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.. _quickstart:
Conventions
==============
hexadecimal
---------------
hexadecimal can be encoded as explained in :meth:`colormap.colors.hex2rgb`:
* #FFF
* #0000FF
* 0x0000FF
* 0xFA1
normalisation
---------------
By default, input should be normalised (e.g., RGB values between 0 and 1) and outputs are normalised.
If you provide unnormalised values (e.g., RGB in 0-255) then set the noramlised
parameter to True (see example in codecs).
Codecs
==========
list
--------
There is a bunch of codecs available in :mod:`colormap.colors` such as
hex2rgb::
>>> from colormap.colors import hex2rgb
>>> hex2rgb("#FFF", normalise=False)
(255, 255, 255)
>>> hex2rgb("#FFFFFF", normalise=True)
(1.0, 1.0, 1.0)
=============== =====================================
codecs
=============== =====================================
hex2web :meth:`colormap.colors.hex2web`
web2hex :meth:`colormap.colors.web2hex`
hex2rgb :meth:`colormap.colors.hex2rgb`
rgb2hex :meth:`colormap.colors.rgb2hex`
rgb2hls :meth:`colormap.colors.rgb2hls`
rgb2hsv :meth:`colormap.colors.rgb2hsv`
hsv2rgb :meth:`colormap.colors.hsv2rgb`
hls2rgb :meth:`colormap.colors.hls2rgb`
hex2dec :meth:`colormap.colors.hex2dec`
yuv2rgb :meth:`colormap.colors.yuv2rgb`
rgb2yuv_int :meth:`colormap.colors.rgb2yuv_int`
yuv2rgb_int :meth:`colormap.colors.yuv2rgb_int`
=============== =====================================
format
----------
* RGB (red/green/blue): a triple of values between 0 and 255
* HLS (): H in 0-360 and L,S in 0-100
* HSV (): H in 0-360, S,V in
* YUV: all in 0-1
Color class
===========
On task, which is quite common is to know the hexadecimal code of a color known
by name (e.g. red). The :class:`colormap.colors.Color` would be useful::
>>> c = Color('red')
>>> c.rgb
(1.0, 0.0, 0.0)
>>> c.hls
(0.0, 0.5, 1.0)
>>> c.hex
'#FF0000'
>>> print(c)
Color Red
hexa code: #FF0000
RGB code: (1.0, 0.0, 0.0)
RGB code (un-normalised): [255.0, 0.0, 0.0]
HSV code: (0.0, 1.0, 1.0)
HSV code: (un-normalised) 0.0 100.0 100.0
HLS code: (0.0, 0.5, 1.0)
HLS code: (un-normalised) 0.0 50.0 100.0
Input when instanciating can be anything in RGB, HEX, HLS, common name from
:mod:`colormap.xfree86`::
>>> sorted(colormap.xfree86.XFree86_colors.keys())
colormap
============
There are lots of colormaps in matplotlib. This is great but some may be missing
or it is not obvious to know what the colormap will look like.
The :class:`colormap.colors.Colormap` class allows you:
- To build easily new colormaps and visualise them
- Visualise existing colormaps
visualise colormaps
-------------------------
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_category
>>> plot_categoryp('sequentials')
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_category
>>> plot_category('sequentials2')
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_category
>>> plot_category('misc')
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_category
>>> plot_category('diverging')
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_category
>>> plot_category('qualitative')
Visualise existing colormap
-----------------------------
.. plot::
:include-source:
:width: 80%
>>> from colormap import plot_colormap,
>>> plot_colormap("viridis")
Create a linear colormap
-------------------------------
The simplest colormap are linear with 3 colors. In such case, we provide a
method that is easy to use. Imagine you want a colormap from red to green with
white color in between:
.. plot::
:include-source:
:width: 80%
from colormap import Colormap
c = Colormap()
cmap = c.cmap_linear('red', 'white', 'green')
cmap = c.test_colormap(cmap)
Here, we use color names, which are the xfree86 names. However, you could have
used any format accepted by :class:`~colormap.Colors`::
red = Color('red')
cmap = cmap_linear(red, 'white', '#0000FF')
Create a general colormap
-----------------------------
In the previous example, we used 3 colors assuming a linear scale. However, you
may want a different scale, in which case, you need to provide more colors. In
such case, you can use :meth:`~colormap.colors.Colormap.cmap` method.
Here we again use the same example a above but it can be generalised easily.
First, we need to know the RGB components of the colors::
>>> from colormap import Color, Colormap
>>> green = Color('Dark Green').rgb
>>> red = Color('red').rgb
>>> white = Color('white').rgb
>>> white
(1.0, 1.0, 1.0)
For instance RGB values of white are 1,1,1
Second, built a dictionary with the three RGB name (red/green/blue) as keys and with the values being the
evolution of the red/green/blue when a value goes from 0 to 1. Here, we use a
linear scaling so we just need 3 values at 0, 0.5, and 1. Therefore we have list of 4 values.
You could provide list of arbitrary lengths if required ::
>>> c = Colormap()
>>> mycmap = c.cmap( {'red':[1,1,0,1], 'green':[0,1,.39,1], 'blue':[0,1,0,1]})
Finally, test it::
c.test_colormap(mycmap)
.. plot::
from colormap import Colormap
c = Colormap()
c.test_colormap(c.cmap({'red':[1,1,0,1], 'green':[0,1,.39,1],
'blue':[0,1,0,1]}))
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