Python中的2D网格数据可视化 [英] 2D grid data visualization in Python

问题描述

我需要可视化一些数据。它是基本的2D网格，其中每个单元格都有浮点值。我知道如何。在OpenCV中为颜色赋值和绘制网格。但是这里的观点是，有这么多的价值观，所以几乎不可能做到这一点。我在寻找一些方法，在那里我可以使用渐变。例如，值-5.0将由蓝色，0-黑色和+5.0表示为红色。

这里是我所说的示例数据

  ABCD 
 A -1.045 2.0 3.5 -4.890 
 B -5.678 3.2 2.89 5.78 
  

解决方案

它解释了边界的数量需要是一个大于然后数量的颜色。

EDIT

您应该，使用 grid 方法。将网格颜色设置为白色与颜色映射使用的颜色（即默认黑色不会很好地显示）非常吻合。

  pyplot.grid（True，color ='white'）
  

在 savefig 调用之前包含此绘图（为了清晰起见，使用11x11网格进行绘制）：

有许多选项 grid ，在matplotlib 文档中进行了说明。您可能会感兴趣的是 linewidth 。

I need to visualize some data. It's basic 2D grid, where each cell have float value. I know how to e.g. assign color to value and paint grid in OpenCV. But the point here is that there are so many values so it's nearly impossible to do that. I am looking for some method, where I could use gradient. For example value -5.0 will be represented by blue, 0 - black, and +5.0 as red. Is there any way to do that in Python?

Here is sample data I am talking about

        A       B       C        D
A    -1.045    2.0     3.5    -4.890
B    -5.678    3.2     2.89    5.78

解决方案

Matplotlib has the imshow method for plotting arrays:

from matplotlib import mpl,pyplot
import numpy as np

# make values from -5 to 5, for this example
zvals = np.random.rand(100,100)*10-5

# make a color map of fixed colors
cmap = mpl.colors.ListedColormap(['blue','black','red'])
bounds=[-6,-2,2,6]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)

# tell imshow about color map so that only set colors are used
img = pyplot.imshow(zvals,interpolation='nearest',
                    cmap = cmap,norm=norm)

# make a color bar
pyplot.colorbar(img,cmap=cmap,
                norm=norm,boundaries=bounds,ticks=[-5,0,5])

pyplot.show()

This is what it looks like:

The details for the color bar setup were taken from a matplotlib example: colorbar_only.py. It explains that the number of boundaries need to be one larger then then number of colors.

EDIT

You should note, that imshow accepts the origin keyword, which sets the where the first point is assigned. The default is 'upper left', which is why in my posted plot the y axis has 0 in the upper left and 99 (not shown) in the lower left. The alternative is to set origin="lower", so that first point is plotted in the lower left corner.

EDIT 2

If you want a gradient and not a discrete color map, make a color map by linearly interpolating through a series of colors:

fig = pyplot.figure(2)

cmap2 = mpl.colors.LinearSegmentedColormap.from_list('my_colormap',
                                           ['blue','black','red'],
                                           256)

img2 = pyplot.imshow(zvals,interpolation='nearest',
                    cmap = cmap2,
                    origin='lower')

pyplot.colorbar(img2,cmap=cmap2)

fig.savefig("image2.png")

This produces:

EDIT 3

To add a grid, as shown in this example, use the grid method. Setting the grid color to 'white' works well with the colors used by the colormap (ie the default black does not show up well).

pyplot.grid(True,color='white')

Including this before the savefig call produces this plot (made using 11x11 grid for clarity): There are many options for grid, which are described in the matplotlib documentation. One you might be interested in is linewidth.

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