def generate_plottable_points_along_line(model:LineModelND, xmin:int,xmax:int, ymin:int, ymax:int):
"""
Computes points along the specified line model
The visual range is
between xmin and xmax along X axis
and
between ymin and ymax along Y axis
return shape is [[x1,y1],[x2,y2]]
"""
unit_vector=model.params[1]
slope=abs(unit_vector[1]/unit_vector[0])
x_values=None
y_values=None
if (slope > 1):
y_values=np.arange(ymin, ymax,1)
x_values=model.predict_x(y_values)
else:
x_values=np.arange(xmin, xmax,1)
y_values=model.predict_y(x_values)
np_data_points=np.column_stack((x_values,y_values))
return np_data_points
def test_line_model_nd_predict():
model = LineModelND()
model.params = (np.array([0, 0]), np.array([0.2, 0.8]))
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
def test_line_model_predict():
model = LineModelND()
model.params = ((0, 0), (1, 1))
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
def test_line_modelND_predict():
model = LineModelND()
model.params = (np.array([0, 0]), np.array([0.2, 0.98]))
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
def test_line_model_predict():
model = LineModelND()
model.params = ((0, 0), (1, 1))
x = np.arange(-10, 10)
y = model.predict_y(x)
assert_almost_equal(x, model.predict_x(y))
