matplotlib将来自csv的X Y Z数据绘制为pcolormesh [英] matplotlib plot X Y Z data from csv as pcolormesh

问题描述

我的数据格式如下:

X,Y,Z
0,0,0.0
0,1,0.0
1,0,1.0
1,1,0.55
2,0,4.0
2,1,3.216

我不确定如何将数据输入到pcolormesh.我想我必须使用np.meshgrid，但是在这种情况下我不确定如何使用.

I am not sure how to feed this data to pcolormesh. I think I have to use np.meshgrid but I'm not sure how to in this case.

dat = pd.read_csv('my_dat.csv')
plt.pcolormesh(dat['X'], dat['Y'], dat['Z'])
plt.show()

Value error: need more than one value to unpack

我不明白-为什么这行不通?

I don't understand - why doesn't this just work?

推荐答案

您的数据仅需要重塑.此处无需使用np.meshgrid，因为每个单元格已经有了x和y坐标.

Your data just needs to be reshaped. No need to use np.meshgrid here, since you already have an x and y coord for each cell.

如果x坐标为nx，y坐标为ny，则可以执行以下操作:

If you have nx coordinates in x, and ny coordinates in y, then you can do this:

X = dat['X'].reshape(nx,ny).T
Y = dat['Y'].reshape(nx,ny).T
Z = dat['Z'].reshape(nx,ny).T

plt.pcolormesh(X,Y,Z)
plt.show()

请注意，pcolormesh希望您的x和y尺寸比z尺寸大一倍，因为x和y定义了单元格的边缘，而z定义了单元格的边缘单元中心的颜色.从文档中:

Note that pcolormesh prefers that you have your x and y dimensions be one greater that the z dimension, since x and y define the edges of the cells, and z defines the colour at the cell centre. From the docs:

理想地，X和Y的尺寸应比C的尺寸大一；如果尺寸相同，则C的最后一行和最后一列将被忽略.

Ideally the dimensions of X and Y should be one greater than those of C; if the dimensions are the same, then the last row and column of C will be ignored.

因此，在您的示例中，除非添加的虚拟单元格的行和列的x和y坐标比您的单元格数大1，否则最后一行的颜色将丢失.一种替代方法可能是使用 plt.contourf ，对于x，y ，并且z的长度应该相同.

So, in you example, the colours from the final row and column will be lost, unless you add a row and column of dummy cells with x and y coordinates 1 greater than your number of cells. An alternative might be to use plt.contourf, for which x, y, and z should be the same length.

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