diff --git a/pyzebra/app/panel_ccl_compare.py b/pyzebra/app/panel_ccl_compare.py
index 481fddd..a21e225 100644
--- a/pyzebra/app/panel_ccl_compare.py
+++ b/pyzebra/app/panel_ccl_compare.py
@@ -72,8 +72,8 @@ for (let i = 0; i < js_data.data['fname'].length; i++) {
 
 def create():
     doc = curdoc()
-    det_data1 = []
-    det_data2 = []
+    dataset1 = []
+    dataset2 = []
     fit_params = {}
     js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
 
@@ -99,17 +99,17 @@ def create():
     proposal_textinput.on_change("name", proposal_textinput_callback)
 
     def _init_datatable():
-        # det_data2 should have the same metadata to det_data1
-        scan_list = [s["idx"] for s in det_data1]
-        hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in det_data1]
-        export = [s["export"] for s in det_data1]
+        # dataset2 should have the same metadata as dataset1
+        scan_list = [s["idx"] for s in dataset1]
+        hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in dataset1]
+        export = [s["export"] for s in dataset1]
 
-        twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in det_data1]
-        gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in det_data1]
-        omega = [np.median(s["omega"]) if "omega" in s else None for s in det_data1]
-        chi = [np.median(s["chi"]) if "chi" in s else None for s in det_data1]
-        phi = [np.median(s["phi"]) if "phi" in s else None for s in det_data1]
-        nu = [np.median(s["nu"]) if "nu" in s else None for s in det_data1]
+        twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in dataset1]
+        gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in dataset1]
+        omega = [np.median(s["omega"]) if "omega" in s else None for s in dataset1]
+        chi = [np.median(s["chi"]) if "chi" in s else None for s in dataset1]
+        phi = [np.median(s["phi"]) if "phi" in s else None for s in dataset1]
+        nu = [np.median(s["nu"]) if "nu" in s else None for s in dataset1]
 
         scan_table_source.data.update(
             scan=scan_list,
@@ -163,9 +163,9 @@ def create():
         new_data1 = new_data1[:min_len]
         new_data2 = new_data2[:min_len]
 
-        nonlocal det_data1, det_data2
-        det_data1 = new_data1
-        det_data2 = new_data2
+        nonlocal dataset1, dataset2
+        dataset1 = new_data1
+        dataset2 = new_data2
         _init_datatable()
 
     file_open_button = Button(label="Open New", width=100, disabled=True)
@@ -201,9 +201,9 @@ def create():
         new_data1 = new_data1[:min_len]
         new_data2 = new_data2[:min_len]
 
-        nonlocal det_data1, det_data2
-        det_data1 = new_data1
-        det_data2 = new_data2
+        nonlocal dataset1, dataset2
+        dataset1 = new_data1
+        dataset2 = new_data2
         _init_datatable()
 
     upload_div = Div(text="or upload 2 .ccl files:", margin=(5, 5, 0, 5))
@@ -213,17 +213,17 @@ def create():
     upload_button.on_change("filename", upload_button_callback)
 
     def monitor_spinner_callback(_attr, old, new):
-        if det_data1 and det_data2:
-            pyzebra.normalize_dataset(det_data1, new)
-            pyzebra.normalize_dataset(det_data2, new)
+        if dataset1 and dataset2:
+            pyzebra.normalize_dataset(dataset1, new)
+            pyzebra.normalize_dataset(dataset2, new)
             _update_plot()
 
     monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145)
     monitor_spinner.on_change("value", monitor_spinner_callback)
 
     def _update_table():
-        fit_ok = [(1 if "fit" in scan else 0) for scan in det_data1]
-        export = [scan["export"] for scan in det_data1]
+        fit_ok = [(1 if "fit" in scan else 0) for scan in dataset1]
+        export = [scan["export"] for scan in dataset1]
         scan_table_source.data.update(fit=fit_ok, export=export)
 
     def _update_plot():
@@ -382,7 +382,7 @@ def create():
     def scan_table_source_callback(_attr, _old, new):
         # unfortunately, we don't know if the change comes from data update or user input
         # also `old` and `new` are the same for non-scalars
-        for scan1, scan2, export in zip(det_data1, det_data2, new["export"]):
+        for scan1, scan2, export in zip(dataset1, dataset2, new["export"]):
             scan1["export"] = export
             scan2["export"] = export
         _update_preview()
@@ -426,14 +426,14 @@ def create():
 
     def _get_selected_scan():
         ind = scan_table_source.selected.indices[0]
-        return det_data1[ind], det_data2[ind]
+        return dataset1[ind], dataset2[ind]
 
     merge_from_select = Select(title="scan:", width=145)
 
     def merge_button_callback():
         scan_into1, scan_into2 = _get_selected_scan()
-        scan_from1 = det_data1[int(merge_from_select.value)]
-        scan_from2 = det_data2[int(merge_from_select.value)]
+        scan_from1 = dataset1[int(merge_from_select.value)]
+        scan_from2 = dataset2[int(merge_from_select.value)]
 
         if scan_into1 is scan_from1:
             print("WARNING: Selected scans for merging are identical")
@@ -577,7 +577,7 @@ def create():
     fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in [*det_data1, *det_data2]:
+        for scan in [*dataset1, *dataset2]:
             if scan["export"]:
                 pyzebra.fit_scan(
                     scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@@ -628,7 +628,7 @@ def create():
             temp_file = temp_dir + "/temp"
             export_data1 = []
             export_data2 = []
-            for scan1, scan2 in zip(det_data1, det_data2):
+            for scan1, scan2 in zip(dataset1, dataset2):
                 if scan1["export"]:
                     export_data1.append(scan1)
                     export_data2.append(scan2)
diff --git a/pyzebra/app/panel_ccl_integrate.py b/pyzebra/app/panel_ccl_integrate.py
index ef8d54d..d70ca43 100644
--- a/pyzebra/app/panel_ccl_integrate.py
+++ b/pyzebra/app/panel_ccl_integrate.py
@@ -72,7 +72,7 @@ for (let i = 0; i < js_data.data['fname'].length; i++) {
 
 def create():
     doc = curdoc()
-    det_data = []
+    dataset = []
     fit_params = {}
     js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
 
@@ -100,16 +100,16 @@ def create():
     proposal_textinput.on_change("name", proposal_textinput_callback)
 
     def _init_datatable():
-        scan_list = [s["idx"] for s in det_data]
-        hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in det_data]
-        export = [s["export"] for s in det_data]
+        scan_list = [s["idx"] for s in dataset]
+        hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in dataset]
+        export = [s["export"] for s in dataset]
 
