implement plotting function on log scale #9

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maksimva wants to merge 1 commit from maksimva/2024-heraklion-parallel-python:plot-log-solution into main
2 changed files with 15 additions and 4 deletions
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@ -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(',')
threads.append(int(n))
timings.append(float(t))
if 'None' not in file:
n, t = f.read().strip().split(',')
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)

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