This demo shows off an interactive visualization using Bokeh for plotting, and Ipython interactors for widgets. The demo runs entirely inside the Ipython notebook, with no Bokeh server required.
The dropdown offers a choice of trig functions to plot, and the sliders control the frequency, amplitude, and phase.
To run, click on, Cell->Run All in the top menu, then scroll to the bottom and move the sliders.
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from ipywidgets import interact
import numpy as np
from bokeh.io import push_notebook, show, output_notebook
from bokeh.plotting import figure
output_notebook()
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x = np.linspace(0, 2*np.pi, 2000)
y = np.sin(x)
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p = figure(title="simple line example", plot_height=300, plot_width=600, y_range=(-5,5),
background_fill_color='#efefef')
r = p.line(x, y, color="#8888cc", line_width=1.5, alpha=0.8)
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def update(f, w=1, A=1, phi=0):
if f == "sin": func = np.sin
elif f == "cos": func = np.cos
r.data_source.data['y'] = A * func(w * x + phi)
push_notebook()
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show(p, notebook_handle=True)
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interact(update, f=["sin", "cos"], w=(0,50), A=(1,10), phi=(0, 20, 0.1))
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