import numpy as np
from matplotlib.mlab import bivariate_normal
from bokeh.plotting import figure, output_file, show
from bokeh.models import LogColorMapper, LogTicker, ColorBar
output_file('color_bar.html')
N = 100
X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
Z1 = bivariate_normal(X, Y, 0.1, 0.2, 1.0, 1.0) + \
0.1 * bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
image = Z1 * 1e6
color_mapper = LogColorMapper(palette="Viridis256", low=1, high=1e7)
plot = figure(x_range=(0,1), y_range=(0,1), toolbar_location=None)
plot.image(image=[image], color_mapper=color_mapper,
dh=[1.0], dw=[1.0], x=[0], y=[0])
color_bar = ColorBar(color_mapper=color_mapper, ticker=LogTicker(),
label_standoff=12, border_line_color=None, location=(0,0))
plot.add_layout(color_bar, 'right')
show(plot)
