有三个 Matplotlib 函数可以帮助完成这个任务：`plt.contour用于等高线图，plt.contourf用于填充的等高线图...
我试图在matplotlib中使用颜色映射,其中每种颜色都“本地化”为一个整数。例如,当我正在绘制的数据在[-1,1]范围内时,我希望能够清楚地知道哪些数据在-1、0和1之间。cmap=mpl.cm.coolwarm fig, axs = plt.subplots(1, 1) cmap = mpl.cm.coolwarm levels = np.arange(-1.2,1.21,.01) cs = axs.contou...
im = axes[0].pcolormesh(X, Y, Z, cmap=cmap, norm=norm, shading='nearest') cbar = fig.colorbar(im, ax=axes[0], extend='both') axes[0].set_title('pcolormesh') # 第二张图画contourf. im = axes[1].contourf(X, Y, Z, levels=levels, cmap=cmap, norm=norm, extend='both') ...
contourf(X, Y, Z, levels=levels, cmap=custom_cmap) # Add a color bar to show the discrete color classes plt.colorbar(contour, label='Gaussian Function Value') # Add labels for the axes plt.xlabel('X') plt.ylabel('Y') # Add a title plt.title(f'2D Gaussian with {num_classes} ...
contourf(X, Y, Z, 20, cmap='RdGy') plt.colorbar(); Figure 4-32. Visualizing three-dimensional data with filled contours The colorbar makes it clear that the black regions are “peaks,” while the red regions are “valleys.” One potential issue with this plot is that it is a bit...
from matplotlibimportcm # 使用现成的 color map cmap=cm.get_cmap('Set1')res=cmap(score_map)# 会根据 score map 的值从 cmap 中找 color,返回的是 rgba 图像 # 自己定义COLOR_MAP=ones(100,3)cmap=colors.ListedColormap(COLOR_MAP)res=cmap(score_map)...
bring contourf3d in feature parity with contour3d. - BVR2011-01-04 Tag 1.0.1 for release at r88962011-01-03 Added display of ticker offset to 3d plots. - BVR2011-01-03 Turn off tick labeling on interior subplots for pyplots.subplots when sharex/sharey is True. - JDH2010...
%matplotlibinlineimportmatplotlib.pyplotasplt plt.style.use('seaborn-white')importnumpyasnp x=np.linspace(0,5,50)y=np.linspace(0,5,40)X,Y=np.meshgrid(x,y)Z=f(X,Y)plt.contour(X,Y,Z,colors='black');plt.contour(X,Y,Z,20,cmap='RdGy');plt.contourf(X,Y,Z,20,cmap='RdGy')plt...
plt.contourf(Xm,Ym,Zm,levels=,cmap=)为contourf的基本用法,对分格密度和色彩模式进行了设置 plt.colorbar()用来生成colorbar,colorbar的名称,刻度,字体大小可以分别通过.set_label(),.set_ticks(),.ax.tick_params()进行设置 这次在脚本中也加入了argv变量的设置,实现了直接读入文件名进行处理。脚本的具体内容...
contour """ _Underride(options, linewidth=3, cmap=matplotlib.cm.Blues) X, Y = np.meshgrid(xs, ys) Z = zs x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False) axes = plt.gca() axes.xaxis.set_major_formatter(x_formatter) if pcolor: plt.pcolormesh(X, Y, Z, **options) ...