Matplotlib discrete colorbar

Question

I am trying to make a discrete colorbar for a scatterplot in matplotlib  I have my x  y data and for each point an integer tag value which I want to be represented with a unique colour  e g   plt scatter x  y  c tag    typically tag will be an integer ranging from 0-20  but the exact range may change  so far I have just used the default settings  e g   plt colorbar     which gives a continuous range of colours  Ideally i would like a set of n discrete colours  n 20 in this example   Even better would be to get a tag value of 0 to produce a gray colour and 1-20 be colourful   I have found some  cookbook  scripts but they are very complicated and I cannot think they are the right way to solve a seemingly simple problem

User · Answer

To set a values above or below the range of the colormap, you'll want to use the set_over and set_under methods of the colormap. If you want to flag a particular value, mask it (i.e. create a masked array), and use the set_bad method. (Have a look at the documentation for the base colormap class: http://matplotlib.org/api/colors_api.html#matplotlib.colors.Colormap )

It sounds like you want something like this:

import matplotlib.pyplot as plt
import numpy as np

# Generate some data
x, y, z = np.random.random((3, 30))
z = z * 20 + 0.1

# Set some values in z to 0...
z[:5] = 0

cmap = plt.get_cmap('jet', 20)
cmap.set_under('gray')

fig, ax = plt.subplots()
cax = ax.scatter(x, y, c=z, s=100, cmap=cmap, vmin=0.1, vmax=z.max())
fig.colorbar(cax, extend='min')

plt.show()

enter image description here

User · Answer

You could follow this example      usr bin env python     Use a pcolor or imshow with a custom colormap to make a contour plot   Since this example was initially written  a proper contour routine was added to matplotlib - see contour demo py and http   matplotlib sf net matplotlib pylab html -contour       from pylab import     delta   0 01 x   arange -3 0  3 0  delta  y   arange -3 0  3 0  delta  X Y   meshgrid x  y  Z1   bivariate normal X  Y  1 0  1 0  0 0  0 0  Z2   bivariate normal X  Y  1 5  0 5  1  1  Z   Z2 - Z1   difference of Gaussians  cmap   cm get cmap  PiYG   11       11 discrete colors  im   imshow Z  cmap cmap  interpolation  bilinear               vmax abs Z  max    vmin -abs Z  max    axis  off   colorbar    show     which produces the following image

User · Answer

You can create a custom discrete colorbar quite easily by using a BoundaryNorm as normalizer for your scatter  The quirky bit  in my method  is making 0 showup as grey    For images i often use the cmap set bad   and convert my data to a numpy masked array  That would be much easier to make 0 grey  but i couldnt get this to work with the scatter or the custom cmap    As an alternative you can make your own cmap from scratch  or read-out an existing one and override just some specific entries   import numpy as np import matplotlib as mpl import matplotlib pylab as plt  fig  ax   plt subplots 1  1  figsize  6  6      setup the plot  x   np random rand 20     define the data y   np random rand 20     define the data tag   np random randint 0  20  20  tag 10 12    0    make sure there are some 0 values to show up as grey  cmap   plt cm jet    define the colormap   extract all colors from the  jet map cmaplist    cmap i  for i in range cmap N     force the first color entry to be grey cmaplist 0      5   5   5  1 0     create the new map cmap   mpl colors LinearSegmentedColormap from list       Custom cmap   cmaplist  cmap N     define the bins and normalize bounds   np linspace 0  20  21  norm   mpl colors BoundaryNorm bounds  cmap N     make the scatter scat   ax scatter x  y  c tag  s np random randint 100  500  20                     cmap cmap  norm norm     create a second axes for the colorbar ax2   fig add axes  0 95  0 1  0 03  0 8   cb   plt colorbar ColorbarBase ax2  cmap cmap  norm norm      spacing  proportional   ticks bounds  boundaries bounds  format   1i    ax set title  Well defined discrete colors   ax2 set ylabel  Very custom cbar  -    size 12      I personally think that with 20 different colors its a bit hard to read the specific value  but thats up to you of course

User · Answer

The above answers are good  except they don t have proper tick placement on the colorbar  I like having the ticks in the middle of the color so that the number -  color mapping is more clear  You can solve this problem by changing the limits of the matshow call   import matplotlib pyplot as plt import numpy as np  def discrete matshow data        get discrete colormap     cmap   plt get cmap  RdBu   np max data -np min data  1        set limits  5 outside true range     mat   plt matshow data cmap cmap vmin   np min data - 5  vmax   np max data   5       tell the colorbar to tick at integers     cax   plt colorbar mat  ticks np arange np min data  np max data  1     generate data a np random randint 1  9  size  10  10   discrete matshow a

User · Answer

I think you d want to look at colors ListedColormap to generate your colormap  or if you just need a static colormap I ve been working on an app that might help

User · Answer

This topic is well covered already but I wanted to add something more specific   I wanted to be sure that a certain value would be mapped to that color  not to any color    It is not complicated but as it took me some time  it might help others not lossing as much time as I did     import matplotlib from matplotlib colors import ListedColormap    Let s design a dummy land use field A   np reshape  7 2 13 7 2 2    2 3   vals   np unique A     Let s also design our color mapping  1s should be plotted in blue  2s in red  etc    col dict  1  blue             2  red             13  orange             7  green      We create a colormar from our list of colors cm   ListedColormap  col dict x  for x in col dict keys        Let s also define the description of each category   1  blue  is Sea  2  red  is burnt  etc    Order should be respected here   Or using another dict maybe could help  labels   np array   Sea   City   Sand   Forest    len lab   len labels     prepare normalizer    Prepare bins for the normalizer norm bins   np sort   col dict keys       0 5 norm bins   np insert norm bins  0  np min norm bins  - 1 0  print norm bins     Make normalizer and formatter norm   matplotlib colors BoundaryNorm norm bins  len lab  clip True  fmt   matplotlib ticker FuncFormatter lambda x  pos  labels norm x       Plot our figure fig ax   plt subplots   im   ax imshow A  cmap cm  norm norm   diff   norm bins 1   - norm bins  -1  tickz   norm bins  -1    diff   2 cb   fig colorbar im  format fmt  ticks tickz  fig savefig  example landuse png   plt show

User · Answer

I have been investigating these ideas and here is my five cents worth  It avoids calling BoundaryNorm as well as specifying norm as an argument to scatter and colorbar  However I have found no way of eliminating the rather long-winded call to matplotlib colors LinearSegmentedColormap from list   Some background is that matplotlib provides so-called qualitative colormaps  intended to use with discrete data  Set1  e g   has 9 easily distinguishable colors  and tab20 could be used for 20 colors  With these maps it could be natural to use their first n colors to color scatter plots with n categories  as the following example does  The example also produces a colorbar with n discrete colors approprately labelled   import matplotlib  numpy as np  matplotlib pyplot as plt n   5 from list   matplotlib colors LinearSegmentedColormap from list cm   from list None  plt cm Set1 range 0 n    n  x   np arange 99  y   x   11 z   x   n plt scatter x  y  c z  cmap cm  plt clim -0 5  n-0 5  cb   plt colorbar ticks range 0 n   label  Group   cb ax tick params length 0    which produces the image below  The n in the call to Set1 specifies the first n colors of that colormap  and the last n in the call to from list specifies to construct a map with n colors  the default being 256   In order to set cm as the default colormap with plt set cmap  I found it to be necessary to give it a name and register it  viz   cm   from list  Set15   plt cm Set1 range 0 n    n  plt cm register cmap None  cm  plt set cmap cm      plt scatter x  y  c z

[python] Matplotlib discrete colorbar

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