Everybody loves plots!

Visualizing of training result

There are different plotting backends supported:

matplotlib (default, de-facto standard plotting library),
plotly (proprietary package with interactive plots, information is kept on the server),
ROOT (the library used by CERN employer),
bokeh (open-source package with interactive plots)

You create plotting object and can show it using the following functions:

matplotlib plot()
plotly plot_plotly()
ROOT plot_tmva()
bokeh plot_bokeh()

mpld3 library allows you plot matplotlib in intarecative regime.



In [1]:

    
%pylab inline









    



Populating the interactive namespace from numpy and matplotlib



In [2]:

    
import mpld3

FunctionsPlot



In [3]:

    
from rep.plotting import FunctionsPlot



In [4]:

    
n_points = 30
first_func = (numpy.linspace(0, 10, n_points), numpy.random.random(n_points))
second_func = (numpy.linspace(-10, 0, n_points), numpy.random.random(n_points))

obj = FunctionsPlot({'first': first_func, 'second': second_func})

matplotlib



In [5]:

    
obj.plot(new_plot=True)

matplotlib using mpld3 interactive plots



In [6]:

    
obj.plot(new_plot=True, xlim=(-5, 5), ylim=(0.2, 0.8), title='example', xlabel='x', ylabel='y', fontsize=15)
mpld3.display()









    Out[6]:

plotly interactive plots



In [7]:

    
obj.plot_plotly("functions")









    Out[7]:

bokeh interactive plots



In [8]:

    
obj.plot_bokeh(figsize=(15, 10), xlabel='x', title='Example', ylim=(0, 0.5))









    




    


    

    
        
        BokehJS successfully loaded.

tmva style



In [9]:

    
obj.plot_tmva(new_plot=True, figsize=(6, 6), title='TMVA example')









    Out[9]:

separate two lines



In [10]:

    
obj1 = FunctionsPlot({'first': first_func})
obj2 = FunctionsPlot({'second': second_func})



In [11]:

    
# put new_plot to separate figures for lines in matplotlib
obj1.plot(new_plot=True)
obj2.plot(new_plot=True, xlabel='x')



In [12]:

    
obj1.plot(new_plot=True)
obj2.plot(new_plot=True, xlabel='x', show_legend=False)



In [13]:

    
obj1.plot(new_plot=True)
obj2.plot(new_plot=True, xlabel='x', show_legend=False)
mpld3.display()









    Out[13]:



In [14]:

    
obj1.plot_plotly('one', title='plotly', xlabel='x', ylabel='points')
obj2.plot_plotly('two', title='plotly', xlabel='x', ylabel='points', xlim=(-8, -2), ylim=(0.2, 0.8), fontsize=13,
                 show_legend=False)









    Out[14]:



In [15]:

    
obj1.plot_bokeh()
obj2.plot_bokeh(title='bokeh', xlabel='x', ylabel='points', xlim=(-8, -2), ylim=(0.2, 0.8), fontsize=13,
                show_legend=False)









    




    


    

    
        
        BokehJS successfully loaded.