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Redefine residual as d_pred - d_obs #65

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Merged
santisoler merged 1 commit into from
Oct 27, 2025
Merged

Redefine residual as d_pred - d_obs #65

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6 changes: 3 additions & 3 deletions src/inversion_ideas/data_misfit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,7 +109,7 @@ def gradient(self, model: Model) -> npt.NDArray[np.float64]:
"""
jac = self.simulation.jacobian(model)
weights_matrix = self.weights_matrix
return -2 * jac.T @ (weights_matrix.T @ weights_matrix @ self.residual(model))
return 2 * jac.T @ (weights_matrix.T @ weights_matrix @ self.residual(model))

def hessian(
self, model: Model
Expand Down Expand Up @@ -171,12 +171,12 @@ def residual(self, model: Model):

.. math::

\mathbf{r} = \mathbf{d} - \mathcal{F}(\mathbf{m})
\mathbf{r} = \mathcal{F}(\mathbf{m}) - \mathbf{d}

where :math:`\mathbf{d}` is the vector with observed data, :math:`\mathcal{F}`
is the forward model, and :math:`\mathbf{m}` is the model vector.
"""
return self.data - self.simulation(model)
return self.simulation(model) - self.data

@property
def weights(self) -> npt.NDArray[np.float64]:
Expand Down