[Python] Changing point color depending on value in real-time plotting with Bokeh

I am using Bokeh in an experiment to plot data in realtime and the library provides a convenient way to do that.

Here a snippet of my code to accomplish this tasks:

# do the imports
import pandas as pd
import numpy as np
import time
from bokeh.plotting import *
from bokeh.models import ColumnDataSource

# here is simulated fake time series data
ts = pd.date_range("8:00", "10:00", freq="5S")
ts.name = 'timestamp'
ms = pd.Series(np.arange(0, len(ts)), index=ts)
ms.name = 'measurement'
data = pd.DataFrame(ms)
data['state'] = np.random.choice(3, len(ts))
data['observation'] = np.random.choice(2, len(ts))
data.reset_index(inplace=True)
data.head()


This is how the data looks like.

Next I have used the following snipped to push the data to the server in real time

output_server("observation")

p = figure(plot_width=800, plot_height=400, x_axis_type="datetime")
x = np.array(data.head(2).timestamp, dtype=np.datetime64)
y = np.array(data.head(2).observation)
p.diamond_cross(x,y, size=30, fill_color=None, line_width=2, name='observation')
show(p)

renderer = p.select(dict(name="observation"))[0]
ds = renderer.data_source

for mes in range(len(data)):

x = np.append(x, np.datetime64(data.loc[mes].timestamp))
y = np.append(y, np.int64(data.loc[mes].observation))
ds.data["x"] = x
ds.data["y"] = y

ds._dirty = True
cursession().store_objects(ds)
time.sleep(.1)


This produces a very nice result, however I need to change the color of each data point conditioned on a value.

In this case, the condition is the state variable which takes three values -- 0, 1, and 2. So my data should be able to reflect that.



Continue reading...