add pre-commit hook

.pre-commit-config.yaml

@@ -0,0 +1,21 @@
+repos:
+  - repo: https://github.com/astral-sh/ruff-pre-commit  
+    rev: v0.6.8  # Make sure you're using the correct version of Ruff
+    hooks:
+    # Run the linter.
+      - id: ruff
+        types_or: [ python, pyi ]  # Target Python files and type stub files
+        args: [ --fix ]  # Automatically fix linting issues if possible
+    # Run the formatter.
+      - id: ruff-format
+        types_or: [ python, pyi ]  # Format Python and stub files
+
+  # Mypy type checker
+  - repo: local
+    hooks:
+      - id: mypy
+        name: Analyze with Mypy
+        entry: mypy --strict  # Runs Mypy with the strictest settings
+        language: python
+        types: ['python']  # Targets Python files
+        files: \.py$  # Only .py files

.ruff.toml

@@ -57,7 +57,7 @@ line-ending = "auto"
 #
 # This is currently disabled by default, but it is planned for this
 # to be opt-out in the future.
-docstring-code-format = false
+docstring-code-format = true
 
 # Set the line length limit used when formatting code snippets in
 # docstrings.

app.py

@@ -30,8 +30,12 @@
 
     if selected_tab == "Trajectories":
         msg = st.empty()
-        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))
+        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)
 
@@ -48,7 +52,11 @@
     #     run_explorer()
 
     if selected_tab == "Geometry":
-        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))
+        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_tab_animation(file_name_to_path[filename])

requirements-dev.txt

@@ -1,2 +1,3 @@
 ruff
 mypy
+pre-commit

src/classes/datafactory.py

@@ -54,7 +54,9 @@ def retrieve_files(self) -> None:
         if not self.trajectories_directory.exists():
             st.warning(f"{self.trajectories_directory} does not exist yet!")
             with st.status("Downloading ...", expanded=False):
-                download_and_unzip_files(self.url, "data.zip", self.trajectories_directory)
+                download_and_unzip_files(
+                    self.url, "data.zip", self.trajectories_directory
+                )
 
         else:
             logging.info("Found trajectory directory. Nothing to retrieve!")
@@ -97,7 +99,9 @@ def init_state_bg_image() -> None:
 def init_session_state() -> None:
     """Init session_state throughout the app."""
     path = Path(__file__)
-    trajectories_directory = path.parent.parent.parent.absolute() / "data" / "trajectories"
+    trajectories_directory = (
+        path.parent.parent.parent.absolute() / "data" / "trajectories"
+    )
     flow_directory = path.parent.parent.parent.absolute() / "data" / "flow"
     processed_directory = path.parent.parent.parent.absolute() / "data" / "processed"
 
@@ -130,7 +134,11 @@ def init_session_state() -> None:
     if not hasattr(st.session_state, "trajectory_data"):
         st.session_state.trajectoryData = pedpy.TrajectoryData
 
-    dataconfig = DataConfig(trajectories_directory=trajectories_directory, processed_directory=processed_directory, flow_directory=flow_directory)
+    dataconfig = DataConfig(
+        trajectories_directory=trajectories_directory,
+        processed_directory=processed_directory,
+        flow_directory=flow_directory,
+    )
     st.session_state.files = dataconfig.files
     st.session_state.config = dataconfig
 
@@ -151,16 +159,23 @@ 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)
+                )
                 st.info(f"targe_path {target_path}")
                 # 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.
 

src/helpers/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 +72,17 @@ def get_measurement_lines(trajectory_data: pd.DataFrame, distance_to_bounding: f
 
     return [
         Direction(
-            info=DirectionInfo(id=get_id_by_name("Right"), name="Right", color=get_color_by_name("Right")),
+            info=DirectionInfo(
+                id=get_id_by_name("Right"),
+                name="Right",
+                color=get_color_by_name("Right"),
+            ),
             line=pedpy.MeasurementLine([[min_x, min_y], [min_x, max_y]]),
         ),
         Direction(
-            info=DirectionInfo(id=get_id_by_name("Left"), name="Left", color=get_color_by_name("Left")),
+            info=DirectionInfo(
+                id=get_id_by_name("Left"), name="Left", color=get_color_by_name("Left")
+            ),
             line=pedpy.MeasurementLine([[max_x, min_y], [max_x, max_y]]),
         ),
         Direction(
@@ -112,7 +120,9 @@ 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],

src/plotting/anim.py

@@ -20,8 +20,11 @@
 from plotly.graph_objs.layout import Shape
 from shapely import Polygon
 
