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python - 在 matplotlib 中显示小的标准偏差

问题描述

我有以下条形图，其中标准偏差太小而无法看到。y 轴使用对数刻度。是否可以配置脚本以显示标准偏差？

在此处输入图像描述 

from os import listdir
from os.path import isfile, join
import csv
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from collections import namedtuple
from matplotlib.pyplot import figure

NS_FILE = '..\\overhead.csv'

OUTPUT_PATH = '..\\'

sboti = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[1], names=['sboti'])
sboti_nds = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[2], names=['sboti_nds'])
greedy = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[3], names=['greedy'])
simdijkstra = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[4], names=['simdijkstra'])
random = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[5], names=['random'])

sboti_stdev = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[7], names=['sboti_stdev'])
sboti_nds_stdev = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[8], names=['sboti_nds_stdev'])
greedy_stdev = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[9], names=['greedy_stdev'])
simdijkstra_stdev = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[10], names=['simdijkstra_stdev'])
random_stdev = pd.read_csv(filepath_or_buffer=NS_FILE, header=None, usecols=[11], names=['random_stdev'])

sboti_list = sboti['sboti'].values.tolist()
sboti_nds_list = sboti_nds['sboti_nds'].values.tolist()
greedy_list = greedy['greedy'].values.tolist()
simdijkstra_list = simdijkstra['simdijkstra'].values.tolist()
random_list = random['random'].values.tolist()

sboti_stdev_list = sboti_stdev['sboti_stdev'].values.tolist()
sboti_nds_stdev_list = sboti_nds_stdev['sboti_nds_stdev'].values.tolist()
greedy_stdev_list = greedy_stdev['greedy_stdev'].values.tolist()
simdijkstra_stdev_list = simdijkstra_stdev['simdijkstra_stdev'].values.tolist()
random_stdev_list = random_stdev['random_stdev'].values.tolist()

n_groups = 4

fig, ax = plt.subplots()

fig.set_size_inches(10.5, 4.5, forward=True)

plt.yticks(fontsize=24)

index = np.arange(n_groups)
bar_width = 0.55

error_config = {'ecolor': '0.3'}

ax.grid(which='major', axis='y', linestyle='--') 

ax.bar(index, sboti_list, bar_width/5, color='r', 
       yerr=sboti_stdev_list, error_kw=error_config, label='Sboti')

ax.bar(index + bar_width * 0.25, sboti_nds_list, bar_width/5, color='cornflowerblue', 
       yerr=sboti_nds_stdev_list, error_kw=error_config, label='Sboti_nds')

ax.bar(index + bar_width * 0.5, greedy_list, bar_width/5, color='g', 
       yerr=greedy_stdev_list, error_kw=error_config, label='GoCoMo')

ax.bar(index + bar_width * 0.75, simdijkstra_list, bar_width/5, color='yellow', 
       yerr=simdijkstra_stdev_list, error_kw=error_config, label='SimDijkstra')

ax.bar(index + bar_width * 1.0, random_list, bar_width/5, color='orange', 
       yerr=random_stdev_list, error_kw=error_config, label='Random')

ax.set_xlabel('Configuration Size', fontsize=24, fontweight="bold")
ax.set_ylabel('Communication \n Overhead (#)', fontsize=24, fontweight="bold")
ax.set_xticks(index + bar_width * 0.6)
ax.set_xticklabels(('k=2', 'k=3', 'k=4', 'k=5'), fontsize=26)
ax.legend()

plt.legend(['SBOTI', 'SBOTI-NDS', 'GoCoMo', 'SimDijkstra', 'Random'],
           fontsize=24, loc='upper center', ncol=1, bbox_to_anchor=(1.225, 1.05), 
           borderpad=0.5, edgecolor='black', fancybox=False, handletextpad=0.05)


ax.set_yscale('log',nonposy='clip')
plt.ylim([0.0, 1000000.0])

fig.tight_layout()
plt.savefig(join(OUTPUT_PATH, 'overhead_plot_final.pdf'), bbox_inches='tight')
plt.show()

开销.csv 的内容：

k2,37460.22,37460.42,5928.02,60.56,352.26,,21.92593283334245,25.202923380805963,3128.397082487178,20.88858686518764,242.4525040800649
k3,99930.06,99932.76,4358.62,25.2,217.42,,76.54621386549994,82.02651636973927,516.8570595435453,5.941895526595833,26.101911729188863
k4,212409.94,212406.28,9603.56,29.5,430.18,,166.80495881632027,153.9937767096649,7.52725659432005,9.653697610295259,17.54724235558722
k5,416936.9,416930.14,18754.28,35.04,844.4,,31.603571226773,29.936674661623975,4.549231825713175,10.540417836275054,31.93040902350239

标签： pythonmatplotlib

解决方案

您可以替换如下所示的代码：

sboti_list = sboti['sboti'].values.tolist()
sboti_stdev_list = sboti_stdev['sboti_stdev'].values.tolist()
ax.bar(index, sboti_list, bar_width/5, color='r', 
       yerr=sboti_stdev_list, error_kw=error_config, label='Sboti')

通过删除将数据框列转换为列表的前两行并使用

ax.bar(index, sboti['sboti'], bar_width/5, color='r', 
       yerr=sboti_stdev['sboti_stdev'], error_kw=error_config, label='Sboti')

反而。这将清理一些代码混乱。

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