y)# 设置刻度位置ticks=[0,np.pi,2*np.pi,3*np.pi,4*np.pi]ax.xaxis.set_ticks(ticks)# 设置刻度标签labels=['0','π','2π','3π','4π']ax.xaxis.set_ticklabels(labels)plt.title('Custom tick labels - how2matplotlib.com')plt.show()...
4],[1,4,2,3])ax1.xaxis.set_tick_params(bottom=False,labelbottom=False)ax1.set_title('Hidden Bottom Ticks and Labels - how2matplotlib.com')ax2.plot([1,2,3,4],[1,4,2,3])ax2.xaxis.set_tick_params(top=True,labeltop=True)ax2.set_title('Visible Top Ticks and Labels -...
ax.spines['top'].set_color('none')#隐藏掉左边框线 ax.xaxis.set_ticks_position('bottom')#设置坐标轴位置 ax.yaxis.set_ticks_position('left')#设置坐标轴位置 ax.spines['bottom'].set_position(('data',0))#绑定坐标轴位置,data为根据数据自己判断 ax.spines['left'].set_position(('data',0...
ax.yaxis.set_major_locator(ticker.NullLocator())ax.spines['right'].set_color('none')ax.spines['left'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.tick_params(which='major',width=1.00,length=5)ax.tick_params(which='minor',width=0.75...
yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) ... 添加图例[源码文件] 我们在图的左上角添加一个图例。为此,我们只需要在 plot 函数里以「键 - 值」的形式增加一个参数。 ... plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine") plot...
ticklabel.set_rotation(30) ## 刻度标签相对于坐标轴的位置 ax.xaxis.set_ticks_position("bottom")## x轴刻度在x轴下方 ax.yaxis.set_ticks_position("left")## y轴刻度在y轴左侧 frommatplotlib.tickerimportMultipleLocator, FormatStrFormatter, AutoMinorLocator ...
ax.plot([2], [1], 'o') # 带箭头注释 ax.annotate('annotate', xy=(2, 1), xytext=(3, 4), arrowprops=dict(facecolor='black', shrink=0.05)) plt.show() 二、x-y轴标签 本节用 set_xlabel 和 set_ylabel 方法指定 x 轴和 y 轴的标签。
set_xlim & set_ylim:在Axes对象上定制轴范围。 ax.set_xlim(0,10) ax.set_ylim(-1,1) set_xticks & set_yticks:在Axes对象上指定刻度。 ax.set_xticks([0,5,10]) ax.set_yticks([-1,0,1]) set_xticklabels & set_yticklabels:在Axes对象上自定义刻度标签。
ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.tick_params(which='major', width=1.00, length=5) ax.tick_params(which='minor', width=0.75, length=2.5) ax.set_xlim(0, 5) ax.set_ylim(0, 1)
new_ticks = np.linspace(-1, 2, 5) plt.xticks(new_ticks) plt.yticks([-2, -1.8, -1, 1.22, 3],['$really\ bad$', '$bad$', '$normal$', '$good$', '$really\ good$']) ax = plt.gca() #设置上边和右边无边框 ax.spines['right'].set_color('none') ...