formating

analysis_tab.py

@@ -1,7 +1,7 @@
 """Analysis data, speed, density, flow, etc."""
 
-import logging
 import glob
+import logging
 import os
 import pickle
 import time
@@ -577,7 +577,7 @@ def calculate_speed_profile(
     plots.download_file(figname)
 
 
-def ui_tab3_analysis() -> Tuple[Optional[str], Optional[int], st_column]:
+def ui_tab3_analysis() -> Tuple[str, Optional[int], st_column]:
     """Prepare ui elements."""
     c0, c1, c2 = st.columns((1, 1, 1))
     if st.sidebar.button(
@@ -595,31 +595,35 @@ def ui_tab3_analysis() -> Tuple[Optional[str], Optional[int], st_column]:
 
     st.sidebar.divider()
     if utilities.is_running_locally():
-        calculations = st.radio(
-            "**Choose calculation**",
-            [
-                "N-T",
-                "Time series",
-                "FD_classical",
-                "FD_voronoi (load)",
-                "FD_voronoi (calculate)",
-                "Density profile",
-                "Speed profile",
-            ],
-            horizontal=True,
+        calculations = str(
+            st.radio(
+                "**Choose calculation**",
+                [
+                    "N-T",
+                    "Time series",
+                    "FD_classical",
+                    "FD_voronoi (load)",
+                    "FD_voronoi (calculate)",
+                    "Density profile",
+                    "Speed profile",
+                ],
+                horizontal=True,
+            )
         )
     else:
-        calculations = st.radio(
-            "**Choose calculation**",
-            [
-                "N-T",
-                "Time series",
-                "FD_classical",
-                "FD_voronoi (load)",
-                "Density profile",
-                "Speed profile",
-            ],
-            horizontal=True,
+        calculations = str(
+            st.radio(
+                "**Choose calculation**",
+                [
+                    "N-T",
+                    "Time series",
+                    "FD_classical",
+                    "FD_voronoi (load)",
+                    "Density profile",
+                    "Speed profile",
+                ],
+                horizontal=True,
+            )
         )
     exclude = ["N-T", "Density profile", "Speed profile", "FD_voronoi (load)"]
     if calculations in exclude:

anim.py

@@ -40,7 +40,9 @@ def _get_line_color(disk_color: str) -> str:
     return "black" if brightness > 127 else "white"
 
 
-def _create_orientation_line(row: pd.DataFrame, line_length: float = 0.2, color: str = "black") -> Shape:
+def _create_orientation_line(
+    row: pd.DataFrame, line_length: float = 0.2, color: str = "black"
+) -> Shape:
     """Create orientation Shape object."""
     end_x = row["x"] + line_length * 0
     end_y = row["y"] + line_length * 0
@@ -111,7 +113,9 @@ def _get_colormap(frame_data: pd.DataFrame, max_speed: float) -> List[Scatter]:
     return [scatter_trace]
 
 
-def _get_shapes_for_frame(frame_data: pd.DataFrame, min_speed: float, max_speed: float) -> Tuple[Shape, Scatter, Shape]:
+def _get_shapes_for_frame(
+    frame_data: pd.DataFrame, min_speed: float, max_speed: float
+) -> Tuple[Shape, Scatter, Shape]:
     """Construct circles as Shapes for agents, Hover and Directions."""
 
     def create_shape(row: pd.DataFrame) -> Shape:
@@ -206,7 +210,9 @@ def _create_fig(
     fig = go.Figure(
         data=geometry_traces + initial_scatter_trace + initial_hover_trace,
         frames=frames,
-        layout=go.Layout(shapes=initial_shapes + initial_arrows, title=title, title_x=0.5),
+        layout=go.Layout(
+            shapes=initial_shapes + initial_arrows, title=title, title_x=0.5
+        ),
     )
     fig.update_layout(
         updatemenus=[_get_animation_controls()],
@@ -269,7 +275,9 @@ def _get_slider_controls(steps: List[Dict[str, Any]]) -> Dict[str, Any]:
     }
 
