version with 6 leds

make_artikel/grafiken/illustrationen/beaterkennung.py

@@ -1,3 +1,49 @@
 
 import matplotlib.pyplot as plt
+import numpy as np
 
+
+n_plots = 5
+endtime = 4
+size = 1000
+
+time = np.linspace(0,endtime,size)
+audio = 1023*np.random.random(size=(size))
+audio = 512+(audio-512)*(0.2)*np.sin(np.linspace(0,endtime*2*3.14*2, size))+(audio-512)*0.3
+
+fig, axs = plt.subplots(n_plots, 1)
+axs[0].plot(time,audio)
+
+audio_norm = audio-512
+axs[1].plot(time,audio_norm)
+
+spc = size/endtime
+
+
+
+audio_norm = np.array(audio_norm)
+audio_squared = np.square(audio_norm)
+
+axs[2].plot(time, audio_squared)
+
+spc = int(size/endtime/40)
+
+chunks = list()
+chunktimes = list()
+energy = 0
+i = 0
+for sample, timepoint in zip(audio_squared, time):
+    energy += sample
+    i += 1
+    if i > spc:
+        i = 0
+        chunks.append(energy)
+        chunktimes.append(timepoint)
+        energy = 0
+
+axs[3].plot(chunktimes, chunks)
+
+
+
+
+plt.show()