added flat_targets

Author: lfarv

pyat/at/latticetools/observablelist.py

@@ -651,6 +651,26 @@ def get_sum_residuals(self, *obsid: str | int, err: float | None = None) -> floa
         """
         return sum(np.sum(res) for res in self._collect("residual", *obsid, err=err))
 
+    def get_targets(self, *obsid: str | int, err: float | None = None) -> tuple:
+        """Return the target values of observables.
+
+        Args:
+            *obsid: name or index of selected observables (Default all)
+            err:    Default observable value to be used when the evaluation failed. By
+                default, an Exception is raised.
+        """
+        return self._collect("target", *obsid)
+
+    def get_flat_targets(self, *obsid: str | int) -> tuple:
+        """Return a 1-D array of target values of observables.
+
+        Args:
+            *obsid: name or index of selected observables (Default all)
+            err:    Default observable value to be used when the evaluation failed. By
+              default, an Exception is raised.
+        """
+        return _flatten(self._collect("target", *obsid))
+
     shapes = property(get_shapes, doc="Shapes of all values")
     flat_shape = property(get_flat_shape, doc="Shape of the flattened values")
     values = property(get_values, doc="values of all observables")
@@ -675,3 +695,5 @@ def get_sum_residuals(self, *obsid: str | int, err: float | None = None) -> floa
     flat_weights = property(get_flat_weights, doc="1-D array of Observable weights")
     residuals = property(get_residuals, doc="Residuals of all observable")
     sum_residuals = property(get_sum_residuals, doc="Sum of all residual values")
+    targets = property(get_targets, doc="Target values of all observables")
+    flat_targets = property(get_flat_targets, doc="1-D array of target values")

pyat/at/latticetools/response_matrix.py

@@ -366,19 +366,19 @@ def correction_matrix(self, nvals: int | None = None) -> FloatArray:
         return cormat
 
     def get_correction(
-        self, observed: FloatArray, nvals: int | None = None
+        self, deviation: FloatArray, nvals: int | None = None
     ) -> FloatArray:
         """Compute the correction of the given observation.
 
         Args:
-            observed:   Vector of observed deviations,
+            deviation:  Vector of observed deviations,
             nvals:      Desired number of singular values. If :py:obj:`None`, use
               all singular values
 
         Returns:
             corr:       Correction vector
         """
-        return -self.correction_matrix(nvals=nvals) @ observed
+        return -self.correction_matrix(nvals=nvals) @ deviation
 
     def save(self, file) -> None:
         """Save a response matrix in the NumPy .npy format.
@@ -513,12 +513,12 @@ def correct(
         for it, nv in zip(range(niter), np.broadcast_to(nvals, (niter,))):
             print(f"step {it + 1}, nvals = {nv}")
             obs.evaluate(ring, **self._eval_args)
-            err = obs.flat_deviations
-            if np.any(np.isnan(err)):
+            deviation = obs.flat_deviations
+            if np.any(np.isnan(deviation)):
                 raise AtError(
                     f"Step {it + 1}: Invalid observables, cannot compute correction"
                 )
-            corr = self.get_correction(obs.flat_deviations, nvals=nv)
+            corr = self.get_correction(deviation, nvals=nv)
             sumcorr = sumcorr + corr  # non-broadcastable sumcorr
             if apply:
                 self.variables.increment(corr, ring=ring)