 
-def _get_processed_frame_data(data_df: pd.DataFrame, frame_num: int, max_agents: int) -> Tuple[pd.DataFrame, int]:
+def _get_processed_frame_data(
+    data_df: pd.DataFrame, frame_num: int, max_agents: int
+) -> Tuple[pd.DataFrame, int]:
     """Process frame data and ensure it matches the maximum agent count."""
     frame_data = data_df[data_df["frame"] == frame_num]
     agent_count = len(frame_data)
@@ -342,7 +350,9 @@ def animate(
     # Calculate page_end
     frame_end = st.session_state.start_frame + page_size
     frame_start = st.session_state.start_frame
-    data_df = data_df0[(data_df0["frame"] >= frame_start) & (data_df0["frame"] <= frame_end)]
+    data_df = data_df0[
+        (data_df0["frame"] >= frame_start) & (data_df0["frame"] <= frame_end)
+    ]
 
     min_speed = data_df["speed"].min()
     max_speed = data_df["speed"].max()
@@ -361,8 +371,12 @@ def animate(
     ) = _get_shapes_for_frame(initial_frame_data, min_speed, max_speed)
     color_map_trace = _get_colormap(initial_frame_data, max_speed)
     for frame_num in selected_frames:
-        frame_data, agent_count = _get_processed_frame_data(data_df, frame_num, max_agents)
-        shapes, hover_traces, arrows = _get_shapes_for_frame(frame_data, min_speed, max_speed)
+        frame_data, agent_count = _get_processed_frame_data(
+            data_df, frame_num, max_agents
+        )
+        shapes, hover_traces, arrows = _get_shapes_for_frame(
+            frame_data, min_speed, max_speed
+        )
         # title = f"<b>{title_note + '  |  ' if title_note else ''}N: {agent_count}</b>"
         title = f"<b>{title_note + '  |  ' if title_note else ''}Number of Agents: {initial_agent_count}. Frame: {frame_num}</b>"
         frame_name = str(int(frame_num))

app.py

@@ -1,5 +1,7 @@
 """Main entry point to the data visualisator for MADRAS project."""
 
+import logging
+
 import streamlit as st
 
 import analysis_tab
@@ -8,8 +10,6 @@
 import map_tab
 import traj_tab
 import ui
-from utilities import is_running_locally
-import logging
 
 # Basic configuration for logging
 logging.basicConfig(

datafactory.py

@@ -132,15 +132,21 @@ def unzip_files(zip_path: Union[str, Path], destination: Union[str, Path]) -> No
             # Extract only if file (ignores directories)
             if not member.is_dir():
                 # Build target filename path
-                target_path = os.path.join(destination, os.path.basename(member.filename))
+                target_path = os.path.join(
+                    destination, os.path.basename(member.filename)
+                )
                 # Ensure target directory exists (e.g., if not extracting directories)
                 os.makedirs(os.path.dirname(target_path), exist_ok=True)
                 # Extract file
-                with zip_ref.open(member, "r") as source, open(target_path, "wb") as target:
+                with zip_ref.open(member, "r") as source, open(
+                    target_path, "wb"
+                ) as target:
                     shutil.copyfileobj(source, target)
 
 
-def download_and_unzip_files(url: str, destination: Union[str, Path], unzip_destination: Union[str, Path]) -> None:
+def download_and_unzip_files(
+    url: str, destination: Union[str, Path], unzip_destination: Union[str, Path]
+) -> None:
     """
     Download a ZIP file from a specified URL.
 

