scrupt to generate processed_data for resolution calculation

scripts/scans_rez.py

@@ -0,0 +1,66 @@
+from tavi.data.nxdict import NXdataset, NXentry
+from tavi.data.nxentry import NexusEntry
+from tavi.data.tavi import TAVI
+from tavi.instrument.resolution.cooper_nathans import CN
+from tavi.sample.xtal import Xtal
+
+instrument_config_json_path = "./src/tavi/instrument/instrument_params/cg4c.json"
+tas = CN(SPICE_CONVENTION=False)
+tas.load_instrument_params_from_json(instrument_config_json_path)
+
+sample_json_path = "./test_data/test_samples/nitio3.json"
+sample = Xtal.from_json(sample_json_path)
+tas.mount_sample(sample)
+
+tavi = TAVI()
+tavi.load_spice_data_from_disk("./test_data/exp424")
+
+scan_list = list(range(42, 49, 1)) + list(range(70, 76, 1))
+
+for scan_num in scan_list:
+    scan = tavi.get_scan(scan_num)
+
+    scan_data = scan.get_data(axes=("en", "detector"))
+
+    ei_list = scan.data["ei"]
+    ef_list = scan.data["ef"]
+    qh_list = scan.data["qh"]
+    qk_list = scan.data["qk"]
+    ql_list = scan.data["ql"]
+
+    projection = ((1, 1, 0), (0, 0, 1), (1, -1, 0))
+    R0 = True
+
+    rez_mat_list = []
+    rez_r0_list = []
+
+    for i in range(len(ei_list)):
+
+        rez = tas.cooper_nathans(
+            ei=ei_list[i],
+            ef=ef_list[i],
+            hkl=(qh_list[i], qk_list[i], ql_list[i]),
+            projection=projection,
+            R0=R0,
+        )
+        rez_mat_list.append(rez.mat)
+        rez_r0_list.append(rez.r0)
+
+    rez_entry = NXentry(
+        qh=NXdataset(ds=qh_list),
+        qk=NXdataset(ds=qk_list),
+        ql=NXdataset(ds=ql_list),
+        ei=NXdataset(ds=ei_list),
+        ef=NXdataset(ds=ef_list),
+        detector=NXdataset(ds=scan_data.y),
+        err=NXdataset(ds=scan_data.err),
+        rez_mat=NXdataset(ds=rez_mat_list),
+        rez_r0=NXdataset(ds=rez_r0_list),
+        projection=NXdataset(ds=projection),
+    )
+
+    tavi.processed_data.update(NexusEntry._dict_to_nexus_entry({scan.name: rez_entry}))
+
+
+file_path = "./test_data/tavi_rez.h5"
+tavi.save(file_path)

src/tavi/data/nxentry.py

@@ -250,10 +250,10 @@ def to_nexus(self, path_to_nexus: str, name="scan") -> None:
                         scan_grp_data[def_x].attrs["target"] = path_x
 
             # Create the ATTRIBUTES
-            scan_grp.attrs["file_name"] = os.path.abspath(path_to_nexus)
-            scan_grp.attrs["file_time"] = datetime.now().isoformat()
-            scan_grp.attrs["h5py_version"] = h5py.version.version
-            scan_grp.attrs["HDF5_Version"] = h5py.version.hdf5_version
+            nexus_file.attrs["file_name"] = os.path.abspath(path_to_nexus)
+            nexus_file.attrs["file_time"] = datetime.now().isoformat()
+            nexus_file.attrs["h5py_version"] = h5py.version.version
+            nexus_file.attrs["HDF5_Version"] = h5py.version.hdf5_version
 
     def get(self, key, ATTRS=False, default=None):
         """
@@ -273,8 +273,15 @@ def get(self, key, ATTRS=False, default=None):
         for log in ("SPICElogs", "DASlogs"):
             if log in self.keys():
                 self.pop(log)
+
+        # special treatment for annoying cases!!!
         if (key == "detector") and (not ATTRS):
             key = "detector/data"
+        if (key == "monitor") and (not ATTRS):
+            key = "monitor/monitor"
+        if (key == "sample") and (not ATTRS):
+            key = "sample/sample"
+
         value = NexusEntry._getitem_recursively(self, key, ATTRS)
 
         return value if value is not None else default

src/tavi/data/tavi.py

@@ -130,6 +130,10 @@ def save(self, file_path: Optional[str] = None):
                         nxentry.to_nexus(file_path, name=name)
                 # TODO save pdata, fits and plots
                 grp_pdata = root.create_group("processed_data", track_order=True)
+                for entry_name, nxentry in self.processed_data.items():
+                    name = f"processed_data/{entry_name}"
+                    nxentry.to_nexus(file_path, name=name)
+
                 grp_fits = root.create_group("fits", track_order=True)
                 grp_plots = root.create_group("plots", track_order=True)
         except OSError: