使用matplotlib python将表对齐到x轴

Question

我正在尝试将条形图的python表对齐。 例如，在附图中，您将看到x轴未正确对齐到python表所关闭的垂直线。

我试着修改图的比例

我希望表格的字体大小为40，以便在我打印IEEEtran纸张时可见。

#!/usr/bin/env python
import csv
import numpy as np
import matplotlib.pyplot as plt
import matplotlib

def plot_bar(dataset):
    matplotlib.rc('font', family='sans-serif')
    matplotlib.rc('font', serif='Helvetica Neue')
    matplotlib.rc('text', usetex='false')
    matplotlib.rcParams.update({'font.size': 30})
    fig = plt.figure()
    ax = fig.add_subplot(111)
    fig = matplotlib.pyplot.gcf()
    fig.set_size_inches(30.0,7.5)
    N = len(dataset[1])

    Load    = dataset[0]
    QoS     = dataset[1]
    Energy  = dataset[2]

    ind = np.arange(N)
    width = 0.35

    plt.tick_params(axis='both', which='major', labelsize=35, pad=15)
    plt.tick_params(axis='y', which='minor', labelsize=35, pad=15)



    rects1 = ax.bar(ind, QoS, width,
                color='0.2',
                label='HP')

    rects3 = ax.bar(ind+width, Energy, width,
                color='0.4',
                label='OM')

    lns = [rects1, rects3]
    labs = [l.get_label() for l in lns]

    ax.legend(lns, labs, ncol=2)

    ax.set_xlim(-width,len(ind)+width)
    ax.set_ylim(0, 16000)

    ax.set_ylabel('RPS/Watt', fontsize=35)
    ax.set_xlabel('Percentage of Max Capacity', fontsize=35)

    xTickMarks = dataset[0]
    ax.set_xticks(ind+width)
    xtickNames = ax.set_xticklabels(xTickMarks)
    plt.setp(xtickNames, rotation=0, fontsize=40)
    plt.xticks([])
    ax.yaxis.grid()

    cell_text = [['2S-0.65GHz', '3S-0.65GHz', '4S-0.65GHz', '4S-0.65GHz', '2B2S-1.15GHz', '2B2S-1.15GHz', '3B2S-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz','2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz'],
            ['2S-0.65GHz', '3S-0.65GHz', '4S-0.65GHz', '4S-0.65GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz', '2B-1.15GHz']]
    colors=['0.2','0.4']
    rows = ['HP','OM']
    Loc='right'
    the_table = plt.table(cellText=cell_text,
                          rowLabels=rows,
                          colLabels=Load,
                          rowColours=colors,
                        cellLoc='right',
                          loc='bottom')
    the_table.scale(1,2.5)

    the_table.auto_set_font_size(False)
    the_table.set_fontsize(12)
    plt.subplots_adjust(left=0.2, bottom=0.2)

    ax.xaxis.labelpad = 70

    ax.yaxis.labelpad = 20
    fig.savefig('rps-watt' +'.eps',format='eps',bbox_inches='tight', pad_inches=0.1, dpi=1000)

dataset = [['29%', '40%', '51%', '63%', '69%', '71%', '74%', '77%', '80%', '83%', '86%', '89%', '91%', '94%', '97%', '100%'], [6524.0, 8749.0, 10470.0, 13096.0, 13126.0, 12965.0, 13493.0, 13717.0, 14351.0, 14993.0, 15308.0, 14320.0, 13179.0, 9809.0, 10168.0, 10621.0], [6524.0, 8749.0, 10470.0, 13096.0, 6827.0, 5586.0, 7697.0, 8205.0, 8298.0, 8733.0, 8887.0, 9278.0, 9659.0, 9809.0, 10168.0, 10621.0]]
plot_bar(dataset)

