Remove copy_and_sanitize_non_cal_data from AgipdCorrections

src/cal_tools/agipdlib.py

@@ -1272,72 +1272,6 @@ class AgipdCorrections:
 
         return n_img_sel
 
-    def copy_and_sanitize_non_cal_data(self, infile, outfile, agipd_base,
-                                       idx_base, trains):
-        """ Copy and sanitize data in `infile` that is not touched by
-        `correctAGIPD`
-        """
-        # these are touched in the correct function, do not copy them here
-        dont_copy = ["data", "cellId", "trainId", "pulseId", "status",
-                     "length"]
-        dont_copy = [posixpath.join(agipd_base, "image", ds)
-                     for ds in dont_copy]
-
-        # don't copy index as we may need to adjust if we filter trains
-        dont_copy.append(posixpath.join(idx_base, "image"))
-
-        h5_copy_except_paths(infile, outfile, dont_copy)
-
-        # sanitize indices
-        for do in ["image", ]:
-            # uq: INDEX/trainID
-            # fidxv: INDEX/.../image/first idx values
-            # cntsv: INDEX/.../image/counts values
-
-            # Extract parameters through identifying
-            # unique trains, index and numbers.
-            uq, fidxv, cntsv = np.unique(trains, return_index=True, return_counts=True)  # noqa
-
-            # Validate calculated CORR INDEX contents by checking
-            # difference between trainId stored in RAW data and trains from
-            train_diff = np.isin(np.array(infile["/INDEX/trainId"]), uq, invert=True)  # noqa
-
-            # Insert zeros for missing trains.
-            # fidxv and cntsv should have same length as
-            # raw INDEX/.../image/first and INDEX/.../image/count,
-            # respectively
-
-            # first_inc = first incrementation
-            first_inc = True
-            for i, diff in enumerate(train_diff):
-                if diff:
-                    if i < len(cntsv):
-                        cntsv = np.insert(cntsv, i, 0)
-                        fidxv = np.insert(fidxv, i, 0) if i == 0 else np.insert(fidxv, i, fidxv[i])
-                    else:
-                        # append if at the end of the array
-                        cntsv = np.append(cntsv, 0)
-                        # increment fidxv once with the
-                        # no. of processed mem-cells.
-                        if first_inc:
-                            fidxv = np.append(fidxv,
-                                              (2 * fidxv[i-1]) - fidxv[i-2])
-                            first_inc = False
-                        else:
-                            fidxv = np.append(fidxv, fidxv[i-1])
-
-            # save INDEX contents (first, count) in CORR files
-            outfile.create_dataset(idx_base + "{}/first".format(do),
-                                   fidxv.shape,
-                                   dtype=fidxv.dtype,
-                                   data=fidxv,
-                                   fletcher32=True)
-            outfile.create_dataset(idx_base + "{}/count".format(do),
-                                   cntsv.shape,
-                                   dtype=cntsv.dtype,
-                                   data=cntsv,
-                                   fletcher32=True)
-
     def init_constants(
         self, cons_data: dict, module_idx: int, variant: dict):
         """