Merge branch 'han_bug_fix'

Author: hanhou

README.md

@@ -3,24 +3,24 @@
 A streamlit app for browsing foraging behavior sessions in AIND.
 
 ## The app
-- The one running on ECS: https://foraging-behavior-browser.allenneuraldynamics-test.org/
+- The one running on ECS: https://foraging-behavior-browser.allenneuraldynamics.org/
     - If you see a window "Select a certificate for authentication", just click "Cancel".
 - To debug, use this [Code Ocean capsule](https://codeocean.allenneuraldynamics.org/capsule/3373065/tree?cw=true)
-- See also a streamlit app for ephys sessions https://foraging-ephys-browser.allenneuraldynamics-test.org/ ([Git repo](https://github.com/AllenNeuralDynamics/foraging-ephys-browser/))
+- See also a streamlit app for ephys sessions https://foraging-ephys-browser.allenneuraldynamics.org/ ([Git repo](https://github.com/AllenNeuralDynamics/foraging-ephys-browser/))
 
 ## Sharing a contextual app
 Starting from this [PR](https://github.com/AllenNeuralDynamics/foraging-behavior-browser/pull/25), the URL contains (part of) the session state of the app. Meaning that the user can "query" pre-set filters and plot settings in the URL. On the other hand, after interacting with the app, the URL is automatically updated to reflect the user interactions, and the user can then copy and paste the URL to share/save the new context. Essentially, this becomes a cool way of sharing a data analysis.
 
 For example, this URL show all plots of mouse 699982
 
-> https://foraging-behavior-browser.allenneuraldynamics-test.org/?filter_subject_id=699982&session_plot_mode=all+sessions+filtered+from+sidebar&tab_id=tab_session_inspector
+> https://foraging-behavior-browser.allenneuraldynamics.org/?filter_subject_id=699982&session_plot_mode=all+sessions+filtered+from+sidebar&tab_id=tab_session_inspector
 
 ![image](https://github.com/AllenNeuralDynamics/foraging-behavior-browser/assets/24734299/4389e251-1305-4a85-8936-7e5d737f8408)
 
 
 and this URL will show exactly the plot below. Note the filters and plot settings are preserved.
 
-> https://foraging-behavior-browser.allenneuraldynamics-test.org/Old_mice?filter_subject_id=HH&filter_session=1.0&filter_session=81.0&filter_finished_trials=825.6&filter_finished_trials=1872.0&filter_foraging_eff=0.793295&filter_foraging_eff=1.2966&filter_task=coupled_block_baiting&filter_photostim_location=None&tab_id=tab_session_x_y&x_y_plot_xname=foraging_eff&x_y_plot_yname=finished_trials&x_y_plot_group_by=subject_id&x_y_plot_if_show_dots=True&x_y_plot_if_aggr_each_group=True&x_y_plot_aggr_method_group=linear+fit&x_y_plot_if_aggr_all=False&x_y_plot_aggr_method_all=mean+%2B%2F-+sem&x_y_plot_smooth_factor=5&x_y_plot_if_use_x_quantile_group=False&x_y_plot_q_quantiles_group=20&x_y_plot_if_use_x_quantile_all=False&x_y_plot_q_quantiles_all=20&x_y_plot_dot_size=21&x_y_plot_dot_opacity=0.4&x_y_plot_line_width=3.5&auto_training_history_x_axis=session&auto_training_history_sort_by=progress_to_graduated&auto_training_history_sort_order=descending
+> https://foraging-behavior-browser.allenneuraldynamics.org/Old_mice?filter_subject_id=HH&filter_session=1.0&filter_session=81.0&filter_finished_trials=825.6&filter_finished_trials=1872.0&filter_foraging_eff=0.793295&filter_foraging_eff=1.2966&filter_task=coupled_block_baiting&filter_photostim_location=None&tab_id=tab_session_x_y&x_y_plot_xname=foraging_eff&x_y_plot_yname=finished_trials&x_y_plot_group_by=subject_id&x_y_plot_if_show_dots=True&x_y_plot_if_aggr_each_group=True&x_y_plot_aggr_method_group=linear+fit&x_y_plot_if_aggr_all=False&x_y_plot_aggr_method_all=mean+%2B%2F-+sem&x_y_plot_smooth_factor=5&x_y_plot_if_use_x_quantile_group=False&x_y_plot_q_quantiles_group=20&x_y_plot_if_use_x_quantile_all=False&x_y_plot_q_quantiles_all=20&x_y_plot_dot_size=21&x_y_plot_dot_opacity=0.4&x_y_plot_line_width=3.5&auto_training_history_x_axis=session&auto_training_history_sort_by=progress_to_graduated&auto_training_history_sort_order=descending
 
