圆月山庄资源网 Design By www.vgjia.com
在作图过程中,需要绘制多个变量,但是每个变量的数量级不同,在一个坐标轴下作图导致曲线变化很难观察,这时就用到多个坐标轴。本文除了涉及多个坐标轴还包括Axisartist相关作图指令、做图中label为公式的表达方式、matplotlib中常用指令。
一、放一个官方例子先
from mpl_toolkits.axisartist.parasite_axes import HostAxes, ParasiteAxes import matplotlib.pyplot as plt import numpy as np fig = plt.figure(1) #定义figure,(1)中的1是什么 ax_cof = HostAxes(fig, [0, 0, 0.9, 0.9]) #用[left, bottom, weight, height]的方式定义axes,0 <= l,b,w,h <= 1 #parasite addtional axes, share x ax_temp = ParasiteAxes(ax_cof, sharex=ax_cof) ax_load = ParasiteAxes(ax_cof, sharex=ax_cof) ax_cp = ParasiteAxes(ax_cof, sharex=ax_cof) ax_wear = ParasiteAxes(ax_cof, sharex=ax_cof) #append axes ax_cof.parasites.append(ax_temp) ax_cof.parasites.append(ax_load) ax_cof.parasites.append(ax_cp) ax_cof.parasites.append(ax_wear) #invisible right axis of ax_cof ax_cof.axis['right'].set_visible(False) ax_cof.axis['top'].set_visible(False) ax_temp.axis['right'].set_visible(True) ax_temp.axis['right'].major_ticklabels.set_visible(True) ax_temp.axis['right'].label.set_visible(True) #set label for axis ax_cof.set_ylabel('cof') ax_cof.set_xlabel('Distance (m)') ax_temp.set_ylabel('Temperature') ax_load.set_ylabel('load') ax_cp.set_ylabel('CP') ax_wear.set_ylabel('Wear') load_axisline = ax_load.get_grid_helper().new_fixed_axis cp_axisline = ax_cp.get_grid_helper().new_fixed_axis wear_axisline = ax_wear.get_grid_helper().new_fixed_axis ax_load.axis['right2'] = load_axisline(loc='right', axes=ax_load, offset=(40,0)) ax_cp.axis['right3'] = cp_axisline(loc='right', axes=ax_cp, offset=(80,0)) ax_wear.axis['right4'] = wear_axisline(loc='right', axes=ax_wear, offset=(120,0)) fig.add_axes(ax_cof) ''' #set limit of x, y ax_cof.set_xlim(0,2) ax_cof.set_ylim(0,3) ''' curve_cof, = ax_cof.plot([0, 1, 2], [0, 1, 2], label="CoF", color='black') curve_temp, = ax_temp.plot([0, 1, 2], [0, 3, 2], label="Temp", color='red') curve_load, = ax_load.plot([0, 1, 2], [1, 2, 3], label="Load", color='green') curve_cp, = ax_cp.plot([0, 1, 2], [0, 40, 25], label="CP", color='pink') curve_wear, = ax_wear.plot([0, 1, 2], [25, 18, 9], label="Wear", color='blue') ax_temp.set_ylim(0,4) ax_load.set_ylim(0,4) ax_cp.set_ylim(0,50) ax_wear.set_ylim(0,30) ax_cof.legend() #轴名称,刻度值的颜色 #ax_cof.axis['left'].label.set_color(ax_cof.get_color()) ax_temp.axis['right'].label.set_color('red') ax_load.axis['right2'].label.set_color('green') ax_cp.axis['right3'].label.set_color('pink') ax_wear.axis['right4'].label.set_color('blue') ax_temp.axis['right'].major_ticks.set_color('red') ax_load.axis['right2'].major_ticks.set_color('green') ax_cp.axis['right3'].major_ticks.set_color('pink') ax_wear.axis['right4'].major_ticks.set_color('blue') ax_temp.axis['right'].major_ticklabels.set_color('red') ax_load.axis['right2'].major_ticklabels.set_color('green') ax_cp.axis['right3'].major_ticklabels.set_color('pink') ax_wear.axis['right4'].major_ticklabels.set_color('blue') ax_temp.axis['right'].line.set_color('red') ax_load.axis['right2'].line.set_color('green') ax_cp.axis['right3'].line.set_color('pink') ax_wear.axis['right4'].line.set_color('blue') plt.show()
该例子的作图结果为:
二、实际绘制
在实际使用中希望绘制的多变量数值如下表所示:
为了实现这个作图,经过反复修改美化,代码如下:
1.导入包
from mpl_toolkits.axisartist.parasite_axes import HostAxes, ParasiteAxes import matplotlib.pyplot as plt
2.导入数据
x = ['ATL','LAX','CLT','LAS','MSP','DTW','PHX','DCA','SLC','ORD','DFW','PHL','PDX','DEN','IAH','BOS','SAN','BWI','MDW','IND'] k_in = [49.160,47.367,26.858,30.315,16.552,28.590,23.905,18.818,28.735,6.721,10.315,26.398,38.575,7.646,11.227,8.864,15.327,19.120,11.521,19.618] k_out = [38.024,19.974,25.011,22.050,30.108,18.327,20.811,28.464,23.72,8.470,4.119,10.000,25.158,7.851,10.450,11.130,15.441,7.519,20.819,32.825] p = [0.0537,0.0301,0.0306,0.0217,0.0229,0.0223,0.0218,0.0179,0.0155,0.0465,0.0419,0.0165,0.0091,0.0357,0.0232,0.0200,0.0129,0.0143,0.0113,0.0064] K = [4.6844,2.0296,1.5858,1.1347,1.0706,1.0442,0.9764,0.8447,0.8141,0.7066,0.6041,0.5990,0.5808,0.5534,0.5023,0.3992,0.3964,0.3799,0.3639,0.3331]
3.作图并保存,相关指令后有备注,可以帮助理解
fig = plt.figure(1) #定义figure ax_k = HostAxes(fig, [0, 0, 0.9, 0.9]) #用[left, bottom, weight, height]的方式定义axes,0 <= l,b,w,h <= 1 #parasite addtional axes, share x ax_p = ParasiteAxes(ax_k, sharex=ax_k) ax_K = ParasiteAxes(ax_k, sharex=ax_k) #append axes ax_k.parasites.append(ax_p) ax_k.parasites.append(ax_K) ax_k.set_ylabel('$K_i^{in}\;/\;K_i^{out}$') ax_k.axis['bottom'].major_ticklabels.set_rotation(45) ax_k.set_xlabel('Airport') ax_k.axis['bottom','left'].label.set_fontsize(12) # 设置轴label的大小 ax_k.axis['bottom'].major_ticklabels.set_pad(8) #设置x轴坐标刻度与x轴的距离,坐标轴刻度旋转会使label和坐标轴重合 ax_k.axis['bottom'].label.set_pad(12) #设置x轴坐标刻度与x轴label的距离,label会和坐标轴刻度重合 ax_k.axis[:].major_ticks.set_tick_out(True) #设置坐标轴上刻度突起的短线向外还是向内 #invisible right axis of ax_k ax_k.axis['right'].set_visible(False) ax_k.axis['top'].set_visible(True) ax_p.axis['right'].set_visible(True) ax_p.axis['right'].major_ticklabels.set_visible(True) ax_p.axis['right'].label.set_visible(True) ax_p.axis['right'].major_ticks.set_tick_out(True) ax_p.set_ylabel('${p_i}$') ax_p.axis['right'].label.set_fontsize(13) ax_K.set_ylabel('${K_i}$') K_axisline = ax_K.get_grid_helper().new_fixed_axis ax_K.axis['right2'] = K_axisline(loc='right', axes=ax_K, offset=(60,0)) ax_K.axis['right2'].major_ticks.set_tick_out(True) ax_K.axis['right2'].label.set_fontsize(13) fig.add_axes(ax_k) curve_k1, = ax_k.plot(list(range(20)), k_in, marker ='v',markersize=8,label="$K_i^{in}$",alpha = 0.7) curve_k2, = ax_k.plot(list(range(20)), k_out, marker ='^',markersize=8, label="$K_i^{out}$",alpha = 0.7) curve_p, = ax_p.plot(list(range(20)), p, marker ='P',markersize=8,label="${p_i}$",alpha = 0.7) curve_K, = ax_K.plot(list(range(20)), K, marker ='o',markersize=8, label="${K_i}$",alpha = 0.7,linewidth=3) plt.xticks(list(range(20)), x) # ax_k.set_xticks(list(range(20))) # ax_k.set_xticklabels(x) ax_k.axis['bottom'].major_ticklabels.set_rotation(45) # ax_k.set_rotation(90) # plt.xticks(list(range(20)), x, rotation = 'vertical') ax_p.set_ylim(0,0.06) ax_K.set_ylim(0,5) ax_k.legend(labelspacing = 0.4, fontsize = 10) #轴名称,刻度值的颜色 ax_p.axis['right'].label.set_color(curve_p.get_color()) # 坐标轴label的颜色 ax_K.axis['right2'].label.set_color(curve_K.get_color()) ax_p.axis['right'].major_ticks.set_color(curve_p.get_color()) # 坐标轴刻度小突起的颜色 ax_K.axis['right2'].major_ticks.set_color(curve_K.get_color()) ax_p.axis['right'].major_ticklabels.set_color(curve_p.get_color()) # 坐标轴刻度值的颜色 ax_K.axis['right2'].major_ticklabels.set_color(curve_K.get_color()) ax_p.axis['right'].line.set_color(curve_p.get_color()) # 坐标轴线的颜色 ax_K.axis['right2'].line.set_color(curve_K.get_color()) plt.savefig('10.key metrics mapping.pdf', bbox_inches='tight', dpi=800) plt.show()
4.绘制结果
PS
该作图是在Axisartist的基础上完成的,一些平时常用的绘制指令在此处是无用的。经过查找相关资料,https://www.osgeo.cn/matplotlib/tutorials/toolkits/axisartist.html 该网站可以提供一些用法的帮助。
以上就是python 用Matplotlib作图中有多个Y轴的详细内容,更多关于python Matplotlib作图的资料请关注其它相关文章!
圆月山庄资源网 Design By www.vgjia.com
广告合作:本站广告合作请联系QQ:858582 申请时备注:广告合作(否则不回)
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
圆月山庄资源网 Design By www.vgjia.com
暂无评论...
更新日志
2024年11月01日
2024年11月01日
- 孟庭苇《情人的眼泪》开盘母带[低速原抓WAV+CUE]
- 孙露《谁为我停留HQCD》[低速原抓WAV+CUE][1.1G]
- 孙悦《时光音乐会》纯银CD[低速原抓WAV+CUE][1.1G]
- 任然《渐晚》[FLAC/分轨][72.32MB]
- 英雄联盟新英雄安蓓萨上线了吗 新英雄安蓓萨技能介绍
- 魔兽世界奥杜尔竞速赛什么时候开启 奥杜尔竞速赛开启时间介绍
- 无畏契约CGRS准星代码多少 CGRS准星代码分享一览
- 张靓颖.2012-倾听【少城时代】【WAV+CUE】
- 游鸿明.1999-五月的雪【大宇国际】【WAV+CUE】
- 曹方.2005-遇见我【钛友文化】【WAV+CUE】
- Unity6引擎上线:稳定性提升、CPU性能最高提升4倍
- 人皇Sky今日举行婚礼!电竞传奇步入新篇章
- 国风与电竞的奇妙邂逅 “电竞北京2024·国风电竞奇妙夜”引领文化新潮流
- 群星《辉煌滚石30男人篇》开盘母带[低速原抓WAV+CUE]
- 群星《藏迷情歌》紫银合金AQCD[低速原抓WAV+CUE]