Create Your Own Colormap

Detailed reference document of the VCS colormap can be found at here. Colormap for example 4 provided by Karl Taylor.

Let's create your own VCS colormap.

The CDAT software was developed by LLNL. This tutorial was written by Charles Doutriaux and Jiwoo Lee (Oct. 2017). This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Download the Jupyter Notebook

Table of Contents

Import modules

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In [1]:
import vcs
import MV2
from matplotlib.colors import LinearSegmentedColormap

Prepare a dummy array

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  • Here I prepare a dummy 2D array (240 x 2), which is being used in this tutorial only for the visualization purpose.
In [2]:
a = []

num_levels = 240

for i in range(0,num_levels):
  a.append(i/float(num_levels))

for i in range(0,num_levels):
  a.append(i/float(num_levels))

a = MV2.array(a)
a = MV2.reshape(a, (-1,num_levels))

a.id = 'dummy'

v = vcs.init()

Create a colormap

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  • List of VCS default colormaps can be shown using vcs.listelements('colormap')
In [3]:
vcs.listelements('colormap')
Out[3]:
['AMIP',
 'NCAR',
 'bl_to_darkred',
 'bl_to_drkorang',
 'blends',
 'blue2darkorange',
 'blue2darkred',
 'blue2green',
 'blue2grey',
 'blue2orange',
 'blue2orange2red',
 'blue_to_grey',
 'blue_to_grn',
 'blue_to_orange',
 'blue_to_orgred',
 'brown2blue',
 'brown_to_blue',
 'categorical',
 'classic',
 'default',
 'green2magenta',
 'grn_to_magenta',
 'inferno',
 'lightblue2darkblue',
 'ltbl_to_drkbl',
 'magma',
 'plasma',
 'rainbow',
 'rainbow_no_grn',
 'rainbownogreen',
 'sequential',
 'viridis',
 'white2blue',
 'white2green',
 'white2magenta',
 'white2red',
 'white2yellow',
 'white_to_blue',
 'white_to_green',
 'white_to_magenta',
 'white_to_red',
 'white_to_yellow']
  • You can create your own colormap by using createcolormap
  • Let's make one named 'my_cmap'. Now you will see that one is included in the list of available colormaps
  • Note that 'my_cmap' colormap is copy of the default colormap at the begining
In [4]:
v.createcolormap('my_cmap')
vcs.listelements('colormap')
Out[4]:
['AMIP',
 'NCAR',
 'bl_to_darkred',
 'bl_to_drkorang',
 'blends',
 'blue2darkorange',
 'blue2darkred',
 'blue2green',
 'blue2grey',
 'blue2orange',
 'blue2orange2red',
 'blue_to_grey',
 'blue_to_grn',
 'blue_to_orange',
 'blue_to_orgred',
 'brown2blue',
 'brown_to_blue',
 'categorical',
 'classic',
 'default',
 'green2magenta',
 'grn_to_magenta',
 'inferno',
 'lightblue2darkblue',
 'ltbl_to_drkbl',
 'magma',
 'my_cmap',
 'plasma',
 'rainbow',
 'rainbow_no_grn',
 'rainbownogreen',
 'sequential',
 'viridis',
 'white2blue',
 'white2green',
 'white2magenta',
 'white2red',
 'white2yellow',
 'white_to_blue',
 'white_to_green',
 'white_to_magenta',
 'white_to_red',
 'white_to_yellow']
  • Set colormap for the canvas by using setcolormap of VCS
In [5]:
v.setcolormap('my_cmap')
  • Let's make the colormap palette as pure white first
  • Note that 'my_cmap' colormap is copy of the default colormap at the beginning
In [6]:
for i in range(0,240):
    v.setcolorcell(i,100,100,100)
  • Assign colors with index number to 'my_cmap' using setcolormap of VCS
  • Below example colors are given from here
In [7]:
v.setcolorcell(0,0,0,0) # black
v.setcolorcell(1,50,50,50) # gray
v.setcolorcell(2,75,75,75) # silver
v.setcolorcell(3,100,100,100) # white
v.setcolorcell(4,50,0,0) # maroon
v.setcolorcell(5,100,0,0) # red
v.setcolorcell(6,50,50,0) # olive
v.setcolorcell(7,100,100,0) # yellow
v.setcolorcell(8,0,50,0) # green
v.setcolorcell(9,0,100,0) # lime
v.setcolorcell(10,0,50,50) # teal
v.setcolorcell(11,0,100,100) # aqua
v.setcolorcell(12,0,0,50) # navy
v.setcolorcell(13,0,0,100) # blue
v.setcolorcell(14,50,0,50) # purple
v.setcolorcell(15,100,0,100) # fuchsia
  • Use box.color_1 and box.color_2 of boxfill to set starting and ending colors
In [8]:
box = v.createboxfill()
box.color_1 = 0
box.color_2 = 15
box.colormap = 'my_cmap'
v.plot(a,box)
Out[8]:

