在matplotlib的图像网格上的两个colorbars [英] Two colorbars on image grid in matplotlib

问题描述

我想在matplotlib中使用以下布局：

I would like to have the following layout in matplotlib:

图像1a图像1b图像2a图像2b Colorbar a Colorbar b

Image 1a Image 1b Image 2a Image 2b Colorbar a Colorbar b

Colorbar a用于图像集a，Colobar b用于图像集b。

The Colorbar a is for Image set a, and the Colobar b is for Image set b.

我试图使用ImageGrid创建轴对于图像，但没有运气使彩色棒正确。例如：

I have tried to use ImageGrid to create the axes for images, but no luck in making the colorbars right. For example:

fig = plt.figure()
grid = ImageGrid(fig, 111, (1,6), aspect=False, share_all=False)

# Get data1a, data1b, ...

im1a = grid[0].pcolormesh(data1a)
im1b = grid[1].pcolormesh(data1b)
im2a = grid[2].pcolormesh(data2a)
im2b = grid[3].pcolormesh(data2b)

plt.colorbar(im1a, cax=grid[4])
plt.colorbar(im1b, cax=grid[5])

这个问题是对colorbar（）的调用搞乱了图像的轴限制，即使我在ImageGrid（）中指定了share_all = False。

The problem with this is that the calls to colorbar() messed up with the axis limits of the images even though I specified share_all=False in ImageGrid().

这有什么提示吗？非常感谢。

Is there any tip on this? Very much appreciated.

推荐答案

为了将来参考，有一个完整的工作示例，以便有人可以复制和粘贴你的编码并直接重现您的问题。例如，我可以看到你导入了 ImageGrid ，但完整的import语句会对此有所帮助，就像为 data1a <创建假数据集一样/ code>， data1b 等。

For future reference, it helps to have a full working example, so that someone could copy and paste your code and reproduce your issue directly. For example, I can see you've imported ImageGrid, but a full import statement would help with this, as would creating fake data sets for data1a, data1b, etc.

此外，看起来你有一个（1,6）您上面的语句中应该有（1,4）： grid = ImageGrid（图111，（1,4），aspect = False，share_all = False），虽然这不是你问题的解决方案。

Also, it looks like you have a (1,6) where you should have (1,4) in your statement above: grid = ImageGrid(fig, 111, (1,4), aspect=False, share_all=False), though this is not the solution to your problem.

当我需要两个或更多颜色条时，我的方法通常是在轴上使用 get_position（），它返回轴角的坐标作为属性 X0，Y0，X1，Y1 。从这里开始，我分别定义每个颜色条的轴，并将它们精确地放置在我想要的位置。为了满足您的需求，您必须修补 fig.add_axes（[1.01，bbox_ax.y0,0.02，bbox_ax.y1-bbox_ax.y0]）在下面的代码中。例如，前两个条目 1.01，bbox_ax.y0 表示将底角放在 x = 1.01 和 Y = bbox_ax.y0 。后两个条目 0.02，bbox_ax.y1-bbox_ax.y0 分别定义颜色条轴的水平和垂直宽度。我喜欢颜色条轴与绘图轴齐平，所以我使用 bbox_ax.y1-bbox_ax.y0 作为垂直宽度。

When I want two or more color bars, my approach is typically to use get_position() on an axis, which returns the coordinates for the axis corners as attributes x0,y0,x1,y1. From here, I define each colorbar's axis separately and place each precisely where I want it to go. To get this to suit your needs, you'll have to tinker with the details of fig.add_axes([1.01, bbox_ax.y0, 0.02, bbox_ax.y1-bbox_ax.y0]) in the code below. For example, the first two entries 1.01, bbox_ax.y0 mean "place the bottom corner at x=1.01 and y=bbox_ax.y0". The second two entries, 0.02, bbox_ax.y1-bbox_ax.y0 define the horizontal and vertical width of the colorbar axis, respectively. I like the colorbar axes to be flush with the plot axes, so I use bbox_ax.y1-bbox_ax.y0 for the vertical width.

请注意，我使用 mp.subplots（）而不是 ImageGrid（），因为我对后者并不熟悉，我认为没必要。

Note that I'm using mp.subplots() instead of ImageGrid(), since I'm not as familiar with the latter, and I don't think it's necessary.

import matplotlib.pyplot as mp
import numpy
import mpl_toolkits.axes_grid1

data1a = numpy.random.rand(100,100)
data1b = numpy.random.rand(100,100)
data2a = numpy.random.rand(100,100)
data2b = numpy.random.rand(100,100)

fig, axes = mp.subplots(1, 4, figsize=(8,2))

im1a = axes[0].pcolormesh(data1a, cmap='magma')
im1b = axes[1].pcolormesh(data1b, cmap='magma')
im2a = axes[2].pcolormesh(data2a, cmap='viridis')
im2b = axes[3].pcolormesh(data2b, cmap='viridis')

fig.tight_layout()

# get bounding box information for the axes (since they're in a line, you only care about the top and bottom)
bbox_ax = axes[0].get_position()

# fig.add_axes() adds the colorbar axes
# they're bounded by [x0, y0, x_width, y_width]
cbar_im1a_ax = fig.add_axes([1.01, bbox_ax.y0, 0.02, bbox_ax.y1-bbox_ax.y0])
cbar_im1a = mp.colorbar(im1a, cax=cbar_im1a_ax)

cbar_im2a_ax = fig.add_axes([1.09, bbox_ax.y0, 0.02, bbox_ax.y1-bbox_ax.y0])
cbar_im1a = mp.colorbar(im2a, cax=cbar_im2a_ax)

这产生如下数字：

您也可以使用略有不同语法的2x2网格执行此操作：

You can also do this as a 2x2 grid with slightly different syntax:

fig, axes = mp.subplots(2, 2, figsize=(4,4))

im1a = axes[0,0].pcolormesh(data1a, cmap='magma')
im1b = axes[0,1].pcolormesh(data1b, cmap='magma')
im2a = axes[1,0].pcolormesh(data2a, cmap='viridis')
im2b = axes[1,1].pcolormesh(data2b, cmap='viridis')

fig.tight_layout()

bbox_ax_top = axes[0,1].get_position()
bbox_ax_bottom = axes[1,1].get_position()

cbar_im1a_ax = fig.add_axes([1.01, bbox_ax_top.y0, 0.02, bbox_ax_top.y1-bbox_ax_top.y0])
cbar_im1a = mp.colorbar(im1a, cax=cbar_im1a_ax)

cbar_im2a_ax = fig.add_axes([1.01, bbox_ax_bottom.y0, 0.02, bbox_ax_bottom.y1-bbox_ax_bottom.y0])
cbar_im1a = mp.colorbar(im2a, cax=cbar_im2a_ax)

产生这个数字：

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