填充轮廓图中的轮廓栅格化 [英] Rasterization of contours in filled contour plot

问题描述

我有一个填充的轮廓图，我希望将其另存为.svg或.pdf文件.下面是一个简化的例子.我想栅格化等高线图本身(彩色部分！)，同时将其他所有内容(所有轴、标签等)保留为矢量图形.

I have a filled contour plot, which I wish to save as an .svg or .pdf file. The following is a simplified example. I want to rasterize the contour plot itself (the colorful part!), while keeping everything else (all axes, labels etc.) as vector graphics.

import numpy as np
import matplotlib.pylab as plt

x = np.linspace(0, 2*np.pi, 100)
y = np.linspace(0, 2*np.pi, 100)
xi, yi = np.meshgrid(x, y)
zi = np.cos(xi)**2 + np.sin(yi)**2

plt.figure()
plt.contourf(xi, yi, zi, rasterized=True)
plt.savefig('fig.svg', dpi=100)

但是，当我检查fig.svg或在Inkscape中打开它进行编辑时(我可以将填充的轮廓取消分组为矢量形状)，显然光栅化没有用！

However, when I inspect fig.svg or open it for editing in Inkscape (I am able to ungroup the filled contour into vector shapes) it is clear that rasterization has not worked!

对于这样一个简单的图而言，这很好，但是如果我的图具有更高的轮廓级别(如下所示)，则矢量图像将需要许多曲线，并且文件大小会更大.

That's fine for such a simple plot, but if my plot has a higher number of contour levels (below) the vector image will need many many curves and the filesize would be much bigger.

plt.close()
plt.figure()
plt.contourf(xi, yi, zi, 100, rasterized=True)
plt.savefig('fig.svg', dpi=100)

有人可以提出解决方案并解释为什么这个 rasterized=True 标志没有完成我的要求吗?

Can someone please suggest a solution and explain why this rasterized=True flag has not done what I require?

推荐答案

我刚刚发现这是 使用 rasterized=True 作为 contour 或 contourf 的参数应该显示一个

Using rasterized=True as argument to contour or contourf should show a

UserWarning: The following kwargs were not used by contour: 'rasterized'

要栅格化等高线图，您需要栅格化其各个部分，即

In order to rasterize a contour plot, you need to rasterize its individual parts, i.e.

cs = plt.contour(...) 
for c in cs.collections:
    c.set_rasterized(True)

问题的示例因此看起来像

The example from the question would hence look like

import numpy as np
import matplotlib.pylab as plt

x = np.linspace(0, 2*np.pi, 100)
y = np.linspace(0, 2*np.pi, 100)
xi, yi = np.meshgrid(x, y)
zi = np.cos(xi)**2 + np.sin(yi)**2

plt.figure()
cs = plt.contourf(xi, yi, zi)

for c in cs.collections:
    c.set_rasterized(True)

plt.savefig('fig.svg', dpi=100)

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