implement plotting function on log scale

exercises/exerciseA/plot.py

@@ -1,14 +1,19 @@
 import os
 import numpy as np
 import matplotlib.pyplot as plt
+import pdb
+import glob
 
 # IO: This loads the timings for you 
 threads, timings = [], []
-for file in os.listdir('timings'):
+files = os.listdir('timings')
+files.sort(key= lambda x: int(x.split('_')[0]))
+for file in files:
     with open(f'timings/{file}', 'r') as f:
-        n, t = f.read().strip().split(',')
+        if 'None' not in file:
-        threads.append(int(n))
+            n, t = f.read().strip().split(',')
-        timings.append(float(t))
+            threads.append(int(n))
+            timings.append(float(t))
 threads = np.array(threads)
 timings = np.array(timings)
 
@@ -17,7 +22,13 @@ print('This is the data I loaded: threads =', threads, ', timings =',timings)
 fig, axs = plt.subplots()
 
 # CREATE YOUR PLOT HERE
+plt.plot(threads, timings, '.--')
+plt.xlabel('Threads')
+plt.ylabel('Timings')
+plt.xscale('log')
+
 # Remember to label your axis
 # Feel free to make it pretty
 
+
 plt.savefig('threads_v_timings.png', dpi=300)