-        twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in det_data]
-        gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in det_data]
-        omega = [np.median(s["omega"]) if "omega" in s else None for s in det_data]
-        chi = [np.median(s["chi"]) if "chi" in s else None for s in det_data]
-        phi = [np.median(s["phi"]) if "phi" in s else None for s in det_data]
-        nu = [np.median(s["nu"]) if "nu" in s else None for s in det_data]
+        twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in dataset]
+        gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in dataset]
+        omega = [np.median(s["omega"]) if "omega" in s else None for s in dataset]
+        chi = [np.median(s["chi"]) if "chi" in s else None for s in dataset]
+        phi = [np.median(s["phi"]) if "phi" in s else None for s in dataset]
+        nu = [np.median(s["nu"]) if "nu" in s else None for s in dataset]
 
         scan_table_source.data.update(
             scan=scan_list,
@@ -133,7 +133,7 @@ def create():
     file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250)
 
     def file_open_button_callback():
-        nonlocal det_data
+        nonlocal dataset
         new_data = []
         for f_path in file_select.value:
             with open(f_path) as file:
@@ -155,7 +155,7 @@ def create():
                 pyzebra.merge_datasets(new_data, file_data)
 
         if new_data:
-            det_data = new_data
+            dataset = new_data
             _init_datatable()
             append_upload_button.disabled = False
 
@@ -175,7 +175,7 @@ def create():
                     continue
 
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
-            pyzebra.merge_datasets(det_data, file_data)
+            pyzebra.merge_datasets(dataset, file_data)
 
         if file_data:
             _init_datatable()
@@ -184,7 +184,7 @@ def create():
     file_append_button.on_click(file_append_button_callback)
 
     def upload_button_callback(_attr, _old, _new):
-        nonlocal det_data
+        nonlocal dataset
         new_data = []
         for f_str, f_name in zip(upload_button.value, upload_button.filename):
             with io.StringIO(base64.b64decode(f_str).decode()) as file:
@@ -205,7 +205,7 @@ def create():
                 pyzebra.merge_datasets(new_data, file_data)
 
         if new_data:
-            det_data = new_data
+            dataset = new_data
             _init_datatable()
             append_upload_button.disabled = False
 
@@ -227,7 +227,7 @@ def create():
                     continue
 
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
-            pyzebra.merge_datasets(det_data, file_data)
+            pyzebra.merge_datasets(dataset, file_data)
 
         if file_data:
             _init_datatable()
@@ -239,16 +239,16 @@ def create():
     append_upload_button.on_change("filename", append_upload_button_callback)
 
     def monitor_spinner_callback(_attr, old, new):
-        if det_data:
-            pyzebra.normalize_dataset(det_data, new)
+        if dataset:
+            pyzebra.normalize_dataset(dataset, new)
             _update_plot()
 
     monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145)
     monitor_spinner.on_change("value", monitor_spinner_callback)
 
     def _update_table():
-        fit_ok = [(1 if "fit" in scan else 0) for scan in det_data]
-        export = [scan["export"] for scan in det_data]
+        fit_ok = [(1 if "fit" in scan else 0) for scan in dataset]
+        export = [scan["export"] for scan in dataset]
         scan_table_source.data.update(fit=fit_ok, export=export)
 
     def _update_plot():
@@ -368,7 +368,7 @@ def create():
     def scan_table_source_callback(_attr, _old, new):
         # unfortunately, we don't know if the change comes from data update or user input
         # also `old` and `new` are the same for non-scalars
-        for scan, export in zip(det_data, new["export"]):
+        for scan, export in zip(dataset, new["export"]):
             scan["export"] = export
         _update_preview()
 
@@ -410,13 +410,13 @@ def create():
     )
 
     def _get_selected_scan():
-        return det_data[scan_table_source.selected.indices[0]]
+        return dataset[scan_table_source.selected.indices[0]]
 
     merge_from_select = Select(title="scan:", width=145)
 
     def merge_button_callback():
         scan_into = _get_selected_scan()
-        scan_from = det_data[int(merge_from_select.value)]
+        scan_from = dataset[int(merge_from_select.value)]
 
         if scan_into is scan_from:
             print("WARNING: Selected scans for merging are identical")
@@ -557,7 +557,7 @@ def create():
     fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in det_data:
+        for scan in dataset:
             if scan["export"]:
                 pyzebra.fit_scan(
                     scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@@ -602,7 +602,7 @@ def create():
         with tempfile.TemporaryDirectory() as temp_dir:
             temp_file = temp_dir + "/temp"
             export_data = []
-            for scan in det_data:
+            for scan in dataset:
                 if scan["export"]:
                     export_data.append(scan)
 
diff --git a/pyzebra/app/panel_hdf_param_study.py b/pyzebra/app/panel_hdf_param_study.py
index 960663a..bfe3cd8 100644
--- a/pyzebra/app/panel_hdf_param_study.py
+++ b/pyzebra/app/panel_hdf_param_study.py
@@ -48,8 +48,7 @@ IMAGE_PLOT_H = int(IMAGE_H * 2) + 27
 
 def create():
     doc = curdoc()
-    zebra_data = []
-    det_data = {}
+    dataset = []
     cami_meta = {}
 
     num_formatter = NumberFormatter(format="0.00", nan_format="")
@@ -108,15 +107,15 @@ def create():
 
     def _init_datatable():
         file_list = []
-        for scan in zebra_data:
+        for scan in dataset:
             file_list.append(os.path.basename(scan["original_filename"]))
 
         scan_table_source.data.update(
             file=file_list,
-            param=[None] * len(zebra_data),
-            frame=[None] * len(zebra_data),
-            x_pos=[None] * len(zebra_data),
-            y_pos=[None] * len(zebra_data),
+            param=[None] * len(dataset),
+            frame=[None] * len(dataset),
+            x_pos=[None] * len(dataset),
+            y_pos=[None] * len(dataset),
         )
         scan_table_source.selected.indices = []
         scan_table_source.selected.indices = [0]
@@ -127,7 +126,7 @@ def create():
         frame = []
         x_pos = []
         y_pos = []
-        for scan in zebra_data:
+        for scan in dataset:
             if "fit" in scan:
                 framei = scan["fit"]["frame"]
                 x_posi = scan["fit"]["x_pos"]
@@ -150,13 +149,13 @@ def create():
                 print("Could not read data from the file.")
                 return
 
-        zebra_data.extend(new_data)
+        dataset.extend(new_data)
 
         _init_datatable()
 
     def file_open_button_callback():
-        nonlocal zebra_data
-        zebra_data = []
+        nonlocal dataset
+        dataset = []
         _file_open()
 
     file_open_button = Button(label="Open New", width=100)
@@ -170,8 +169,6 @@ def create():
 
