diff --git a/src/dials/algorithms/indexing/bravais_settings.py b/src/dials/algorithms/indexing/bravais_settings.py
index 07d08f3273..b32e028e50 100644
--- a/src/dials/algorithms/indexing/bravais_settings.py
+++ b/src/dials/algorithms/indexing/bravais_settings.py
@@ -111,6 +111,7 @@ def as_dict(self):
                 "rmsd": item.rmsd,
                 "nspots": item.Nmatches,
                 "bravais": item["bravais"],
+                "volume": uc.volume(),
                 "unit_cell": uc.parameters(),
                 "cb_op": str(item["cb_op_inp_best"] * self.cb_op_to_primitive),
                 "max_cc": item.max_cc,
diff --git a/src/dials/algorithms/indexing/indexer.py b/src/dials/algorithms/indexing/indexer.py
index 574f39f0af..ba23c5c072 100644
--- a/src/dials/algorithms/indexing/indexer.py
+++ b/src/dials/algorithms/indexing/indexer.py
@@ -907,6 +907,8 @@ def refine(self, experiments, reflections):
         predicted = refiner.predict_for_indexed()
         reflections["xyzcal.mm"] = predicted["xyzcal.mm"]
         reflections["entering"] = predicted["entering"]
+        if "wavelength_cal" in predicted:
+            reflections["wavelength_cal"] = predicted["wavelength_cal"]
         reflections.unset_flags(
             flex.bool(len(reflections), True), reflections.flags.centroid_outlier
         )
diff --git a/src/dials/algorithms/refinement/refiner.py b/src/dials/algorithms/refinement/refiner.py
index 0ffcbaa42f..afe4e633d8 100644
--- a/src/dials/algorithms/refinement/refiner.py
+++ b/src/dials/algorithms/refinement/refiner.py
@@ -247,6 +247,7 @@ def _filter_reflections(reflections):
             "shoebox",
             "delpsical.weights",
             "wavelength",
+            "wavelength_cal",
             "tof",
             "s0",
         ]
diff --git a/src/dials/array_family/flex_ext.py b/src/dials/array_family/flex_ext.py
index 541109906d..2435d183e1 100644
--- a/src/dials/array_family/flex_ext.py
+++ b/src/dials/array_family/flex_ext.py
@@ -1065,8 +1065,7 @@ def contains_tof_data(self):
 
     def get_pixel_bbox_centroid_positions(
         self, panel: int, pixel_pos: Tuple[int, int]
-    ) -> Tuple[list, list, list]:
-
+    ) -> Tuple[list, list, list, list]:
         """
         Finds any bounding boxes within px and py on panel
         and returns their pz positions along with
@@ -1080,11 +1079,16 @@ def get_pixel_bbox_centroid_positions(
             centroids = self["xyzobs.px.value"].select(sel)
         else:
             centroids = None
+        if "miller_index" in self:
+            miller_indices = self["miller_index"].select(sel)
+        else:
+            miller_indices = None
         py = int(pixel_pos[0])
         px = int(pixel_pos[1])
         bbox_pos = []
         centroid_pos = []
         refl_ids = []
+        selected_miller_indices = []
         for i in range(len(x0)):
             if px >= x0[i] and px <= x1[i]:
                 if py >= y0[i] and py <= y1[i]:
@@ -1095,7 +1099,12 @@ def get_pixel_bbox_centroid_positions(
                         ci = centroids[i][2]
                         x, y = z0[i], z1[i]
                         assert ci >= x and ci <= y, f"{ci} {x} {y}"
-        return bbox_pos, centroid_pos, refl_ids
+                    if miller_indices:
+                        selected_miller_indices.append(miller_indices[i])
+                    else:
+                        selected_miller_indices.append((0, 0, 0))
+
+        return bbox_pos, centroid_pos, refl_ids, selected_miller_indices
 
     def find_overlaps(self, experiments=None, border=0):
         """
@@ -1337,7 +1346,6 @@ def centroid_px_to_mm(self, experiments):
                 self["xyzobs.mm.variance"].set_selected(sel, centroid_variance)
 
     def add_beam_data(self, experiments):
-
         """
         Adds wavelength, tof, s0, and unit_s0 columns to self.
         All experiments with a TOFSequence have values set from their time-of-flight.
@@ -1519,10 +1527,7 @@ def map_centroids_to_reciprocal_space(
                 if self.contains_beam_data():
                     import numpy as np
 
-                    if calculated:
-                        wavelengths = self["wavelength_cal"].select(sel)
-                    else:
-                        wavelengths = self["wavelength"].select(sel)
+                    wavelengths = self["wavelength"].select(sel)
                     S = cctbx.array_family.flex.vec3_double(len(s1))
                     s1 = s1 / s1.norms()
                     for s1_idx in range(len(s1)):
diff --git a/src/dials/command_line/simple_tof_integrate.py b/src/dials/command_line/simple_tof_integrate.py
index 0a271365a0..8af38c39fa 100644
--- a/src/dials/command_line/simple_tof_integrate.py
+++ b/src/dials/command_line/simple_tof_integrate.py
@@ -531,6 +531,8 @@ def run_simple_integrate(params, experiments, reflections):
     )
     sel = predicted_reflections.get_flags(predicted_reflections.flags.reference_spot)
     predicted_reflections = predicted_reflections.select(sel)
+    if "idx" in reflections:
+        predicted_reflections["idx"] = reflections["idx"]
 
     """
     Create profile model and add it to erperiment.