Merge remote-tracking branch 'origin/smail' into lbaumberger

forces.cpp

@@ -28,7 +28,7 @@ void compute_acceleration_term(Pedestrian *p) {
 
 // # 55(N - 1) = 55N - 55 flops
 //
-// $\sum_{\beta} \vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
+// $\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
 //
 void compute_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestrian *p, int N) {
 
@@ -68,25 +68,25 @@ void compute_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestr
 
     // # 7 flops = 1 SQRT, 3 ADDs, 2 MULTs, 1 DIV
     //
-    // $(4):2b = \sqrt{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert)^2 - (v_\beta \Delta t)^2}$
+    // $2b = \sqrt{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert)^2 - (v_\beta \Delta t)^2}$
     //
     double b = sqrt((r_ab_norm + r_ab2_norm) * (r_ab_norm + r_ab2_norm) - s_b * s_b) / 2;
 
     // # 12 flops = 6 DIVs, 3 ADDs, 3 MULTs
     //
-    // $(7):\grad_{\vec{r}_{\alpha \beta}}b = \frac{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert) (\frac{\vec{r}_{\alpha \beta}}{\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert} + \frac{\vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta}{\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert})}{4b}$
+    // $\grad_{\vec{r}_{\alpha \beta}}b = \frac{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert) (\frac{\vec{r}_{\alpha \beta}}{\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert} + \frac{\vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta}{\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert})}{4b}$
     //
-    Vector2d b_grad = (r_ab / r_ab_norm + r_ab2 / r_ab2_norm) * (r_ab_norm + r_ab2_norm) / (4 * b);
+    Vector2d b_grad = ((r_ab / r_ab_norm + r_ab2 / r_ab2_norm) * (r_ab_norm + r_ab2_norm)) / (4 * b);
 
     // # 6 flops = 3 MULTs, 2 DIVs, 1 EXP
     //
-    // $(5):\vec{f}_{\alpha \beta}(\vec{r}_{\alpha \beta}) = \frac{V^0_{\alpha \beta}}{\sigma}e^{-b / \sigma} \grad_{\vec{r}_{\alpha \beta}}b$
+    // $\vec{f}_{\alpha \beta}(\vec{r}_{\alpha \beta}) = \frac{V^0_{\alpha \beta}}{\sigma}e^{-b / \sigma} \grad_{\vec{r}_{\alpha \beta}}b$
     //
     Vector2d f_ped = b_grad * ((V0_AB / SIGMA) * (exp(-b / SIGMA)));
 
     // # 14 flops: 9 MULTs, 4 ADDs, 1 SQRT
     //
-    // $(11):\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta}) = w(\vec{e}_{\alpha}, -\vec{f}_{\alpha\beta})\vec{f}_{\alpha\beta}(\vec{r}_{\alpha} - \vec{r}_{\beta})$
+    // $\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta}) = w(\vec{e}_{\alpha}, -\vec{f}_{\alpha\beta})\vec{f}_{\alpha\beta}(\vec{r}_{\alpha} - \vec{r}_{\beta})$
     //
     p->f_i += f_ped * w(p->e, f_ped * -1);
   }
@@ -94,6 +94,9 @@ void compute_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestr
 
 // # Assume that the four borders are also 4 obstacles
 // # 48 n_obstacles flops = 192 flops
+//
+// $\vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{B})$
+//
 void compute_repulsive_effects_from_borders(Board &board, Pedestrian *p) {
 
   Obstacle *obstacles = board.obstacles;

main.cpp

@@ -33,7 +33,7 @@ Pedestrian *init_pedestrians(int n_p) {
   for (int i = 0; i < n_p / 2; i++) {
     double y = y_gen(gen);
     Vector2d start_pos = Vector2d(x_gen(gen), y);
-    Vector2d destination = Vector2d(BOARD_LENGTH + 300, BOARD_WIDTH / 2);
+    Vector2d destination = Vector2d(BOARD_LENGTH + 30, BOARD_WIDTH / 2);
     // double desired_v0 = velocity_gen(gen);
     double desired_v0;
     do {
@@ -46,7 +46,7 @@ Pedestrian *init_pedestrians(int n_p) {
   for (int i = n_p / 2; i < n_p; i++) {
     double y = y_gen(gen);
     Vector2d start_pos = Vector2d(x_gen(gen), y);
-    Vector2d destination = Vector2d(-300, BOARD_WIDTH / 2);
+    Vector2d destination = Vector2d(-30, BOARD_WIDTH / 2);
     // double desired_v0 = velocity_gen(gen);
     double desired_v0;
     do {
@@ -88,7 +88,7 @@ int main(int argc, const char *argv[]) {
   const int dump_interval = 50; // dump every 5 iterations -> 20 fps (since dt = 0.01)
   const char *dump_path = (argc >= 4) ? argv[3] : nullptr;
 
-  std::vector<std::tuple<int, int, double, double, int>> samples; // t, id, x, y, color
+  std::vector<std::tuple<int, int, double, double, double, double, int>> samples; // t, id, x, y, e.x, e.y, color
   if (dump_path)
     samples.reserve((size_t)n_iter / dump_interval * n_p);
 
@@ -137,7 +137,7 @@ int main(int argc, const char *argv[]) {
 
       // # 4 flops = 2 ADDs, 2 MULTs
       //
-      // $\vec{r}_i^{t+1} += \vec{r}^t_i + v^t_idt$
+      // $\vec{r}_i^{t+1} = \vec{r}^t_i + v^t_idt$
       //
       p.curr_pos = p.curr_pos + p.curr_vel * dt;
 
