How to use the colorcet.kbc function in colorcet

import bokeh.transform as btr
import holoviews as hv
import holoviews.operation.datashader as hd

import sklearn.decomposition
import sklearn.cluster
import sklearn.neighbors

from umap.nndescent import initialise_search, initialized_nnd_search
from umap.utils import deheap_sort, submatrix

from bokeh.plotting import output_notebook, output_file, show
from warnings import warn

fire_cmap = matplotlib.colors.LinearSegmentedColormap.from_list('fire', colorcet.fire)
darkblue_cmap = matplotlib.colors.LinearSegmentedColormap.from_list('darkblue', colorcet.kbc)
darkgreen_cmap = matplotlib.colors.LinearSegmentedColormap.from_list('darkgreen', colorcet.kgy)
darkred_cmap = matplotlib.colors.LinearSegmentedColormap.from_list('darkred',
                                                                   colors=colorcet.linear_kry_5_95_c72[:192],
                                                                   N=256)
darkpurple_cmap = matplotlib.colors.LinearSegmentedColormap.from_list('darkpurple',
                                                                      colorcet.linear_bmw_5_95_c89)

plt.register_cmap('fire', fire_cmap)
plt.register_cmap('darkblue', darkblue_cmap)
plt.register_cmap('darkgreen', darkgreen_cmap)
plt.register_cmap('darkred', darkred_cmap)
plt.register_cmap('darkpurple', darkpurple_cmap)


def _to_hex(arr):
    return [matplotlib.colors.to_hex(c) for c in arr]