drawing.py

@@ -11,7 +11,9 @@
 import utilities
 
 
-def drawing_canvas(trajectory_data: pedpy.TrajectoryData, walkable_area: pedpy.WalkableArea) -> Tuple[Any, float, float, float]:
+def drawing_canvas(
+    trajectory_data: pedpy.TrajectoryData, walkable_area: pedpy.WalkableArea
+) -> Tuple[Any, float, float, float]:
     """Draw trajectories as img and prepare canvas."""
     drawing_mode = st.sidebar.radio(
         "**Measurement:**",
@@ -27,14 +29,16 @@ def drawing_canvas(trajectory_data: pedpy.TrajectoryData, walkable_area: pedpy.W
 
     stroke_width = st.sidebar.slider("**Stroke width:**", 1, 25, 3)
     if st.session_state.bg_img is None:
-        logging("START new canvas")
+        logging.info("START new canvas")
         data = trajectory_data.data
         min_x = trajectory_data.data["x"].min()
         max_x = trajectory_data.data["x"].max()
         min_y = trajectory_data.data["y"].min()
         max_y = trajectory_data.data["y"].max()
 
-        bg_img, img_width, img_height, dpi, scale = plots.bg_img(data, min_x, max_x, min_y, max_y)
+        bg_img, img_width, img_height, dpi, scale = plots.bg_img(
+            data, min_x, max_x, min_y, max_y
+        )
         st.session_state.scale = scale
         st.session_state.dpi = dpi
         st.session_state.img_width = img_width
@@ -84,14 +88,18 @@ def get_measurement_area(
         boundaries,
     )
     if not rects:
-        measurement_areas.append(utilities.setup_measurement_area(min_x, max_x, min_y, max_y))
+        measurement_areas.append(
+            utilities.setup_measurement_area(min_x, max_x, min_y, max_y)
+        )
         return measurement_areas
 
     for ir, _ in enumerate(rects):
         from_x = rects[ir]["x"][0]
         to_x = rects[ir]["x"][1]
         from_y = rects[ir]["y"][3]
         to_y = rects[ir]["y"][0]
-        measurement_areas.append(utilities.setup_measurement_area(from_x, to_x, from_y, to_y))
+        measurement_areas.append(
+            utilities.setup_measurement_area(from_x, to_x, from_y, to_y)
+        )
 
     return measurement_areas

map_tab.py

@@ -51,8 +51,12 @@ def load_cameras_from_json(file_path: str) -> Dict[str, Camera]:
         try:
             # Ensure the data structure is as expected
             location = tuple(info["location"])
-            assert isinstance(location, tuple) and len(location) == 2, "Location must be a tuple of two floats."
-            assert all(isinstance(x, float) for x in location), "Location elements must be floats."
+            assert (
+                isinstance(location, tuple) and len(location) == 2
+            ), "Location must be a tuple of two floats."
+            assert all(
+                isinstance(x, float) for x in location
+            ), "Location elements must be floats."
             location = cast(Tuple[float, float], location)
             url = info["url"]
             name = info["name"]

traj_tab.py

@@ -1,7 +1,8 @@
 """Show general results, including ploting, animation, ..."""
 
-import time
 import logging
+import time
+
 import pedpy
 import streamlit as st
 from shapely import Polygon
@@ -41,7 +42,9 @@ def run_tab2(selected_file: str, msg: DeltaGenerator) -> None:
         frame_step=5,
         speed_calculation=pedpy.SpeedCalculation.BORDER_SINGLE_SIDED,
     )
-    data_with_speed = data_with_speed.merge(trajectory_data.data, on=["id", "frame"], how="left")
+    data_with_speed = data_with_speed.merge(
+        trajectory_data.data, on=["id", "frame"], how="left"
+    )
 
     ids = trajectory_data.data["id"].unique()
     start_time = time.time()
@@ -111,11 +114,17 @@ def run_tab2(selected_file: str, msg: DeltaGenerator) -> None:
             max_value=5.0,
         )
 