Answer 1

我想这就是你要找的东西。
- 添加了一个参数“spare_width”，使条形图正确。
-resized的图例字体和xlabel间距看起来更好，而不是阻止数据。
- 添加了“ggplot”风格 - 我更喜欢它。
- 通过将频率（GHz）移动到自己的行并通过bbox设置高度，将字体大小增加到35。

import csv
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import matplotlib

def plot_bar(dataset):
    matplotlib.rc('font', family='sans-serif')
    matplotlib.rc('font', serif='Helvetica Neue')
    matplotlib.rc('text', usetex='false')
    matplotlib.rcParams.update({'font.size': 30})
    fig = plt.figure()
    ax = fig.add_subplot(111)
    fig = matplotlib.pyplot.gcf()
    fig.set_size_inches(30.0,7.5)
    N = len(dataset[1])

    Load    = dataset[0]
    QoS     = dataset[1]
    Energy  = dataset[2]

    ind = np.arange(N)
    width = 0.35
    spare_width = (1 - width*2)/2

    plt.tick_params(axis='both', which='major', labelsize=35, pad=15)
    plt.tick_params(axis='y', which='minor', labelsize=35, pad=15)



    rects1 = ax.bar(ind, QoS, width,
                color='0.2',
                label='HP')

    rects3 = ax.bar(ind+width, Energy, width,
                color='0.4',
                label='OM')

    lns = [rects1, rects3]
    labs = [l.get_label() for l in lns]

    ax.legend(lns, labs, ncol=2, fontsize=30,framealpha=0)

    ax.set_xlim(-spare_width,len(ind)-spare_width)
    ax.set_ylim(0, 16000)

    ax.set_ylabel('RPS/Watt', fontsize=35)
    ax.set_xlabel('Percentage of Max Capacity', fontsize=35)

    xTickMarks = dataset[0]
    ax.set_xticks(ind+width)
    xtickNames = ax.set_xticklabels(xTickMarks)
    plt.setp(xtickNames, rotation=0, fontsize=40)
    plt.xticks([])
    ax.yaxis.grid()

    cell_text = [['2S\n0.65', '3S\n0.65', '4S\n0.65', '4S\n0.65', 
                  '2B2S\n1.15','2B2S\n1.15', '3B2S\n1.15', '2S\n1.15', 
                  '2S\n1.15', '2S\n1.15', '2S\n1.15','2S\n1.15', 
                  '2S\n1.15', '2S\n1.15', '2S\n1.15', '2S\n1.15'],
            ['2S\n0.65', '3S\n0.65', '4S\n0.65', '4S\n0.65',
             '2S\n1.15', '2S\n1.15', '2S\n1.15', '2S\n1.15', 
             '2S\n1.15', '2S\n1.15', '2S\n1.15', '2S\n1.15', 
             '2S\n1.15', '2S\n1.15', '2S\n1.15', '2B\n1.15']]
    colors=['0.2','0.4']
    rows = ['HP\nGHz','OM\nGHz']
    Loc='right'
    the_table = plt.table(cellText=cell_text,
                          rowLabels=rows,
                          colLabels=Load,
                          rowColours=colors,
                        cellLoc='center',
                          loc='bottom',
                          bbox=[0,-0.65,1,0.65])#x,y,w,h
    the_table.scale(1,2.5)

    the_table.auto_set_font_size(False)
    the_table.set_fontsize(35)
    plt.subplots_adjust(left=0.2, bottom=0.2)

    ax.xaxis.labelpad = 260

    ax.yaxis.labelpad = 20
    fig.savefig('rps-watt' +'.eps',format='eps',bbox_inches='tight', pad_inches=0.1, dpi=1000)

dataset = [['29%', '40%', '51%', '63%', '69%', '71%', '74%', '77%', '80%', '83%', '86%', '89%', '91%', '94%', '97%', '100%'], [6524.0, 8749.0, 10470.0, 13096.0, 13126.0, 12965.0, 13493.0, 13717.0, 14351.0, 14993.0, 15308.0, 14320.0, 13179.0, 9809.0, 10168.0, 10621.0], [6524.0, 8749.0, 10470.0, 13096.0, 6827.0, 5586.0, 7697.0, 8205.0, 8298.0, 8733.0, 8887.0, 9278.0, 9659.0, 9809.0, 10168.0, 10621.0]]
plot_bar(dataset)

这个图使用WinPython-64bit-3.4.4.1Qt5 在这里下载