hRIXS: Use xarray.values instead of .to_numpy()

The new Toolbox environment script uses the XFEL environment, which has an older version of xarray.

This MR fixes the compatibility of the hRIXS code on the said version.

(this is also already deployed in the 3078 environment, please be aware of similar calls in the notebook)

@teichman @merzoni

src/toolbox_scs/detectors/hrixs.py

@@ -331,7 +331,7 @@ class hRIXS:
         data = self.from_run(runNB, proposal)
 
         image = data['hRIXS_det'].sum(dim='trainId') \
-                .to_numpy()[self.X_RANGE, self.Y_RANGE].T
+                .values[self.X_RANGE, self.Y_RANGE].T
         if args is None:
             spec = (image - image[:10, :].mean()).mean(axis=1)
             mean = np.average(np.arange(len(spec)), weights=spec)
@@ -347,7 +347,7 @@ class hRIXS:
         ret = np.zeros((len(data["hRIXS_det"]), bins))
         for image, r in zip(data["hRIXS_det"], ret):
             c = centroid(
-                image.to_numpy()[self.X_RANGE, self.Y_RANGE].T,
+                image.values[self.X_RANGE, self.Y_RANGE].T,
                 threshold=self.THRESHOLD,
                 std_threshold=self.STD_THRESHOLD,
                 curvature=(self.CURVE_A, self.CURVE_B))
@@ -370,7 +370,7 @@ class hRIXS:
         for image, r in zip(data["hRIXS_det"], ret):
             if self.USE_DARK:
                 image = image - self.dark_image
-            r[:] = integrate(image.to_numpy()[self.X_RANGE, self.Y_RANGE].T, factor=1,
+            r[:] = integrate(image.values[self.X_RANGE, self.Y_RANGE].T, factor=1,
                              range=(10, bins - 10),
                              curvature=(self.CURVE_A, self.CURVE_B))
         data = data.assign_coords(