Animation of a clock to understand the parameters

animation_script.py

@@ -0,0 +1,29 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.animation as animation
+
+
+fig = plt.figure(figsize=(16, 12))
+ax = fig.add_subplot(111)
+# You can initialize this with whatever
+im = ax.imshow(np.random.rand(6, 10), cmap='bone_r', interpolation='nearest')
+
+
+def animate(i):
+    aux = np.zeros(60)
+    aux[i] = 1
+    image_clock = np.reshape(aux, (6, 10))
+    im.set_array(image_clock)
+
+ani = animation.FuncAnimation(fig, animate, frames=60, interval=2000)
+ani.save('clock.mp4', fps=1.0, dpi=200)
+plt.show()
+
+"""Interval is for the printing animation. So in this case, the animation that will be reproduced
+that is, the one that is not saved, by changing the image every 2 seconds (interval=2000 (ms))*[]:
+
+The fps (frames per second) in the other hand is for the image that will be saved.
+"""
+
+
+

digit_recall.py

@@ -22,7 +22,7 @@
 data[data >= 8] = 1
 
 # Let's get two images and learn them as a pattern
-number_of_patterns = 10
+number_of_patterns = 2
 patterns = []
 for i in range(number_of_patterns):
     patterns.append(data[i])
@@ -36,7 +36,7 @@
 beta = get_beta(p)
 
 # Here we have the evolution
-T = 100
+T = 10
 dt = 0.1
 tau_m = 1.0
 G = 1.0
@@ -87,5 +87,8 @@ def update_system():
 ax11.set_title('Final image')
 ax11.set_axis_off()
 
+fig.subplots_adjust(right=0.8)
+cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
+fig.colorbar(im11, cax=cbar_ax)
 
-fig.show()
+plt.show()

digit_recall_animation.py

@@ -41,7 +41,7 @@
 beta = get_beta(p)
 
 # Here we have the evolution
-T = 1000
+T = 10
 dt = 0.1
 tau_m = 1.0
 G = 1.0
@@ -76,3 +76,4 @@ def update(*args):
 
 ani = animation.FuncAnimation(fig, update, frames=40, interval=200, blit=True)
 ani.save('animation.mp4', fps=2, dpi=200)
+plt.show()