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import math
import os
from matplotlib import pyplot as plt
distribution_names = {
"shuffled_16_values_int": "Shuffled (16 values)",
"shuffled_int": "Shuffled",
"all_equal_int": "All equal",
"ascending_int": "Ascending",
"descending_int": "Descending",
"pipe_organ_int": "Pipe organ",
"push_front_int": "Push front",
"push_middle_int": "Push middle"
}
for filename in os.listdir("profiles"):
data = {}
for line in open(os.path.join("profiles", filename)):
size, distribution, algo, *results = line.split()
size = int(size)
distribution = distribution_names[distribution]
results = [int(result) for result in results]
if not size in data: data[size] = {}
if not distribution in data[size]: data[size][distribution] = {}
data[size][distribution][algo] = results
def skin_boxplot(bp):
plt.setp(bp["boxes"], color="black")
plt.setp(bp["fliers"], color="black")
plt.setp(bp["whiskers"], color="black")
plt.setp(bp["medians"], color="black", linewidth=3, solid_capstyle="butt")
size = 10**6
distributions = ("Shuffled", "Shuffled (16 values)", "All equal", "Ascending", "Descending", "Pipe organ", "Push front", "Push middle")
algos = ("heapsort", "introsort", "pdqsort")
if "timsort" in data[size]["Shuffled"]: algos += ("timsort",)
groupnames = distributions
groupsize = len(algos)
groups = [[data[size][distribution][algo] for algo in algos] for distribution in distributions]
for i, group in enumerate(groups):
skin_boxplot(plt.boxplot(group, positions=[.75 + (0.5 + groupsize)*i + n for n in range(groupsize)], widths=0.6))
# Set axes limits and labels.
plt.margins(0.1)
plt.xticks([0.25 + (groupsize)/2 + (0.5 + groupsize) * n for n in range(len(groupnames))], groupnames)
plt.xlim(0, (0.5 + groupsize) * len(groups))
plt.ylim(0, plt.ylim()[1] * 1.05)
plt.xlabel("Distribution")
plt.ylabel("Cycles per element")
# Turn off ticks for x-axis.
plt.tick_params(
axis="x",
which="both",
bottom="off",
top="off",
labelbottom="on"
)
ax = plt.gca()
for i in range(len(groups)):
for n in range(groupsize):
ax.text(0.75 + (0.5 + groupsize) * i + n, plt.ylim()[1] * 0.92, str(n + 1), horizontalalignment="center", size="x-small")
for i in range(len(groups) - 1):
x = (1 + i) * (0.5 + groupsize)
plt.plot((x, x), (0, plt.ylim()[1] * 0.95), "-", color="lightgrey")
plt.plot((0, plt.xlim()[1]), (plt.ylim()[1] * 0.95, plt.ylim()[1] * 0.95), "-", color="lightgrey")
plt.title("Sorting $10^{}$elements".format(round(math.log(size, 10))))
plt.suptitle(" ".join("({}) {}".format(n + 1, algo) for n, algo in enumerate(algos)), y=.885)
figure = plt.gcf() # get current figure
figure.set_size_inches(19.2, 10.8)
plt.savefig(os.path.join("plots", os.path.splitext(filename)[0] + ".png"), dpi = 100)
plt.clf()
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