def plot_npendulum(self, ax, m, time=999): func = simulation.step(m, 1000 * self.dt) s = simulation.simulate(self.n, self.x0, self.dt, func) s_cartesian = simulation.cartesian(self.n, s[time]) x = s_cartesian[:len(s_cartesian) / 2] y = s_cartesian[len(s_cartesian) / 2:] ax.plot(x, y) ax.plot(x[0], y[0], 'o', ms=6) ax.plot(x[-1], y[-1], 's', ms=6)
def compute_sensori_effect(self, m): """ This function generates the end effector position at the end of the movement. .. note:: The duration of the movement is 1000*self.dt .. note:: To use basis functions rather than step functions, set :use_basis_functions: to 1 """ if self.use_basis_functions: func = simulation.step(m, 1000 * self.dt) else: traj = self.bf.trajectory(m).flatten() func = lambda t: traj[int(1000 * self.dt * t)] states = simulation.simulate(self.n, self.x0, self.dt, func) last_state_cartesian = simulation.cartesian(self.n, states[-1]) end_effector_pos = array( [last_state_cartesian[self.n], last_state_cartesian[2 * self.n]]) end_effector_pos += self.noise * random.randn(len(end_effector_pos)) return end_effector_pos
def GET(self): step(myGrid)