Created basic outline of Displayer class

display/dislpay_2d.py

@@ -0,0 +1,35 @@
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+import numpy as np
+import matplotlib.gridspec as gridspec
+from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
+import functools
+
+
+class Displayer:
+    def __init__(self, width, height):
+        self._fig, self._ax = plt.subplots()
+        self._fig.set_figwidth(width)
+        self._fig.set_figheight(height)
+        self._xdata, self._ydata = [], []
+        self._obj, = plt.plot([], [], 'ro')
+        self._circle = plt.Circle((5, 5), 1, color='r', fill=False)
+    
+        self._objects = [self._obj, self._circle]
+
+    def __init_animation(self):
+        self._ax.set_xlim(0, 20)
+        self._ax.set_ylim(0, 20)
+        self._ax.add_patch(self._circle)
+        return self._objects
+
+    def __update_animation(self, t):
+        self._obj.set_data([t, t])
+        self._circle.center = (t, t)
+        self._circle.radius = t*0.1
+        return self._objects
+
+    def animate(self, n_steps):
+        anim = FuncAnimation(self._fig, self.__update_animation, frames=np.linspace(0, n_steps-1, n_steps),
+                            init_func=self.__init_animation, blit=True)
+        plt.show()

examples/gps_fusion.py

@@ -0,0 +1,13 @@
+import matplotlib.pyplot as plt
+import numpy as np
+from time import sleep
+from matplotlib.animation import FuncAnimation
+
+from display.dislpay_2d import Displayer
+
+
+
+def run():
+    disp = Displayer(width=6, height=6)
+   # disp.show_object([1, 1], 4, "green")
+    disp.animate(n_steps = 100)

examples/gps_measurement.py

@@ -1,4 +1,3 @@
-from filter.kalman_filter import LinearKalmanFilter
 import matplotlib.pyplot as plt
 import csv
 import numpy as np
@@ -53,7 +52,7 @@ The reset of the parameters are empirically determined
 """
 
 
-def simulate(kalman_filter_t):
+def run(kalman_filter_t):
     # Read data
     
     x0_actual     = [48.993552704, 8.371038159]

examples/second_order_system.py

@@ -1,4 +1,3 @@
-from filter.kalman_filter import LinearKalmanFilter
 import matplotlib.pyplot as plt
 import numpy as np
 
@@ -25,7 +24,7 @@ The reset of the parameters are empirically determined
 """
 
 
-def simulate(kalman_filter_t):
+def run(kalman_filter_t):
     # Simulation parameter definitions
 
     n_iterations = 500

main.py

@@ -1,11 +1,13 @@
 from examples import gps_measurement as gps
 from examples import second_order_system as sos
-from filter.kalman_filter import LinearKalmanFilter
+from examples import gps_fusion
 
 
 def main():
-    gps.simulate(LinearKalmanFilter)
-    #sos.simulate(LinearKalmanFilter)
+    #gps.run(LinearKalmanFilter)
+    #sos.run(LinearKalmanFilter)
+    gps_fusion.run()
+    
 
 if __name__ == '__main__':
     main()