def test_pow_operations_CMG():
x = CMG(1, np.array([1, 0]))
f = x**2 + 2**x + x**x**x**2**x
x2 = CMG(3.0, np.array([1, 0]))
f2 = x2.__rpow__(x2)
assert f.val == 4.0
assert np.array_equal(f.grad, np.array([4.386294361119891, 0.]))
assert f2.val == 27.0
assert np.array_equal(f2.grad, np.array([56.66253179403897, 0.]))
def sin(x):
try:
val = np.sin(x.val)
grad = np.cos(x.val) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.sin(x) # if x is a constant
def log(x, base=np.e): # handles ln(x) == log(x) because default base = np.e
try:
val = np.log(x.val) / np.log(base)
grad = (1 / (x.val * np.log(base))) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.log(x) / np.log(base)
def exp(x):
try:
val = np.exp(x.val)
grad = np.exp(x.val) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.exp(x)
def arctan(x):
try:
val = np.arctan(x.val)
grad = ((1 + x.val**2)**(-2)) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.arctan(x) # if x is a constant
def arccos(x):
try:
val = np.arccos(x.val)
grad = -((1 - x.val**2)**(-0.5)) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.arccos(x)
def tan(x):
try:
val = np.tan(x.val)
grad = ((np.cos(x.val))**(-2)) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.tan(x)
def cos(x):
try:
val = np.cos(x.val)
grad = -np.sin(x.val) * x.grad
y = CMGobject(val, grad)
return y
except AttributeError:
return np.cos(x)
def test_repr_CMG():
x = CMG(3, np.array([1, 0]))
assert x.__repr__() == 'CMGobject(val = 3.0, grad = [1 0])'