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 ###################################
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