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matplotlib.pyplot api 绘制子图
面向对象方式绘制子图
matplotlib.gridspec.GridSpec绘制子图
任意位置添加子图
关于pyplot和面向对象两种绘图方式可参考之前文章: matplotlib.pyplot api verus matplotlib object-oriented
1、matplotlib.pyplot api 方式添加子图
import?matplotlib.pyplot?as?plt my_dpi=96 plt.figure(figsize=(480/my_dpi,480/my_dpi),dpi=my_dpi) plt.subplot(221) plt.plot([1,2,3]) plt.subplot(222) plt.bar([1,2,3],[4,5,6]) plt.title('plt.subplot(222)')#注意比较和上面面向对象方式的差异 plt.xlabel('set_xlabel') plt.ylabel('set_ylabel',fontsize=15,color='g')#设置y轴刻度标签 plt.xlim(0,8)#设置x轴刻度范围 plt.xticks(range(0,10,2))???#?设置x轴刻度间距 plt.tick_params(axis='x',?labelsize=20,?rotation=45)#x轴标签旋转、字号等 plt.subplot(223) plt.plot([1,2,3]) plt.subplot(224) plt.bar([1,2,3],[4,5,6]) plt.suptitle('matplotlib.pyplot?api',color='r') fig.tight_layout(rect=(0,0,1,0.9)) plt.subplots_adjust(left=0.125, ????????????????????bottom=-0.51, ????????????????????right=1.3, ????????????????????top=0.88, ????????????????????wspace=0.2, ????????????????????hspace=0.2 ???????????????????) ??????????????????? #plt.tight_layout() plt.show()
2、面向对象方式添加子图
import?matplotlib.pyplot?as?plt my_dpi=96 fig,?axs?=?plt.subplots(2,2,figsize=(480/my_dpi,480/my_dpi),dpi=my_dpi, ???????????????????????sharex=False,#x轴刻度值共享开启 ???????????????????????sharey=False,#y轴刻度值共享关闭???????????????????????? ???????????????????????? ???????????????????????) #fig为matplotlib.figure.Figure对象 #axs为matplotlib.axes.Axes,把fig分成2x2的子图 axs[0][0].plot([1,2,3]) axs[0][1].bar([1,2,3],[4,5,6]) axs[0][1].set(title='title')#设置axes及子图标题 axs[0][1].set_xlabel('set_xlabel',fontsize=15,color='g')#设置x轴刻度标签 axs[0][1].set_ylabel('set_ylabel',fontsize=15,color='g')#设置y轴刻度标签 axs[0][1].set_xlim(0,8)#设置x轴刻度范围 axs[0][1].set_xticks(range(0,10,2))???#?设置x轴刻度间距 axs[0][1].tick_params(axis='x',?#可选'y','both' ??????????????????????labelsize=20,?rotation=45)#x轴标签旋转、字号等 axs[1][0].plot([1,2,3]) axs[1][1].bar([1,2,3],[4,5,6]) fig.suptitle('matplotlib?object-oriented',color='r')#设置fig即整整张图的标题 #修改子图在整个figure中的位置(上下左右) plt.subplots_adjust(left=0.125, ????????????????????bottom=-0.61, ????????????????????right=1.3,#防止右边子图y轴标题与左边子图重叠 ????????????????????top=0.88, ????????????????????wspace=0.2, ????????????????????hspace=0.2 ???????????????????) #?参数介绍 ''' ##?The?figure?subplot?parameters.??All?dimensions?are?a?fraction?of?the?figure?width?and?height. #figure.subplot.left:???0.125??#?the?left?side?of?the?subplots?of?the?figure #figure.subplot.right:??0.9????#?the?right?side?of?the?subplots?of?the?figure #figure.subplot.bottom:?0.11???#?the?bottom?of?the?subplots?of?the?figure #figure.subplot.top:????0.88???#?the?top?of?the?subplots?of?the?figure #figure.subplot.wspace:?0.2????#?the?amount?of?width?reserved?for?space?between?subplots, ???????????????????????????????#?expressed?as?a?fraction?of?the?average?axis?width #figure.subplot.hspace:?0.2????#?the?amount?of?height?reserved?for?space?between?subplots, ???????????????????????????????#?expressed?as?a?fraction?of?the?average?axis?height ''' plt.show()
