r = [1, 5]
w = [2*np.pi, 1]
sample_rate = 20
d_t = 1 / sample_rate
d_theta = [el * d_t for el in w]
num_steps = 140
theta = [[(d_theta[j] * i) % (2 * np.pi) for j in range(2)] for i in range(num_steps)]
lines = [[[r[j] * cos(loc[j]), r[j] * sin(loc[j])] for j in range(2)] for loc in theta]
fig, ax = plt.subplots(figsize=(10,10))
ax.set_aspect('equal')
ax.autoscale()
for i in range(2):
t = np.linspace(0, 2 * np.pi,500)
x_1 = r[i] * np.cos(t)
y_1 = r[i] * np.sin(t)
ax.plot(x_1,y_1,'k');
for line in lines:
line = np.array(line).T
ax.plot(*line, 'b', linewidth=.5)