-        fig2 = plots.plot_trajectories_figure_mpl(trajectory_data, walkable_area, with_colors=True, alpha=alpha, lw=lw)
+        fig2 = plots.plot_trajectories_figure_mpl(
+            trajectory_data, walkable_area, with_colors=True, alpha=alpha, lw=lw
+        )
         # pfig, ax = plt.subplots()
         # pedpy.plot_trajectories(traj=trajectory_data, walkable_area=walkable_area, axes=ax)
         c1.pyplot(fig2)
-        figname = "trajectories_" + selected_file.split("/")[-1].split(".txt")[0] + "_colors.pdf"
+        figname = (
+            "trajectories_"
+            + selected_file.split("/")[-1].split(".txt")[0]
+            + "_colors.pdf"
+        )
         fig2.savefig(figname, bbox_inches="tight", pad_inches=0.1)
         plots.download_file(figname, c1, label="color")
         # fig3z = plots.plot_trajectories_figure_mpl(trajectory_data, walkable_area, with_colors=False)
@@ -126,7 +135,7 @@ def run_tab2(selected_file: str, msg: DeltaGenerator) -> None:
 
         end_time = time.time()
         elapsed_time = end_time - start_time
-        logging(f"Time taken to plot trajectories: {elapsed_time:.2f} seconds")
+        logging.info(f"Time taken to plot trajectories: {elapsed_time:.2f} seconds")
 
     if do_animate:
         #        pr = cProfile.Profile()

ui.py

@@ -31,7 +31,9 @@ def init_app_looks() -> None:
     repo_name = f"[![Repo]({gh})]({repo})"
     c1, c2 = st.sidebar.columns((1.2, 0.5))
     c2.markdown(repo_name, unsafe_allow_html=True)
-    c1.write("[![DOI](https://zenodo.org/badge/760394097.svg)](https://zenodo.org/doi/10.5281/zenodo.10694866)")
+    c1.write(
+        "[![DOI](https://zenodo.org/badge/760394097.svg)](https://zenodo.org/doi/10.5281/zenodo.10694866)"
+    )
     st.sidebar.image(f"{ROOT_DIR}/logo.png", use_column_width=True)
 
 

utilities.py

@@ -61,7 +61,9 @@ def get_id_by_name(direction_name: str) -> int:
     return -1
 
 
-def get_measurement_lines(trajectory_data: pd.DataFrame, distance_to_bounding: float) -> List[Direction]:
+def get_measurement_lines(
+    trajectory_data: pd.DataFrame, distance_to_bounding: float
+) -> List[Direction]:
     """Create 4 measurement lines inside the walkable_area."""
     min_x = trajectory_data.data["x"].min() + distance_to_bounding
     max_x = trajectory_data.data["x"].max() - distance_to_bounding
@@ -70,11 +72,15 @@ def get_measurement_lines(trajectory_data: pd.DataFrame, distance_to_bounding: f
 
     return [
         Direction(
-            info=DirectionInfo(id=get_id_by_name("East"), name="East", color=get_color_by_name("East")),
+            info=DirectionInfo(
+                id=get_id_by_name("East"), name="East", color=get_color_by_name("East")
+            ),
             line=pedpy.MeasurementLine([[min_x, min_y], [min_x, max_y]]),
         ),
         Direction(
-            info=DirectionInfo(id=get_id_by_name("West"), name="West", color=get_color_by_name("West")),
+            info=DirectionInfo(
+                id=get_id_by_name("West"), name="West", color=get_color_by_name("West")
+            ),
             line=pedpy.MeasurementLine([[max_x, min_y], [max_x, max_y]]),
         ),
         Direction(
@@ -112,7 +118,9 @@ def setup_walkable_area(trajectory_data: pd.DataFrame) -> pedpy.WalkableArea:
     return pedpy.WalkableArea(rectangle_polygon)
 
 
-def setup_measurement_area(min_x: float, max_x: float, min_y: float, max_y: float) -> pedpy.MeasurementArea:
+def setup_measurement_area(
+    min_x: float, max_x: float, min_y: float, max_y: float
+) -> pedpy.MeasurementArea:
     """Create measurement_area from trajectories."""
     rectangle_coords = [
         [min_x, min_y],