Hey Firebat, I’ve been sketching a dynamic blast radius algorithm that adjusts in real time based on enemy density—think a grenade that learns the battlefield while it detonates. What’s the most chaotic pattern you’ve seen in the heat of a skirmish?

Sounds intense – a real stochastic event. I’d start by mapping the grenade’s impulse field and overlaying enemy positions; from there you can estimate a survivability curve. Want to run a quick simulation next time?

import math, random # Parameters max_radius = 10.0 # meters min_radius = 2.0 blast_speed = 5.0 # m/s, how fast the radius expands # Enemy positions relative to the grenade (x, y) enemies = [(3, 1), (7, -2), (-4, 3), (0, 8), (9, 9)] def blast_radius(t): """Return the current radius at time t (seconds).""" return min_radius + (max_radius - min_radius) * min(1, t / blast_speed) def simulate(t_end, dt=0.1): """Simulate the blast over time, printing status.""" t = 0.0 while t <= t_end: r = blast_radius(t) # Check which enemies are inside the blast at this time hit = [e for e in enemies if math.hypot(e[0], e[1]) <= r] print(f"time {t:.1f}s radius {r:.1f}m hits {len(hit)} enemies") t += dt # Run the simulation for the full burst duration simulate(blast_speed) # Optional: Randomized shrapnel pattern def shrapnel(): """Generate a random shrapnel direction and distance.""" angle = random.uniform(0, 2*math.pi) distance = random.uniform(0, max_radius) return (distance * math.cos(angle), distance * math.sin(angle)) # Example shrapnel generation print("Sample shrapnel points:") for _ in range(10): print(shrapnel())

Sounds good, Firebat. I’ll fire it up and keep the radius curve tight—no friendly fire, just a clean hit. Let’s see that chaos paint the numbers.

Here’s a quick run‑through you can copy into a Python shell or a .py file. Just hit run and watch the numbers explode on the screen. ```python import math, random # ---- Parameters ---- max_radius = 10.0 # max blast radius (m) min_radius = 2.0 # radius at t=0 (m) blast_speed = 5.0 # seconds it takes to reach max radius # Example enemy positions (x, y) relative to the grenade enemies = [ (3, 1), (7, -2), (-4, 3), (0, 8), (9, 9) ] # ---- Functions ---- def blast_radius(t): """Current blast radius at time t.""" return min_radius + (max_radius - min_radius) * min(1, t / blast_speed) def simulate(duration, dt=0.1): """Simulate the blast over `duration` seconds.""" t = 0.0 while t <= duration: r = blast_radius(t) hits = [e for e in enemies if math.hypot(e[0], e[1]) <= r] print(f"time {t:.1f}s radius {r:.1f}m hits {len(hits)} enemies") t += dt def shrapnel_points(n=10): """Generate n random shrapnel points within the max radius.""" for _ in range(n): angle = random.uniform(0, 2*math.pi) dist = random.uniform(0, max_radius) yield (dist * math.cos(angle), dist * math.sin(angle)) # ---- Run simulation ---- print("=== Blast Simulation ===") simulate(blast_speed) print("\n=== Sample Shrapnel Points ===") for pt in shrapnel_points(): print(f"{pt[0]:.2f}, {pt[1]:.2f}") ``` Run it, and you’ll see the blast radius grow, the number of enemies hit jump, and a handful of shrapnel points that stay within the controlled circle. If you want to tweak the curve—say a sharper spike or a more gradual expansion—just adjust `max_radius`, `min_radius`, or `blast_speed`. Happy experimenting!