def test_unstandardize2(self):
# Arrange
X = np.random.randn(1e4, 1, 32, 32) * 10 + 12
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='individual')
ds.unstandardize()
# Assert
np.testing.assert_allclose(X, ds.X, atol=1e-5)
def test_unstandardize2(self):
# Arrange
X = np.random.randn(1e4, 1, 32, 32) * 10 + 12
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='individual')
ds.unstandardize()
# Assert
np.testing.assert_allclose(X, ds.X, atol=1e-5)
def test_swap_standardization(self):
# Arrange
X = np.random.randn(1e4, 1, 32, 32) * 10 + 12
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='individual')
ds.standardize(standardization_type='global')
# Assert
assert ds.mean.shape == ()
np.testing.assert_allclose(ds.mean, 12, atol=1e-1)
np.testing.assert_allclose(ds.std, 10, atol=1e-1)
def test_unstandardize_global(self):
# Arrange
X = np.random.randn(1e4, 1, 32, 32) * 10 + 12
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='global')
ds.unstandardize()
# Assert
assert ds.mean.shape == ()
np.testing.assert_allclose(ds.mean, 12, atol=1e-1)
np.testing.assert_allclose(ds.std, 10, atol=1e-1)
def test_standardize_none(self):
# Arrange
x1 = np.array([[0, 1, 0], [0, 1, 0], [0, 1, 0]])
x2 = np.array([[1, 0, 1], [1, 0, 1], [1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
Xorig = ds.X.copy()
# Apply
ds.standardize(standardization_type=None)
# Assert
np.testing.assert_allclose(Xorig, ds.X)
def test_standardize_global(self):
# Arrange
x1 = np.array([[0, 1, 0], [0, 1, 0], [0, 1, 0]])
x2 = np.array([[1, 0, 1], [1, 0, 1], [1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='global')
# Assert
assert ds.mean.shape == ()
assert ds.mean == 0.5
assert ds.X.std() == 1
def test_unstandardize(self):
# Arrange
x1 = np.array([[0, 1, 0], [0, 1, 0], [0, 1, 0]])
x2 = np.array([[1, 0, 1], [1, 0, 1], [1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize()
ds.unstandardize()
# Assert
np.testing.assert_allclose(ds.X[0].squeeze(), x1)
np.testing.assert_allclose(ds.X[1].squeeze(), x2)
def test_standardize(self):
# Arrange
x1 = np.array([[0, 1, 0], [0, 1, 0], [0, 1, 0]])
x2 = np.array([[1, 0, 1], [1, 0, 1], [1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize()
# Assert
for x in ds.X:
np.testing.assert_allclose(x.mean(), 0, atol=1e-7)
np.testing.assert_allclose(x.std(), 1, atol=1e-7)
def test_standardize_none(self):
# Arrange
x1 = np.array([[0, 1, 0],
[0, 1, 0],
[0, 1, 0]])
x2 = np.array([[1, 0, 1],
[1, 0, 1],
[1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
Xorig = ds.X.copy()
# Apply
ds.standardize(standardization_type=None)
# Assert
np.testing.assert_allclose(Xorig, ds.X)
def test_standardize_global(self):
# Arrange
x1 = np.array([[0, 1, 0],
[0, 1, 0],
[0, 1, 0]])
x2 = np.array([[1, 0, 1],
[1, 0, 1],
[1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize(standardization_type='global')
# Assert
assert ds.mean.shape == ()
assert ds.mean == 0.5
assert ds.X.std() == 1
def test_unstandardize(self):
# Arrange
x1 = np.array([[0, 1, 0],
[0, 1, 0],
[0, 1, 0]])
x2 = np.array([[1, 0, 1],
[1, 0, 1],
[1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize()
ds.unstandardize()
# Assert
np.testing.assert_allclose(ds.X[0].squeeze(), x1)
np.testing.assert_allclose(ds.X[1].squeeze(), x2)
def test_standardize(self):
# Arrange
x1 = np.array([[0, 1, 0],
[0, 1, 0],
[0, 1, 0]])
x2 = np.array([[1, 0, 1],
[1, 0, 1],
[1, 0, 1]])
X = np.array([x1, x2])
y = np.arange(len(X))
ds = DataSet(X, y)
# Apply
ds.standardize()
# Assert
for x in ds.X:
np.testing.assert_allclose(x.mean(), 0, atol=1e-7)
np.testing.assert_allclose(x.std(), 1, atol=1e-7)