upload exercises

exercises/exerciseC/plot.py

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+import os
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patheffects as PathEffects
+
+N_processes = 5
+N_threads = 5
+
+# Load measured timings
+times = np.empty((N_processes, N_threads))
+for fname in os.listdir('timings'):
+    values = open(f'timings/{fname}').read().split()
+    n_processes = int(values[0])
+    n_threads = int(values[1])
+    dt = float(values[2])
+    times[n_processes-1][n_threads-1] = dt
+print(times)
+
+""" Plot measured time"""
+fig_time, axs_time = plt.subplots()
+im = axs_time.imshow(times.T, origin='lower')
+axs_time.set_title('Computation time')
+fig_time.colorbar(im, ax=axs_time, label='Measured computation time (s)')
+
+""" Plot speedup """
+workers = np.arange(N_processes + 1)[:, None] * np.arange(N_threads + 1)
+speedup = times[0, 0] / times
+
+fig_speedup, axs_speedup = plt.subplots()
+im = axs_speedup.imshow(speedup.T, origin='lower')
+axs_speedup.set_title('Computation speed-up')
+fig_speedup.colorbar(im, ax=axs_speedup, label='Speed-up')
+
+# Set same style for both plots
+for axs, data in zip([axs_time, axs_speedup], [times, speedup]):
+    axs.set_xlabel('# processes')
+    axs.set_ylabel('# threads')
+    axs.set_xticks(np.arange(N_processes))
+    axs.set_xticklabels(np.arange(N_processes)+1)
+    axs.set_yticks(np.arange(N_threads))
+    axs.set_yticklabels(np.arange(N_threads)+1)
+
+    for i in range(N_processes):
+        for j in range(N_threads):
+            txt = axs.text(i, j, f'{data[i, j]:.2f}', fontsize=10, color='w',
+                        ha='center', va='center', fontweight='bold')
+            txt.set_path_effects([PathEffects.withStroke(linewidth=0.5, foreground='k')])
+    axs.spines[['right', 'top']].set_visible(False)
+
+# Save plots
+fig_time.savefig('time.png', dpi=300)
+fig_speedup.savefig('speedup.png', dpi=300)
+