Bokeh

This integration lets you log interactive charts generated in bokeh, like confusion matrix or distribution, in Neptune.

Log bokeh interactive charts

Follow these steps:

Create a run

import neptune.new as neptune
run = neptune.init(project='my_workspace/my_project')

Create bokeh figure

from bokeh.models import LogColorMapper
from bokeh.palettes import Viridis6 as palette
from bokeh.plotting import figure
from bokeh.sampledata.unemployment import data as unemployment
from bokeh.sampledata.us_counties import data as counties
palette = tuple(reversed(palette))
counties = {
code: county for code, county in counties.items() if county["state"] == "tx"
}
county_xs = [county["lons"] for county in counties.values()]
county_ys = [county["lats"] for county in counties.values()]
county_names = [county['name'] for county in counties.values()]
county_rates = [unemployment[county_id] for county_id in counties]
color_mapper = LogColorMapper(palette=palette)
data=dict(
x=county_xs,
y=county_ys,
name=county_names,
rate=county_rates,
)
TOOLS = "pan,wheel_zoom,reset,hover,save"
p = figure(
title="Texas Unemployment, 2009", tools=TOOLS,
x_axis_location=None, y_axis_location=None,
tooltips=[
("Name", "@name"),
("Unemployment rate", "@rate%"),
("(Long, Lat)", "($x, $y)")
])
p.grid.grid_line_color = None
p.hover.point_policy = "follow_mouse"
p.patches('x', 'y', source=data,
fill_color={'field': 'rate', 'transform': color_mapper},
fill_alpha=0.7, line_color="white", line_width=0.5)

Log interactive figure

run['visuals/bokeh-fig'] = neptune.types.File.as_html(p)

Explore the results in the Neptune