NumPy and Matplotlib examples

First import NumPy and Matplotlib:



In [1]:

    
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
print(matplotlib.backends.backend)









    



module://ipykernel.pylab.backend_inline



In [2]:

    
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('png', 'pdf')
matplotlib.rcParams['figure.figsize'] = (2,1)



In [3]:

    
ip.display_formatter.formatters['application/pdf'].type_printers









    Out[3]:





{matplotlib.figure.Figure: <function IPython.core.pylabtools.<lambda>>}



In [4]:

    
import numpy as np

Now we show some very basic examples of how they can be used.



In [5]:

    
a = np.random.uniform(size=(100,100))



In [6]:

    
a.shape









    Out[6]:





(100, 100)



In [7]:

    
evs = np.linalg.eigvals(a)



In [8]:

    
evs.shape









    Out[8]:





(100,)

Here is a very long heading that pandoc will wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap and wrap

Here is a cell that has both text and PNG output:



In [9]:

    
plt.hist(evs.real)









    Out[9]:





(array([97,  2,  0,  0,  0,  0,  0,  0,  0,  1]),
 array([ -2.59479443,   2.67371141,   7.94221725,  13.21072308,
         18.47922892,  23.74773476,  29.0162406 ,  34.28474644,
         39.55325228,  44.82175812,  50.09026395]),
 <a list of 10 Patch objects>)

import math 
import numpy as np
def matrix_calc(L=None):
    """docstring"""
    if L is None:       L = np.random.random(size=(1,1))    raise Exception("message")

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