     # Scan select
     def scan_table_select_callback(_attr, old, new):
-        nonlocal det_data
-
         if not new:
             # skip empty selections
             return
@@ -186,21 +183,21 @@ def create():
             # skip unnecessary update caused by selection drop
             return
 
-        det_data = zebra_data[new[0]]
+        scan = dataset[new[0]]
 
-        zebra_mode = det_data["zebra_mode"]
+        zebra_mode = scan["zebra_mode"]
         if zebra_mode == "nb":
             metadata_table_source.data.update(geom=["normal beam"])
         else:  # zebra_mode == "bi"
             metadata_table_source.data.update(geom=["bisecting"])
 
-        if "mf" in det_data:
-            metadata_table_source.data.update(mf=[det_data["mf"][0]])
+        if "mf" in scan:
+            metadata_table_source.data.update(mf=[scan["mf"][0]])
         else:
             metadata_table_source.data.update(mf=[None])
 
-        if "temp" in det_data:
-            metadata_table_source.data.update(temp=[det_data["temp"][0]])
+        if "temp" in scan:
+            metadata_table_source.data.update(temp=[scan["temp"][0]])
         else:
             metadata_table_source.data.update(temp=[None])
 
@@ -240,12 +237,15 @@ def create():
         autosize_mode="none",
     )
 
+    def _get_selected_scan():
+        return dataset[scan_table_source.selected.indices[0]]
+
     def param_select_callback(_attr, _old, new):
         if new == "user defined":
-            param = [None] * len(zebra_data)
+            param = [None] * len(dataset)
         else:
             # TODO: which value to take?
-            param = [scan[new][0] for scan in zebra_data]
+            param = [scan[new][0] for scan in dataset]
 
         scan_table_source.data["param"] = param
         _update_param_plot()
@@ -259,7 +259,8 @@ def create():
     param_select.on_change("value", param_select_callback)
 
     def update_overview_plot():
-        h5_data = det_data["data"]
+        scan = _get_selected_scan()
+        h5_data = scan["data"]
         n_im, n_y, n_x = h5_data.shape
         overview_x = np.mean(h5_data, axis=1)
         overview_y = np.mean(h5_data, axis=2)
@@ -290,10 +291,10 @@ def create():
         frame_range.reset_end = n_im
         frame_range.bounds = (0, n_im)
 
-        scan_motor = det_data["scan_motor"]
+        scan_motor = scan["scan_motor"]
         overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}"
 
-        var = det_data[scan_motor]
+        var = scan[scan_motor]
         var_start = var[0]
         var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1)
 
@@ -470,7 +471,7 @@ def create():
         x = []
         y = []
         fit_param = fit_param_select.value
-        for s, p in zip(zebra_data, scan_table_source.data["param"]):
+        for s, p in zip(dataset, scan_table_source.data["param"]):
             if "fit" in s and fit_param:
                 x.append(p)
                 y.append(s["fit"][fit_param])
@@ -498,7 +499,7 @@ def create():
     fit_param_select.on_change("value", fit_param_select_callback)
 
     def proc_all_button_callback():
-        for scan in zebra_data:
+        for scan in dataset:
             pyzebra.fit_event(
                 scan,
                 int(np.floor(frame_range.start)),
@@ -511,7 +512,7 @@ def create():
 
         _update_table()
 
-        for scan in zebra_data:
+        for scan in dataset:
             if "fit" in scan:
                 options = list(scan["fit"].keys())
                 fit_param_select.options = options
@@ -524,8 +525,9 @@ def create():
     proc_all_button.on_click(proc_all_button_callback)
 
     def proc_button_callback():
+        scan = _get_selected_scan()
         pyzebra.fit_event(
-            det_data,
+            scan,
             int(np.floor(frame_range.start)),
             int(np.ceil(frame_range.end)),
             int(np.floor(det_y_range.start)),
@@ -536,7 +538,7 @@ def create():
 
         _update_table()
 
-        for scan in zebra_data:
+        for scan in dataset:
             if "fit" in scan:
                 options = list(scan["fit"].keys())
                 fit_param_select.options = options
diff --git a/pyzebra/app/panel_hdf_viewer.py b/pyzebra/app/panel_hdf_viewer.py
index 3fbfb78..f3b9c72 100644
--- a/pyzebra/app/panel_hdf_viewer.py
+++ b/pyzebra/app/panel_hdf_viewer.py
@@ -52,7 +52,7 @@ IMAGE_PLOT_H = int(IMAGE_H * 2) + 27
 
 def create():
     doc = curdoc()
-    det_data = {}
+    scan = {}
     cami_meta = {}
 
     num_formatter = NumberFormatter(format="0.00", nan_format="")
@@ -108,14 +108,14 @@ def create():
     upload_cami_button.on_change("value", upload_cami_button_callback)
 
     def _file_open(file, cami_meta):
-        nonlocal det_data
+        nonlocal scan
         try:
-            det_data = pyzebra.read_detector_data(file, cami_meta)
+            scan = pyzebra.read_detector_data(file, cami_meta)
         except KeyError:
             print("Could not read data from the file.")
             return
 
-        last_im_index = det_data["data"].shape[0] - 1
+        last_im_index = scan["data"].shape[0] - 1
 
         index_spinner.value = 0
         index_spinner.high = last_im_index
@@ -125,7 +125,7 @@ def create():
             index_slider.disabled = False
             index_slider.end = last_im_index
 
-        zebra_mode = det_data["zebra_mode"]
+        zebra_mode = scan["zebra_mode"]
         if zebra_mode == "nb":
             metadata_table_source.data.update(geom=["normal beam"])
         else:  # zebra_mode == "bi"
@@ -157,7 +157,7 @@ def create():
         if index is None:
             index = index_spinner.value
 
-        current_image = det_data["data"][index]
+        current_image = scan["data"][index]
         proj_v_line_source.data.update(
             x=np.arange(0, IMAGE_W) + 0.5, y=np.mean(current_image, axis=0)
         )
@@ -180,24 +180,24 @@ def create():
             image_glyph.color_mapper.low = im_min
             image_glyph.color_mapper.high = im_max
 
-        if "mf" in det_data:
-            metadata_table_source.data.update(mf=[det_data["mf"][index]])
+        if "mf" in scan:
+            metadata_table_source.data.update(mf=[scan["mf"][index]])
         else:
             metadata_table_source.data.update(mf=[None])
 
-        if "temp" in det_data:
-            metadata_table_source.data.update(temp=[det_data["temp"][index]])
+        if "temp" in scan:
+            metadata_table_source.data.update(temp=[scan["temp"][index]])
         else:
             metadata_table_source.data.update(temp=[None])
 
