Visualize the results of all the aggregated stats profiles

get_stats_profile_visualization.py

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter

WIDTH = 0.4

ind = np.arange(len(time_sliced_counters))

x_axis = tuple(time for (time, c) in time_sliced_counters)
y_axis = [[] for _ in range(len(headers))]
for idx, header in enumerate(headers):
    for (time, counter) in time_sliced_counters:
        y_axis[idx].append(counter[header])

fig = matplotlib.pyplot.gcf()
fig.set_size_inches(18.5, 10.5)  

boxes = []
titles = []
bottom = np.zeros(len(y_axis[0]))
for idx, header in enumerate(headers):
    p = plt.bar(ind, tuple(y_axis[idx]), WIDTH, bottom=bottom)
    bottom += np.array(y_axis[idx])
    boxes.append(p[0])
    titles.append(header)

plt.ylabel("Total time (s)", fontsize=12)
plt.yticks(np.arange(0, round(max(bottom) + 5), 1), fontsize=12)
plt.gca().yaxis.set_major_formatter(FormatStrFormatter('%.2f'))

plt.xlabel('time (epoch)', fontsize=12)
plt.xticks(ind, x_axis, fontsize=12, rotation=45)

plt.title(f"Application profile at {TIME_SLICE}s time slices")
plt.legend(tuple(boxes), tuple(titles), fontsize=12, ncol=3, fancybox=True, loc='upper center', bbox_to_anchor=(0.5, -0.2), shadow=True)

plt.show()