3、matplotlib.pyplot add_subplot方式添加子图
my_dpi=96 fig?=?plt.figure(figsize=(480/my_dpi,480/my_dpi),dpi=my_dpi) fig.add_subplot(221) plt.plot([1,2,3]) fig.add_subplot(222) plt.bar([1,2,3],[4,5,6]) plt.title('fig.add_subplot(222)') fig.add_subplot(223) plt.plot([1,2,3]) fig.add_subplot(224) plt.bar([1,2,3],[4,5,6]) plt.suptitle('matplotlib.pyplot?api:add_subplot',color='r')
4、matplotlib.gridspec.GridSpec方式添加子图
语法:matplotlib.gridspec.GridSpec(nrows, ncols, figure=None, left=None, bottom=None, right=None, top=None, wspace=None, hspace=None, width_ratios=None, height_ratios=None)
import?matplotlib.pyplot?as?plt from?matplotlib.gridspec?import?GridSpec fig?=?plt.figure(dpi=100, ?????????????????constrained_layout=True,#类似于tight_layout,使得各子图之间的距离自动调整【类似excel中行宽根据内容自适应】 ????????????????? ????????????????) gs?=?GridSpec(3,?3,?figure=fig)#GridSpec将fiure分为3行3列,每行三个axes,gs为一个matplotlib.gridspec.GridSpec对象,可灵活的切片figure ax1?=?fig.add_subplot(gs[0,?0:1]) plt.plot([1,2,3]) ax2?=?fig.add_subplot(gs[0,?1:3])#gs[0,?0:3]中0选取figure的第一行,0:3选取figure第二列和第三列 #ax3?=?fig.add_subplot(gs[1,?0:2]) plt.subplot(gs[1,?0:2])#同样可以使用基于pyplot?api的方式 plt.scatter([1,2,3],[4,5,6],marker='*') ax4?=?fig.add_subplot(gs[1:3,?2:3]) plt.bar([1,2,3],[4,5,6]) ax5?=?fig.add_subplot(gs[2,?0:1]) ax6?=?fig.add_subplot(gs[2,?1:2]) fig.suptitle("GridSpec",color='r') plt.show()
5、子图中绘制子图
import?matplotlib.pyplot?as?plt import?matplotlib.gridspec?as?gridspec def?format_axes(fig): ????for?i,?ax?in?enumerate(fig.axes): ????????ax.text(0.5,?0.5,?"ax%d"?%?(i+1),?va="center",?ha="center") ????????ax.tick_params(labelbottom=False,?labelleft=False) #?子图中再绘制子图 fig?=?plt.figure(dpi=100, ????????????????constrained_layout=True, ????????????????) gs0?=?GridSpec(1,?2,?figure=fig)#将figure切片为1行2列的两个子图 gs00?=?gridspec.GridSpecFromSubplotSpec(3,?3,?subplot_spec=gs0[0])#将以上第一个子图gs0[0]再次切片为3行3列的9个axes #gs0[0]子图自由切片 ax1?=?fig.add_subplot(gs00[:-1,?:]) ax2?=?fig.add_subplot(gs00[-1,?:-1]) ax3?=?fig.add_subplot(gs00[-1,?-1]) gs01?=?gs0[1].subgridspec(3,?3)#将以上第二个子图gs0[1]再次切片为3行3列的axes #gs0[1]子图自由切片 ax4?=?fig.add_subplot(gs01[:,?:-1]) ax5?=?fig.add_subplot(gs01[:-1,?-1]) ax6?=?fig.add_subplot(gs01[-1,?-1]) plt.suptitle("GridSpec?Inside?GridSpec",color='r') format_axes(fig) plt.show()
6、任意位置绘制子图(plt.axes)
plt.subplots(1,2,dpi=100) plt.subplot(121) plt.plot([1,2,3]) plt.subplot(122) plt.plot([1,2,3]) plt.axes([0.7,?0.2,?0.15,?0.15],?##?[left,?bottom,?width,?height]四个参数(fractions?of?figure)可以非常灵活的调节子图中子图的位置????? ????????) plt.bar([1,2,3],[1,2,3],color=['r','b','g']) plt.axes([0.2,?0.6,?0.15,?0.15],? ????????) plt.bar([1,2,3],[1,2,3],color=['r','b','g'])
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