-        gamma, nu = calculate_pol(det_data, index)
-        omega = np.ones((IMAGE_H, IMAGE_W)) * det_data["omega"][index]
+        gamma, nu = calculate_pol(scan, index)
+        omega = np.ones((IMAGE_H, IMAGE_W)) * scan["omega"][index]
         image_source.data.update(gamma=[gamma], nu=[nu], omega=[omega])
 
         # update detector center angles
         det_c_x = int(IMAGE_W / 2)
         det_c_y = int(IMAGE_H / 2)
-        if det_data["zebra_mode"] == "nb":
+        if scan["zebra_mode"] == "nb":
             gamma_c = gamma[det_c_y, det_c_x]
             nu_c = nu[det_c_y, det_c_x]
             omega_c = omega[det_c_y, det_c_x]
@@ -205,13 +205,13 @@ def create():
             phi_c = None
 
         else:  # zebra_mode == "bi"
-            wave = det_data["wave"]
-            ddist = det_data["ddist"]
-            gammad = det_data["gamma"][index]
-            om = det_data["omega"][index]
-            ch = det_data["chi"][index]
-            ph = det_data["phi"][index]
-            nud = det_data["nu"]
+            wave = scan["wave"]
+            ddist = scan["ddist"]
+            gammad = scan["gamma"][index]
+            om = scan["omega"][index]
+            ch = scan["chi"][index]
+            ph = scan["phi"][index]
+            nud = scan["nu"]
 
             nu_c = 0
             chi_c, phi_c, gamma_c, omega_c = pyzebra.ang_proc(
@@ -223,7 +223,7 @@ def create():
         )
 
     def update_overview_plot():
-        h5_data = det_data["data"]
+        h5_data = scan["data"]
         n_im, n_y, n_x = h5_data.shape
         overview_x = np.mean(h5_data, axis=1)
         overview_y = np.mean(h5_data, axis=2)
@@ -254,10 +254,10 @@ def create():
         frame_range.reset_end = n_im
         frame_range.bounds = (0, n_im)
 
-        scan_motor = det_data["scan_motor"]
+        scan_motor = scan["scan_motor"]
         overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}"
 
-        var = det_data[scan_motor]
+        var = scan[scan_motor]
         var_start = var[0]
         var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1) if n_im != 1 else var_start + 1
 
@@ -374,9 +374,9 @@ def create():
 
     # calculate hkl-indices of first mouse entry
     def mouse_enter_callback(_event):
-        if det_data and np.array_equal(image_source.data["h"][0], np.zeros((1, 1))):
+        if scan and np.array_equal(image_source.data["h"][0], np.zeros((1, 1))):
             index = index_spinner.value
-            h, k, l = calculate_hkl(det_data, index)
+            h, k, l = calculate_hkl(scan, index)
             image_source.data.update(h=[h], k=[k], l=[l])
 
     plot.on_event(MouseEnter, mouse_enter_callback)
@@ -438,7 +438,7 @@ def create():
 
     def box_edit_callback(_attr, _old, new):
         if new["x"]:
-            h5_data = det_data["data"]
+            h5_data = scan["data"]
             x_val = np.arange(h5_data.shape[0])
             left = int(np.floor(new["x"][0]))
             right = int(np.ceil(new["x"][0] + new["width"][0]))
@@ -739,7 +739,7 @@ def create():
 
     def add_event_button_callback():
         pyzebra.fit_event(
-            det_data,
+            scan,
             int(np.floor(frame_range.start)),
             int(np.ceil(frame_range.end)),
             int(np.floor(det_y_range.start)),
@@ -748,21 +748,21 @@ def create():
             int(np.ceil(det_x_range.end)),
         )
 
-        wave = det_data["wave"]
-        ddist = det_data["ddist"]
-        cell = det_data["cell"]
+        wave = scan["wave"]
+        ddist = scan["ddist"]
+        cell = scan["cell"]
 
-        gamma = det_data["gamma"][0]
-        omega = det_data["omega"][0]
-        nu = det_data["nu"][0]
-        chi = det_data["chi"][0]
-        phi = det_data["phi"][0]
+        gamma = scan["gamma"][0]
+        omega = scan["omega"][0]
+        nu = scan["nu"][0]
+        chi = scan["chi"][0]
+        phi = scan["phi"][0]
 
-        scan_motor = det_data["scan_motor"]
-        var_angle = det_data[scan_motor]
+        scan_motor = scan["scan_motor"]
+        var_angle = scan[scan_motor]
 
-        snr_cnts = det_data["fit"]["snr"]
-        frC = det_data["fit"]["frame"]
+        snr_cnts = scan["fit"]["snr"]
+        frC = scan["fit"]["frame"]
 
         var_F = var_angle[int(np.floor(frC))]
         var_C = var_angle[int(np.ceil(frC))]
@@ -781,11 +781,11 @@ def create():
         elif scan_motor == "phi":
             phi = var_p
 
-        intensity = det_data["fit"]["intensity"]
-        x_pos = det_data["fit"]["x_pos"]
-        y_pos = det_data["fit"]["y_pos"]
+        intensity = scan["fit"]["intensity"]
+        x_pos = scan["fit"]["x_pos"]
+        y_pos = scan["fit"]["y_pos"]
 
-        if det_data["zebra_mode"] == "nb":
+        if scan["zebra_mode"] == "nb":
             chi = None
             phi = None
 
@@ -883,22 +883,22 @@ def create():
     return Panel(child=tab_layout, title="hdf viewer")
 
 
-def calculate_hkl(det_data, index):
+def calculate_hkl(scan, index):
     h = np.empty(shape=(IMAGE_H, IMAGE_W))
     k = np.empty(shape=(IMAGE_H, IMAGE_W))
     l = np.empty(shape=(IMAGE_H, IMAGE_W))
 
-    wave = det_data["wave"]
-    ddist = det_data["ddist"]
-    gammad = det_data["gamma"][index]
-    om = det_data["omega"][index]
-    nud = det_data["nu"]
-    ub = det_data["ub"]
-    geometry = det_data["zebra_mode"]
+    wave = scan["wave"]
+    ddist = scan["ddist"]
+    gammad = scan["gamma"][index]
+    om = scan["omega"][index]
+    nud = scan["nu"]
+    ub = scan["ub"]
+    geometry = scan["zebra_mode"]
 
     if geometry == "bi":
-        chi = det_data["chi"][index]
-        phi = det_data["phi"][index]
+        chi = scan["chi"][index]
+        phi = scan["phi"][index]
     elif geometry == "nb":
         chi = 0
         phi = 0
@@ -914,10 +914,10 @@ def calculate_hkl(det_data, index):
     return h, k, l
 
