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numpy.common_type() function – Python

numpy.correlate() function – Python

Last Updated : 11 Jun, 2020

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numpy.correlate() function defines the cross-correlation of two 1-dimensional sequences. This function computes the correlation as generally defined in signal processing texts: c_{av}[k] = sum_n a[n+k] * conj(v[n])

Syntax : numpy.correlate(a, v, mode = ‘valid’)

Parameters :
a, v : [array_like] Input sequences.
mode : [{‘valid’, ‘same’, ‘full’}, optional] Refer to the convolve docstring. Default is ‘valid’.

Return : [ndarray] Discrete cross-correlation of a and v.

Code #1 :

   # Python program explaining 
# numpy.correlate() function 
       
# importing numpy as geek  
import numpy as geek  
   
a = [2, 5, 7] 
v = [0, 1, 0.5] 
   
gfg = geek.correlate(a, v) 
   
print (gfg)

Output :

  [8.5]

Code #2 :

   # Python program explaining 
# numpy.correlate() function 
       
# importing numpy as geek  
import numpy as geek  
   
a = [2, 5, 7] 
v = [0, 1, 0.5] 
   
gfg = geek.correlate(a, v, "same") 
   
print (gfg)

Output :

  [4.5 8.5 7. ]

numpy.common_type() function – Python

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Article Tags :

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Practice Tags :

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