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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]
@numba.vectorize(['uint8(uint32)', 'uint8(uint32)'])
def _red(x):
return (x & 0xff0000) >> 16