 
-def calculate_pol(det_data, index):
-    ddist = det_data["ddist"]
-    gammad = det_data["gamma"][index]
-    nud = det_data["nu"]
+def calculate_pol(scan, index):
+    ddist = scan["ddist"]
+    gammad = scan["gamma"][index]
+    nud = scan["nu"]
     yi, xi = np.ogrid[:IMAGE_H, :IMAGE_W]
     gamma, nu = pyzebra.det2pol(ddist, gammad, nud, xi, yi)
 
diff --git a/pyzebra/app/panel_param_study.py b/pyzebra/app/panel_param_study.py
index 26e1271..e73cbfe 100644
--- a/pyzebra/app/panel_param_study.py
+++ b/pyzebra/app/panel_param_study.py
@@ -83,7 +83,7 @@ def color_palette(n_colors):
 
 def create():
     doc = curdoc()
-    det_data = []
+    dataset = []
     fit_params = {}
     js_data = ColumnDataSource(data=dict(content=[""], fname=[""], ext=[""]))
 
@@ -111,15 +111,15 @@ def create():
     proposal_textinput.on_change("name", proposal_textinput_callback)
 
     def _init_datatable():
-        scan_list = [s["idx"] for s in det_data]
-        export = [s["export"] for s in det_data]
+        scan_list = [s["idx"] for s in dataset]
+        export = [s["export"] for s in dataset]
         if param_select.value == "user defined":
-            param = [None] * len(det_data)
+            param = [None] * len(dataset)
         else:
-            param = [scan[param_select.value] for scan in det_data]
+            param = [scan[param_select.value] for scan in dataset]
 
         file_list = []
-        for scan in det_data:
+        for scan in dataset:
             file_list.append(os.path.basename(scan["original_filename"]))
 
         scan_table_source.data.update(
@@ -128,8 +128,8 @@ def create():
         scan_table_source.selected.indices = []
         scan_table_source.selected.indices = [0]
 
-        scan_motor_select.options = det_data[0]["scan_motors"]
-        scan_motor_select.value = det_data[0]["scan_motor"]
+        scan_motor_select.options = dataset[0]["scan_motors"]
+        scan_motor_select.value = dataset[0]["scan_motor"]
 
         merge_options = [(str(i), f"{i} ({idx})") for i, idx in enumerate(scan_list)]
         merge_from_select.options = merge_options
@@ -138,7 +138,7 @@ def create():
     file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250)
 
     def file_open_button_callback():
-        nonlocal det_data
+        nonlocal dataset
         new_data = []
         for f_path in file_select.value:
             with open(f_path) as file:
@@ -160,7 +160,7 @@ def create():
                 pyzebra.merge_datasets(new_data, file_data)
 
         if new_data:
-            det_data = new_data
+            dataset = new_data
             _init_datatable()
             append_upload_button.disabled = False
 
@@ -180,7 +180,7 @@ def create():
                     continue
 
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
-            pyzebra.merge_datasets(det_data, file_data)
+            pyzebra.merge_datasets(dataset, file_data)
 
         if file_data:
             _init_datatable()
@@ -189,7 +189,7 @@ def create():
     file_append_button.on_click(file_append_button_callback)
 
     def upload_button_callback(_attr, _old, _new):
-        nonlocal det_data
+        nonlocal dataset
         new_data = []
         for f_str, f_name in zip(upload_button.value, upload_button.filename):
             with io.StringIO(base64.b64decode(f_str).decode()) as file:
@@ -210,7 +210,7 @@ def create():
                 pyzebra.merge_datasets(new_data, file_data)
 
         if new_data:
-            det_data = new_data
+            dataset = new_data
             _init_datatable()
             append_upload_button.disabled = False
 
@@ -232,7 +232,7 @@ def create():
                     continue
 
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
-            pyzebra.merge_datasets(det_data, file_data)
+            pyzebra.merge_datasets(dataset, file_data)
 
         if file_data:
             _init_datatable()
@@ -244,8 +244,8 @@ def create():
     append_upload_button.on_change("filename", append_upload_button_callback)
 
     def monitor_spinner_callback(_attr, _old, new):
-        if det_data:
-            pyzebra.normalize_dataset(det_data, new)
+        if dataset:
+            pyzebra.normalize_dataset(dataset, new)
             _update_single_scan_plot()
             _update_overview()
 
@@ -253,8 +253,8 @@ def create():
     monitor_spinner.on_change("value", monitor_spinner_callback)
 
     def scan_motor_select_callback(_attr, _old, new):
-        if det_data:
-            for scan in det_data:
+        if dataset:
+            for scan in dataset:
                 scan["scan_motor"] = new
             _update_single_scan_plot()
             _update_overview()
@@ -263,12 +263,12 @@ def create():
     scan_motor_select.on_change("value", scan_motor_select_callback)
 
     def _update_table():
-        fit_ok = [(1 if "fit" in scan else 0) for scan in det_data]
-        export = [scan["export"] for scan in det_data]
+        fit_ok = [(1 if "fit" in scan else 0) for scan in dataset]
+        export = [scan["export"] for scan in dataset]
         if param_select.value == "user defined":
-            param = [None] * len(det_data)
+            param = [None] * len(dataset)
         else:
-            param = [scan[param_select.value] for scan in det_data]
+            param = [scan[param_select.value] for scan in dataset]
 
         scan_table_source.data.update(fit=fit_ok, export=export, param=param)
 
@@ -322,7 +322,7 @@ def create():
         par = []
         for s, p in enumerate(scan_table_source.data["param"]):
             if p is not None:
-                scan = det_data[s]
+                scan = dataset[s]
                 scan_motor = scan["scan_motor"]
                 xs.append(scan[scan_motor])
                 x.extend(scan[scan_motor])
@@ -331,8 +331,8 @@ def create():
                 param.append(float(p))
                 par.extend(scan["counts"])
 
-        if det_data:
-            scan_motor = det_data[0]["scan_motor"]
+        if dataset:
+            scan_motor = dataset[0]["scan_motor"]
             ov_plot.axis[0].axis_label = scan_motor
             ov_param_plot.axis[0].axis_label = scan_motor
 
