Add start/end date selectors for experiment filtering

dashboard/app.py

@@ -105,7 +105,10 @@ def update(
         ctrl.figure_update(fig)
 
 
-@state.change("experiment")
+@state.change(
+    "experiment",
+    "experiment_date_range",
+)
 def update_on_change_experiment(**kwargs):
     # skip if triggered on server ready (all state variables marked as modified)
     if len(state.modified_keys) == 1:
@@ -361,14 +364,24 @@ def gui_setup():
         # add toolbar components
         with layout.toolbar:
             vuetify.VSpacer()
+            # experiment selector
             vuetify.VSelect(
                 v_model=("experiment",),
                 label="Experiments",
                 items=(experiments,),
                 dense=True,
                 hide_details=True,
                 prepend_icon="mdi-atom",
-                style="max-width: 250px",
+                style="max-width: 250px; margin-right: 14px;",
+            )
+            # date range selector for experiment filtering
+            vuetify.VDateInput(
+                v_model=("experiment_date_range",),
+                label="Date range",
+                multiple="range",
+                dense=True,
+                hide_details=True,
+                style="max-width: 250px; margin-right: 14px;",
             )
         # set up router view
         with layout.content:

dashboard/state_manager.py

@@ -1,5 +1,6 @@
 from pathlib import Path
 from trame.app import get_server
+from trame.widgets import vuetify3 as vuetify
 
 
 EXPERIMENTS_PATH = Path.cwd().parent / "experiments/"
@@ -8,6 +9,7 @@
 server = get_server(client_type="vue3")
 state = server.state
 ctrl = server.controller
+vuetify.enable_lab()  # Enable Labs components
 
 
 def initialize_state():
@@ -23,6 +25,7 @@ def initialize_state():
     ][0]
     print(f"Setting default experiment to {default_experiment}...")
     state.experiment = default_experiment
+    state.experiment_date_range = []
     # ML model
     state.model_type = "Neural Network (single)"
     state.model_training = False

dashboard/utils.py

@@ -73,8 +73,44 @@ def load_variables(experiment):
 @timer
 def load_data(db):
     print("Loading data from database...")
+    # build date filter if date range is set
+    date_filter = {}
+    if state.experiment_date_range:
+        # convert to naive datetime to match database format
+        start_date = (
+            pd.to_datetime(state.experiment_date_range[0].to_datetime())
+            .to_pydatetime()
+            .replace(hour=0, minute=0, second=0)
+        )
+        end_date = pd.to_datetime(state.experiment_date_range[-1].to_datetime())
+        # VDateInput returns exclusive end date for date ranges, but single-date selection has len=1
+        if len(state.experiment_date_range) == 1:
+            # single date selection: use the end date as-is
+            end_date = end_date.replace(hour=23, minute=59, second=59)
+        else:
+            # date range selection: subtract 1 day from exclusive end date
+            end_date = (
+                (end_date - pd.Timedelta(days=1))
+                .to_pydatetime()
+                .replace(hour=23, minute=59, second=59)
+            )
+        # remove timezone info to match naive datetime in database
+        start_date = (
+            start_date.replace(tzinfo=None) if start_date.tzinfo else start_date
+        )
+        end_date = end_date.replace(tzinfo=None) if end_date.tzinfo else end_date
+        date_filter = {
+            "date": {
+                "$gte": start_date,
+                "$lte": end_date,
+            }
+        }
+        print(date_filter)
+        print(f"Filtering data between {start_date.date()} and {end_date.date()}...")
     # load experiment and simulation data points in dataframes
-    exp_data = pd.DataFrame(db[state.experiment].find({"experiment_flag": 1}))
+    exp_data = pd.DataFrame(
+        db[state.experiment].find({**{"experiment_flag": 1}, **date_filter})
+    )
     sim_data = pd.DataFrame(db[state.experiment].find({"experiment_flag": 0}))
     # Store '_id', 'date' as string
     for key in ["_id", "date"]: