Added done Work

prak4/prak4/ADU-Kennlinie_manuell.csv

@@ -0,0 +1,6 @@
+Von,Bis,Code
+-5,-4.67,000
+-4.67,-4.0,001
+-4.0,-3.33,010
+-3.33,-2.67,011
+-2.67,-2,100

prak4/read.py

@@ -0,0 +1,51 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Feb 15 17:59:51 2018
+
+@author: Hauke Brunken
+"""
+
+import matplotlib.pyplot as plt
+plt.close()
+import numpy as np
+import mdt
+
+file = r"C:\Users\Student\Desktop\Neuer Ordner\Aliasingfilter_mit_box"
+
+rates=[10000,44000]
+for rate in rates:
+    data = mdt.dataRead(amplitude = 10, samplingRate = rate, duration = 1, channels = [0], resolution = 14, outType = 'Volt', continues=False )
+    f,u = mdt.spectrum(data, rate)
+    fig, (ax1,ax2) = plt.subplots(2)
+    ax1.plot(data)
+    ax2.plot(f,u)
+    Title= "Alialising Rechtecksignal Filtered" +str(rate/1000) +"kHz"
+    file_name = f"{file}_{rate}.csv"
+    with open(file_name, 'w') as f:
+        np.savetxt(f, data, delimiter=',')
+   # np.save(Title, data)
+    #plt.savefig('Alialasing' + strate + "Hz.pdf")
+
+#file = r"C:\Users\Student\Desktop\Neuer Ordner\Aliasing"
+
+#rates = [40000, 35000, 30000, 25000, 20000, 17500, 15000, 12500, 10000]
+
+
+#for i in range(len(rates)):
+#    data =  mdt.dataRead(amplitude=10, samplingRate=rates[i], duration=1, channels=[0], resolution=14, outType='Volt')
+#    file_name = f"{file}_{rates[i]}.csv"
+#    with open(file_name, 'w') as f:
+#        np.savetxt(f, data, delimiter=',')
+#data =  mdt.dataRead(amplitude=10, samplingRate=rates[len(rates)-1], duration=1, channels=[0], resolution=14, outType='Volt')
+#plt.plot(data, marker='x')
+#plt.show()
+    
+#plt.tight_layout() 
+#plt.show()
+#np.save("ADUKennlinie Sinussignal", data)
+#data = np.load("TP_5kOhm.npy")
+#plt.plot(data[0])
+#plt.plot(data[1])
+
+
+# hey ihr! holt euch euren eigenen code!