@@ -371,7 +371,7 @@ def create():
         y_lower = []
         y_upper = []
         fit_param = fit_param_select.value
-        for s, p in zip(det_data, scan_table_source.data["param"]):
+        for s, p in zip(dataset, scan_table_source.data["param"]):
             if "fit" in s and fit_param:
                 x.append(p)
                 param_fit_val = s["fit"].params[fit_param].value
@@ -534,7 +534,7 @@ def create():
     def scan_table_source_callback(_attr, _old, new):
         # unfortunately, we don't know if the change comes from data update or user input
         # also `old` and `new` are the same for non-scalars
-        for scan, export in zip(det_data, new["export"]):
+        for scan, export in zip(dataset, new["export"]):
             scan["export"] = export
         _update_overview()
         _update_param_plot()
@@ -563,7 +563,7 @@ def create():
 
     def merge_button_callback():
         scan_into = _get_selected_scan()
-        scan_from = det_data[int(merge_from_select.value)]
+        scan_from = dataset[int(merge_from_select.value)]
 
         if scan_into is scan_from:
             print("WARNING: Selected scans for merging are identical")
@@ -587,7 +587,7 @@ def create():
     restore_button.on_click(restore_button_callback)
 
     def _get_selected_scan():
-        return det_data[scan_table_source.selected.indices[0]]
+        return dataset[scan_table_source.selected.indices[0]]
 
     def param_select_callback(_attr, _old, _new):
         _update_table()
@@ -720,7 +720,7 @@ def create():
     fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
 
     def proc_all_button_callback():
-        for scan in det_data:
+        for scan in dataset:
             if scan["export"]:
                 pyzebra.fit_scan(
                     scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@@ -735,7 +735,7 @@ def create():
         _update_overview()
         _update_table()
 
-        for scan in det_data:
+        for scan in dataset:
             if "fit" in scan:
                 options = list(scan["fit"].params.keys())
                 fit_param_select.options = options
@@ -760,7 +760,7 @@ def create():
         _update_overview()
         _update_table()
 
-        for scan in det_data:
+        for scan in dataset:
             if "fit" in scan:
                 options = list(scan["fit"].params.keys())
                 fit_param_select.options = options
@@ -782,7 +782,7 @@ def create():
             temp_file = temp_dir + "/temp"
             export_data = []
             param_data = []
-            for scan, param in zip(det_data, scan_table_source.data["param"]):
+            for scan, param in zip(dataset, scan_table_source.data["param"]):
                 if scan["export"] and param:
                     export_data.append(scan)
                     param_data.append(param)
diff --git a/pyzebra/ccl_io.py b/pyzebra/ccl_io.py
index 411e448..bd053ae 100644
--- a/pyzebra/ccl_io.py
+++ b/pyzebra/ccl_io.py
@@ -93,9 +93,9 @@ def load_1D(filepath):
     """
     with open(filepath, "r") as infile:
         _, ext = os.path.splitext(filepath)
-        det_variables = parse_1D(infile, data_type=ext)
+        dataset = parse_1D(infile, data_type=ext)
 
-    return det_variables
+    return dataset
 
 
 def parse_1D(fileobj, data_type):
@@ -133,7 +133,7 @@ def parse_1D(fileobj, data_type):
         metadata["zebra_mode"] = "nb"
 
     # read data
-    scan = []
+    dataset = []
     if data_type == ".ccl":
         ccl_first_line = CCL_FIRST_LINE + CCL_ANGLES[metadata["zebra_mode"]]
         ccl_second_line = CCL_SECOND_LINE
@@ -143,47 +143,49 @@ def parse_1D(fileobj, data_type):
             if not line or line.isspace():
                 continue
 
-            s = {}
-            s["export"] = True
+            scan = {}
+            scan["export"] = True
 
             # first line
             for param, (param_name, param_type) in zip(line.split(), ccl_first_line):
-                s[param_name] = param_type(param)
+                scan[param_name] = param_type(param)
 
             # second line
             next_line = next(fileobj)
             for param, (param_name, param_type) in zip(next_line.split(), ccl_second_line):
-                s[param_name] = param_type(param)
+                scan[param_name] = param_type(param)
 
-            if s["scan_motor"] != "om":
+            if scan["scan_motor"] != "om":
                 raise Exception("Unsupported variable name in ccl file.")
 
             # "om" -> "omega"
-            s["scan_motor"] = "omega"
-            s["scan_motors"] = ["omega", ]
+            scan["scan_motor"] = "omega"
+            scan["scan_motors"] = ["omega", ]
             # overwrite metadata, because it only refers to the scan center
-            half_dist = (s["n_points"] - 1) / 2 * s["angle_step"]
-            s["omega"] = np.linspace(s["omega"] - half_dist, s["omega"] + half_dist, s["n_points"])
+            half_dist = (scan["n_points"] - 1) / 2 * scan["angle_step"]
+            scan["omega"] = np.linspace(
+                scan["omega"] - half_dist, scan["omega"] + half_dist, scan["n_points"]
+            )
 
             # subsequent lines with counts
             counts = []
-            while len(counts) < s["n_points"]:
+            while len(counts) < scan["n_points"]:
                 counts.extend(map(float, next(fileobj).split()))
-            s["counts"] = np.array(counts)
-            s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1))
+            scan["counts"] = np.array(counts)
+            scan["counts_err"] = np.sqrt(np.maximum(scan["counts"], 1))
 
-            if s["h"].is_integer() and s["k"].is_integer() and s["l"].is_integer():
-                s["h"], s["k"], s["l"] = map(int, (s["h"], s["k"], s["l"]))
+            if scan["h"].is_integer() and scan["k"].is_integer() and scan["l"].is_integer():
+                scan["h"], scan["k"], scan["l"] = map(int, (scan["h"], scan["k"], scan["l"]))
 
-            scan.append({**metadata, **s})
+            dataset.append({**metadata, **scan})
 
     elif data_type == ".dat":
         # TODO: this might need to be adapted in the future, when "gamma" will be added to dat files
         if metadata["zebra_mode"] == "nb":
             metadata["gamma"] = metadata["twotheta"]
 
-        s = defaultdict(list)
-        s["export"] = True
+        scan = defaultdict(list)
+        scan["export"] = True
 
         match = re.search("Scanning Variables: (.*), Steps: (.*)", next(fileobj))
         motors = [motor.lower() for motor in match.group(1).split(", ")]
@@ -192,8 +194,8 @@ def parse_1D(fileobj, data_type):
         match = re.search("(.*) Points, Mode: (.*), Preset (.*)", next(fileobj))
         if match.group(2) != "Monitor":
             raise Exception("Unknown mode in dat file.")
-        s["n_points"] = int(match.group(1))
-        s["monitor"] = float(match.group(3))
+        scan["n_points"] = int(match.group(1))
+        scan["monitor"] = float(match.group(3))
 
         col_names = list(map(str.lower, next(fileobj).split()))
 
@@ -203,56 +205,56 @@ def parse_1D(fileobj, data_type):
                 break
 
             for name, val in zip(col_names, line.split()):
-                s[name].append(float(val))
+                scan[name].append(float(val))
 
         for name in col_names:
-            s[name] = np.array(s[name])
+            scan[name] = np.array(scan[name])
 
