From bb1e6c1f126b46d91b4f6dbe9e5cd4b22fd15c21 Mon Sep 17 00:00:00 2001
From: Yael-II <154762804+Yael-II@users.noreply.github.com>
Date: Wed, 22 Jan 2025 19:05:46 +0100
Subject: [PATCH] removed unused file

---
 Source/TODO_chaos.py | 73 --------------------------------------------
 1 file changed, 73 deletions(-)
 delete mode 100644 Source/TODO_chaos.py

diff --git a/Source/TODO_chaos.py b/Source/TODO_chaos.py
deleted file mode 100644
index 7ad29c9..0000000
--- a/Source/TODO_chaos.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.integrate import quad
-
-import potentials as pot
-import integrator as itg
-import initial_conditions as init
-
-DEFAULT_N_iter = 30000
-DEFAULT_N_part = 100
-DEFAULT_h = 0.01
-DEFAULT_c = 1.7
-
-E_all = np.array([1/100, 1/12, 1/10, 1/8, 1/6])
-
-
-
-def compute_coordinates(E: float,
-                        N_iter: int = DEFAULT_N_iter,
-                        N_part: int = DEFAULT_N_part,
-                        h: float = DEFAULT_h) -> tuple:
-    W_part = init.n_energy_part(pot.hh_potential, N_part, E)
-
-    # Perform integration
-    t_part, coord_part = itg.rk4(0, W_part, h, N_iter, pot.hh_evolution)
-
-    # Extract positions and velocities
-    x_part = coord_part[:, 0, 0]
-    y_part = coord_part[:, 0, 1]
-    u_part = coord_part[:, 1, 0]
-    v_part = coord_part[:, 1, 1]
-
-    return t_part, x_part, y_part, u_part, v_part
-
-def x(t: float,
-      x_part: np.ndarray,
-      h: float = DEFAULT_h):
-    return x_part[t//h]
-
-def theta(t: float, 
-          x,
-          x_part: np.ndarray,
-          c: float = DEFAULT_c, 
-          h: float = DEFAULT_h,
-          ds: float = DEFAULT_h):
-    """theta(t) = c*t + int_0^t phi(x(s)) ds"""
-    I = quad(lambda s: x(s, x_part), 0, t)
-    return c*t + I
-
-def p(t: float,
-      x,
-      theta,
-      x_part: np.ndarray,
-      h: float = DEFAULT_h,
-      ds: float = DEFAULT_h):
-    I = quad(lambda s: x(s, x_part)*cos(theta(s, x, x_part)), 0, t)
-    return I
-
-def M(t,
-      p,
-      x_part: np.ndarray,
-      h: float = DEFAULT_h,
-      dtau: float = DEFAULT_h):
-    I = quad(lambda tau: (p(t+tau, x, theta, x_part) 
-                          - p(tau, x, theta, x_part)))**2, 0, np.max(t))
-    return I
-
-if __name__ == "__main__":
-    for i in range(len(E_all)):
-        E = E_all[i]
-        t_part, x_part, y_part, v_part, u_part = compute_coordinates(E)
-        I = M(t_part, x_part)
-