Set routines



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import numpy as np



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np.__version__









    Out[5]:





'1.11.2'



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author = 'kyubyong. longinglove@nate.com'

Making proper sets

Q1. Get unique elements and reconstruction indices from x. And reconstruct x.



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x = np.array([1, 2, 6, 4, 2, 3, 2])
out, indices = np.unique(x, return_inverse=True)
print "unique elements =", out
print "reconstruction indices =", indices
print "reconstructed =", out[indices]









    



unique elements = [1 2 3 4 6]
reconstruction indices = [0 1 4 3 1 2 1]
reconstructed = [1 2 6 4 2 3 2]

Boolean operations

Q2. Create a boolean array of the same shape as x. If each element of x is present in y, the result will be True, otherwise False.



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x = np.array([0, 1, 2, 5, 0])
y = np.array([0, 1])
print np.in1d(x, y)









    



[ True  True False False  True]

Q3. Find the unique intersection of x and y.



In [20]:

    
x = np.array([0, 1, 2, 5, 0])
y = np.array([0, 1, 4])
print np.intersect1d(x, y)

Q4. Find the unique elements of x that are not present in y.



In [21]:

    
x = np.array([0, 1, 2, 5, 0])
y = np.array([0, 1, 4])
print np.setdiff1d(x, y)

Q5. Find the xor elements of x and y.



In [40]:

    
x = np.array([0, 1, 2, 5, 0])
y = np.array([0, 1, 4])
out1 = np.setxor1d(x, y)
out2 = np.sort(np.concatenate((np.setdiff1d(x, y), np.setdiff1d(y, x))))
assert np.allclose(out1, out2)
print out1

Q6. Find the union of x and y.



In [42]:

    
x = np.array([0, 1, 2, 5, 0])
y = np.array([0, 1, 4])
out1 = np.union1d(x, y)
out2 = np.sort(np.unique(np.concatenate((x, y))))
assert np.allclose(out1, out2)
print np.union1d(x, y)









    



[0 1 2 4 5]



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