Try
nm = matplotlib.colors.Normalize(desired_min, desired_max)
plt.scatter(x1,y1,c=myarr1,cmap=plt.get_cmap("gist_heat"),norm=nm)
You could just use the vmin/vmax keywords in the scatter() call, but
I've just always preferred using Normalize(); you have more control
over what happens that way (see docs for Normalize).
ref:
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.scatter
On Mon, Oct 31, 2011 at 12:02 PM, Tommy Grav <tg...@mac.com> wrote:
> Hi,
>
> I have been looking around but can't find what I want.
> I have two arrays, one with numbers from 0.02 to 0.20 and
> the other from 0.03 to 0.50. I am trying to plot them together
> with other arrays in a scatterplot where these two are the
> color term
>
> plt.scatter(x1,y1,c=myarr1,cmap=plt.get_cmap("gist_heat))
> plt.scatter(x2,y2,c=myarr2,cmap=plt.get_cmap("gist_heat))
>
> but it seems that each instance of the plot command rescales
> the array such that myarr1.max() and myarr2.max() are both with,
> which means that the two color scales are out of sync. Is there
> a way to force the two plots to respect the values in the array
> have the cmap go from 0 to 1, not from myarr1.min() to myarr1.max()?
>
> Cheers
> Tommy
>
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