def test_func_with_incorrect_datatype(self):
with self.assertRaises(TypeError) as context:
_ = validate_array_input((1, 2, 3), np.float64, 'arr')
msg = ["The array {} must be either a list, ".format('arr'),
"numpy.ndarray or pandas.Series"]
self.assertTrue("".join(msg) in str(context.exception))
def test_func_with_non_numerical_input(self):
with self.assertRaises(ValueError) as context:
_ = validate_array_input(['a', 'b', 1], np.float64, 'arr')
msg = [
"The data in the parameter array '{}'".format('arr'),
" must be purely numerical."
]
self.assertTrue("".join(msg) in str(context.exception))
def test_func_with_list(self):
vals = [1., 2., 3., 4.]
arr = validate_array_input(vals, np.float64, 'arr')
self.assertSequenceEqual(vals, arr.tolist())
def test_func_with_pandas_series(self):
vals = [1, 2, 3, 4]
data = pd.Series(data=vals, dtype=np.float64)
arr = validate_array_input(data, np.float64, 'arr')
self.assertSequenceEqual(arr.tolist(),
np.array(vals, np.float64).tolist())