python colorbar刻度,python matplotlib colorbar设置刻度格式或定位器更改刻度标签

users,

I want to customize the ticks on a colorbar. However, I found the following strange behavior. I try to change the tick formator to the default formator (I thought this should change nothing at all) but I end up with different labels. Does anybody know what I am doing wrong? Or is this a bug?

I use matplotlib from git (v1.0.1-961-gb516ae0 , git describe).

The following code produces the two plots:

#http://matplotlib.sourceforge.net/examples/pylab_examples/griddata_demo.html

from numpy.random import uniform, seed

from matplotlib.mlab import griddata

import matplotlib.pyplot as plt

import matplotlib.ticker

import numpy as np

# make up data.

seed(0)

npts = 200

x = uniform(-2,2,npts)

y = uniform(-2,2,npts)

z = x*np.exp(-x**2-y**2)

# define grid

xi = np.linspace(-2.1,2.1,100)

yi = np.linspace(-2.1,2.1,200)

# grid the data.

zi = griddata(x,y,z,xi,yi,interp='linear')

##### FIRST PLOT

plt.figure()

CS = plt.contour(xi,yi,zi,25,cmap=plt.cm.jet)

bar = plt.colorbar() # draw colorbar

# plot data points.

#plt.scatter(x,y,marker='o',c='b',s=5,zorder=10)

plt.xlim(-2,2)

plt.ylim(-2,2)

plt.title('griddata test (%d points)' % npts)

plt.show()

##### SECOND PLOT

plt.figure()

CS = plt.contour(xi,yi,zi,25,cmap=plt.cm.jet)

bar = plt.colorbar() # draw colorbar

bar.ax.yaxis.set_minor_locator(matplotlib.ticker.AutoLocator())

bar.ax.yaxis.set_major_locator(matplotlib.ticker.AutoLocator())

# plot data points.

#plt.scatter(x,y,marker='o',c='b',s=5,zorder=10)

plt.xlim(-2,2)

plt.ylim(-2,2)

plt.title('griddata test (%d points)' % npts)

plt.show()

解决方案

I just found the solution. One has to call

bar.update_ticks()

after the formators/locators are changed, see

Then everything works well.

Update:

Here is also the code which changes the Formator/Locator. It is based on the internal structure of the colorbar-code, so maybe someone else has a better solution:

#http://matplotlib.sourceforge.net/examples/pylab_examples/griddata_demo.html

from numpy.random import uniform, seed

from matplotlib.mlab import griddata

import matplotlib.pyplot as plt

import matplotlib.ticker

import numpy as np

# make up data.

seed(0)

npts = 200

x = uniform(-2,2,npts)

y = uniform(-2,2,npts)

z = x*np.exp(-x**2-y**2)

# define grid

xi = np.linspace(-2.1,2.1,100)

yi = np.linspace(-2.1,2.1,200)

# grid the data.

zi = griddata(x,y,z,xi,yi,interp='linear')

##### PLOT

plt.figure()

CS = plt.contour(xi,yi,zi,25,cmap=plt.cm.jet)

bar = plt.colorbar(orientation='horizontal') # draw colorbar

tick_locs = [-3.9e-1,-2.6e-1,-1.3e-1,0e-1,1.3e-1,2.6e-1,3.9e-1]

tick_labels = ['-0.390','-0.260','-0.130','0','0.13','0.26','0.390']

bar.locator = matplotlib.ticker.FixedLocator(tick_locs)

bar.formatter = matplotlib.ticker.FixedFormatter(tick_labels)

bar.update_ticks()

# plot data points.

#plt.scatter(x,y,marker='o',c='b',s=5,zorder=10)

plt.xlim(-2,2)

plt.ylim(-2,2)

plt.title('griddata test (%d points)' % npts)

plt.show()