"""Tier-1 physical systems: simple, single-variable, no damping.""" from __future__ import annotations import numpy as np from physix.systems.base import PhysicalSystem, SystemTier class FreeFall(PhysicalSystem): """Simple free fall under constant gravity. Equation of motion: ``d2y/dt2 = -g``. State variables: ``y`` (vertical position), ``vy`` (vertical velocity). """ system_id: str = "free_fall" tier: SystemTier = SystemTier.TIER_1 state_variables: tuple[str, ...] = ("y", "vy") duration: float = 3.0 # short enough that the object does not pass y=0 hint_template: str = ( "Object dropped near Earth's surface in vacuum. " "Mass {mass:.1f} kg, released from rest at altitude {y0:.1f} m." ) def sample_parameters(self, rng: np.random.Generator) -> dict[str, float]: return { "g": 9.81, "mass": float(rng.uniform(0.5, 5.0)), } def sample_initial_conditions(self, rng: np.random.Generator) -> dict[str, float]: return { "y": float(rng.uniform(20.0, 60.0)), "vy": 0.0, } def rhs( self, t: float, state: np.ndarray, params: dict[str, float], ) -> np.ndarray: _y, vy = state return np.array([vy, -params["g"]], dtype=float) def ground_truth_equation(self) -> str: return "d2y/dt2 = -g" def hint(self, parameters: dict[str, float]) -> str: ic = self.initial_conditions or {"y": 30.0} return self.hint_template.format(mass=parameters["mass"], y0=ic["y"]) class FreeFallWithDrag(PhysicalSystem): """Free fall with quadratic air drag — the demo system. Equation of motion: ``d2y/dt2 = -g + k * vy**2`` (drag opposes motion; when ``vy < 0`` the ``vy**2`` term provides a positive deceleration). """ system_id: str = "free_fall_drag" tier: SystemTier = SystemTier.TIER_1 state_variables: tuple[str, ...] = ("y", "vy") duration: float = 6.0 # long enough to clearly see terminal-velocity onset hint_template: str = ( "Object dropped from altitude {y0:.1f} m, mass {mass:.1f} kg, " "in air. Air resistance may be non-negligible." ) def sample_parameters(self, rng: np.random.Generator) -> dict[str, float]: return { "g": 9.81, "mass": float(rng.uniform(1.0, 3.0)), # Drag coefficient tuned so terminal velocity is reached within ~5s # for the altitudes we sample. "k": float(rng.uniform(0.02, 0.10)), } def sample_initial_conditions(self, rng: np.random.Generator) -> dict[str, float]: return { "y": float(rng.uniform(40.0, 80.0)), "vy": 0.0, } def rhs( self, t: float, state: np.ndarray, params: dict[str, float], ) -> np.ndarray: _y, vy = state # vy is negative on descent; vy**2 keeps the magnitude correct. return np.array([vy, -params["g"] + params["k"] * vy * vy], dtype=float) def ground_truth_equation(self) -> str: return "d2y/dt2 = -g + k * vy**2" def hint(self, parameters: dict[str, float]) -> str: ic = self.initial_conditions or {"y": 50.0} return self.hint_template.format(mass=parameters["mass"], y0=ic["y"]) class SimplePendulum(PhysicalSystem): """Idealised pendulum (small or large angle), no damping. Equation of motion: ``d2theta/dt2 = -(g / L) * sin(theta)``. """ system_id: str = "simple_pendulum" tier: SystemTier = SystemTier.TIER_1 state_variables: tuple[str, ...] = ("theta", "dtheta") hint_template: str = ( "Simple pendulum of length {L:.2f} m swinging in vacuum. " "No friction, no air resistance." ) def sample_parameters(self, rng: np.random.Generator) -> dict[str, float]: return { "g": 9.81, "L": float(rng.uniform(0.5, 2.0)), } def sample_initial_conditions(self, rng: np.random.Generator) -> dict[str, float]: return { "theta": float(rng.uniform(0.3, 1.0)), # ~17-57 degrees "dtheta": 0.0, } def rhs( self, t: float, state: np.ndarray, params: dict[str, float], ) -> np.ndarray: theta, dtheta = state return np.array( [dtheta, -(params["g"] / params["L"]) * np.sin(theta)], dtype=float, ) def ground_truth_equation(self) -> str: return "d2theta/dt2 = -(g / L) * sin(theta)"