-from ..classes.datafactory import (decrement_frame_start,
-                                   increment_frame_start, reset_frame_start)
+from ..classes.datafactory import (
+    decrement_frame_start,
+    increment_frame_start,
+    reset_frame_start,
+)
 
 DUMMY_SPEED = -1000
 
@@ -40,7 +43,9 @@ 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 +116,9 @@ 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 +213,9 @@ 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 +278,9 @@ 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 +353,9 @@ 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 +374,12 @@ 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))

src/plotting/drawing.py

@@ -11,7 +11,9 @@
 from .plots import draw_bg_img, draw_rects
 
 
-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:**",
@@ -34,7 +36,9 @@ def drawing_canvas(trajectory_data: pedpy.TrajectoryData, walkable_area: pedpy.W
         min_y = trajectory_data.data["y"].min()
         max_y = trajectory_data.data["y"].max()
 
-        bg_img, img_width, img_height, dpi, scale = draw_bg_img(data, min_x, max_x, min_y, max_y)
+        bg_img, img_width, img_height, dpi, scale = draw_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

src/scripts/calculate_profiles.py

@@ -12,9 +12,13 @@
 import pedpy as pp
 from joblib import Parallel, delayed
 from log_config import setup_logging
-from pedpy import (DensityMethod, SpeedMethod,
-                   compute_grid_cell_polygon_intersection_area,
-                   compute_speed_profile, get_grid_cells)
+from pedpy import (
+    DensityMethod,
+    SpeedMethod,
+    compute_grid_cell_polygon_intersection_area,
+    compute_speed_profile,
+    get_grid_cells,
+)
 from profile_config_data import Config
 from tqdm import tqdm
 

src/scripts/ploting_profiles.py

@@ -49,7 +49,8 @@ def init_parameters(config: Config) -> Tuple[List[Any], pp.WalkableArea, List[st
             "title": "Flow profile",
             "ylabel": r"$J\, /\, 1/ms$",
             "vmax": jmax,
-            "data_func": lambda file_: np.array(density_profiles[file_]) * np.array(speed_profiles[file_]),
+            "data_func": lambda file_: np.array(density_profiles[file_])
+            * np.array(speed_profiles[file_]),
         },
     ]
     return plot_params, walkable_area, files

src/scripts/run_profile_calculations.py

@@ -17,7 +17,9 @@ def run_all() -> None:
     """Initialize the configuration."""
     path = Path(__file__)
     data_directory = path.parent.parent.parent.absolute() / "data" / "processed"
-    trajectories_directory = path.parent.parent.parent.absolute() / "data" / "trajectories"
+    trajectories_directory = (
+        path.parent.parent.parent.absolute() / "data" / "trajectories"
+    )
     area = [[-6, 0], [5, 0], [5, 7], [-6, 7]]
     config = Config(
         files=sorted(glob.glob(f"{str(trajectories_directory)}/*.txt")),

src/tabs/explorer.py

@@ -27,16 +27,26 @@ def prepare_data(selected_file: str, delta_frame: int) -> pd.DataFrame:
                 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)
+            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")
+            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:
@@ -52,7 +62,12 @@ def run_walker(df: pd.DataFrame) -> None:
     @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")})
+        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()

src/tabs/traj_tab.py

@@ -11,8 +11,11 @@
 
 from ..classes.datafactory import load_file
 from ..plotting.anim import animate
-from ..plotting.plots import (download_file, plot_trajectories,
-                              plot_trajectories_figure_mpl)
+from ..plotting.plots import (
+    download_file,
+    plot_trajectories,
+    plot_trajectories_figure_mpl,
+)
 
 # import cProfile
 # import pstats
@@ -42,7 +45,9 @@ 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()
@@ -112,7 +117,9 @@ def run_tab2(selected_file: str, msg: DeltaGenerator) -> None:
             max_value=5.0,
         )
         # TODO: remove
-        fig2 = plot_trajectories_figure_mpl(trajectory_data, walkable_area, with_colors=True, alpha=alpha, lw=lw)
+        fig2 = plot_trajectories_figure_mpl(
+            trajectory_data, walkable_area, with_colors=True, alpha=alpha, lw=lw
+        )
         c1.pyplot(fig2)
         path = Path(__file__)
         data_directory = path.parent.parent.parent.absolute() / "data" / "processed"