def test_line_model_residuals():
model = LineModel()
model._params = (0, 0)
assert_equal(abs(model.residuals(np.array([[0, 0]]))), 0)
assert_equal(abs(model.residuals(np.array([[0, 10]]))), 0)
assert_equal(abs(model.residuals(np.array([[10, 0]]))), 10)
model._params = (5, np.pi / 4)
assert_equal(abs(model.residuals(np.array([[0, 0]]))), 5)
assert_equal(abs(model.residuals(np.array([[np.sqrt(50), 0]]))), 5)
def test_line_model_residuals():
model = LineModel()
model._params = (0, 0)
assert_equal(abs(model.residuals(np.array([[0, 0]]))), 0)
assert_equal(abs(model.residuals(np.array([[0, 10]]))), 0)
assert_equal(abs(model.residuals(np.array([[10, 0]]))), 10)
model._params = (5, np.pi / 4)
assert_equal(abs(model.residuals(np.array([[0, 0]]))), 5)
assert_almost_equal(abs(model.residuals(np.array([[np.sqrt(50), 0]]))), 0)
def test_line_model_estimate():
# generate original data without noise
model0 = LineModel()
model0._params = (10, 1)
x0 = np.arange(-100, 100)
y0 = model0.predict_y(x0)
data0 = np.column_stack([x0, y0])
# add gaussian noise to data
np.random.seed(1234)
data = data0 + np.random.normal(size=data0.shape)
# estimate parameters of noisy data
model_est = LineModel()
model_est.estimate(data)
# test whether estimated parameters almost equal original parameters
assert_almost_equal(model0._params, model_est._params, 1)
def test_line_model_estimate():
# generate original data without noise
model0 = LineModel()
model0._params = (10, 1)
x0 = np.arange(-100, 100)
y0 = model0.predict_y(x0)
data0 = np.column_stack([x0, y0])
# add gaussian noise to data
np.random.seed(1234)
data = data0 + np.random.normal(size=data0.shape)
# estimate parameters of noisy data
model_est = LineModel()
model_est.estimate(data)
# test whether estimated parameters almost equal original parameters
assert_almost_equal(model0._params, model_est._params, 1)
def test_line_model_predict():
model = LineModel()
model._params = (10, 1)
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
def test_line_model_predict():
model = LineModel()
model._params = (10, 1)
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
