numpy.inner()


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This function returns the inner product of vectors for 1-D arrays. For higher dimensions, it returns the sum product over the last axes.

Example

import numpy as np 
print np.inner(np.array([1,2,3]),np.array([0,1,0])) 
# Equates to 1*0+2*1+3*0

It will produce the following output −

2

Example

# Multi-dimensional array example 
import numpy as np 
a = np.array([[1,2], [3,4]]) 

print 'Array a:' 
print a 
b = np.array([[11, 12], [13, 14]]) 

print 'Array b:' 
print b 

print 'Inner product:' 
print np.inner(a,b)

It will produce the following output −

Array a:
[[1 2]
[3 4]]

Array b:
[[11 12]
[13 14]]

Inner product:
[[35 41]
[81 95]]

In the above case, the inner product is calculated as −

1*11+2*12, 1*13+2*14 
3*11+4*12, 3*13+4*14 
numpy_linear_algebra.htm
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