-        s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1))
+        scan["counts_err"] = np.sqrt(np.maximum(scan["counts"], 1))
 
-        s["scan_motors"] = []
+        scan["scan_motors"] = []
         for motor, step in zip(motors, steps):
             if step == 0:
                 # it's not a scan motor, so keep only the median value
-                s[motor] = np.median(s[motor])
+                scan[motor] = np.median(scan[motor])
             else:
-                s["scan_motors"].append(motor)
+                scan["scan_motors"].append(motor)
 
         # "om" -> "omega"
-        if "om" in s["scan_motors"]:
-            s["scan_motors"][s["scan_motors"].index("om")] = "omega"
-            s["omega"] = s["om"]
-            del s["om"]
+        if "om" in scan["scan_motors"]:
+            scan["scan_motors"][scan["scan_motors"].index("om")] = "omega"
+            scan["omega"] = scan["om"]
+            del scan["om"]
 
         # "tt" -> "temp"
-        if "tt" in s["scan_motors"]:
-            s["scan_motors"][s["scan_motors"].index("tt")] = "temp"
-            s["temp"] = s["tt"]
-            del s["tt"]
+        if "tt" in scan["scan_motors"]:
+            scan["scan_motors"][scan["scan_motors"].index("tt")] = "temp"
+            scan["temp"] = scan["tt"]
+            del scan["tt"]
 
         # "mf" stays "mf"
         # "phi" stays "phi"
 
-        s["scan_motor"] = s["scan_motors"][0]
+        scan["scan_motor"] = scan["scan_motors"][0]
 
-        if "h" not in s:
-            s["h"] = s["k"] = s["l"] = float("nan")
+        if "h" not in scan:
+            scan["h"] = scan["k"] = scan["l"] = float("nan")
 
         for param in ("mf", "temp"):
             if param not in metadata:
-                s[param] = 0
+                scan[param] = 0
 
-        s["idx"] = 1
+        scan["idx"] = 1
 
-        scan.append({**metadata, **s})
+        dataset.append({**metadata, **scan})
 
     else:
         print("Unknown file extention")
 
-    return scan
+    return dataset
 
 
-def export_1D(data, path, export_target, hkl_precision=2):
+def export_1D(dataset, path, export_target, hkl_precision=2):
     """Exports data in the .comm/.incomm format for fullprof or .col/.incol format for jana.
 
     Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files
@@ -262,11 +264,11 @@ def export_1D(data, path, export_target, hkl_precision=2):
     if export_target not in EXPORT_TARGETS:
         raise ValueError(f"Unknown export target: {export_target}.")
 
-    zebra_mode = data[0]["zebra_mode"]
+    zebra_mode = dataset[0]["zebra_mode"]
     exts = EXPORT_TARGETS[export_target]
     file_content = {ext: [] for ext in exts}
 
-    for scan in data:
+    for scan in dataset:
         if "fit" not in scan:
             continue
 
@@ -306,7 +308,7 @@ def export_1D(data, path, export_target, hkl_precision=2):
                 out_file.writelines(content)
 
 
-def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2):
+def export_ccl_compare(dataset1, dataset2, path, export_target, hkl_precision=2):
     """Exports compare data in the .comm/.incomm format for fullprof or .col/.incol format for jana.
 
     Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files
@@ -316,11 +318,11 @@ def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2):
     if export_target not in EXPORT_TARGETS:
         raise ValueError(f"Unknown export target: {export_target}.")
 
-    zebra_mode = data1[0]["zebra_mode"]
+    zebra_mode = dataset1[0]["zebra_mode"]
     exts = EXPORT_TARGETS[export_target]
     file_content = {ext: [] for ext in exts}
 
-    for scan1, scan2 in zip(data1, data2):
+    for scan1, scan2 in zip(dataset1, dataset2):
         if "fit" not in scan1:
             continue
 
@@ -363,9 +365,9 @@ def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2):
                 out_file.writelines(content)
 
 
-def export_param_study(data, param_data, path):
+def export_param_study(dataset, param_data, path):
     file_content = []
-    for scan, param in zip(data, param_data):
+    for scan, param in zip(dataset, param_data):
         if "fit" not in scan:
             continue
 
diff --git a/pyzebra/ccl_process.py b/pyzebra/ccl_process.py
index 02595e5..718760c 100644
--- a/pyzebra/ccl_process.py
+++ b/pyzebra/ccl_process.py
@@ -1,7 +1,7 @@
 import os
 
 import numpy as np
-from lmfit.models import Gaussian2dModel, GaussianModel, LinearModel, PseudoVoigtModel, VoigtModel
+from lmfit.models import GaussianModel, LinearModel, PseudoVoigtModel, VoigtModel
 from scipy.integrate import simpson, trapezoid
 
 from .ccl_io import CCL_ANGLES
@@ -259,31 +259,3 @@ def get_area(scan, area_method, lorentz):
         area_s = np.abs(area_s * corr_factor)
 
     scan["area"] = (area_v, area_s)
-
-
-def fit_event(scan, fr_from, fr_to, y_from, y_to, x_from, x_to):
-    data_roi = scan["data"][fr_from:fr_to, y_from:y_to, x_from:x_to]
-
-    model = GaussianModel()
-    fr = np.arange(fr_from, fr_to)
-    counts_per_fr = np.sum(data_roi, axis=(1, 2))
-    params = model.guess(counts_per_fr, fr)
-    result = model.fit(counts_per_fr, x=fr, params=params)
-    frC = result.params["center"].value
-    intensity = result.params["height"].value
-
-    counts_std = counts_per_fr.std()
-    counts_mean = counts_per_fr.mean()
-    snr = 0 if counts_std == 0 else counts_mean / counts_std
-
-    model = Gaussian2dModel()
-    xs, ys = np.meshgrid(np.arange(x_from, x_to), np.arange(y_from, y_to))
-    xs = xs.flatten()
-    ys = ys.flatten()
-    counts = np.sum(data_roi, axis=0).flatten()
-    params = model.guess(counts, xs, ys)
-    result = model.fit(counts, x=xs, y=ys, params=params)
-    xC = result.params["centerx"].value
-    yC = result.params["centery"].value
-
-    scan["fit"] = {"frame": frC, "x_pos": xC, "y_pos": yC, "intensity": intensity, "snr": snr}
diff --git a/pyzebra/h5.py b/pyzebra/h5.py
index afebdb5..3228dab 100644
--- a/pyzebra/h5.py
+++ b/pyzebra/h5.py
@@ -1,6 +1,6 @@
 import h5py
 import numpy as np
-
+from lmfit.models import Gaussian2dModel, GaussianModel
 
