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Merge branch 'smail' into lbaumberger

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lbaumberger
2026-04-27 14:25:29 +02:00
parent 1b79bd15f4 cde82faa4d
commit 1cf29bfdd8
5 changed files with 174 additions and 227 deletions
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main.cpp
+43 -115
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@@ -2,15 +2,14 @@
#include "forces.hpp"
#include "math.h"
#include "pedestrian.hpp"
#include "tsc_x86.h"
#include "vector2d.hpp"
#include <fstream>
#include <iostream>
#include <tuple>
#include <vector>
#define BOARD_WIDTH 10.0
#define BOARD_LENGTH 50.0
double g(double v_max_alpha, double w_alpha_norm) {
if (w_alpha_norm <= v_max_alpha) {
return 1;
}
return v_max_alpha / w_alpha_norm;
}
using namespace std;
@@ -24,140 +23,69 @@ using namespace std;
Pedestrian *init_pedestrians(int n_p) {
Pedestrian *P = new Pedestrian[n_p];
std::random_device rd; // use for truly random simulation
// std::mt19937 gen(rd()); // use rd instead of 42 as seed for real randomness
std::mt19937 gen(42); // use fixed seed for reproducibility
std::normal_distribution<double> velocity_gen(1.34, 0.26); // 1.34 and 0.26 are the mean and stdrd deviation used in paper
std::uniform_real_distribution<double> x_gen(2, BOARD_LENGTH - 2);
std::uniform_real_distribution<double> y_gen(2, BOARD_WIDTH - 2);
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);
// double desired_v0 = velocity_gen(gen);
double desired_v0;
do {
desired_v0 = velocity_gen(gen);
} while (desired_v0 <= 0.1); // to avoid small values (Way below the social force -> that would make the walk backwards) (we discovered some weird stuff in the simulation)
double v_max = 1.3 * desired_v0;
P[i] = Pedestrian(WHITE, (destination - start_pos) / (destination - start_pos).norm() * desired_v0, start_pos, (destination - start_pos) / (destination - start_pos).norm(), v_max, desired_v0, destination, Vector2d());
}
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);
// double desired_v0 = velocity_gen(gen);
double desired_v0;
do {
desired_v0 = velocity_gen(gen);
} while (desired_v0 <= 0.1);
double v_max = 1.3 * desired_v0;
P[i] = Pedestrian(BLACK, (destination - start_pos) / (destination - start_pos).norm() * desired_v0, start_pos, (destination - start_pos) / (destination - start_pos).norm(), v_max, desired_v0, destination, Vector2d(0, 0));
for (int i = 0; i < n_p; i++) {
P[i] = Pedestrian();
}
return P;
}
Board init_board(int width, int length) {
Vector2d obs[] = {Vector2d(2.0, 1.0), Vector2d(4.0, 1.0), Vector2d(6.0, 2.0), Vector2d(6.0, 4.0)};
return Board(width, length, 4, obs);
}
int main(int argc, const char *argv[]) {
Obstacle obs[] = {};
Board board = Board(BOARD_LENGTH, BOARD_WIDTH, 0, obs);
Board B = init_board(10, 15);
int n_p = atoi(argv[1]);
int n_iter = atoi(argv[2]);
// Logic to get/dump the simulation data
const int dump_interval = 5; // 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
if (dump_path)
samples.reserve((size_t)n_iter / dump_interval * n_p);
Pedestrian *pedestrians = init_pedestrians(n_p);
// # Start here or right after function signature
uint64_t start = start_tsc();
// # (8 + 55N - 55 + 192 + 4 + 8 + 4 + 10)*n_p*n_iter
for (int t = 0; t < n_iter; t++) {
// Pass1: conmpute all forces from the current state
for (int i = 0; i < n_p; i++) {
Pedestrian &p = pedestrians[i];
p.f_i.reset();
p.F_i.reset();
// # 8 flops
//
// $\vec{F}_\alpha(\vec{v}_\alpha, v^0_\alpha \vec{e}_\alpha) \vec{e}_\alpha(t) = \frac{1}{\tau_\alpha}(v^0_\alpha \vec{e}_\alpha - \vec{v}_\alpha)$
//
compute_acceleration_term(&p);
// # 55N - 55 flops
//
// $\sum_{\beta} \vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
//
compute_repulsive_effects_from_pedestrians(pedestrians, &p, n_p);
// # 192 flops
compute_repulsive_effects_from_borders(board, &p);
//
// $\sum_{B} \vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{B})$
//
compute_repulsive_effects_from_borders(B, &p);
//
// $\vec{w}_i = \vec{v}_i + \vec{F}_idt$
//
p.w_alpha = p.curr_vel + p.F_i * delta_t;
//
// $\vec{v}_i^{t+1} = \vec{w}_ig(\frac{v^{max}_i}{\Arrowvert \vec{w}_i \Arrowvert}) $
//
p.next_vel = p.w_alpha * g(p.v_max, p.w_alpha.norm());
//
// $\vec{r}_i^{t+1} += \vec{r}^t_i + v^t_idt$
//
p.curr_pos = p.curr_pos + p.curr_vel * delta_t;
}
// Pass2: integrate the forces and update the current state
for (int i = 0; i < n_p; i++) {
Pedestrian &p = pedestrians[i];
// # 4 flops = 2 ADDs, 2 MULTs
// integrate preferred velocity: dw/dt = F (Eq. 10)
p.w = p.w + p.f_i * dt;
// Vector2d w_alpha = p.curr_vel + p.f_i * dt; // commented since this was using p.curr_vel instead of p.w (different from paper)
// # 8 flops = 2 MULTs, 2 DIVs, 1 SQRT, 2 MULTs, 1 ADD
p.curr_vel = p.w * g(p.v_max, p.w.norm());
// # 4 flops = 2 ADDs, 2 MULTs
p.curr_pos = p.curr_pos + p.curr_vel * dt;
// how to handle if a pedestrian reached the end of our simulation/end of the hallway
// The option we do here is to just "teleport" the person back to the beginning
// the good thing is we will have a constant flow of pedestrians and in the simulation we should see how lines build up
if (p.color == WHITE && p.curr_pos.x > (BOARD_LENGTH - 1.5)) {
// basically just keep the y position and reset the x
p.curr_pos.x = 1.0;
p.destination.y = p.curr_pos.y;
}
if (p.color == BLACK && p.curr_pos.x < 1.5) {
p.curr_pos.x = BOARD_LENGTH - 1.0;
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();
// 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);
}
}
}
long long W = (long long)(8 + 55 * n_p - 55 + 192 + 4 + 8 + 4 + 10) * n_p * n_iter;
std::cout << "W(n): ";
std::cout << W;
std::cout << " flops\n";
double T = stop_tsc(start);
std::cout << "T(n): ";
std::cout << T;
std::cout << " cycles\n";
double P = W / T;
std::cout << "P(n): ";
std::cout << P;
std::cout << " flops/cycle\n";
// now we wanna save the data to a csv
if (dump_path) {
std::ofstream out(dump_path);
out << "time,id,x,y,color\n";
for (auto &[t, id, x, y, c] : samples) {
out << t << ',' << id << ',' << x << ',' << y << ',' << c << '\n';
pedestrians[i].update();
}
}
delete[] pedestrians;
return 0;
}