 <img width="1664" alt="image" src="https://github.com/AllenNeuralDynamics/foraging-behavior-browser/assets/24734299/2eaa7697-01cc-4eb3-bd0c-7d91c1eb64e0">
 

code/Home.py

@@ -60,6 +60,14 @@
     pass
 
 
+# Inhibit the deprecated user warning from streamlit 1.45.1
+# https://discuss.streamlit.io/t/can-not-find-cause-of-st-experimental-user-deprecation-warning/111680
+def no_op(*args, **kwargs):
+    """This function replaces the original one and does not perform any action."""
+    pass
+st.user_info.maybe_show_deprecated_user_warning = no_op
+
+
 def _trainer_mapper(trainer):
     user_mapper = {
         'Avalon Amaya': ['Avalon'],
@@ -693,6 +701,6 @@ def add_main_tabs():
         st.markdown('# Something went wrong! :scream: ')
         st.markdown('## :bulb: Please follow these steps to troubleshoot:')
         st.markdown('####  1. Reload the page')
-        st.markdown('####  2. Click this original URL https://foraging-behavior-browser.allenneuraldynamics-test.org/')
+        st.markdown('####  2. Click this original URL https://foraging-behavior-browser.allenneuraldynamics.org/')
         st.markdown('####  3. Report your bug here: https://github.com/AllenNeuralDynamics/foraging-behavior-browser/issues (paste your URL and screenshoots)')
         raise e

code/__init__.py

@@ -1 +1 @@
-__ver__ = 'v3.2.1'
+__ver__ = 'v2025.11.13'

code/util/plot_autotrain_manager.py

@@ -50,15 +50,16 @@ def plot_manager_all_progress_bokeh_source(
             on=["subject_id", "session"],
             how="inner",
         )
+        df_to_draw = df_to_draw.copy()
 
-    df_to_draw["color"] = df_to_draw["current_stage_actual"].map(stage_color_mapper)
-    df_to_draw["edge_color"] = (  # Use grey edge to indicate stage without suggestion 
+    df_to_draw.loc[:, "color"] = df_to_draw["current_stage_actual"].map(stage_color_mapper)
+    df_to_draw.loc[:, "edge_color"] = (  # Use grey edge to indicate stage without suggestion 
         df_to_draw["current_stage_suggested"].map(stage_color_mapper).fillna("#d3d3d3")
     )
 
     # Convert session_date to string for URL generation
-    df_to_draw["session_date_str"] = df_to_draw["session_date"].astype(str)
-    df_to_draw["imgs_1"] = df_to_draw.apply(
+    df_to_draw.loc[:, "session_date_str"] = df_to_draw["session_date"].astype(str)
+    df_to_draw.loc[:, "imgs_1"] = df_to_draw.apply(
         lambda x: get_s3_public_url(
             subject_id=x["subject_id"],
             session_date=x["session_date_str"],
@@ -67,7 +68,7 @@ def plot_manager_all_progress_bokeh_source(
         ),
         axis=1,
     )
-    df_to_draw["imgs_2"] = df_to_draw.apply(
+    df_to_draw.loc[:, "imgs_2"] = df_to_draw.apply(
         lambda x: get_s3_public_url(
             subject_id=x["subject_id"],
             session_date=x["session_date_str"],
@@ -80,13 +81,13 @@ def plot_manager_all_progress_bokeh_source(
 
