Bokeh

PyConsole supports visualization with bokeh

Usage

Steps

1. import data processing library and bokeh figure

import numpy as np
from scipy.integrate import odeint

from bokeh.plotting import figure

2. create bokeh figure

sigma = 10
rho = 28
beta = 8.0/3
theta = 3 * np.pi / 4

def lorenz(xyz, t):
    x, y, z = xyz
    x_dot = sigma * (y - x)
    y_dot = x * rho - x * z - y
    z_dot = x * y - beta* z
    return [x_dot, y_dot, z_dot]

initial = (-10, -7, 35)
t = np.arange(0, 100, 0.006)

solution = odeint(lorenz, initial, t)

x = solution[:, 0]
y = solution[:, 1]
z = solution[:, 2]
xprime = np.cos(theta) * x - np.sin(theta) * y

colors = ["#C6DBEF", "#9ECAE1", "#6BAED6", "#4292C6", "#2171B5", "#08519C", "#08306B"]

p = figure(title="Lorenz attractor example", background_fill_color="#fafafa")

p.multi_line(np.array_split(xprime, 7), np.array_split(z, 7),
             line_color=colors, line_alpha=0.8, line_width=1.5)

3. show bokeh figure

p.show()