Matplotlib离散颜色条标签未正确放置

Question

I am just plotting image in matplotlib but the labels in colorbar are not getting placed properly.I have placed 12 classes in colorbar but it is showing only some of them. I shall be thankful for the help.

from PIL import Image
from scipy import misc
import scipy
import pylab as pl
import numpy as np
from sklearn import svm
from sklearn import neighbors
import matplotlib.pyplot as plt
import matplotlib as mpl

def plotimage(labels,image,imname):#input - array of labels and image of 1..n classes
cmap = mpl.colors.ListedColormap(['r', 'g', 'b', 'c','k','y','m','w','#FFFF00','#FF8C00','#FF8EFC','#962404'])#only 12 classes at present  
#need to create pallate and labels later out of this def
bounds = [0,1, 2, 3,4, 5,6,7,8,9,10,11,12,13]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
img = plt.imshow(image, cmap=cmap )
cbar = plt.colorbar(img, cmap=cmap)  #norm=norm, boundaries=bounds, ticks=bounds
cbar.ax.set_yticklabels(labels)
plt.gcf().canvas.set_window_title("Classification")
#imsave("expr1_im", image.reshape(image.shape[0]/256,256), cmap=cmap)
#savefig(imname)
plt.title(imname)
plt.show()

b_imgarray = np.loadtxt("PlotData2001_Solar/SVM2001PixelArray.csv", delimiter=',')

labels = ['D','F','A','G','R','I','BS','ABG','W','BG','COAG','BSMIX']

a = np.reshape(b_imgarray, (1500,1500))
c = 'SVmimage'
plotimage(labels,a,c)

The image of misplaced bar legend. As you can see i have define 12 labels from 'D' to 'BSMIX' but it is showing upto ABG.

Answer 1

imshow usually restricts the range of your cmap to the values which appear in the image. In order to force imshow to use all values of your cmap use vmin and vmax :

img = plt.imshow(image, cmap=cmap, vmin=0, vmax=13)

Answer 2

In order to align the labels at the centers of the discrete colorbar fields, you have to define fixed number of ticks (to avoid sub-units) and use clim() .

For example, if there are N discrete levels to be shown in the colorbar:

cbar = plt.colorbar(ticks=range(N))
plt.clim(-0.5, N - 0.5)

It's old question but it's still difficult to find the correct answer, and none of the above worked for me.

Answer 3

thanks a lot @plosner... I have little bit tweaked it it and it works...

 def plotimage(labels,image,imname):#input - array of labels and image of 1..n classes cmap = mpl.colors.ListedColormap(['r', 'g', 'b', 'c','y','k','#FFFF00','#00FF00','#ADBE34','#FF8C00','w','#FF8EFC','#00FFDD','#673E03','#ADEE12','m','#12ABDE','#22EEAB','#33DDEF'])#only 8 classes at present ,'#FF8EFC','#00FF00','#00FFDD''#962404' '#FF8EFC','#962404' #need to create pallate and labels later out of this def #cmap = mpl.colors.ListedColormap(['r', 'g', 'b', 'c','m','k','y','w','#7FFF00','#FF8C00','#FFFF00','#FE6D06','#6E6E6E','#04B4AE'])#only 8 classes at present ,'#FF8EFC','#00FF00','#00FFDD''#962404' '#FF8EFC','#962404' bounds = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20] norm = mpl.colors.BoundaryNorm(bounds, cmap.N) print cmap.N img = plt.imshow(image, cmap=cmap , vmin = 1, vmax =20) cbar = plt.colorbar(img, cmap=cmap,norm=norm, boundaries=bounds, ticks=bounds) #norm=norm, boundaries=bounds, ticks=bounds cbar.ax.set_yticklabels(labels) plt.gcf().canvas.set_window_title("Classification") #imsave("expr1_im", image.reshape(image.shape[0]/256,256), cmap=cmap) #savefig(imname) plt.title(imname) plt.show()