get_ydata() ind = event.ind print('onpick1 line:', np.column_stack([xdata[ind], ydata[ind]])) elif isinstance(event.artist, Rectangle): patch = event.artist print('onpick1 patch:', patch.get_path()) elif isinstance(event.artist, Text): text = event.artist print('onpick1 text...
self.xs = list(line.get_xdata()) self.ys = list(line.get_ydata()) self.cid = line.figure.canvas.mpl_connect('button_press_event', self) def __call__(self, event): print('click', event) if event.inaxes!=self.line.axes: return self.xs.append(event.xdata) self.ys.append(event...
from matplotlibimportpyplotaspltclassLineBuilder:def__init__(self,line):self.line=line self.xs=list(line.get_xdata())self.ys=list(line.get_ydata())self.cid=line.figure.canvas.mpl_connect('button_press_event',self)def__call__(self,event):print('click',event)ifevent.inaxes!=self.line....
xdata:横坐标的取值,默认就是range(1,len(data)+1) ydata:纵坐标取值 linewidth:线条的宽度 linestyle:线型 color:线条的颜色 marker:点的标注样式 markersize:标注的大小如何设置参数属性对于上面提到的各个参数有三种修改方法:在plot函数里面进行设置 x = range(0,5) y = [2,5,7,9,11] plt.plot(x,y,...
运行程序后,当在画布上单击时,会在鼠标点击处,绘制出事件的 x、y、xdata、和 ydata 属性值: 接下来,我们编写另一个示例程序,此程序会在每次按下鼠标时绘制一条线段: frommatplotlibimportpyplotaspltclassLineBuilder:def__init__(self,line):self.line=lineself.xs=list(line.get_xdata())self.ys=list(lin...
= lambda x: x * np.sin(x) xdata = np.array([1, 3, 5, 6, 8]) ydata = model(xdata...
ax.plot(xdata,plot_data,"b-") ax.set_xticks(range(len(labels))) ax.set_xticklabels(labels) ax.set_yticks([1.4,1.6,1.8]) # grow the y axis down by0.05ax.set_ylim(1.35,1.8) # expand the x axis by0.5at two ends ax.set_xlim(-0.5,len(labels)-0.5) ...
gp.fit(xdata[:, np.newaxis], ydata) xfit = np.linspace(0,10,1000) yfit, std = gp.predict(xfit[:, np.newaxis], return_std=True) dyfit =2* std# 两倍sigma ~ 95% 确定区域 我们现在有了xfit、yfit和dyfit,作为对我们数据的连续拟合值...
xdisplay,ydisplay=ax.transData.transform((xdata,ydata))ax.annotate('data = (%.1f, %.1f)'%(xdata,ydata),(xdata,ydata),xytext=(-2*offset,offset),textcoords='offset points',bbox=bbox,arrowprops=arrowprops)ax.annotate('display = (%.1f, %.1f)'%(xdisplay,ydisplay),(xdisplay,ydispl...
此时,通过指定索引值获取相应数据 boxplot['fliers'][1].get_xdata() Out[137]: array([2.]) boxplot['fliers'][1].get_ydata() Out[138]: array([1.79881989])发布于 2020-05-27 14:03 Matplotlib 数据可视化 可视化 赞同1添加评论 分享喜欢收藏申请转载 ...