Change to a cheap visualisation

Author: chraibi

anim.py

@@ -15,6 +15,8 @@
 import pandas as pd
 import pedpy
 import plotly.graph_objects as go
+from matplotlib.patches import Circle
+from matplotlib.figure import Figure as MatplotlibFigure
 from plotly.graph_objs import Figure, Scatter
 from plotly.graph_objs.layout import Shape
 from shapely import Polygon
@@ -141,8 +143,6 @@ def _get_colormap(
     )
 
     return [scatter_trace]
-
-
 def _get_shapes_for_frame(
     frame_data: pd.DataFrame,
     min_value: float,
@@ -444,3 +444,54 @@ def animate(
         height=height,
         title_note=title_note,
     )
+def plot_frame_fast(
+    data_df: pd.DataFrame,
+    area: pedpy.WalkableArea,
+    frame_num: int,
+    *,
+    radius: float = 0.1,
+    xlim: Tuple[float, float] | None = None,
+    ylim: Tuple[float, float] | None = None,
+) -> MatplotlibFigure:
+    """Render a single frame with matplotlib for fast inspection."""
+    frame_data = data_df[data_df["frame"] == frame_num].copy()
+    frame_data["radius"] = radius
+    min_value = float(data_df["motivation"].min())
+    max_value = float(data_df["motivation"].max())
+
+    fig, ax = plt.subplots(figsize=(7, 9), constrained_layout=True)
+    x, y = area.polygon.exterior.xy
+    ax.plot(np.array(x), np.array(y), color="black", linewidth=1.0)
+    for inner in area.polygon.interiors:
+        xi, yi = zip(*inner.coords[:])
+        ax.plot(np.array(xi), np.array(yi), color="black", linewidth=1.0)
+
+    cmap = plt.cm.jet_r
+    norm = plt.Normalize(vmin=min_value, vmax=max_value if max_value > min_value else min_value + 1.0)
+    for row in frame_data.itertuples():
+        circle = Circle(
+            (row.x, row.y),
+            radius=row.radius,
+            facecolor=cmap(norm(row.motivation)),
+            edgecolor="none",
+        )
+        ax.add_patch(circle)
+
+    sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
+    sm.set_array([])
+    fig.colorbar(sm, ax=ax, label="Motivation")
+    minx, miny, maxx, maxy = area.bounds
+    if xlim is None:
+        xlim = (minx - 0.5, maxx + 0.5)
+    if ylim is None:
+        ylim = (miny - 0.5, maxy + 0.5)
+    ax.set_xlim(*xlim)
+    ax.set_ylim(*ylim)
+    ax.set_aspect("equal")
+    ax.set_xticks([])
+    ax.set_yticks([])
+    for spine in ax.spines.values():
+        spine.set_visible(False)
+    ax.set_xlabel("")
+    ax.set_ylabel("")
+    return fig

app.py

@@ -11,7 +11,7 @@
 import pandas as pd
 import pedpy
 import streamlit as st
-from anim import animate
+from anim import plot_frame_fast
 from jupedsim.internal.notebook_utils import read_sqlite_file
 from src import docs
 import glob
@@ -43,13 +43,20 @@
             c1, c2, _c3 = st.columns(3)
             data = simulation_tab()
             config_file, output_file, fps = ui_simulation_controls(data)
+            if "show_frame_viewer" not in st.session_state:
+                st.session_state.show_frame_viewer = False
 
             if c1.button("Run Simulation"):
                 call_simulation(config_file, output_file, data)
 
             if c2.button("Visualization"):
+                st.session_state.show_frame_viewer = True
+
+            if st.session_state.show_frame_viewer:
                 output_path = Path(output_file)
-                if output_path.exists():
+                if not output_path.exists():
+                    st.warning(f"Trajectory file not found: {output_file}")
+                else:
                     trajectory_data, walkable_area = read_sqlite_file(output_file)
                     motivation_path = output_path.with_name(
                         output_path.stem + "_motivation.csv"
@@ -67,31 +74,22 @@
                         data_with_motivation["motivation"] = data_with_motivation[
                             "motivation"
                         ].fillna(1.0)
-                        data_with_motivation["gender"] = 1
-                        data_with_motivation["speed"] = 0.0
-                        width = data["motivation_parameters"]["width"]
-                        vertices = data["motivation_parameters"]["motivation_doors"][
-                            0
-                        ]["vertices"]
-                        x0 = 0.5 * (vertices[0][0] + vertices[1][0]) - width
-                        y0 = 0.5 * (vertices[0][1] + vertices[1][1]) - width
-                        x1 = 0.5 * (vertices[0][0] + vertices[1][0]) + width
-                        y1 = 0.5 * (vertices[1][1] + vertices[1][1]) + width
-
-                        animation = animate(
+                        frames = sorted(data_with_motivation["frame"].unique().tolist())
+                        frame_step = max(1, int(fps))
+                        selected_frame = st.slider(
+                            "Frame",
+                            min_value=int(frames[0]),
+                            max_value=int(frames[-1]),
+                            value=int(frames[0]),
+                            step=frame_step,
+                        )
+                        fig = plot_frame_fast(
                             data_with_motivation,
                             walkable_area,
-                            every_nth_frame=int(fps),
-                            color_mode="Motivation",
+                            frame_num=selected_frame,
                             radius=0.1,
-                            x0=x0,
-                            y0=y0,
-                            x1=x1,
-                            y1=y1,
                         )
-                        st.plotly_chart(animation)
-                else:
-                    st.warning(f"Trajectory file not found: {output_file}")
+                        st.pyplot(fig)
 
             params = extract_motivation_parameters(data)
             mapping = params.get("mapping_block", {})