def test_to_ice_data_one_sample(X, x_s):
n_cols = X.shape[1]
columns = ['x{}'.format(i) for i in range(n_cols)]
data = pd.DataFrame(X, columns=list(columns))
ice_data = ice.to_ice_data(data, 'x1', x_s)
ice_data_expected_values = np.repeat(X, x_s.size, axis=0)
ice_data_expected_values[:, 1] = x_s
ice_data_expected = pd.DataFrame(ice_data_expected_values, columns=columns)
assert compare_with_NaN(ice_data, ice_data_expected).all().all()
def test_to_ice_data():
X = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
data = pd.DataFrame(X, columns=['x1', 'x2', 'x3'])
x_s = np.array([10, 11])
ice_data = ice.to_ice_data(data, 'x3', x_s)
ice_data_expected = pd.DataFrame(np.array([[1, 2, 10], [1, 2, 11],
[4, 5, 10], [4, 5, 11],
[7, 8, 10], [7, 8, 11]]),
columns=['x1', 'x2', 'x3'])
assert (ice_data == ice_data_expected).all().all()
def test_to_ice_data_one_test_point(l, x_s):
X = np.array(l)
n_cols = X.shape[1]
columns = ['x{}'.format(i) for i in range(n_cols)]
data = pd.DataFrame(X, columns=columns)
x_s = np.array(x_s)
ice_data = ice.to_ice_data(data, 'x0', x_s)
ice_data_expected_values = X.copy()
ice_data_expected_values[:, 0] = x_s
ice_data_expected = pd.DataFrame(ice_data_expected_values, columns=columns)
assert compare_with_NaN(ice_data, ice_data_expected).all().all()
def test_to_ice_data_one_test_point(l, x_s):
X = np.array(l)
n_cols = X.shape[1]
columns = ['x{}'.format(i) for i in xrange(n_cols)]
data = pd.DataFrame(X, columns=columns)
x_s = np.array(x_s)
ice_data = ice.to_ice_data(data, 'x0', x_s)
ice_data_expected_values = X.copy()
ice_data_expected_values[:, 0] = x_s
ice_data_expected = pd.DataFrame(ice_data_expected_values, columns=columns)
assert compare_with_NaN(ice_data, ice_data_expected).all().all()
def test_to_ice_data_one_sample(l, x_s):
X = np.atleast_2d(l)
n_cols = X.shape[1]
columns = ['x{}'.format(i) for i in xrange(n_cols)]
data = pd.DataFrame(X, columns=list(columns))
x_s = np.array(x_s)
ice_data = ice.to_ice_data(data, 'x1', x_s)
ice_data_expected_values = np.repeat(X, x_s.size, axis=0)
ice_data_expected_values[:, 1] = x_s
ice_data_expected = pd.DataFrame(ice_data_expected_values, columns=columns)
assert compare_with_NaN(ice_data, ice_data_expected).all().all()
def test_to_ice_data():
X = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
data = pd.DataFrame(X, columns=['x1', 'x2', 'x3'])
x_s = np.array([10, 11])
ice_data = ice.to_ice_data(data, 'x3', x_s)
ice_data_expected = pd.DataFrame(np.array([[1, 2, 10],
[1, 2, 11],
[4, 5, 10],
[4, 5, 11],
[7, 8, 10],
[7, 8, 11]]),
columns=['x1', 'x2', 'x3'])
assert (ice_data == ice_data_expected).all().all()
