Add in-memory hdf append functionality

Fix #71

pyzebra/app/panel_hdf_viewer.py

@@ -49,6 +49,7 @@ IMAGE_PLOT_H = int(IMAGE_H * 2.4) + 27
 def create():
     doc = curdoc()
     log = doc.logger
+    uploaded_files = {}
     dataset = []
     ub_matrix_global = None
 
@@ -81,15 +82,18 @@ def create():
     ub_matrix.on_change("value", ub_matrix_callback)
 
     def file_select_update():
-        proposal_path = proposal_textinput.name
-        if proposal_path:
-            file_list = []
-            for file in os.listdir(proposal_path):
-                if file.endswith(".hdf"):
-                    file_list.append((os.path.join(proposal_path, file), file))
-            file_select.options = file_list
-        else:
-            file_select.options = []
+        if data_source.value == "proposal number":
+            proposal_path = proposal_textinput.name
+            if proposal_path:
+                file_list = []
+                for file in os.listdir(proposal_path):
+                    if file.endswith(".hdf"):
+                        file_list.append((os.path.join(proposal_path, file), file))
+                file_select.options = file_list
+            else:
+                file_select.options = []
+        else:  # data_source.value == "uploaded files"
+            file_select.options = list(uploaded_files.keys())
 
     doc.add_periodic_callback(file_select_update, 5000)
 
@@ -99,47 +103,43 @@ def create():
     proposal_textinput = doc.proposal_textinput
     proposal_textinput.on_change("name", proposal_textinput_callback)
 
-    def upload_hdf_button_callback(_attr, _old, new):
-        nonlocal dataset
-        try:
-            scan = pyzebra.read_detector_data(io.BytesIO(base64.b64decode(new)), ub_matrix_global)
-        except Exception as e:
-            log.exception(e)
-            return
+    def data_source_callback(_attr, _old, _new):
+        file_select_update()
 
-        dataset = [scan]
-        last_im_index = scan["counts"].shape[0] - 1
+    data_source = Select(
+        title="Data Source:",
+        value="proposal number",
+        options=["proposal number", "uploaded files"],
+        width=210,
+    )
+    data_source.on_change("value", data_source_callback)
 
-        index_spinner.value = 0
-        index_spinner.high = last_im_index
-        if last_im_index == 0:
-            index_slider.disabled = True
-        else:
-            index_slider.disabled = False
-            index_slider.end = last_im_index
-
-        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"])
-
-        _init_datatable()
+    def upload_hdf_button_callback(_attr, _old, _new):
+        nonlocal uploaded_files
+        for f_name, f_val in zip(upload_hdf_button.filename, upload_hdf_button.value):
+            uploaded_files[f_name] = io.BytesIO(base64.b64decode(f_val))
 
     upload_hdf_div = Div(text="Upload .hdf file:", margin=(5, 5, 0, 5))
-    upload_hdf_button = FileInput(accept=".hdf", width=200)
-    upload_hdf_button.on_change("value", upload_hdf_button_callback)
+    upload_hdf_button = FileInput(accept=".hdf", multiple=True, width=200)
+    upload_hdf_button.on_change("filename", upload_hdf_button_callback)
 
     def file_open_button_callback():
         nonlocal dataset
         new_data = []
         for f_path in file_select.value:
+            if data_source.value == "uploaded files":
+                f_name = f_path
+                f_path = uploaded_files[f_path]
+
             try:
-                file_data = [pyzebra.read_detector_data(f_path, ub_matrix_global)]
+                file_data = [pyzebra.read_detector_data(f_path, ub_matrix=ub_matrix_global)]
             except Exception as e:
                 log.exception(e)
                 continue
 
+            if data_source.value == "uploaded files":
+                file_data[0]["original_filename"] = os.path.join("/uploaded_files", f_name)
+
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
 
             if not new_data:  # first file
@@ -157,12 +157,19 @@ def create():
     def file_append_button_callback():
         file_data = []
         for f_path in file_select.value:
+            if data_source.value == "uploaded files":
+                f_name = f_path
+                f_path = uploaded_files[f_path]
+
             try:
-                file_data = [pyzebra.read_detector_data(f_path, ub_matrix_global)]
+                file_data = [pyzebra.read_detector_data(f_path, ub_matrix=ub_matrix_global)]
             except Exception as e:
                 log.exception(e)
                 continue
 
+            if data_source.value == "uploaded files":
+                file_data[0]["original_filename"] = os.path.join("/uploaded_files", f_name)
+
             pyzebra.normalize_dataset(file_data, monitor_spinner.value)
             pyzebra.merge_datasets(dataset, file_data, log=log)
 
@@ -885,7 +892,11 @@ def create():
     )
 
     import_layout = column(
-        upload_hdf_div, upload_hdf_button, file_select, row(file_open_button, file_append_button)
+        data_source,
+        upload_hdf_div,
+        upload_hdf_button,
+        file_select,
+        row(file_open_button, file_append_button),
     )
 
     layout_image = column(grid([[proj_v, None], [plot, proj_h]]))