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Fix compute_gradient to include frozen parameters #156

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Fix compute_gradient to include frozen parameters #156

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f5427bf
Add test case for shape error when no user gradient
mcfarljm Nov 23, 2022
f28f50e
Fix compute_gradient to include frozen parameters
mcfarljm Nov 23, 2022
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6 changes: 3 additions & 3 deletions src/george/modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,15 +115,15 @@ def compute_gradient(self, *args, **kwargs):

"""
_EPS = 1.254e-5
vector = self.get_parameter_vector()
vector = self.get_parameter_vector(include_frozen=True)
value0 = self.get_value(*args, **kwargs)
grad = np.empty([len(vector)] + list(value0.shape), dtype=np.float64)
for i, v in enumerate(vector):
vector[i] = v + _EPS
self.set_parameter_vector(vector)
self.set_parameter_vector(vector, include_frozen=True)
value = self.get_value(*args, **kwargs)
vector[i] = v
self.set_parameter_vector(vector)
self.set_parameter_vector(vector, include_frozen=True)
grad[i] = (value - value0) / _EPS
return grad

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21 changes: 21 additions & 0 deletions tests/test_modeling.py
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Expand Up @@ -72,6 +72,13 @@ def compute_gradient(self, x):
return dict(m=x, b=np.ones(len(x)))


class LinearWhiteNoiseWithoutGrad(Model):
parameter_names = ("m", "b")

def get_value(self, x):
return self.m * x + self.b


def test_gp_callable_white_noise(N=50, seed=1234):
np.random.seed(seed)
x = np.random.uniform(0, 5)
Expand All @@ -86,6 +93,20 @@ def test_gp_callable_white_noise(N=50, seed=1234):
check_gradient(gp, y)


def test_gp_callable_white_noise_without_grad(N=50, seed=1234):
np.random.seed(seed)
x = np.random.uniform(0, 5)
y = 5 + np.sin(x)
gp = GP(10. * kernels.ExpSquaredKernel(1.3), mean=5.0,
white_noise=LinearWhiteNoiseWithoutGrad(-6, 0.01),
fit_white_noise=True)
gp.compute(x)
check_gradient(gp, y)

gp.freeze_parameter("white_noise:m")
check_gradient(gp, y)


def test_parameters():
kernel = 10 * kernels.ExpSquaredKernel(1.0)
kernel += 0.5 * kernels.RationalQuadraticKernel(log_alpha=0.1, metric=5.0)
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