     # --- Remove rows with NaN in color or edge_color ---
     # to fix a bug where non-normalized stages appears in the autotrain table
-    df_to_draw = df_to_draw.dropna(subset=["color", "edge_color"])
+    df_to_draw = df_to_draw.dropna(subset=["color", "edge_color"]).copy()
 
     # --- Filter recent days ---
-    df_to_draw['session_date'] = pd.to_datetime(df_to_draw['session_date'])
+    df_to_draw.loc[:, 'session_date'] = pd.to_datetime(df_to_draw['session_date'])
     if not if_use_filtered_data and x_axis == 'date' and recent_days is not None:
         date_start = datetime.today() - pd.Timedelta(days=recent_days)
-        df_to_draw = df_to_draw.query('session_date >= @date_start')
+        df_to_draw = df_to_draw.query('session_date >= @date_start').copy()
 
     # Sort subjects
     if sort_by == "subject_id":
@@ -114,26 +115,29 @@ def plot_manager_all_progress_bokeh_source(
     else:
         raise ValueError("Invalid sort_by value.")
 
+    df_to_draw = df_to_draw.copy()
+
     # Select x
     if x_axis == 'session':
-        df_to_draw["x"] = df_to_draw['session']
+        df_to_draw.loc[:, "x"] = df_to_draw['session']
     elif x_axis == 'date':
-        df_to_draw["x"] = df_to_draw['session_date']
+        df_to_draw.loc[:, "x"] = df_to_draw['session_date']
     elif x_axis == 'relative_date':
         # groupby subject_id and all subtracted by the min date of each subject
-        df_to_draw["x"] = (
+        df_to_draw.loc[:, "x"] = (
             df_to_draw.groupby("subject_id")["session_date"]
             .transform(lambda x: x - x.min())
             .dt.days
         )
 
-    df_to_draw["session_date"] = df_to_draw["session_date"].dt.strftime('%Y-%m-%d')
+    # Convert session_date to string format AFTER x-axis calculations
+    df_to_draw.loc[:, "session_date"] = df_to_draw["session_date"].dt.strftime('%Y-%m-%d')
 
     # --- Reorder subjects ---
     df_subjects = []
 
     for n, subject_id in enumerate(subject_ids):
-        df_subject = df_to_draw[df_to_draw['subject_id'] == subject_id]
+        df_subject = df_to_draw[df_to_draw['subject_id'] == subject_id].copy()
         df_subject["y"] = len(subject_ids) - n
         df_subjects.append(df_subject)
 

code/util/streamlit.py

@@ -698,7 +698,7 @@ def add_dot_property_mapper():
 
     return size_mapper, size_mapper_range, size_mapper_gamma
 
-@st.fragment(run_every=5)
+@st.fragment()
 def data_selector():
 
     with st.expander(f'Session selector', expanded=True):        
@@ -1177,7 +1177,7 @@ def _add_agg(df_this, x_name, y_name, group, aggr_method, if_use_x_quantile, q_q
 
 def add_footnote():
     st.markdown('---')
-    st.markdown(f'#### AIND Behavior Team @ 2025 {__ver__}')
+    st.markdown(f'#### Han Hou @ AIND Behavior Team\n{__ver__}')
     st.markdown('[bug report / feature request](https://github.com/AllenNeuralDynamics/foraging-behavior-browser/issues)')
 
 

requirements.txt

@@ -1,4 +1,4 @@
-streamlit==1.41.1
+streamlit==1.45.1
 streamlit-aggrid==0.3.5
 streamlit-bokeh3-events==0.1.4
 streamlit_dynamic_filters==0.1.9