Colour maps

Colour maps can be specified with the colourmap() function

Calling colourmap() on a vis object loads a colourmap and applies it to that object in a single command.

It can also be called from the viewer object which just loads a colourmap and returns its id, which can be saved and used to set the “colourmap” property of a one or more or objects.

#First set up a basic vis so we can display the colourmaps
import lavavu
lv = lavavu.Viewer(border=False, axis=False, background="gray90", quality=3, fontscale=1.5)

Specifying colour maps

Maps can be loaded as strings or lists of colours, positions can optionally be provided in range [0,1] to set where on the scale the colour will be placed, eg:

"red white blue"
"0.0=red 0.25=white 1.0=blue"
[(0.0, 'red'), (0.25, 'white'), (1.0, 'blue')]
['red', 'white', 'blue']

To provide specific values for colours in their original scale (rather than positions normalized to [0,1] range), place the value in parenthesis instead, eg:

"red (100)white (200)blue"

When specifying colours you can use either: 1. colour names from https://en.wikipedia.org/wiki/X11_color_names eg: ‘red’ 2. RGB hex values such as ‘#ff0000’ 3. HTML style rgb(a) values, eg: ‘rgb(255,0,0)’ or ‘rgba(255,0,0,1)’

Colour order and positions can be reversed by passing reverse=True.
Pass discrete=True to produce a discrete colour map instead of a continuously varying one.
log=True will apply a logarithmic scale.
Addional properties to the colour map can be passed, for details see: https://lavavu.github.io/Documentation/Property-Reference#colourmap

Colour bars

The colourbar() function creates a colour bar plot, it can be called from an object and uses that objects colour map, if called on the viewer it must have its map specified at some point with colourmap(data).

There are several properties that specify how the colour bar is displayed, see: https://lavavu.github.io/Documentation/Property-Reference#colourbar

#Create colour bar then load a colourmap into it
cbar1 = lv.colourbar(size=[0.95,15], align="top")
cbar1.colourmap([(0, 'green'), (0.75, 'yellow'), (1, 'red')], reverse=True)

"""0.0000=rgba(255,0,0,1)
 0.2500=rgba(255,255,0,1)
 1.0000=rgba(0,255,0,1)
 """

#Create another colour bar and load a map, this time with a log scale
cbar2 = lv.colourbar(size=[0.95,15], align="top", tickvalues=[20,50,100,200,500])
cbar2.colourmap('black (100)goldenrod (101)khaki white', range=[10,1000], logscale=True)

"""0.0000=rgba(0,0,0,1)
 0.5000=rgba(218,165,32,1)
 0.5022=rgba(240,230,140,1)
 1.0000=rgba(255,255,255,1)
 """

lv.display(resolution=[640,90], transparent=True)

print(cbar1)

{
  align="top"
  colourbar=true
  colourmap="colourbar_colourmap"
  name="colourbar"
  size=[0.95, 15]
  visible=true
}

CubeHelix

Custom cube helix maps can be generated with cubehelix(), these will always have monotonically varying intensity values to be when printed in greyscale

cbar1.colourmap(lavavu.cubehelix(samples=16, start=0.5, rot=-0.9, sat=1.0, gamma=1.0, alpha=False))
cbar2.colourmap(lavavu.cubehelix(samples=16, start=1.0, rot=0.9, sat=0.75, gamma=1.0, alpha=False), logscale=False)
cbar2["tickvalues"] = []

lv.display(resolution=[640,90], transparent=True)

#Display in greyscale
cbar1.colourmap(lavavu.cubehelix(samples=16, start=0.5, rot=-0.9, sat=1.0, gamma=1.0, alpha=False), monochrome=True)
cbar2.colourmap(lavavu.cubehelix(samples=16, start=1.0, rot=0.9, sat=0.75, gamma=1.0, alpha=False), monochrome=True)
lv.display(resolution=[640,90], transparent=True)

Getting data

Colourmap data can be retreived with .getcolourmap() on an object, which returns the map formatted as a string, .getcolourmap(string=False) returns a python list of (position, colour) tuples instead. Either of these formats are supported when creating a colourmap so the data can be modified and passed to a new colour map.

