def test_jacobian():
g = sad.AutoDiff('g', 3)
h = sad.AutoDiff('h', -4)
i = sad.AutoDiff('i', 7)
# Create functions
f1 = g + 4
f2 = h**2 + 2 * h - 12
variables = ['g', 'h', 'i']
functions = [f1, f2]
jacob = sad.jacobian(variables, functions)
test = np.array([[1., 0., 0.], [0., -6., 0.]])
for row in range(jacob.shape[0]):
for col in range(jacob.shape[1]):
assert jacob[row, col] == pytest.approx(test[row, col])
functions = sad.AutoDiffVector([f1, f2])
jacob = sad.jacobian(variables, functions)
test = np.array([[1., 0., 0.], [0., -6., 0.]])
for row in range(jacob.shape[0]):
for col in range(jacob.shape[1]):
assert jacob[row, col] == pytest.approx(test[row, col])
with pytest.raises(ValueError):
sad.jacobian('incorrect', 'input')
def test_vector_add():
f1 = sad.AutoDiff('x', 1)
f2 = sad.AutoDiff('y', 1)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = sad.AutoDiffVector([f1, f2]) + 2
vec1_other = sad.AutoDiffVector([f1, f2]) + other
vec2 = sad.vectorize(['x', 'y'], [1, 1]) + 2
vec2_other = sad.vectorize(['x', 'y'], [1, 1]) + other
f3 = f1 + 2
f4 = f1 + other
#
der = f3.der['x']
val = f3.val
der_other = f4.der['x']
val_other = f4.val
do_vector_tests(vec1, vec1_other, vec2, vec2_other, der, der_other, val,
val_other)
def test_vector_rdiv():
f1 = sad.AutoDiff('x', 2)
f2 = sad.AutoDiff('y', 2)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = 3 / sad.AutoDiffVector([f1, f2])
vec1_other = other / sad.AutoDiffVector([f1, f2])
vec2 = 3 / sad.vectorize(['x', 'y'], [2, 2])
vec2_other = other / sad.vectorize(['x', 'y'], [2, 2])
f3 = 3 / f1
f4 = other / f1
#
der = f3.der['x']
val = f3.val
der_other = f4.der['x']
val_other = f4.val
do_vector_tests(vec1, vec1_other, vec2, vec2_other, der, der_other, val,
val_other)
def test_vector_div():
f1 = sad.AutoDiff('x', 2)
f2 = sad.AutoDiff('y', 2)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = sad.AutoDiffVector([f1, f2]) / 3
vec1_other = sad.AutoDiffVector([f1, f2]) / other
vec2 = sad.vectorize(['x', 'y'], [2, 2]) / 3
vec2_other = sad.vectorize(['x', 'y'], [2, 2]) / other
f3 = f1 / 3
f4 = f1 / other
#
der = f3.der['x']
val = f3.val
der_other = f4.der['x']
val_other = f4.val
do_vector_tests(vec1, vec1_other, vec2, vec2_other, der, der_other, val,
val_other)
def test_vector_rsub():
f1 = sad.AutoDiff('x', 1)
f2 = sad.AutoDiff('y', 1)
other = sad.AutoDiff('z', 1)
# do operations on objects
vec1 = 1 - sad.AutoDiffVector([f1, f2])
vec1_other = other - sad.AutoDiffVector([f1, f2])
vec2 = 1 - sad.vectorize(['x', 'y'], [1, 1])
vec2_other = other - sad.vectorize(['x', 'y'], [1, 1])
f3 = 1 - f1
f4 = other - f1
#
der = f3.der['x']
val = f3.val
der_other = f4.der['x']
val_other = f4.val
do_vector_tests(vec1, vec1_other, vec2, vec2_other, der, der_other, val,
val_other)
def test_vector_log10():
f1 = sad.AutoDiff('x', 2)
f2 = sad.AutoDiff('y', 2)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = sad.log(sad.AutoDiffVector([f1, f2]), base=10)
vec2 = sad.log(sad.vectorize(['x', 'y'], [2, 2]), base=10)
f3 = sad.log(f1, base=10)
#
der = f3.der['x']
val = f3.val
do_vector_tests_no_other(vec1, vec2, der, val)
def test_vector_rpow():
f1 = sad.AutoDiff('x', 2)
f2 = sad.AutoDiff('y', 2)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = 3.0**sad.AutoDiffVector([f1, f2])
vec2 = 3.0**sad.vectorize(['x', 'y'], [2, 2])
f3 = 3.0**f1
#
der = f3.der['x']
val = f3.val
do_vector_tests_no_other(vec1, vec2, der, val)
def test_vector_tanh():
f1 = sad.AutoDiff('x', 0.5)
f2 = sad.AutoDiff('y', 0.5)
# do operations on objects
vec1 = sad.tanh(sad.AutoDiffVector([f1, f2]))
vec2 = sad.tanh(sad.vectorize(['x', 'y'], [0.5, 0.5]))
f3 = sad.tanh(f1)
#
der = f3.der['x']
val = f3.val
do_vector_tests_no_other(vec1, vec2, der, val)
with pytest.raises(AttributeError):
x1 = sad.AutoDiff('x', 1)
sad._tanhV(x1)
def test_vector_ln():
f1 = sad.AutoDiff('x', 2)
f2 = sad.AutoDiff('y', 2)
other = sad.AutoDiff('z', 2)
# do operations on objects
vec1 = sad.log(sad.AutoDiffVector([f1, f2]))
vec2 = sad.log(sad.vectorize(['x', 'y'], [2, 2]))
f3 = sad.log(f1)
#
der = f3.der['x']
val = f3.val
do_vector_tests_no_other(vec1, vec2, der, val)
with pytest.raises(AttributeError):
x1 = sad.AutoDiff('x', 1)
sad._logV(x1)
def test_vector_inputlist_duplicate_var():
with pytest.raises(ValueError):
x = sad.AutoDiff('x', 2)
y = sad.AutoDiff('x', 2)
x1 = sad.AutoDiffVector([x, y])
def test_vector_inputlist_not_autodiff():
with pytest.raises(ValueError):
x = sad.AutoDiff('x', 2)
y = 'asd'
x1 = sad.AutoDiffVector([x, y])
def test_vector_input_two_args():
with pytest.raises(TypeError):
x1 = sad.AutoDiffVector('x', 1)