Alternative way of creating own colormaps

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  • Alternative way of creating your own VCS colormap uses combined capability of UV-CDAT's VCS and Matplotlib.
  • Below simply written function receives name of colormap (cmap_name as string), and list of colors (colors as list of strings or tuples). User can define colors using either (1) named color of Matplotlib or (2) tuples of R, G, B numbers (0-1).
  • LinearSegmentedColormap of matplotlib.colors, imported from the begining, stretchs given colors with smooth transition.
  • matplotlib2vcs of vcs.colors convert given Matplotlib colormap to VCS colormap.
In [9]:
def CreateOwnColormap(cmap_name, colors):
    
    # Create a Matplotlib colomap
    cm = LinearSegmentedColormap.from_list(cmap_name, colors, N=240)
    
    # Convert Matplotlib colormap to VCS one
    vcs_cmap = vcs.colors.matplotlib2vcs(cm, vcs_name=cmap_name)
    
    return vcs_cmap

Define name and colors for your own colormap

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Example 1

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In [10]:
# Define my own colormap (name and sequentially varying colors)
cmap_name = 'cmap1'
colors = ['white','red','orange',
          'yellow','green','blue','violet',
          'purple','black']
CreateOwnColormap(cmap_name, colors)
Out[10]:
<vcs.colormap.Cp at 0x7efe93427b38>
  • Visualize example 1
In [11]:
box = v.createboxfill()
box.color_1 = 0
box.color_2 = 239

box.colormap = 'cmap1'
v.plot(a,box)
Out[11]:

Example 2

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  • Define colors by using list of tuples of R, G, B numbers (0-1)
In [12]:
cmap_name2 = 'cmap2'
colors2 = [(1,0,0),(1,1,1),(0,0,1)] # red, white, blue
CreateOwnColormap(cmap_name2, colors2)
Out[12]:
<vcs.colormap.Cp at 0x7efe9027ff48>
  • Visualize example 2
In [13]:
v.clear()
box.colormap = 'cmap2'
v.plot(a,box)
Out[13]:

Example 3

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  • Similar to example 1 but with more complicated set up.
In [14]:
cmap_name3 = 'cmap3'
colors3 = ['white','lavender','royalblue','navy',
           'darkviolet','darkred','tomato','darkorange',
           'orange','yellow']
CreateOwnColormap(cmap_name3, colors3)
Out[14]:
<vcs.colormap.Cp at 0x7efe90281f48>
  • Visualize example 3
In [15]:
v.clear()
box.colormap = 'cmap3'
v.plot(a,box)
Out[15]:

Example 4

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  • Similar to example 2 but with more complicated set up.
In [16]:
cmap_name4 = 'cmap4'

colors4 = [(99,93,60),
           (99,80,40),
           (99,60,20),
           (99,40,11),
           (99,0,0),
           (51,0,0),
           (44,11,62),
           (0,40,99),
           (20,60,99),
           (40,80,99),
           (60,93,99),
           (80,99,99),
          ]

colors4 = MV2.divide(colors4,100.) # Convert range 0-100 to 0-1

CreateOwnColormap(cmap_name4, colors4)
Out[16]:
<vcs.colormap.Cp at 0x7efe90287f48>
In [17]:
v.clear()
box.colormap = 'cmap4'
v.plot(a,box)
Out[17]: