ax=plt.subplots()ax.plot(x,y,label='sin(x)')# 隐藏顶部和右侧边框ax.spines['top'].set_visible(False)ax.spines['right'].set_visible(False)# 设置标题和标签ax.set_title('How to Hide Axis Borders - how2matplotlib.com')ax.set_xlabel('X-axis')ax.set_ylabel('Y-...
cbar.set_ticks([0, 0.4, 0.8, 1.2, 1.6]) cbar.set_ticklabels(['0','0.4','0.8','1.2','1.6'], fontsize=20.0) plt.clim(0,1.6) ax.set_position([0.18, 0.2, 0.7, 0.7]) cbar.ax.tick_params(axis='both', which='major', direction='in', length=3) cbar.ax.set_position([0.9...
plt.title('cjavapy', loc='left', fontsize='large', color='blue', style='italic', weight='bold') plt.xlabel('X Axis', labelpad=15, fontsize='medium', color='green') plt.ylabel('Y Axis', labelpad=20, fontsize='medium', color='red') # 使用 plt.draw() 显示画布 plt.draw()...
plt.title('cjavapy', loc='left', fontsize='large', color='blue', style='italic', weight='bold') plt.xlabel('X Axis', labelpad=15, fontsize='medium', color='green') plt.ylabel('Y Axis', labelpad=20, fontsize='medium', color='red') # 使用 plt.draw() 显示画布 plt.draw()...
xticks & yticks:设置轴上的刻度值。 plt.xticks([0,5,10]) plt.yticks([-1,0,1]) tick_params:调整刻度的样式。 plt.tick_params(axis='both', which='major', labelsize=10) 三、面向对象接口:高级篇 set_xlabel & set_ylabel:在Axes对象上设置轴标签。
→ ax.set_[xy]ticks(rotation=90) … hide top spine? → ax.spines[’top’].set_visible(False) … hide legend border? → ax.legend(frameon=False) … show error as shaded region? → ax.fill_between(X, Y+error, Y‐error) … draw a rectangle? → ax.add_patch(plt.Rectangle((0, ...
Axes:TheAxesclass represents one (sub-)plot in a figure. It contains the plotted data, axis ticks, labels, title, legend, etc.Its methods are the main interface for manipulating the plot. 在matplotlib中,一个artist可能有很多properties,下面是一种简单方式查看某个artist的所有properties: ...
fig.add_subplot(ax3)# 前两位表示X轴范围,后两位表示Y轴范围ax3.axis([40,160,0,0.03]) ax3.axis["left"].set_axis_direction("right") ax3.axis[:].major_ticks.set_tick_out(True) ax3.axis["left"].label.set_text("Long Label Left") ...
axis():获取或设置某些轴属性的方便方法。 参数: pro =['on','off','equal','scaled','tight','auto','normal','image','square'] 添加方式:plt.axis(pro[2]) 设置横纵坐标的范围,是一个列表很纵坐标相等 如: x = np.linspace(0,2*np.pi,100) ...
plt.axis((0, 100, 0, 100)) # 坐标轴区间: x 为 10 , y 为 20 plt.xticks([i * 10 for i in range(11)]) plt.yticks([i * 20 for i in range(6)]) plt.tight_layout() plt.show() plot_normal(values) 1. 2. 3. 4. ...