 META_MATRIX = ("UB")
 META_CELL = ("cell")
@@ -74,69 +74,97 @@ def read_detector_data(filepath, cami_meta=None):
         n, cols, rows = data.shape
         data = data.reshape(n, rows, cols)
 
-        det_data = {"data": data}
-        det_data["original_filename"] = filepath
+        scan = {"data": data}
+        scan["original_filename"] = filepath
 
         if "/entry1/zebra_mode" in h5f:
-            det_data["zebra_mode"] = h5f["/entry1/zebra_mode"][0].decode()
+            scan["zebra_mode"] = h5f["/entry1/zebra_mode"][0].decode()
         else:
-            det_data["zebra_mode"] = "nb"
+            scan["zebra_mode"] = "nb"
 
         # overwrite zebra_mode from cami
         if cami_meta is not None:
             if "zebra_mode" in cami_meta:
-                det_data["zebra_mode"] = cami_meta["zebra_mode"][0]
+                scan["zebra_mode"] = cami_meta["zebra_mode"][0]
 
         # om, sometimes ph
-        if det_data["zebra_mode"] == "nb":
-            det_data["omega"] = h5f["/entry1/area_detector2/rotation_angle"][:]
+        if scan["zebra_mode"] == "nb":
+            scan["omega"] = h5f["/entry1/area_detector2/rotation_angle"][:]
         else:  # bi
-            det_data["omega"] = h5f["/entry1/sample/rotation_angle"][:]
+            scan["omega"] = h5f["/entry1/sample/rotation_angle"][:]
 
-        det_data["gamma"] = h5f["/entry1/ZEBRA/area_detector2/polar_angle"][:]  # gammad
-        det_data["nu"] = h5f["/entry1/ZEBRA/area_detector2/tilt_angle"][:]  # nud
-        det_data["ddist"] = h5f["/entry1/ZEBRA/area_detector2/distance"][:]
-        det_data["wave"] = h5f["/entry1/ZEBRA/monochromator/wavelength"][:]
-        det_data["chi"] = h5f["/entry1/sample/chi"][:]  # ch
-        det_data["phi"] = h5f["/entry1/sample/phi"][:]  # ph
-        det_data["ub"] = h5f["/entry1/sample/UB"][:].reshape(3, 3)
-        det_data["name"] = h5f["/entry1/sample/name"][0].decode()
-        det_data["cell"] = h5f["/entry1/sample/cell"][:]
+        scan["gamma"] = h5f["/entry1/ZEBRA/area_detector2/polar_angle"][:]  # gammad
+        scan["nu"] = h5f["/entry1/ZEBRA/area_detector2/tilt_angle"][:]  # nud
+        scan["ddist"] = h5f["/entry1/ZEBRA/area_detector2/distance"][:]
+        scan["wave"] = h5f["/entry1/ZEBRA/monochromator/wavelength"][:]
+        scan["chi"] = h5f["/entry1/sample/chi"][:]  # ch
+        scan["phi"] = h5f["/entry1/sample/phi"][:]  # ph
+        scan["ub"] = h5f["/entry1/sample/UB"][:].reshape(3, 3)
+        scan["name"] = h5f["/entry1/sample/name"][0].decode()
+        scan["cell"] = h5f["/entry1/sample/cell"][:]
 
         if n == 1:
             # a default motor for a single frame file
-            det_data["scan_motor"] = "omega"
+            scan["scan_motor"] = "omega"
         else:
             for var in ("omega", "gamma", "nu", "chi", "phi"):
-                if abs(det_data[var][0] - det_data[var][-1]) > 0.1:
-                    det_data["scan_motor"] = var
+                if abs(scan[var][0] - scan[var][-1]) > 0.1:
+                    scan["scan_motor"] = var
                     break
             else:
                 raise ValueError("No angles that vary")
 
         # optional parameters
         if "/entry1/sample/magnetic_field" in h5f:
-            det_data["mf"] = h5f["/entry1/sample/magnetic_field"][:]
+            scan["mf"] = h5f["/entry1/sample/magnetic_field"][:]
 
         if "/entry1/sample/temperature" in h5f:
-            det_data["temp"] = h5f["/entry1/sample/temperature"][:]
+            scan["temp"] = h5f["/entry1/sample/temperature"][:]
 
         # overwrite metadata from .cami
         if cami_meta is not None:
             if "crystal" in cami_meta:
                 cami_meta_crystal = cami_meta["crystal"]
                 if "name" in cami_meta_crystal:
-                    det_data["name"] = cami_meta_crystal["name"]
+                    scan["name"] = cami_meta_crystal["name"]
                 if "UB" in cami_meta_crystal:
-                    det_data["ub"] = cami_meta_crystal["UB"]
+                    scan["ub"] = cami_meta_crystal["UB"]
                 if "cell" in cami_meta_crystal:
-                    det_data["cell"] = cami_meta_crystal["cell"]
+                    scan["cell"] = cami_meta_crystal["cell"]
                 if "lambda" in cami_meta_crystal:
-                    det_data["wave"] = cami_meta_crystal["lambda"]
+                    scan["wave"] = cami_meta_crystal["lambda"]
 
             if "detector parameters" in cami_meta:
                 cami_meta_detparam = cami_meta["detector parameters"]
                 if "dist2" in cami_meta_detparam:
-                    det_data["ddist"] = cami_meta_detparam["dist2"]
+                    scan["ddist"] = cami_meta_detparam["dist2"]
 
-    return det_data
+    return scan
+
+
+def fit_event(scan, fr_from, fr_to, y_from, y_to, x_from, x_to):
+    data_roi = scan["data"][fr_from:fr_to, y_from:y_to, x_from:x_to]
+
+    model = GaussianModel()
+    fr = np.arange(fr_from, fr_to)
+    counts_per_fr = np.sum(data_roi, axis=(1, 2))
+    params = model.guess(counts_per_fr, fr)
+    result = model.fit(counts_per_fr, x=fr, params=params)
+    frC = result.params["center"].value
+    intensity = result.params["height"].value
+
+    counts_std = counts_per_fr.std()
+    counts_mean = counts_per_fr.mean()
+    snr = 0 if counts_std == 0 else counts_mean / counts_std
+
+    model = Gaussian2dModel()
+    xs, ys = np.meshgrid(np.arange(x_from, x_to), np.arange(y_from, y_to))
+    xs = xs.flatten()
+    ys = ys.flatten()
+    counts = np.sum(data_roi, axis=0).flatten()
+    params = model.guess(counts, xs, ys)
+    result = model.fit(counts, x=xs, y=ys, params=params)
+    xC = result.params["centerx"].value
+    yC = result.params["centery"].value
+
+    scan["fit"] = {"frame": frC, "x_pos": xC, "y_pos": yC, "intensity": intensity, "snr": snr}