Fix bug in shift inversion methods

Convergence criterion was excluding margins even though those points were actually valid.

lisainstrument/shift_inversion_dask.py

@@ -76,7 +76,7 @@ class ShiftInverseDask:
             )
 
         def f_err(x1: NumpyArray1D, x2: NumpyArray1D) -> float:
-            return np.max(np.abs(x1 - x2)[self.margin_left : -self.margin_right])
+            return np.max(np.abs(x1 - x2))
 
         return fixed_point_iter(
             f_iter, f_err, make_numpy_array_1d(dx), tol, self._max_iter

lisainstrument/shift_inversion_numpy.py

@@ -129,7 +129,7 @@ class ShiftInverseNumpy:  # pylint: disable=too-few-public-methods
             return self._interp_np.apply_shift(dx_pad, -x, self.margin_left)
 
         def f_err(x1: NumpyArray1D, x2: NumpyArray1D) -> float:
-            return np.max(np.abs(x1 - x2)[self.margin_left : -self.margin_right])
+            return np.max(np.abs(x1 - x2))
 
         shift_idx_inv = fixed_point_iter(
             f_iter, f_err, dx, self._tolerance * fsample, self._max_iter