In [1]:

    

import numpy


    

In [2]:

    

import ipywidgets as widgets
from IPython.display import display


    

In [3]:

    

import matplotlib.pyplot as plt
%matplotlib notebook


    

In [4]:

    

x = [1,2,3]
y = numpy.array([2,5,4])
fig = plt.figure()
ax = fig.add_subplot(111)
line1, = ax.plot(x, y, 'r-')


    

In [5]:

    

slider = widgets.FloatSlider(min=0.0,max=10.0,value=5.0,description="Value:")
display(slider)


    

In [6]:

    

def on_value_change(change):
    line1.set_ydata(y*(10/change['new']))
    fig.canvas.draw()

slider.observe(on_value_change, names='value')


    

In [11]:

    

line1.set_ydata(numpy.array([2,1,3]))
fig.canvas.draw()


    

In [10]:

    

line1.get_ydata()


    

    
Out[10]:





array([2.7027027 , 6.75675676, 5.40540541])

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