def pad_test_Jacobian():
var_names = ['x','y']
func = ['_x + _y + sin(_x)', 'exp(_x+_y) - _x - sqrt(_y)']
PAD = Parallelized_AD(fun=func, var=var_names)
PAD.get_Jacobian([1, 2])
out = PAD.Jacobian
assert out[0][0] == 1 + np.cos(1)
assert out[0][1] == 1
assert out[1][0] == np.exp(3) - 1
assert out[1][1] == np.exp(3) - 1 / (2*np.sqrt(2))
def pad_test_forward_reverse():
'''
Here's a quick check to ensure our equality condition is working (and our forward
and reverse modes!). If everything is in order, forward mode and reverse mode should
be equal.
'''
func = ['_x + sin(_y)*_z', '_x + sin(_y)*exp(_z)']
PAD = Parallelized_AD(fun = func, var = ['x', 'y', 'z'])
a = PAD.get_Jacobian([1,2,3])
b = PAD.get_value([1,2,3])
PAD2 = Parallelized_AD(fun = func, var = ['x', 'y', 'z'])
a2 = PAD2.get_Jacobian([1,2,3], forward=True)
b2 = PAD2.get_value([1,2,3])
for i in range(2):
for j in range(3):
assert a[i][j] == a2[i][j]
for i in range(2):
assert b[i] == b2[i]
def pad_test_add_function():
var_names = ['x','y']
PAD = Parallelized_AD(var=var_names)
PAD.add_function('_x + _y + sin(_x)')
PAD.add_function('exp(_x+_y) - _x - sqrt(_y)')
PAD.add_function('_x+1+_y ')
out = PAD.get_Jacobian([1, 2])
assert out[0][0] == 1 + np.cos(1)
assert out[0][1] == 1
assert out[1][0] == np.exp(3) - 1
assert out[1][1] == np.exp(3) - 1 / (2*np.sqrt(2))
assert out[2][0] == 1
assert out[2][1] == 1
def pad_test_add_var():
func = ['_x + _y + sin(_x)', 'exp(_x+_y) - _x - sqrt(_y)']
PAD = Parallelized_AD(fun=func)
PAD.add_var('x')
PAD.add_var('y')
PAD.add_function('_z**2')
PAD.add_var('z')
out = PAD.get_Jacobian([1, 2, 3])
assert out[0][0] == 1 + np.cos(1)
assert out[0][1] == 1
assert out[0][2] == 0
assert out[1][0] == np.exp(3) - 1
assert out[1][1] == np.exp(3) - 1 / (2*np.sqrt(2))
assert out[1][2] == 0
assert out[2][0] == 0
assert out[2][1] == 0
assert out[2][2] == 6