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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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