print(cbar1.getcolourmap())

"""0.0000=rgba(0,0,0,1); 0.0625=rgba(21,21,21,1); 0.1250=rgba(38,38,38,1); 0.1875=rgba(54,54,54,1); 0.2500=rgba(73,73,73,1); 0.3125=rgba(93,93,93,1); 0.3750=rgba(114,114,114,1); 0.4375=rgba(133,133,133,1); 0.5000=rgba(147,147,147,1); 0.5625=rgba(158,158,158,1); 0.6250=rgba(168,168,168,1); 0.6875=rgba(179,179,179,1); 0.7500=rgba(192,192,192,1); 0.8125=rgba(208,208,208,1); 0.8750=rgba(222,222,222,1); 0.9375=rgba(236,236,236,1); 1.0000=rgba(255,255,255,1); """

CPT colour tables

Most files in the Generic Map Tools CPT format can be imported.
A large library of these can be found at cpt-city

The positions=False argument can be passed to ignore the position data and load only the colours.

try:
    #Check if file exists, if not download it from cpt-city
    import os
    fn = 'arctic.cpt'
    if not os.path.isfile(fn):
        import urllib
        url = 'http://soliton.vm.bytemark.co.uk/pub/cpt-city/arendal/arctic.cpt'
        urllib.urlretrieve(url, fn)

    #Load with positions calibrated
    cbar1.colourmap(lavavu.loadCPT(fn))
    #Load colour data only
    cbar2.colourmap(lavavu.loadCPT(fn, positions=False))

    lv.display(resolution=[640,90], transparent=True)
except:
    pass

Predefined maps

There are a number of colour maps available for convenience which can be accessed by passing their name instead of a list of colours when creating a colour map.

#Get the list of colormap names
#suggest: lv.colourmaps.(names)
maps = lv.defaultcolourmaps()
print(maps)

['diverge', 'isolum', 'isorainbow', 'cubelaw', 'cubelaw2', 'smoothheat', 'coolwarm', 'spectral', 'drywet', 'elevation', 'dem1', 'dem2', 'dem3', 'dem4', 'ocean', 'bathy', 'seafloor', 'abyss', 'ibcso', 'gebco', 'topo', 'sealand', 'nighttime', 'world', 'geo', 'terra', 'relief', 'globe', 'earth', 'etopo1', 'cubhelix', 'hot', 'cool', 'copper', 'gray', 'split', 'polar', 'red2green', 'paired', 'categorical', 'haxby', 'jet', 'panoply', 'no_green', 'wysiwyg', 'seis', 'rainbow', 'nih']
The first eight maps are selected to vary evenly in luminance to reduce banding artifacts
Following these are further maps inspired by the default colour tables from the Generic Mapping Tools
Those maps that have fixed colour positions included can also be loaded without the position data by preceding the name with ‘@’

The colourmap data can be retrieved for modification as follows:

print(lv.defaultcolourmap('cubelaw'))

#440088 #831bb9 #578ee9 #3db6b6 #6ce64d #afeb56 #ffff88
Plot of all built in maps
Finally we will plot all the available built in colourmaps in continuous and discrete modes
#Clear the plot and create some new colour bars
lv.clear()
#Default continuous colour bar
cbar1 = lv.colourbar(size=[0.95,15], align="top")
#Discrete colour bar with bin labels enabled
cbar2 = lv.colourbar(size=[0.95,15], align="top", binlabels=True)

#Plot each map in the list
for name in maps:
    print(name)
    #Load as continuous colourmap
    cbar1.colourmap(name)
    #Load as discrete colourmap
    cbar2.colourmap(name, discrete=True, range=[-6,6])
    lv.display(resolution=[640,90], transparent=True)

diverge

isolum

isorainbow

cubelaw

cubelaw2

smoothheat

coolwarm

spectral

drywet

elevation

dem1

dem2

dem3

dem4

ocean

bathy

seafloor

abyss

ibcso

gebco

topo

sealand

nighttime

world

geo

terra

relief

globe

earth

etopo1

cubhelix

hot

cool

copper

gray

split

polar

red2green

paired

categorical

haxby

jet

panoply

no_green

wysiwyg

seis

rainbow

nih