@@ -157,9 +157,14 @@ int main(int argc, const char *argv[]) {
         // p.destination.y = p.curr_pos.y;
       }
 
+      // # 10 flops = 5 ADDs, 2 DIVs, 1 SQRT, 2 MULTs
+      // p.e = (p.destination - p.curr_pos) / (p.destination - p.curr_pos).norm();
+      // p.e = (p.curr_vel - p.destination) / (p.curr_vel - p.destination).norm();
+      p.e = (p.destination - (p.curr_vel / p.curr_vel.norm())) / (p.destination - (p.curr_vel / p.curr_vel.norm())).norm();
+
       // if we have a dump path/file we wanna save the data for visualisation
       if (dump_path && (t % dump_interval == 0)) {
-        samples.emplace_back(t, i, p.curr_pos.x, p.curr_pos.y, p.color);
+        samples.emplace_back(t, i, p.curr_pos.x, p.curr_pos.y, p.e.x, p.e.y, p.color);
       }
     }
   }
@@ -182,9 +187,9 @@ int main(int argc, const char *argv[]) {
   // now we wanna save the data to a csv
   if (dump_path) {
     std::ofstream out(dump_path);
-    out << "time,id,x,y,color\n";
+    out << "time,id,x,y,p.e.x,p.e.y,color\n";
-    for (auto &[t, id, x, y, c] : samples) {
+    for (auto &[t, id, x, y, e_x, e_y, c] : samples) {
-      out << t << ',' << id << ',' << x << ',' << y << ',' << c << '\n';
+      out << t << ',' << id << ',' << x << ',' << y << ',' << e_x << ',' << e_y << ',' << c << '\n';
     }
   }
 

pedestrian.hpp

@@ -14,7 +14,7 @@ struct Pedestrian {
   // $\vec{r}_\alpha(t)$
   Vector2d curr_pos;
   // $\vec{e}_{\alpha}(t)$
-  Vector2d e;
+  Vector2d e;  // desired direction vector
   // $v_{\alpha}^{max} = 1.3 v^{0}_{\alpha}$
   double v_max;
   // $v_\alpha^0$

visualization.py

@@ -1,52 +1,63 @@
 import sys
 import pandas as pd
 import matplotlib.pyplot as plt
-
 from matplotlib.animation import FuncAnimation
 
-
+if len(sys.argv) < 2:
-
+    sys.exit("Use it like the following: python visualization.py positions.csv (out.mp4)")
-
-if len(sys.argv)<2:
-    sys.exit("Use it like the following: python visualization.py positions.csv (out.gif)")
-
 
 df = pd.read_csv(sys.argv[1])
 frames = sorted(df["time"].unique())
 
-fig, ax = plt.subplots(figsize = (10,2.2))
+fig, ax = plt.subplots(figsize=(10, 2.2))
 ax.set_xlim(0, 50); ax.set_ylim(0, 10)
 ax.set_aspect("equal"); ax.set_facecolor("white")
 ax.set_xticks([]); ax.set_yticks([])
 for s in ("top", "right", "left", "bottom"):
     ax.spines[s].set_color("gray")
 
-
+s_white = ax.scatter([], [], s=30, facecolors="black", edgecolor="black", zorder=2)
-# Lets define the 2 groups
+s_black = ax.scatter([], [], s=30, facecolors="white", edgecolor="black", zorder=2)
-# WHITE = 1 (left -> right, drawn as filled black circles, like paper)
-# BLACK = 0 (right -> left, drawn as empty circles)
-s_white = ax.scatter([],[], s=30, facecolors = "black", edgecolor = "black", zorder = 2)
-s_black = ax.scatter([],[], s=30, facecolors = "white", edgecolor = "black", zorder = 2)
-
-
-
-# update our graphic from t to t+1
 title = ax.set_title("")
+
+# Keep a reference to quiver objects so we can remove them each frame
+quivers = []
+
 def update(t):
     sub = df[df["time"] == t]
     w = sub[sub["color"] == 1]
     b = sub[sub["color"] == 0]
+
     s_white.set_offsets(w[["x", "y"]].values)
     s_black.set_offsets(b[["x", "y"]].values)
+
+    # Remove old quiver arrows
+    for q in quivers:
+        q.remove()
+    quivers.clear()
+
+    # Draw fresh arrows each frame
+    arrow_scale = 1.5  # Tune this to change arrow length visually
+    if len(w):
+        q_white = ax.quiver(w["x"], w["y"], w["p.e.x"], w["p.e.y"],
+                            color="black", angles="xy", scale_units="xy",
+                            scale=1/arrow_scale, width=0.003,
+                            headwidth=4, headlength=5, zorder=3)
+        quivers.append(q_white)
+    if len(b):
+        q_black = ax.quiver(b["x"], b["y"], b["p.e.x"], b["p.e.y"],
+                            color="gray", angles="xy", scale_units="xy",
+                            scale=1/arrow_scale, width=0.003,
+                            headwidth=4, headlength=5, zorder=3)
+        quivers.append(q_black)
+
     title.set_text(f"t = {t}")
     return s_white, s_black, title
 
-anim = FuncAnimation(fig,update, frames = frames, interval=50, blit=False)
+anim = FuncAnimation(fig, update, frames=frames, interval=50, blit=False)
-
-
 
 if len(sys.argv) >= 3:
     anim.save(sys.argv[2], writer="ffmpeg", fps=20)
-    print(f"saved {sys.argv[2]}")
+    print(f"Saved {sys.argv[2]}")
 else:
     plt.show()