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Fix RMSE gradient #355

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merged 3 commits into from
Jun 10, 2024
Merged

Fix RMSE gradient #355

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301599f
Update RMSE gradient
NicolaCourtier Jun 10, 2024
64767fd
Update test value
NicolaCourtier Jun 10, 2024
046946c
Update CHANGELOG.md
NicolaCourtier Jun 10, 2024
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4 changes: 1 addition & 3 deletions pybop/costs/fitting_costs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,9 +89,7 @@ def _evaluateS1(self, x):

r = np.array([y[signal] - self._target[signal] for signal in self.signal])
e = np.sqrt(np.mean(r**2, axis=1))
de = np.mean((r * dy.T), axis=2) / (
np.sqrt(np.mean((r * dy.T) ** 2, axis=2)) + np.finfo(float).eps
)
de = np.mean((r * dy.T), axis=2) / (e + np.finfo(float).eps)

if self.n_outputs == 1:
return e.item(), de.flatten()
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2 changes: 1 addition & 1 deletion tests/unit/test_standalone.py
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Expand Up @@ -75,7 +75,7 @@ def test_standalone_problem(self):
rmse_grad_x = rmse_cost.evaluateS1([1, 2])

np.testing.assert_allclose(rmse_x, 3.05615, atol=1e-2)
np.testing.assert_allclose(rmse_grad_x[1], [-0.81758337, 0.0], atol=1e-2)
np.testing.assert_allclose(rmse_grad_x[1], [-0.54645, 0.0], atol=1e-2)

# Test the sensitivities
sums_cost = pybop.SumSquaredError(problem)
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