import numpy as np
import holoviews as hv
hv.extension('matplotlib')

ls  = np.linspace(0, 10, 400)
x,y = np.meshgrid(ls, ls)
img = hv.Image(np.sin(x)*np.cos(y)+0.1*np.random.rand(400,400), 
               bounds=(-20,-20,20,20)).options(colorbar=True, xaxis=None, yaxis=None)

hv.Layout([img.options(cmap=c).relabel(c) for c in ['gray','PiYG','flag','Set1']])

from math import ceil
from holoviews.plotting.util import process_cmap

colormaps = hv.plotting.list_cmaps()
spacing = np.linspace(0, 1, 64)[np.newaxis]
opts = dict(aspect=6, xaxis=None, yaxis=None, sublabel_format='')

def filter_cmaps(category):
    return hv.plotting.util.list_cmaps(records=True,category=category,reverse=False)

def cmap_examples(category,cols=4):
    cms = filter_cmaps(category)
    n = len(cms)*1.0
    c=ceil(n/cols) if n>cols else cols
    bars = [hv.Image(spacing, ydensity=1, label="{0} ({1})".format(r.name,r.provider))\
            .options(cmap=process_cmap(r.name,provider=r.provider), **opts)
           for r in cms]
    return hv.Layout(bars).options(vspace=0.1, hspace=0.1, transpose=(n>cols)).cols(c)

cmap_examples('Uniform Sequential')

cmap_examples('Diverging')

cmap_examples('Rainbow')

cmap_examples('Categorical')

cmap_examples('Mono Sequential')

cmap_examples('Other Sequential')

cmap_examples('Miscellaneous')

from holoviews.plotting import list_cmaps
def format_list(l):
    print(' '.join(sorted([k for k in l])))

format_list(list_cmaps(provider='colorcet',reverse=True))

format_list(list_cmaps(name='20', source='d3', provider='matplotlib', reverse=False))

format_list(list_cmaps(category='Other Sequential', bg='dark'))

format_list(list_cmaps(category='Other Sequential', bg='light'))

format_list(list_cmaps(category='Diverging', bg='dark'))

format_list(list_cmaps(category='Diverging', bg='light'))

format_list(list_cmaps(category='Sequential', bg='a'))

list_cmaps(category="Uniform Sequential", provider='bokeh', bg='light', records=True)

hv.Layout([img.options(cmap=c, colorbar=False, sublabel_format='').relabel(c) 
           for c in list_cmaps(category='Diverging', bg='light', reverse=False)])\
    .options(vspace=0.1, hspace=0.1).cols(7)