Python+matplotlib繪制多子圖的方法詳解
本文速覽
matplotlib.pyplot api 繪制子圖
面向對象方式繪制子圖
matplotlib.gridspec.GridSpec繪制子圖
任意位置添加子圖
關於pyplot和面向對象兩種繪圖方式可參考之前文章:matplotlib.pyplot api verus matplotlib object-oriented
1、matplotlib.pyplot api 方式添加子圖
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)')#註意比較和上面面向對象方式的差異 plt.xlabel('set_xlabel') plt.ylabel('set_ylabel',fontsize=15,color='g')#設置y軸刻度標簽 plt.xlim(0,8)#設置x軸刻度范圍 plt.xticks(range(0,10,2)) # 設置x軸刻度間距 plt.tick_params(axis='x', labelsize=20, rotation=45)#x軸標簽旋轉、字號等 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、面向對象方式添加子圖
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軸刻度值共享開啟 sharey=False,#y軸刻度值共享關閉 ) #fig為matplotlib.figure.Figure對象 #axs為matplotlib.axes.Axes,把fig分成2x2的子圖 axs[0][0].plot([1,2,3]) axs[0][1].bar([1,2,3],[4,5,6]) axs[0][1].set(title='title')#設置axes及子圖標題 axs[0][1].set_xlabel('set_xlabel',fontsize=15,color='g')#設置x軸刻度標簽 axs[0][1].set_ylabel('set_ylabel',fontsize=15,color='g')#設置y軸刻度標簽 axs[0][1].set_xlim(0,8)#設置x軸刻度范圍 axs[0][1].set_xticks(range(0,10,2)) # 設置x軸刻度間距 axs[0][1].tick_params(axis='x', #可選'y','both' labelsize=20, rotation=45)#x軸標簽旋轉、字號等 axs[1][0].plot([1,2,3]) axs[1][1].bar([1,2,3],[4,5,6]) fig.suptitle('matplotlib object-oriented',color='r')#設置fig即整整張圖的標題 #修改子圖在整個figure中的位置(上下左右) plt.subplots_adjust(left=0.125, bottom=-0.61, right=1.3,#防止右邊子圖y軸標題與左邊子圖重疊 top=0.88, wspace=0.2, hspace=0.2 ) # 參數介紹 ''' ## 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方式添加子圖
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方式添加子圖
語法: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,#類似於tight_layout,使得各子圖之間的距離自動調整【類似excel中行寬根據內容自適應】 ) gs = GridSpec(3, 3, figure=fig)#GridSpec將fiure分為3行3列,每行三個axes,gs為一個matplotlib.gridspec.GridSpec對象,可靈活的切片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選取figure的第一行,0:3選取figure第二列和第三列 #ax3 = fig.add_subplot(gs[1, 0:2]) plt.subplot(gs[1, 0:2])#同樣可以使用基於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、子圖中繪制子圖
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) # 子圖中再繪制子圖 fig = plt.figure(dpi=100, constrained_layout=True, ) gs0 = GridSpec(1, 2, figure=fig)#將figure切片為1行2列的兩個子圖 gs00 = gridspec.GridSpecFromSubplotSpec(3, 3, subplot_spec=gs0[0])#將以上第一個子圖gs0[0]再次切片為3行3列的9個axes #gs0[0]子圖自由切片 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)#將以上第二個子圖gs0[1]再次切片為3行3列的axes #gs0[1]子圖自由切片 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、任意位置繪制子圖(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]四個參數(fractions of figure)可以非常靈活的調節子圖中子圖的位置 ) 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'])
以上就是Python+matplotlib繪制多子圖的方法詳解的詳細內容,更多關於Python matplotlib多子圖的資料請關註WalkonNet其它相關文章!
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