gps_fusion.py now shows second order system results with the Displayer (position, not yet uncertainty)
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@ -3,16 +3,13 @@ from matplotlib.animation import FuncAnimation
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import numpy as np
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#
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# Displayer class
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#
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class Displayer:
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def __init__(self, width, height):
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def __init__(self, width, height, frame_interval=50):
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self._fig, self._ax = plt.subplots()
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self._fig.set_figwidth(width)
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self._fig.set_figheight(height)
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self._frame_interval = frame_interval
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self._object_map = {}
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self._circle_map = {}
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self._objects = []
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@ -31,14 +28,12 @@ class Displayer:
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return self._objects
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#
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# Functions for initalization
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#
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def set_axis_limits(self, min, max):
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self._xlim = (min, max)
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self._ylim = (min, max)
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def set_axis_limits(self, xlim, ylim):
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self._xlim = xlim
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self._ylim = ylim
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def register_object(self, obj_name, obj_color='r'):
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@ -49,22 +44,18 @@ class Displayer:
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self._objects.append(self._circle_map[obj_name])
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#
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# Functions to be used in the animation callback
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#
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def move_object(self, obj_name, x, y):
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self._object_map[obj_name].set_data([x, y])
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self._circle_map[obj_name].center = (x, y)
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def move_object(self, obj_name, position):
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self._object_map[obj_name].set_data(position)
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self._circle_map[obj_name].center = position
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def set_circle_radius(self, obj_name, r):
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self._circle_map[obj_name].radius = r
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#
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# Start the animation
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#
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def animate(self, n_steps, anim_callback):
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@ -72,6 +63,10 @@ class Displayer:
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anim_callback(self, t)
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return self._objects
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anim = FuncAnimation(self._fig, anim_callback_wrapper, frames=np.linspace(0, n_steps-1, n_steps),
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init_func=self.__init_animation, blit=True)
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anim = FuncAnimation(self._fig,
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anim_callback_wrapper,
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n_steps,
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interval=self._frame_interval,
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init_func=self.__init_animation,
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blit=True)
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plt.show()
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@ -6,17 +6,57 @@ from matplotlib.animation import FuncAnimation
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from display.dislpay_2d import Displayer
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def update(disp, t):
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disp.move_object("test", t, t)
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disp.move_object("test2", 20-t, t)
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disp.set_circle_radius("test", t*0.2)
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def run(kalman_filter_t):
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# Simulation parameter definitions
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n_iterations = 500
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std_dist = [30, 0.5]
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x0_actual = [50, 3]
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x_actual = np.zeros([n_iterations, 2])
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x_kalman = np.zeros([n_iterations, 2])
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x_measurement = np.zeros([n_iterations, 2])
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def run():
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disp = Displayer(width=6, height=6)
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# Kalman Filter parameter definition
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disp.set_axis_limits(min=0, max=20)
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x0 = [100, 50]
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P0 = [[10, 0], [0, 5]]
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H = [[1, 0], [0, 1]]
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Q = [[0.2, 0], [0, 2]]
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F = [[1, 1], [0, 1]]
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G = 0
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R = [[std_dist[0]**2, 0], [0, std_dist[1]**2]]
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x_actual[0] = x0_actual
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x_kalman[0] = x0
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# Simulation
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f = kalman_filter_t(x0, P0, H, Q, F, G)
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for i in range(1, n_iterations):
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measurement = np.dot(F,x_actual[i-1]) + np.random.normal([0,0], std_dist)
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f.step(measurement, R, 0)
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x_actual[i] = np.dot(F, x_actual[i-1])
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x_kalman[i] = f.x
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x_measurement[i] = measurement
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# Show results
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def update(disp, t):
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disp.move_object("test", [x_kalman[:, 0][t], 0])
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disp.set_circle_radius("test", t*0.2)
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disp = Displayer(width=6, height=6, frame_interval=50)
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disp.set_axis_limits(xlim=[0, 1000], ylim=[-500, 500])
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disp.register_object("test", "red")
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disp.register_object("test2", "black")
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disp.animate(n_steps = 20, anim_callback=update)
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disp.animate(n_steps=n_iterations, anim_callback=update)
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5
main.py
5
main.py
@ -1,13 +1,14 @@
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from examples import gps_measurement as gps
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from examples import second_order_system as sos
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from examples import gps_fusion
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from filter.kalman_filter import LinearKalmanFilter
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def main():
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#gps.run(LinearKalmanFilter)
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#sos.run(LinearKalmanFilter)
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gps_fusion.run()
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gps_fusion.run(LinearKalmanFilter)
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if __name__ == '__main__':
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main()
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