A colormap can be called like a function to get the colors associated to
(normalized) values. In your example, it is called with uniformly spaced values
(linspace) between 0 and 1. This should return the corresponding colors.
print plt.get_cmap('gray')(0.0)
(0.0, 0.0, 0.0, 1.0)
print plt.get_cmap('gray')(1.0)
(1.0, 1.0, 1.0, 1.0)
print plt.get_cmap('gray')(np.linspace(0,1,6))
[[ 0. 0. 0. 1. ]
[ 0.2 0.2 0.2 1. ]
[ 0.4 0.4 0.4 1. ]
[ 0.6 0.6 0.6 1. ]
[ 0.8 0.8 0.8 1. ]
[ 1. 1. 1. 1. ]]
Nicolas
On 08 May 2014, at 11:41, MaxMax <a3233...@drdrb.net> wrote:
> i have found a solution for creating colors for many plots at this page:
> http://stackoverflow.com/questions/7513262/matplotlib-large-set-of-colors-for-plots
>
> what does this the following line do?
> colors = plt.get_cmap('jet')(np.linspace(0, 1.0, len(kinds)))
>
> plt.get_cmap('jet') gets a LinearSegmentedColormap object and np.linspace
> creates a ndarray
> but what happens because of this instruction?
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/creating-colors-for-many-plots-tp43381.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
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