) as context:
get_column_stats.calc_mean([])
self.assertTrue('division by zero' in context.exception)
rand_data = [random.randint(1, 100) for _ in range(100)]
rand_mean = (sum(rand_data) / len(rand_data))
self.assertEqual(get_column_stats.calc_mean(rand_data), rand_mean)
def test_mean(self):
a = get_column_stats.calc_mean(self)
self.assertEqual(a, self.mean)
def test_mean_float_list(self):
t = [1.5, 5.985, 7.43]
r = gcs.calc_mean(t)
e = sum(t) / len(t)
self.assertEqual(r, e)
def test_mean_const_array(self):
r = gcs.calc_mean([1])
self.assertEqual(r, 1)
def test_mean_non_integer(self):
with self.assertRaises(TypeError) as context:
gcs.calc_mean('abc')
self.assertEqual(str(context.exception),
'Bad Argument, Requires list of numbers')
def test_mean_empty_list(self):
t = []
with self.assertRaises(ZeroDivisionError) as context:
gcs.calc_mean(t)
self.assertEqual(str(context.exception), 'list is empty')
def test_mean_random(self):
exp_mean = np.random.uniform(0, 100)
dist = np.random.normal(loc=exp_mean, scale=1, size=10000).tolist()
self.assertAlmostEqual(gcs.calc_mean(dist), exp_mean, places=1)
def test_mean_const(self):
self.assertEqual(gcs.calc_mean([1, 1, 1, 1, 1, 1, 1]), 1)
self.assertEqual(gcs.calc_mean(list(range(1000))), 499.5)
