Merge pull request #18 from PedestrianDynamics/pyg

Pyg

app.py

@@ -7,6 +7,7 @@
 from src.helpers.log_config import setup_logging
 from src.tabs.analysis_tab import run_tab3
 from src.tabs.contacts_tab import run_tab_contact
+from src.tabs.explorer import run_explorer
 from src.tabs.map_tab import run_tab_map
 from src.tabs.traj_tab import run_tab2
 from src.ui.ui import init_app_looks, init_sidebar, setup_app
@@ -26,7 +27,7 @@
 
     if selected_tab == "Trajectories":
         msg = st.empty()
-        file_name_to_path = {path.split('/')[-1]: path for path in st.session_state.files}
+        file_name_to_path = {path.split("/")[-1]: path for path in st.session_state.files}
         filename = str(st.selectbox(":open_file_folder: **Select a file**", file_name_to_path))
         st.session_state.selected_file = file_name_to_path[filename]
         run_tab2(file_name_to_path[filename], msg)
@@ -36,3 +37,6 @@
 
     if selected_tab == "Contacts":
         run_tab_contact()
+
+    if selected_tab == "Explorer":
+        run_explorer()

requirements.txt

@@ -1,11 +1,12 @@
 streamlit
 streamlit_folium
 folium
-pandas
 pedpy@git+https://github.com/PedestrianDynamics/PedPy.git
+pandas
 plotly
 matplotlib
 streamlit_drawable_canvas==0.8.0
 streamlit-option-menu
 gpxpy
 tqdm
+pygwalker

src/tabs/explorer.py

@@ -0,0 +1,74 @@
+import pickle
+from pathlib import Path
+
+import pandas as pd
+import pedpy
+import pygwalker as pyg
+import streamlit as st
+from pygwalker.api.streamlit import StreamlitRenderer
+
+from ..classes.datafactory import load_file
+from ..helpers.utilities import setup_walkable_area
+
+
+def prepare_data(selected_file: str, delta_frame: int) -> pd.DataFrame:
+    if selected_file != st.session_state.file_changed:
+        trajectory_data = load_file(selected_file)
+        st.session_state.trajectory_data = trajectory_data
+        st.session_state.file_changed = selected_file
+
+    result_file = Path(selected_file).stem + "_results.pkl"
+    if not Path(result_file).exists():
+        with st.status("Preparing data ..."):
+            trajectory_data = st.session_state.trajectory_data
+            walkable_area = setup_walkable_area(trajectory_data)
+            speed = pedpy.compute_individual_speed(
+                traj_data=trajectory_data,
+                frame_step=delta_frame,
+                speed_calculation=pedpy.SpeedCalculation.BORDER_SINGLE_SIDED,
+            )
+            individual = pedpy.compute_individual_voronoi_polygons(traj_data=trajectory_data, walkable_area=walkable_area, cut_off=pedpy.Cutoff(radius=1.0, quad_segments=3))
+            density_voronoi, intersecting = pedpy.compute_voronoi_density(individual_voronoi_data=individual, measurement_area=walkable_area)
+            voronoi_speed = pedpy.compute_voronoi_speed(
+                traj_data=trajectory_data,
+                individual_voronoi_intersection=intersecting,
+                individual_speed=speed,
+                measurement_area=walkable_area,
+            )
+            data_with_speed = voronoi_speed.merge(trajectory_data.data, on=["frame"], how="left")
+            data_with_speed_density = density_voronoi.merge(data_with_speed, on=["frame"], how="left")
+            with open(result_file, "wb") as f:
+                pickle.dump(data_with_speed_density, f)
+    else:
+        with open(result_file, "rb") as f:
+            data_with_speed_density = pickle.load(f)
+
+    return data_with_speed_density
+
+
+def run_walker(df: pd.DataFrame) -> None:
+    """You should cache your pygwalker renderer, if you don't want your memory to explode."""
+
+    @st.cache_resource
+    def get_pyg_renderer(df: pd.DataFrame) -> "StreamlitRenderer":
+        # If you want to use feature of saving chart config, set `spec_io_mode="rw"`
+        return StreamlitRenderer(df, spec="./gw_config.json", spec_io_mode="rw", field_specs={"frame": pyg.FieldSpec(analyticType="dimension")})
+
+    renderer = get_pyg_renderer(df)
+    renderer.render_explore()
+
+
+def run_explorer() -> None:
+    """Call explorer woth dataframe from selected file."""
+    file_name_to_path = {path.split("/")[-1]: path for path in st.session_state.files}
+    filename = str(
+        st.selectbox(
+            ":open_file_folder: **Select a file**",
+            file_name_to_path,
+            key="explorer_filename",
+        )
+    )
+    selected_file = file_name_to_path[filename]
+    st.session_state.selected_file = selected_file
+    df = prepare_data(selected_file, delta_frame=10)
+    run_walker(df)

src/ui/ui.py

@@ -36,16 +36,21 @@ def init_app_looks() -> None:
 
 
 def init_sidebar() -> Any:
-    """Init sidebar and 4 tabs."""
+    """Init sidebar and 5 tabs.
+
+    To add more tabs, add the name of the tab and add an icon from
+    https://icons.getbootstrap.com/
+    """
     return option_menu(
         "Multi-agent modelling of dense crowd dynamics: Predict & Understand",
-        ["About", "Map", "Trajectories", "Analysis", "Contacts"],
+        ["About", "Map", "Trajectories", "Analysis", "Contacts", "Explorer"],
         icons=[
             "info-square",
             "pin-map",
             "people",
             "bar-chart-line",
             "exclamation-triangle",
+            "graph-up-arrow",
         ],
         menu_icon="cast",
         default_index=0,