Create own colormap using matplotlib and plot color scale

Question

I have the following problem  I want to create my own colormap  red-mix-violet-mix-blue  that maps to values between -2 and  2 and want to use it to color points in my plot  The plot should then have the colorscale to the right   That is how I create the map so far  But I am not really sure if it mixes the colors   cmap   matplotlib colors ListedColormap   red   violet   blue    name  from list   N None  m   cm ScalarMappable norm norm  cmap cmap    That way I map the colors to the values   colors   itertools cycle  m to rgba 1 22          Then I plot it   for i in range 0  len array dg      plt plot array dg i   markers next   alpha alpha i   c colors next       My problems are  1  I can t plot the color scale  2  I am not completely sure if my scale is creating a continues  smooth  colorscale

User · Accepted Answer

There is an illustrative example of how to create custom colormaps here. The docstring is essential for understanding the meaning of cdict. Once you get that under your belt, you might use a cdict like this:

cdict = {'red':   ((0.0, 1.0, 1.0), 
                   (0.1, 1.0, 1.0),  # red 
                   (0.4, 1.0, 1.0),  # violet
                   (1.0, 0.0, 0.0)), # blue

         'green': ((0.0, 0.0, 0.0),
                   (1.0, 0.0, 0.0)),

         'blue':  ((0.0, 0.0, 0.0),
                   (0.1, 0.0, 0.0),  # red
                   (0.4, 1.0, 1.0),  # violet
                   (1.0, 1.0, 0.0))  # blue
          }

Although the cdict format gives you a lot of flexibility, I find for simple gradients its format is rather unintuitive. Here is a utility function to help generate simple LinearSegmentedColormaps:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors


def make_colormap(seq):
    """Return a LinearSegmentedColormap
    seq: a sequence of floats and RGB-tuples. The floats should be increasing
    and in the interval (0,1).
    """
    seq = [(None,) * 3, 0.0] + list(seq) + [1.0, (None,) * 3]
    cdict = {'red': [], 'green': [], 'blue': []}
    for i, item in enumerate(seq):
        if isinstance(item, float):
            r1, g1, b1 = seq[i - 1]
            r2, g2, b2 = seq[i + 1]
            cdict['red'].append([item, r1, r2])
            cdict['green'].append([item, g1, g2])
            cdict['blue'].append([item, b1, b2])
    return mcolors.LinearSegmentedColormap('CustomMap', cdict)


c = mcolors.ColorConverter().to_rgb
rvb = make_colormap(
    [c('red'), c('violet'), 0.33, c('violet'), c('blue'), 0.66, c('blue')])
N = 1000
array_dg = np.random.uniform(0, 10, size=(N, 2))
colors = np.random.uniform(-2, 2, size=(N,))
plt.scatter(array_dg[:, 0], array_dg[:, 1], c=colors, cmap=rvb)
plt.colorbar()
plt.show()

enter image description here

By the way, the for-loop

for i in range(0, len(array_dg)):
  plt.plot(array_dg[i], markers.next(),alpha=alpha[i], c=colors.next())

plots one point for every call to plt.plot. This will work for a small number of points, but will become extremely slow for many points. plt.plot can only draw in one color, but plt.scatter can assign a different color to each dot. Thus, plt.scatter is the way to go.

User · Answer

This seems to work for me   def make Ramp  ramp colors         from colour import Color     from matplotlib colors import LinearSegmentedColormap      color ramp   LinearSegmentedColormap from list   my list     Color  c1   rgb for c1 in ramp colors         plt figure  figsize    15 3       plt imshow   list np arange 0  len  ramp colors     0 1       interpolation  nearest   origin  lower   cmap  color ramp       plt xticks         plt yticks         return color ramp  custom ramp   make Ramp     754a28    893584    68ad45    0080a5

User · Answer

Since the methods used in other answers seems quite complicated for such easy task  here is a new answer   Instead of a ListedColormap  which produces a discrete colormap  you may use a LinearSegmentedColormap  This can easily be created from a list using the from list method   import numpy as np import matplotlib pyplot as plt import matplotlib colors  x y c   zip  np random rand 30 3  4-2   norm plt Normalize -2 2  cmap   matplotlib colors LinearSegmentedColormap from list       red   violet   blue     plt scatter x y c c  cmap cmap  norm norm  plt colorbar   plt show         More generally  if you have a list of values  e g   -2   -1  2   and corresponding colors   e g    red   violet   blue     such that the nth value should correspond to the nth color  you can normalize the values and supply them as tuples to the from list method    import numpy as np import matplotlib pyplot as plt import matplotlib colors  x y c   zip  np random rand 30 3  4-2   cvals     -2   -1  2  colors     red   violet   blue    norm plt Normalize min cvals  max cvals   tuples   list zip map norm cvals   colors   cmap   matplotlib colors LinearSegmentedColormap from list     tuples   plt scatter x y c c  cmap cmap  norm norm  plt colorbar   plt show

User · Answer

If you want to automate the creating of a custom divergent colormap commonly used for surface plots  this module combined with  unutbu method worked well for me   def diverge map high  0 565  0 392  0 173   low  0 094  0 310  0 635                low and high are colors that will be used for the two     ends of the spectrum  they can be either color strings     or rgb color tuples             c   mcolors ColorConverter   to rgb     if isinstance low  basestring   low   c low      if isinstance high  basestring   high   c high      return make colormap  low  c  white    0 5  c  white    high     The high and low values can be either string color names or rgb tuples   This is the result using the surface plot demo

[python] Create own colormap using matplotlib and plot color scale

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