In [34]: plt.plot(data,'k--', label='Default')# 对该线取名 DefaultOut[34]: [<matplotlib.lines.Line2D at0x7fb624d86160>] In [35]: plt.plot(data,'k-', drawstyle='steps-post', label='steps-post')# 对该线取名 steps-postOut[35]: [<matplotlib.lines.Line2D at0x7fb624d869e8>...
在Matplotlib中,我们可以使用plot()函数来绘制线图,并通过其参数来添加标记点。最简单的方法是在plot()函数中使用marker参数。 importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,10)y=np.sin(x)plt.figure(figsize=(8,6))plt.plot(x,y,marker='o',label='how2matplotlib.com')plt.title('...
importmatplotlib.pyplotaspltimportnumpyasnp# 生成数据x=np.linspace(0,10,100)y=np.sin(x)# 创建图形plt.figure(figsize=(10,5))plt.plot(x,y)plt.title("Sine Wave")plt.xlabel("X-axis")plt.ylabel("Y-axis")# 定义缩放函数defzoom(event):scale_factor=1.1ax=plt.gca()xlim=ax.get_xlim()yl...
这是完整的代码。 N = 9x = np.linspace(0, 6*np.pi, N)mean_stock = (stock(.1, .2, x, 1.2))np.random.seed(100)upper_stock = mean_stock + np.random.randint(N) * 0.02lower_stock = mean_stock - np.random.randint(N) * 0.015plt.plot(x, mean_stock, color = 'darkorchid', l...
Create publication quality plots. Make interactive figures that can zoom, pan, update. Customize visual style and layout. Export to many file formats . Embed in JupyterLab and Graphical User Interfaces. Use a rich array of third-party packages built on Matplotlib. ...
ax.plot(x, y) arr_img = plt.imread("中国.jpeg")#导入图片 im = OffsetImage(arr_img, zoom...
设置图形大小和子图间距fig,axs=plt.subplots(3,3,figsize=(12,10),gridspec_kw={'hspace':0.4,'wspace':0.3})# 生成一些随机数据foriinrange(3):forjinrange(3):data=np.random.rand(10)axs[i,j].bar(range(10),data)axs[i,j].set_title(f'Plot{i*3+j+1}- how2matplotlib.com')plt.show(...
win=gtk.Window()win.connect("destroy",lambda x:gtk.main_quit())win.set_default_size(400,300)win.set_title("Embedding in GTK")vbox=gtk.VBox()win.add(vbox)fig=Figure(figsize=(5,4),dpi=100)ax=fig.add_subplot(111)ax.plot([1,2,3])canvas=FigureCanvas(fig)# a gtk.DrawingArea ...
def zoom(event): ax = self.ax cur_xlim = ax.get_xlim() cur_ylim = ax.get_ylim() xdata = event.xdata # get event x location ydata = event.ydata # get event y location if event.button == 'down': # deal with zoom in
ax2.plot(x, y, 'bo') # zoom-in / limit the view to different portions of the data ax.set_xlim(0,1) # most of the data ax2.set_xlim(9,10) # outliers only # hide the spines between ax and ax2 ax.spines['right'].set_visible(False) ...