Claus,
I agree with Sterling that the colors api page has a great deal of useful
info. However, as another solution to your problem, keep in mind that the
predefined colormaps contained in matplotlib.pyplot.cm return color tuples
when called with a float between 0 and 1. To illustrate with an extension
of your example code, try the following:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0,10,25) # Your x values
# A list of parameters for generating the y values
p = np.linspace(1,10,5)
# An array of values between 0 and 1 with the same length as your parameter
list.
d = np.linspace(0, 1, 5)
for i,j in zip(p,d):
y = np.sin(x*i)
plt.scatter(x, y, color=plt.cm.copper(j))
plt.plot(x, y, color=plt.cm.jet(j))
plt.show()
If you have a lot of parameters, hence a large number of plots, you might
want to start reading up on collections:
http://matplotlib.org/api/collections_api.html
My understanding is that collections plot faster than many repeated calls
to plt.plot or plt.scatter. I've used LineCollection to plot a large number
of lines: I don't know which collection to use for repeated scatter plots,
though.
Good luck
Ryan
On Thu, Nov 15, 2012 at 12:49 PM, Sterling Smith <smit...@fusion.gat.com>wrote:
> Claus,
>
> I think you are looking for something in
> http://matplotlib.org/api/colors_api.html
>
> -Sterling
>
> On Nov 15, 2012, at 8:24AM, Claus wrote:
>
> > Hi,
> > I have this issue, schematically:
> >
> > import numpy as np
> > import matplotlib.pyplot as plt
> >
> > x = np.linspace(0.0, a, b)
> >
> > for i in range(d):
> > y1 = f1(x, p1_i, p2_i)
> > y2 = f2(x, p1_i, p2_i)
> > plt.scatter(x, y1, c=color[i])
> > plt.plot(x, y2, '-', c=color[i]
> >
> >
> > my question:
> > how can I setup color to be d colors from some colormap (like cm.copper
> or cm.jet), they should be somewhat "equally" spaced… maybe the loop is not
> ideal, but I don't know a better way (yet)…
> >
> > Thanks for your help,
> > Cheers,
> > Claus
> >
> >
> >
> >
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