def test_empty(self):
valid, msg = validate_classes([])
assert isinstance(msg, str)
print("\n",
"While passing empty data, the error messages:",
msg,
end="\n")
assert not valid
def test_ndim_3(self):
data = np.linspace(0, 1, 12).reshape((2, 2, -1))
valid, msg = validate_classes(data)
print("\n",
"While passing three-dimensional data, the error messages:",
msg,
end="\n")
assert not valid
def test_type_str(self):
valid, array_or_msg = validate_classes(
self.valid_data.astype(str).tolist())
assert valid
assert isinstance(array_or_msg, np.ndarray)
assert array_or_msg.ndim == 1
assert array_or_msg.shape == self.valid_data.shape
assert np.all(np.less(np.abs(array_or_msg - self.valid_data), 1e-4))
def test_not_evenly_spaced(self):
data = np.linspace(1, 100, 101)
valid, msg = validate_classes(data)
print("\n",
"While it's not evenly spaced, the error messages:",
msg,
end="\n")
assert not valid
def test_not_incremental_left(self):
data = self.valid_data.tolist()
data[0] = 1e4
valid, msg = validate_classes(data)
print("\n",
"While it's incremental at left end, the error messages:",
msg,
end="\n")
assert not valid
def test_not_incremental_middle(self):
data = self.valid_data.tolist()
data[5], data[6] = data[6], data[5]
valid, msg = validate_classes(data)
print("\n",
"While it's incremental at middle, the error messages:",
msg,
end="\n")
assert not valid
def test_has_nan(self):
data = self.valid_data.tolist()
data[0] = np.nan
data[10] = np.nan
data[14] = np.nan
valid, msg = validate_classes(data)
print("\n",
"While it has 3 NaN values, the error messages:",
msg,
end="\n")
assert not valid
def test_type_none(self):
valid, msg = validate_classes(None)
assert isinstance(msg, str)
print("\n", "While passing `None`, the error messages:", msg, end="\n")
assert not valid
def test_with_int(self):
with_int = self.valid_data.tolist()
with_int[-1] = 2000
valid, _ = validate_classes(with_int)
assert valid
def test_list(self):
valid, _ = validate_classes(list(self.valid_data))
assert valid
def test_tuple(self):
valid, _ = validate_classes(tuple(self.valid_data))
assert valid
def test_sliced(self):
valid, _ = validate_classes(self.valid_data[:-1])
assert valid
def test_np_float64(self):
valid, _ = validate_classes(self.valid_data.astype(np.float64))
assert valid
def test_quasi_evenly_spaced(self):
data = np.round(self.valid_data, 3)
valid, _ = validate_classes(data)
assert valid
def test_valid(self):
valid, array_or_msg = validate_classes(self.valid_data)
assert valid
assert isinstance(array_or_msg, np.ndarray)
assert array_or_msg.ndim == 1