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interactivevisualization.py
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Thu, Feb 20, 20:46

interactivevisualization.py
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import matplotlib.pyplot as plt
import ipywidgets as widgets
# Enable interactive backend for matplotlib
from IPython import get_ipython
get_ipython().run_line_magic('matplotlib', 'widget')
def displayInteractiveHouse():
# We will plot a rectangle to model a house
house_x = [2, 2, 4, 4]
house_y = [0, 2, 2, 0]
# We will plot a triangle to model the roof
roof_x = [2, 3, 4]
roof_y = [2, 5, 2]
# Creation of the figure
fig = plt.figure(num='Interactive figure', figsize=(6,4))
# Creation of one subplot/axe - it will take position index number 1 in a grid of 1 row and 1 column, as described by (nrows, ncols, index)
ax = fig.add_subplot(1,1,1)
# Plot the house
ax.plot(house_x, house_y)
# Plot the roof, and get the resulting line, on which we will add interactivity later - NOTICE the syntax with the comma "roof_line, ="
roof_line, = ax.plot(roof_x, roof_y)
# We create a slider with values ranging from 2 to 10 in steps of .5, by default on value 5
roof_widget = widgets.FloatSlider(min=2, max=10, step=0.5, value=5, description='Roof height:')
# This function will be called when the slider is moved
def roof_event_handler(change):
# It allows us to retrieve the new value of the slider
newposition = change.new
# Then we can change the points of the door line
roof_line.set_ydata([2, newposition, 2])
# Finally we tell the figure to draw the changed parts
fig.canvas.draw_idle()
# Finally we link the widget to the callback function
roof_widget.observe(roof_event_handler, names='value')
# The figure is automatically displayed since matplotlib is in interactive mode (if we display it explicitely, it will show up twice!)
# We only need to display the widget
display(roof_widget)

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