# 添加数据,改变了 xlim,ylim,但不会影响 ax.transAxes 的行为fori,labelinenumerate(('A','B','C','D')):Y=curve()X=np.linspace(-3,3,len(Y))ax=fig.add_subplot(2,2,i+1)ax.fill_between(X,3*Y,color=color[i])ax.plot(X,3*Y,color="k",linewidth=0.75)ax.text(0.05,0.95,label,...
最简单的方法是使用多个plot函数调用,每次绘制一段具有特定样式的线条。 importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,100)y=np.sin(x)plt.figure(figsize=(10,6))plt.plot(x[:50],y[:50],'b-',label='Solid - how2matplotlib.com')plt.plot(x[49:],y[49:],'r--',label='...
其中，marker 类型：1、’.’:点（point marker)2、’,’:像素点（pixel marker）3、‘o’:圆形（...
star4、imshow plot【格子图】5、contour plot【等高线图】6、quiver plot【箭头】 star7、pie plot【饼图】 star8、text plot【添加文本】9、fill_between plot【曲线填充图】10、step plot【阶梯图】 star11、box plot【箱图】12、errorbar plot【误差棒】 star13、hist plot【直方图】 star14、violin plot...
add_subplot(grid[-1, 1:], yticklabels=[], sharex=main_ax) # scatter points on the main axes main_ax.plot(x, y, 'ok', markersize=3, alpha=0.2) # histogram on the attached axes x_hist.hist(x, 40, histtype='stepfilled', orientation='vertical', color='gray') x_hist.invert_...
x=[1,2,3,4,5]y=[2,4,6,8,10]plt.plot(x,y,marker='o',markersize=12)plt.title('Custom Marker Size - how2matplotlib.com')plt.show() Python Copy Output: 这里,我们将标记大小设置为 12 点。markersize的单位是点(points),这是一个打印行业常用的单位,约等于 1/72 英寸。
matplotlib includes many customization features, such as different colors, point symbols, and sizing. Depending on our needs, we may want to play around with different scales, using different ranges for our axes. We can change the default parameters by designating new ranges for the axes, like ...
plt.plot(y)的横坐标是从0开始的数组下标。 plt.legend Matplotlib 放置legend(bbox_to_anchor) frameon: bool, default: rcParams["legend.frameon"] (default: True) Whether the legend should be drawn on a patch (frame). handlelength: float, default:2.0 ...
Note:实际上plt.subplot()函数最终调用的也是fig.add_subplot()函数 2.3.2.1 plot()方法 函数调用: ax.plot(x_list, y_list, c=, label=) 函数功能:绘制曲线图 传入参数: x_list, y_list, c, label x_list: list类型,所有需要绘制的点的横坐标列表 ...
def plot_connection(ax, start_point, end_point): x1, y1 = start_point[0], start_point[1] x3, y3 = end_point[0], end_point[1] x2 = (x1 + x3) / 2 y2 = (y1 + y3) / 2 x = np.array([x1, x2, x3]) y = np.array([y1, y2, y3]) ...