Thanks Johann,
that is exactly what I asked for
I knew that matplotlib can do GUI tricks but I didn't felt skilled to go
there. Seeing you code it seems easy now, but it's always like that after
you see the solution :D
Cheers
On Fri, Nov 11, 2011 at 6:05 PM, johanngoetz <jgo...@ucla.edu> wrote:
>
> I have this script that uses the matplotlib Slider object to control the
> colormap of a histogram. This could be very close to what you want. Here is
> the script:
>
> ### begin colormap_slider.py #################################
> import math, copy
> import numpy
> from matplotlib import pyplot, colors, cm
> from matplotlib.widgets import Slider
>
> def cmap_powerlaw_adjust(cmap, a):
> '''
> returns a new colormap based on the one given
> but adjusted via power-law:
>
> newcmap = oldcmap**a
> '''
> if a < 0.:
> return cmap
> cdict = copy.copy(cmap._segmentdata)
> fn = lambda x : (x[0]**a, x[1], x[2])
> for key in ('red','green','blue'):
> cdict[key] = map(fn, cdict[key])
> cdict[key].sort()
> assert (cdict[key][0]<0 or cdict[key][-1]>1), \
> "Resulting indices extend out of the [0, 1] segment."
> return colors.LinearSegmentedColormap('colormap',cdict,1024)
>
> def cmap_center_adjust(cmap, center_ratio):
> '''
> returns a new colormap based on the one given
> but adjusted so that the old center point higher
> (>0.5) or lower (<0.5)
> '''
> if not (0. < center_ratio) & (center_ratio < 1.):
> return cmap
> a = math.log(center_ratio) / math.log(0.5)
> return cmap_powerlaw_adjust(cmap, a)
>
> def cmap_center_point_adjust(cmap, range, center):
> '''
> converts center to a ratio between 0 and 1 of the
> range given and calls cmap_center_adjust(). returns
> a new adjusted colormap accordingly
> '''
> if not ((range[0] < center) and (center < range[1])):
> return cmap
> return cmap_center_adjust(cmap,
> abs(center - range[0]) / abs(range[1] - range[0]))
>
>
> if __name__ == '__main__':
> ### create some 2D histogram-type data
> def func3(x,y):
> return (1- x/2 + x**5 + y**3)*numpy.exp(-x**2-y**2)
> x = numpy.linspace(-3.0, 3.0, 60)
> y = numpy.linspace(-3.0, 3.0, 60)
> X,Y = numpy.meshgrid(x, y)
> Z = func3(X, Y)
> extent = [x[0],x[-1],y[0],y[-1]]
>
>
> plotkwargs = {
> 'extent' : extent,
> 'origin' : 'lower',
> 'interpolation' : 'nearest',
> 'aspect' : 'auto'}
>
> ### interactively adjustable with a slider
> fig = pyplot.figure(figsize=(6,4))
> fig.subplots_adjust(top=0.8)
> ax = fig.add_subplot(1,1,1)
> cmap = cm.seismic
> plt = ax.imshow(Z, cmap=cmap, **plotkwargs)
> cb = fig.colorbar(plt, ax=ax)
>
> axcmap = fig.add_axes([0.1, 0.85, 0.8, 0.05], axisbg='white')
> scmap = Slider(axcmap, '', 0.0, 1.0, valinit=0.5)
>
> def update(val):
> cmapcenter = scmap.val
> plt.set_cmap(cmap_center_adjust(cmap, cmapcenter))
> scmap.on_changed(update)
>
>
>
> pyplot.show()
> ### end colormap_slider.py ###################################
> --
> View this message in context:
> http://old.nabble.com/How-to-shift-colormap--tp32792283p32827012.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
>
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