我有三种算法,A,B和C.我在不同的数据集上运行它们,并希望将它们的运行时间绘制为Python中的分组箱图.
作为我想要的一个视觉例子,我做了一个可怕的绘画,但希望它能得到重点.
如果我在python中的数据如下所示:
import numpy as np
import random
data = {}
data['dataset1'] = {}
data['dataset2'] = {}
data['dataset3'] = {}
n = 5
for k,v in data.iteritems():
upper = random.randint(0, 1000)
v['A'] = np.random.uniform(0, upper, size=n)
v['B'] = np.random.uniform(0, upper, size=n)
v['C'] = np.random.uniform(0, upper, size=n)
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如何让我的情节看起来像我画的画面?
Joe*_*ton 15
使用独立的子图最简单:
import matplotlib.pyplot as plt
import numpy as np
import random
data = {}
data['dataset1'] = {}
data['dataset2'] = {}
data['dataset3'] = {}
n = 500
for k,v in data.iteritems():
upper = random.randint(0, 1000)
v['A'] = np.random.uniform(0, upper, size=n)
v['B'] = np.random.uniform(0, upper, size=n)
v['C'] = np.random.uniform(0, upper, size=n)
fig, axes = plt.subplots(ncols=3, sharey=True)
fig.subplots_adjust(wspace=0)
for ax, name in zip(axes, ['dataset1', 'dataset2', 'dataset3']):
ax.boxplot([data[name][item] for item in ['A', 'B', 'C']])
ax.set(xticklabels=['A', 'B', 'C'], xlabel=name)
ax.margins(0.05) # Optional
plt.show()
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