2010/12/19 Pawel <pawe...@gmail.com>:
> Hi,
>
> I am a new user of matplotlib so maybe my question is elementary, but
> have not been able to find an answer to my problem in the archive.
>
> I would like to make a 2D plot of colored points of 3D data (clusters).
> My data looks like this:
>
> 11837.2120 -0.0858 2.0000
> 23975.2120 -0.0672 2.0000
> 37609.2120 -0.0306 2.0000
> 53263.9800 -0.0690 2.0000
> 72106.6760 0.2708 1.0000
> 92674.6760 -0.0129 3.0000
> 116758.676 -0.1245 3.0000
> ...
>
> So I need to plot the first and second column as points on the x-y axis
> and color the points according to the numbers in the third column (which
> are integers ranging from 1 to5).
>
> I'd appreciate any help. I realize something so typical should be
> somewhere in the documentation but I was not able to find it.
Try this:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
x, y, z = np.loadtxt('data.txt', unpack=True)
cmap = ListedColormap(['b', 'g', 'r', 'c', 'm'])
plt.scatter(x, y, c=z, cmap=cmap, vmin=1, vmax=5)
plt.show()
You'll need to use a single space as column delimiter in your data
file or deal with more loadtxt arguments.
If your z data were color specifications you could just use
plt.scatter(x, y, c=z) as stated in the scatter docstring. Converting
arbitrary data to color specifications is the non trivial issue here.
You can write your own code to do this or use colormaps.
Goyo
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