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Colorscheme

Plottools offers a colorscheme class which can be used to define a set of colors and an order of appearance. The colorscheme object can then be used to cycle through colors using a convinient next method or by indexing using a short or longname.

When a colorscheme is defined in the beginning of a script and referenced in the subsequent plot commands, it allows easy changes of colorscheme if required.

import numpy as np
import matplotlib.pyplot as plt
import plottools as pt

colorscheme = pt.color

plt.figure()
x = np.arange(6)
labels = ['label {}'.format(i+1) for i in range(len(colorscheme.keys()))]

bars = []
y_tot = np.zeros_like(x)
for l in labels:
    y = np.random.random_integers(1,high=10,size=x.shape)
    b = plt.bar(x, y, 0.8, bottom=y_tot , color=colorscheme.next())
    bars.append(b[0])
    y_tot += y

plt.legend(bars,labels)
plt.show()

(Source code, png, hires.png, pdf)

Plottools comes with a default colorscheme plottools.color which includes 6 colors and a shade of grey which looks better than the default colors and have good contrast when printed in greyscale.

import matplotlib.pyplot as plt
import numpy as np

import plottools as pt
from plottools.color.util import plot_colors, to_greyscale

fig = plt.figure()
ax1 = fig.add_subplot(211)
plot_colors(ax1,pt.color.colors,['k','p','b','r','g','o','y'])

ax2 = fig.add_subplot(212)
plot_colors(ax2,{key: to_greyscale(val) for key,val in pt.color.items()} ,['k','p','b','r','g','o','y'])
plt.show()

(Source code)

A colorscheme can also be used as the default color cycler by calling the method set_as_default().

import numpy as np
import matplotlib.pyplot as plt
import plottools as pt

plt.figure()
x = np.linspace(0,2*np.pi,100)

pt.color.set_as_default()

for i,key in enumerate( pt.color.keys() ):
    plt.plot(x,np.sin(x-i*2*2*np.pi/14))

plt.show()

(Source code, png, hires.png, pdf)

When a colorscheme is defined, a lighter and darker variation are automatically created. These can be accessed as a color scheme object by the light and dark attributes respectively.

import numpy as np
import matplotlib.pyplot as plt
import plottools as pt

plt.figure()
x = np.linspace(0,2*np.pi,100)
for i,key in enumerate( pt.color.default.keys() ):
    plt.plot(x,np.sin(x-i*2*2*np.pi/14),color=pt.color[key],label=key)
    plt.plot(x,np.sin(x-i*2*2*np.pi/14)-0.1,color=pt.color.light[key])
    plt.plot(x,np.sin(x-i*2*2*np.pi/14)+0.1,color=pt.color.dark[key])

plt.legend()
plt.show()

(Source code)

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