4.backup

jar_functions.py

@@ -0,0 +1,24 @@
+import os
+
+
+def parse_dataset(dataset_name):
+    assert(os.path.exists(dataset_name))
+    f = open(dataset_name, 'r')
+    lines = f.readlines()
+    f.close()
+
+    time = []
+    frequency = []
+    amplitude = []
+
+    for i in range(len(lines)):
+        l = lines[i].strip()
+
+        if len(l) > 0 and l[0] is not '#':
+            temp = list(map(float, l.split()))
+
+            time.append(temp[0])
+            frequency.append(temp[1])
+            amplitude.append(temp[2])
+
+    return time, frequency, amplitude

second_try.py

@@ -2,35 +2,31 @@ import matplotlib.pyplot as plt
 import os
 import glob
 import IPython
+import numpy as np
 from IPython import embed
+from jar_functions import parse_dataset
+
+
+dataset = os.path.join('D:\\', 'jar_project', 'JAR', '2020-06-22-ac', 'beats-eod.dat')
+
+t, f, a = parse_dataset(dataset)
+
+avg_frequency = np.mean(f)
+print(avg_frequency)
 
-def parse_dataset(dataset_name):
-    assert(os.path.exists(dataset_name))
-    f = open(dataset_name, 'r')
-    lines = f.readlines()
-    f.close()
 
-    time = []
-    frequency = []
-    amplitude = []
 
-    for i in range(len(lines)):
-        print(lines[i])
-        l = lines[i].strip()
 
-        if len(l) > 0 and l[0] is not '#':
-            temp = list(map(float, l.split()))
 
-            time.append(temp[0])
-            frequency.append(temp[1])
-            amplitude.append(temp[2])
 
-    return time, frequency, amplitude
 
 
-dataset = os.path.join('D:\\', 'jar_project', 'JAR', '2020-06-22-ac', 'beats-eod.dat')
 
-t, f, a = parse_dataset(dataset)
 
 plt.plot(t, f)
-plt.show()
+
+plt.xlabel('time [s]')
+plt.ylabel('frequency [Hz]')
+plt.xlim([-10,200])
+plt.title('second try because first try was sold out')
+plt.show()